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2025,19(2):1-9
,DOI: 10.12057/j.issn.1002-0799.2403.15002
Abstract:
This article systematically reviews the current research progress on the effects of heat and drought on maize growth, development, and yield composition. This includes the impacts of heat(anthesis heat stress, rising average temperature, and increase in nighttime temperature) on maize growth and development, the simulation of heat effects using crop models, the effects of drought stress on the anthesis-silking intervals and yield composition, the simulation of anthesis timing and yield composition under drought stress, and the combined effects of heat and drought stress on maize yield composition. This article also prospects future research focuses.
This article systematically reviews the current research progress on the effects of heat and drought on maize growth, development, and yield composition. This includes the impacts of heat(anthesis heat stress, rising average temperature, and increase in nighttime temperature) on maize growth and development, the simulation of heat effects using crop models, the effects of drought stress on the anthesis-silking intervals and yield composition, the simulation of anthesis timing and yield composition under drought stress, and the combined effects of heat and drought stress on maize yield composition. This article also prospects future research focuses.
Variation Characteristics of Spring Dust Weather in Ningxia and Its Abnormal Causes during 1961-2022
2025,19(2):10-18
,DOI: 10.12057/j.issn.1002-0799.2402.29005
Abstract:
Based on the observation data of spring sand-dust weather in Ningxia from 1961 to 2022 and the reanalysis data, this study reveals the variation characteristics of spring sand-dust weather and anomalous causes across different evolutionary periods over the past six decades. The results show: (1) The spring sand-dust days in Ningxia exhibit the spatial distribution characteristic of "more in the central and northern parts and less in the southern regions". From 1961 to 2022, the number of sand-dust days significantly decreased at a rate of 5.4 d·(10 a)-1. The periods of 1961-1980, 1981-2000, and 2001-2022 represent phases with the most, the second most, and the fewest sand-dust days, respectively. (2) From 1961 to 1980, the Eurasian region was dominated by extensive negative anomalies at 500 hPa, with an abnormally strong polar vortex. Additionally, a strong South Indian Ocean sea temperature dipole, and smaller sea ice from Novaya Zemlya to the eastern Siberian Sea created favorable conditions for frequent sand-dust weather events. From 1981 to 2000, the intensity of the polar vortex and the atmospheric circulation that allows cold air from mid-to-high latitudes to move southward was weaker than in the previous period. The Western Pacific Warm Pool was weak, with smaller sea ice north of the Queen Elizabeth Islands and larger sea ice from the Beaufort Sea to the Chukchi Sea, leading to more sand-dust weather. From 2001 to 2022, the Eurasian region experienced a shift to positive anomalies and a weakened polar vortex. The South Indian Ocean sea temperature showed cooling trends, and the sea ice from the Beaufort Sea to the Chukchi Sea expanded, which was conducive to dust transport via cold air, but the overall strength of sand-dust weather weakened compared to the earlier two periods.
Based on the observation data of spring sand-dust weather in Ningxia from 1961 to 2022 and the reanalysis data, this study reveals the variation characteristics of spring sand-dust weather and anomalous causes across different evolutionary periods over the past six decades. The results show: (1) The spring sand-dust days in Ningxia exhibit the spatial distribution characteristic of "more in the central and northern parts and less in the southern regions". From 1961 to 2022, the number of sand-dust days significantly decreased at a rate of 5.4 d·(10 a)-1. The periods of 1961-1980, 1981-2000, and 2001-2022 represent phases with the most, the second most, and the fewest sand-dust days, respectively. (2) From 1961 to 1980, the Eurasian region was dominated by extensive negative anomalies at 500 hPa, with an abnormally strong polar vortex. Additionally, a strong South Indian Ocean sea temperature dipole, and smaller sea ice from Novaya Zemlya to the eastern Siberian Sea created favorable conditions for frequent sand-dust weather events. From 1981 to 2000, the intensity of the polar vortex and the atmospheric circulation that allows cold air from mid-to-high latitudes to move southward was weaker than in the previous period. The Western Pacific Warm Pool was weak, with smaller sea ice north of the Queen Elizabeth Islands and larger sea ice from the Beaufort Sea to the Chukchi Sea, leading to more sand-dust weather. From 2001 to 2022, the Eurasian region experienced a shift to positive anomalies and a weakened polar vortex. The South Indian Ocean sea temperature showed cooling trends, and the sea ice from the Beaufort Sea to the Chukchi Sea expanded, which was conducive to dust transport via cold air, but the overall strength of sand-dust weather weakened compared to the earlier two periods.
2025,19(2):19-27
,DOI: 10.12057/j.issn.1002-0799.2401.05001
Abstract:
Utilizing solar irradiation and irradiance, total cloud forecast data, hourly total cloud comprehensive data, and environmental monitoring station PM10 hourly average concentration measured data from four photovoltaic power stations in Laiyuan, Quyang, Pingshan and Shexian at the eastern foothill of Taihang Mountains from January 2021 to December 2023,this paper analyzed the time and frequency characteristics of solar radiation intensity, studied the clear sky correction model based on radiation ratio and hourly average concentration of PM10, and tested its correction effect. The results indicate that: (1) There were numerous sand-dust weather processes from 2021 to 2022 with a maximum impact time exceeding 63 hours. When PM10 hour concentrations exceeded 1 588 μg/m3, solar irradiance decreased to 26.3% of sunny days. (2) Daily and monthly variations of total solar radiation were evident with a normal distribution centered around 12-13 o'clock BT and a single peak distribution centered around June. In March, July, and November, the solar radiation intensity was lower than the overall trends due to sand-dust, precipitation, and heavy fog. (3) The sand-dust weather irradiance model positively impacted the overall revision of solar irradiance forecast with MAE decreasing by 34.3 W/m2 and RMSE decreasing by 31.0 W/m2. The correction effect is closely related to the forecast quality of PM10 hour average concentration. When the PM10 forecast effect is good, the correction effect is obvious; otherwise it is poor.
Utilizing solar irradiation and irradiance, total cloud forecast data, hourly total cloud comprehensive data, and environmental monitoring station PM10 hourly average concentration measured data from four photovoltaic power stations in Laiyuan, Quyang, Pingshan and Shexian at the eastern foothill of Taihang Mountains from January 2021 to December 2023,this paper analyzed the time and frequency characteristics of solar radiation intensity, studied the clear sky correction model based on radiation ratio and hourly average concentration of PM10, and tested its correction effect. The results indicate that: (1) There were numerous sand-dust weather processes from 2021 to 2022 with a maximum impact time exceeding 63 hours. When PM10 hour concentrations exceeded 1 588 μg/m3, solar irradiance decreased to 26.3% of sunny days. (2) Daily and monthly variations of total solar radiation were evident with a normal distribution centered around 12-13 o'clock BT and a single peak distribution centered around June. In March, July, and November, the solar radiation intensity was lower than the overall trends due to sand-dust, precipitation, and heavy fog. (3) The sand-dust weather irradiance model positively impacted the overall revision of solar irradiance forecast with MAE decreasing by 34.3 W/m2 and RMSE decreasing by 31.0 W/m2. The correction effect is closely related to the forecast quality of PM10 hour average concentration. When the PM10 forecast effect is good, the correction effect is obvious; otherwise it is poor.
2025,19(2):28-36
,DOI: 10.12057/j.issn.1002-0799.2310.10003
Abstract:
Based on observation data from 21 meteorological stations in the Shiyang River Basin from 1957 to 2021, the wind erosion climatic factor index (C factor) was calculated for the Shiyang River Basin. Methods such as Pearson correlation analysis, Mann Kendall (M-K) detection, inverse distance weight interpolation and principal component analysis were employed to analyze the trends and abrupt change characteristics of C factor at annual, seasonal and spatial scales, along with an analysis of relevant influencing factors. The results showed that C factor of the Shiyang River Basin from 1957 to 2021 ranged from 5 to 146, and the average value of the whole basin was 37.Spatially, C factor was higher in the northern desert and along the mountainous areas, and lower in the central oasis areas. The maximum C factor of 145.6 was observed in Hongshagang of Minqin desert area in the northern part of the basin, and the minimum C factor of 5.5 appeared in Tumen of Gulang oasis area of the basin. The basin's C factor showed significant seasonal variations, with the highest in spring, followed by summer, and the lowest in autumn and winter with little difference between them. The sum of C factor in spring and summer accounted for 61.2% of the annual total. On different time scales, the C factor showed a significant declining trend following an abrupt change around 1997, which was most likely caused by the significant abrupt change of wind speed around 1997 in the basin. The primary dynamic factors influencing the basin's C factor were the cumulative number of days with strong wind, cumulative number of sandstorm days and wind speed. The wind erosion climatic erosivity in the Shiyang River Basin was strong, with wind speed identified as the most crucial meteorological factor influencing the basin's C factor.
Based on observation data from 21 meteorological stations in the Shiyang River Basin from 1957 to 2021, the wind erosion climatic factor index (C factor) was calculated for the Shiyang River Basin. Methods such as Pearson correlation analysis, Mann Kendall (M-K) detection, inverse distance weight interpolation and principal component analysis were employed to analyze the trends and abrupt change characteristics of C factor at annual, seasonal and spatial scales, along with an analysis of relevant influencing factors. The results showed that C factor of the Shiyang River Basin from 1957 to 2021 ranged from 5 to 146, and the average value of the whole basin was 37.Spatially, C factor was higher in the northern desert and along the mountainous areas, and lower in the central oasis areas. The maximum C factor of 145.6 was observed in Hongshagang of Minqin desert area in the northern part of the basin, and the minimum C factor of 5.5 appeared in Tumen of Gulang oasis area of the basin. The basin's C factor showed significant seasonal variations, with the highest in spring, followed by summer, and the lowest in autumn and winter with little difference between them. The sum of C factor in spring and summer accounted for 61.2% of the annual total. On different time scales, the C factor showed a significant declining trend following an abrupt change around 1997, which was most likely caused by the significant abrupt change of wind speed around 1997 in the basin. The primary dynamic factors influencing the basin's C factor were the cumulative number of days with strong wind, cumulative number of sandstorm days and wind speed. The wind erosion climatic erosivity in the Shiyang River Basin was strong, with wind speed identified as the most crucial meteorological factor influencing the basin's C factor.
2025,19(2):37-46
,DOI: 10.12057/j.issn.1002-0799.2405.07002
Abstract:
Based on the precipitation observation data from 1 889 automatic meteorological stations in Xinjiang, this study assesses the applicability of the multi-source precipitation fusion product (with a spatial resolution of 1 km and a temporal resolution of 1 hour) released by the CMA Multi-source Precipitation Analysis System (CMPAS) for the warm season (May to September) from 2020 to 2023. The results show that the product has significantly improved in 2022-2023 compared to the 2020-2021 period across all evaluation indicators. The correlation coefficient (COR) and TS score in 2022-2023 increased from 0.86 and 0.648 to 0.939 and 0.854, respectively, representing an increase of 9.2% and 31.8%. The root mean square error decreased from 0.692 mm to 0.484 mm, a reduction of 30%. The false alarm rate dramatically decreased from 0.325 to 0.101, a reduction of 68.9%, while the missed rate showed no significant change. Among the months of the warm season, the comprehensive quality of the precipitation fusion product was the best in August. During periods of high actual precipitation (15:00-21:00), the correlation coefficient between the precipitation fusion product and the actual precipitation was relatively high and stable. However, the TS score was slightly lower due to the higher false alarm rate and missed rates. The performance of the multi-source precipitation fusion product deteriorated with increasing precipitation intensity, but the gap was trending downward annually. The areas with relatively poor precipitation fusion product quality are mainly located in the northwest of northern Xinjiang, the middle section of the Tianshan Mountains (both northern and southern slopes), the western part of southern Xinjiang, the northern slope of the Kunlun Mountains, the Altay Mountains, and the eastern Xinjiang region. Compared to the 2020-2021 period, the quality of the precipitation fusion product improved significantly in 2022-2023 across various time scales, precipitation intensities, and altitudinal ranges. This indicates that the optimization of the precipitation fusion product algorithm in the second half of 2021 has significantly enhanced the product accuracy and reliability.
Based on the precipitation observation data from 1 889 automatic meteorological stations in Xinjiang, this study assesses the applicability of the multi-source precipitation fusion product (with a spatial resolution of 1 km and a temporal resolution of 1 hour) released by the CMA Multi-source Precipitation Analysis System (CMPAS) for the warm season (May to September) from 2020 to 2023. The results show that the product has significantly improved in 2022-2023 compared to the 2020-2021 period across all evaluation indicators. The correlation coefficient (COR) and TS score in 2022-2023 increased from 0.86 and 0.648 to 0.939 and 0.854, respectively, representing an increase of 9.2% and 31.8%. The root mean square error decreased from 0.692 mm to 0.484 mm, a reduction of 30%. The false alarm rate dramatically decreased from 0.325 to 0.101, a reduction of 68.9%, while the missed rate showed no significant change. Among the months of the warm season, the comprehensive quality of the precipitation fusion product was the best in August. During periods of high actual precipitation (15:00-21:00), the correlation coefficient between the precipitation fusion product and the actual precipitation was relatively high and stable. However, the TS score was slightly lower due to the higher false alarm rate and missed rates. The performance of the multi-source precipitation fusion product deteriorated with increasing precipitation intensity, but the gap was trending downward annually. The areas with relatively poor precipitation fusion product quality are mainly located in the northwest of northern Xinjiang, the middle section of the Tianshan Mountains (both northern and southern slopes), the western part of southern Xinjiang, the northern slope of the Kunlun Mountains, the Altay Mountains, and the eastern Xinjiang region. Compared to the 2020-2021 period, the quality of the precipitation fusion product improved significantly in 2022-2023 across various time scales, precipitation intensities, and altitudinal ranges. This indicates that the optimization of the precipitation fusion product algorithm in the second half of 2021 has significantly enhanced the product accuracy and reliability.
2025,19(2):47-54
,DOI: 10.12057/j.issn.1002-0799.2302.27001
Abstract:
Using daily precipitation data in Henan from 1970 to 2021, this study employed mathematical statistics, linear trend analysis and cluster analysis to assess and classify the temporal evolution characteristics of regional rainstorm days and the spatial distribution of rainstorm regions in Henan. The results show that a total of 650 regional rainstorm days occurred in Henan over the 52-year period, with an annual average of 12.5 days. The highest frequency of rainstorms was recorded in summer with 484 days, accounting for 74.5% of the total, while no regional rainstorms were recorded in winter. There was no significant trend of change in the total time series and the sub-series before and after the mean mutation point of regional rainstorm days, rainstorm intensity, first occurrence day, and last occurrence day. From 2008 to 2021, the average first occurrence day of regional rainstorms significantly advanced, while the last occurrence day was noticeably delayed. The rainstorm falling regions can be categorized into four types: northern Henan, central Henan, southern Henan and whole Henan. The average number of regional rainstorm days, the rainstorm intensity, and low-value centers of extreme rainfall were mainly located in the mountainous areas of western Henan, while high-value centers were concentrated in Zhumadian.The intensity of regional rainstorms was greater than that of non-regional rainstorms at most meteorological stations.During regional rainstorms, the longest duration of rainstorms at each station primarily spanned between 2-3 days.
Using daily precipitation data in Henan from 1970 to 2021, this study employed mathematical statistics, linear trend analysis and cluster analysis to assess and classify the temporal evolution characteristics of regional rainstorm days and the spatial distribution of rainstorm regions in Henan. The results show that a total of 650 regional rainstorm days occurred in Henan over the 52-year period, with an annual average of 12.5 days. The highest frequency of rainstorms was recorded in summer with 484 days, accounting for 74.5% of the total, while no regional rainstorms were recorded in winter. There was no significant trend of change in the total time series and the sub-series before and after the mean mutation point of regional rainstorm days, rainstorm intensity, first occurrence day, and last occurrence day. From 2008 to 2021, the average first occurrence day of regional rainstorms significantly advanced, while the last occurrence day was noticeably delayed. The rainstorm falling regions can be categorized into four types: northern Henan, central Henan, southern Henan and whole Henan. The average number of regional rainstorm days, the rainstorm intensity, and low-value centers of extreme rainfall were mainly located in the mountainous areas of western Henan, while high-value centers were concentrated in Zhumadian.The intensity of regional rainstorms was greater than that of non-regional rainstorms at most meteorological stations.During regional rainstorms, the longest duration of rainstorms at each station primarily spanned between 2-3 days.
2025,19(2):55-63
,DOI: 10.12057/j.issn.1002-0799.2307.24001
Abstract:
Based on the assimilation module for Himawari-8 AHI radiance data in the weather research and forecasting model data assimilation (WRFDA) system with WRF model, this paper investigated the impact of direct assimilation of the radiance data of the three water vapor channels from Himawari-8 AHI on the forecast of a heavy rainfall in Northeast China. The results show that the quality control and bias correction are effective in eliminating anomalous data, making the mean of observation minus background (OMB) closer to 0, while the standard deviation and root mean square error of observation minus analysis (OMA) are further reduced. Compared with the control experiment, after assimilating AHI radiance data, the root mean square errors are reduced by about 0.2 m/s and 0.1 K in the middle and lower layers for the wind and temperature respectively, and the root mean square error of specific humidity decreases by about 0.03 g/kg in the lower layers. Besides, the assimilation of satellite data contributes positively to the increment of relative humidity in the central part of Jilin Province. The final forecast of 3 h precipitation is improved. The experiments involving satellite data assimilation show an improvement in the ETS and bias scores exceeding 0.1 of all thresholds. For the 50 mm threshold, the improvement rates for ETS and bias scores reach 64% and 58%, respectively. In addition, the assimilation of AHI radiation data enhances the alignment of the hourly precipitation forecast trends at a single observation station with the actual observations.
Based on the assimilation module for Himawari-8 AHI radiance data in the weather research and forecasting model data assimilation (WRFDA) system with WRF model, this paper investigated the impact of direct assimilation of the radiance data of the three water vapor channels from Himawari-8 AHI on the forecast of a heavy rainfall in Northeast China. The results show that the quality control and bias correction are effective in eliminating anomalous data, making the mean of observation minus background (OMB) closer to 0, while the standard deviation and root mean square error of observation minus analysis (OMA) are further reduced. Compared with the control experiment, after assimilating AHI radiance data, the root mean square errors are reduced by about 0.2 m/s and 0.1 K in the middle and lower layers for the wind and temperature respectively, and the root mean square error of specific humidity decreases by about 0.03 g/kg in the lower layers. Besides, the assimilation of satellite data contributes positively to the increment of relative humidity in the central part of Jilin Province. The final forecast of 3 h precipitation is improved. The experiments involving satellite data assimilation show an improvement in the ETS and bias scores exceeding 0.1 of all thresholds. For the 50 mm threshold, the improvement rates for ETS and bias scores reach 64% and 58%, respectively. In addition, the assimilation of AHI radiation data enhances the alignment of the hourly precipitation forecast trends at a single observation station with the actual observations.
2025,19(2):64-72
,DOI: 10.12057/j.issn.1002-0799.2310.10001
Abstract:
The summer heavy precipitation in Northeast China is characterized by its localized nature, short duration, and high intensity. Such extreme weather events have always been a challenge for numerical forecasting. The traditional precipitation skill scores are often ineffective for verifying heavy precipitation processes in Northeast China due to the "double penalty" effect caused by minor spatial and temporal discrepancies. The ensemble precipitation spatial verification technique can effectively improve the validity of precipitation assessment. In this paper, the heavy precipitation events in Northeast China during the summer of 2018 were categorized into westward trough, shear line, and low vortex types,with typical precipitation cases selected for each weather process.A comparative analysis involving process analysis, ensemble equitable threat score (EETS), and the developed ensemble precipitation spatial verification method was conducted.The results indicate that EETS have certain evaluative capabilities when the precipitation area is extensive and the intensity is high. However, when heavy precipitation is scattered and point rainfall dominates, the inherent evaluation disadvantages become evident. Specifically, it becomes challenging to achieve a perfect match between forecasts and observations in point-to-point verification, leading to significant reliability and discernibility issues in the evaluation conclusions due to the serious "double penalty" problem. However, the ensemble precipitation spatial verification method can effectively compensate for these shortcomings, significantly enhancing the discernibility of the assessment.
The summer heavy precipitation in Northeast China is characterized by its localized nature, short duration, and high intensity. Such extreme weather events have always been a challenge for numerical forecasting. The traditional precipitation skill scores are often ineffective for verifying heavy precipitation processes in Northeast China due to the "double penalty" effect caused by minor spatial and temporal discrepancies. The ensemble precipitation spatial verification technique can effectively improve the validity of precipitation assessment. In this paper, the heavy precipitation events in Northeast China during the summer of 2018 were categorized into westward trough, shear line, and low vortex types,with typical precipitation cases selected for each weather process.A comparative analysis involving process analysis, ensemble equitable threat score (EETS), and the developed ensemble precipitation spatial verification method was conducted.The results indicate that EETS have certain evaluative capabilities when the precipitation area is extensive and the intensity is high. However, when heavy precipitation is scattered and point rainfall dominates, the inherent evaluation disadvantages become evident. Specifically, it becomes challenging to achieve a perfect match between forecasts and observations in point-to-point verification, leading to significant reliability and discernibility issues in the evaluation conclusions due to the serious "double penalty" problem. However, the ensemble precipitation spatial verification method can effectively compensate for these shortcomings, significantly enhancing the discernibility of the assessment.
2025,19(2):73-83
,DOI: 10.12057/j.issn.1002-0799.2308.31003
Abstract:
Using observation data of 125 radiosonde stations in China, comparing CMA-RA with ERA5, CFSv2, and MERRA-2 reanalysis data, the applicability of geopotential height, air temperature, relative humidity and wind speed in China of four types of reanalysis data were compared and evaluated from three aspects: overall effect, time series, and spatial distribution. The results showed that: (1) Reanalysis geopotential height data presents a negative bias generally. CMA-RA performs better than ERA5 in the lower-middle troposphere, while ERA5 performs better than CMA-RA in other isobaric surface, followed by CFSv2, and MERRA-2 performs relatively poorly. (2) Reanalysis air temperature data presents a negative bias generally. CMA-RA air temperature data performs best overall, and ERA5 is similar to CMA-RA, followed by MERRA-2 and CFSv2. (3) Reanalysis relative humidity data presents a positive bias generally, and MERRA-2 relative humidity data performs best overall, followed by ERA5. The spatial distribution of relative humidity data of CMA-RA is similar to that of CFSv2, which performs relatively well in the lower-middle troposphere but has a relatively significant positive bias in the upper-middle troposphere, and the bias in winter is higher than that in summer. (4) Reanalysis wind speed data presents a negative bias generally. CMA-RA wind speed data performs best overall, especially in the lower-middle troposphere, followed by ERA5, MERRA-2 performs worst, and the root mean square error of wind speed in winter half year is generally higher than that in summer half year for the four types of reanalysis data. The root mean square errors of temperature, relative humidity, and wind speed data of CMA-RA are relatively large between October 2019 and February 2020. Therefore, bias correction is needed before using to better improve data applicability.
Using observation data of 125 radiosonde stations in China, comparing CMA-RA with ERA5, CFSv2, and MERRA-2 reanalysis data, the applicability of geopotential height, air temperature, relative humidity and wind speed in China of four types of reanalysis data were compared and evaluated from three aspects: overall effect, time series, and spatial distribution. The results showed that: (1) Reanalysis geopotential height data presents a negative bias generally. CMA-RA performs better than ERA5 in the lower-middle troposphere, while ERA5 performs better than CMA-RA in other isobaric surface, followed by CFSv2, and MERRA-2 performs relatively poorly. (2) Reanalysis air temperature data presents a negative bias generally. CMA-RA air temperature data performs best overall, and ERA5 is similar to CMA-RA, followed by MERRA-2 and CFSv2. (3) Reanalysis relative humidity data presents a positive bias generally, and MERRA-2 relative humidity data performs best overall, followed by ERA5. The spatial distribution of relative humidity data of CMA-RA is similar to that of CFSv2, which performs relatively well in the lower-middle troposphere but has a relatively significant positive bias in the upper-middle troposphere, and the bias in winter is higher than that in summer. (4) Reanalysis wind speed data presents a negative bias generally. CMA-RA wind speed data performs best overall, especially in the lower-middle troposphere, followed by ERA5, MERRA-2 performs worst, and the root mean square error of wind speed in winter half year is generally higher than that in summer half year for the four types of reanalysis data. The root mean square errors of temperature, relative humidity, and wind speed data of CMA-RA are relatively large between October 2019 and February 2020. Therefore, bias correction is needed before using to better improve data applicability.
2025,19(2):84-91
,DOI: 10.12057/j.issn.1002-0799.2310.20001
Abstract:
Using hourly high-altitude and ground conventional observation data, as well as FY-4A satellite products, we analyzed the characteristics of the environmental field and cloud parameter evolution associated with a severe hailstorm in Yan'an. The results show that: (1) The strong convective process was characterized as a cold advection forcing type at high altitude, with the atmospheric stratification described as "dry and cold aloft, warm and humid below", and the ground convergence line triggered instability, leading to widespread thunderstorms. (2) The process was influenced by a highly organized medium-β scale convective system, and the steep drop in TBB values provided an early warning for hail occurrence more than 20 minutes in advance. Hailfall began when the TBB dropped below -32 ℃, and values below -70 ℃ were likely indicative of a hailstorm. (3) The high value area of cloud top height gradient at the front of the mature thunderstorm cloud cluster and the high value area of pressure gradient on the upwind side of the 100 or 200 hPa cloud area correspond to the hail area. The cloud top height exceeding 10 km was an important condition for hailfall onset. (4) The main body of mature thunderstorm cloud was composed of ice clouds. On the upwind side, a transition zone of cirrus, mixed and supercooled water cloudswas observed, and multi-layered cloud structures on the downwind side. (5) The convective initiation product can identify the incipient location of thunderstorm clouds in advance to some extent and predict the enhancement process of these clouds.
Using hourly high-altitude and ground conventional observation data, as well as FY-4A satellite products, we analyzed the characteristics of the environmental field and cloud parameter evolution associated with a severe hailstorm in Yan'an. The results show that: (1) The strong convective process was characterized as a cold advection forcing type at high altitude, with the atmospheric stratification described as "dry and cold aloft, warm and humid below", and the ground convergence line triggered instability, leading to widespread thunderstorms. (2) The process was influenced by a highly organized medium-β scale convective system, and the steep drop in TBB values provided an early warning for hail occurrence more than 20 minutes in advance. Hailfall began when the TBB dropped below -32 ℃, and values below -70 ℃ were likely indicative of a hailstorm. (3) The high value area of cloud top height gradient at the front of the mature thunderstorm cloud cluster and the high value area of pressure gradient on the upwind side of the 100 or 200 hPa cloud area correspond to the hail area. The cloud top height exceeding 10 km was an important condition for hailfall onset. (4) The main body of mature thunderstorm cloud was composed of ice clouds. On the upwind side, a transition zone of cirrus, mixed and supercooled water cloudswas observed, and multi-layered cloud structures on the downwind side. (5) The convective initiation product can identify the incipient location of thunderstorm clouds in advance to some extent and predict the enhancement process of these clouds.
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Display Method:
Abstract:
By utilizing daily maximum and minimum temperatures, sunshine duration data from 11 meteorological observation stations in Tangshan from 1990 to 2023, along with daily total solar radiation data from the Laoting Radiation Observation Station during the same period, the total solar radiation at each meteorological station in Tangshan (except Leting) was calculated. This calculation was based on a comprehensive model incorporating sunshine percentage and diurnal temperature range. The spatial and temporal distribution characteristics of solar radiation in Tangshan were analyzed using methods such as Empirical Orthogonal Function (EOF), Rotated Empirical Orthogonal Function (REOF), the Mann-Kendall mutation test, and Empirical Mode Decomposition (EMD). The results indicate that the first EOF mode reflects a consistent regional variation pattern, with a significant increase in the 1990s and a notable decrease in the early 21st century. An abrupt change in solar radiation occurred in 2006, exhibiting a “more-less-more” pattern near the change point. The second EOF mode reflects the east-west inverse variation characteristics of solar radiation, with interdecadal changes consistent with the first mode, but without abrupt changes. The REOF spatial patterns are categorized into six types: northern, western, northwestern, southern coastal, central-southern, and eastern spatial distributions. The optimal tilt angle for photovoltaic systems is 35°-37° (slightly below local latitude), yielding 5 717-6 253 MJ/m2 annual radiation.
By utilizing daily maximum and minimum temperatures, sunshine duration data from 11 meteorological observation stations in Tangshan from 1990 to 2023, along with daily total solar radiation data from the Laoting Radiation Observation Station during the same period, the total solar radiation at each meteorological station in Tangshan (except Leting) was calculated. This calculation was based on a comprehensive model incorporating sunshine percentage and diurnal temperature range. The spatial and temporal distribution characteristics of solar radiation in Tangshan were analyzed using methods such as Empirical Orthogonal Function (EOF), Rotated Empirical Orthogonal Function (REOF), the Mann-Kendall mutation test, and Empirical Mode Decomposition (EMD). The results indicate that the first EOF mode reflects a consistent regional variation pattern, with a significant increase in the 1990s and a notable decrease in the early 21st century. An abrupt change in solar radiation occurred in 2006, exhibiting a “more-less-more” pattern near the change point. The second EOF mode reflects the east-west inverse variation characteristics of solar radiation, with interdecadal changes consistent with the first mode, but without abrupt changes. The REOF spatial patterns are categorized into six types: northern, western, northwestern, southern coastal, central-southern, and eastern spatial distributions. The optimal tilt angle for photovoltaic systems is 35°-37° (slightly below local latitude), yielding 5 717-6 253 MJ/m2 annual radiation.
Abstract:
Using NCEP/NCAR reanalysis data, and the HYSPLIT model was mainly used to simulate the water vapor source, water vapor transport, and their contributions of 45 snowstorms weather processes which occurred at the Tianshan Mountains from 1991 to 2020. The results showed that: the water vapor during the snowstorms at the Tianshan Mountains mainly comed from the Atlantic Ocean, and which was supplemented by water vapor from Arabian Sea, the Red Sea, the Mediterranean Sea and other places and so on.The western boundary, the middle and lower layers of the northern boundary, and the middle and upper layers of the southern boundary were water vapor inputs, with the northern boundary having the most input. The HYSPLIT model analysis showed that water vapor from Europe and Central Asia was mainly transported to 700hPa and below; Mainly transported to over 700hPa from the Mediterranean and Black Sea, as well as from the Atlantic and its coasts; 80% of water vapor was concentrated in the lower troposphere. After the water vapor in each source area reaches the key area with the westerly airflow, it mainly enters the blizzard area along the westward (southwest) and northwest paths. The westward (southwest) path at 500hPa was the main path, and the water vapor transported by the northwest path at 700hPa and below was the dominant path. Based on the above features, the 3D structure of water vapor contribution during the snowstorms process at the Tianshan Mountains was established.
Using NCEP/NCAR reanalysis data, and the HYSPLIT model was mainly used to simulate the water vapor source, water vapor transport, and their contributions of 45 snowstorms weather processes which occurred at the Tianshan Mountains from 1991 to 2020. The results showed that: the water vapor during the snowstorms at the Tianshan Mountains mainly comed from the Atlantic Ocean, and which was supplemented by water vapor from Arabian Sea, the Red Sea, the Mediterranean Sea and other places and so on.The western boundary, the middle and lower layers of the northern boundary, and the middle and upper layers of the southern boundary were water vapor inputs, with the northern boundary having the most input. The HYSPLIT model analysis showed that water vapor from Europe and Central Asia was mainly transported to 700hPa and below; Mainly transported to over 700hPa from the Mediterranean and Black Sea, as well as from the Atlantic and its coasts; 80% of water vapor was concentrated in the lower troposphere. After the water vapor in each source area reaches the key area with the westerly airflow, it mainly enters the blizzard area along the westward (southwest) and northwest paths. The westward (southwest) path at 500hPa was the main path, and the water vapor transported by the northwest path at 700hPa and below was the dominant path. Based on the above features, the 3D structure of water vapor contribution during the snowstorms process at the Tianshan Mountains was established.
Abstract:
Utilizing the surface radiation data from Nyingchi Airport in the typical river valley of the lower reaches of the Brahmaputra River in 2014, and combining it with the clear-sky index to identify sunny and cloudy days, this study analyzed the monthly variations of surface radiation components, surface albedo, and diurnal variations under typical sunny and cloudy conditions in different seasons at that location. The results show that: (1) The monthly average variations in the components of surface radiation show that, except for shortwave radiation, all other components exhibit distinct unimodal monthly changes. The monthly maximum averages of surface longwave radiation, atmospheric longwave radiation, and net radiation occur from June to August, at 414.1 W/m2, 371.2 W/m2, and 151.4 W/m2 respectively. The monthly average maximum of reflected shortwave radiation occurs in March, at 98.4 W/m2. Due to the higher cloud cover during the summer months and a significantly higher number of overcast days compared to the average for the other 14 years, the monthly maximum of total solar radiation occurs in October, at 560.3 W/m2 .(2) The diurnal variations of radiation components on typical sunny days exhibit a smooth single-peak shape, while on cloudy days, they show an irregular multi-peak shape. Compared to sunny days, cloudy days show enhanced atmospheric longwave radiation, which decreases in the afternoon due to local circulations. Other radiation intensities significantly weaken during the day, with surface longwave radiation and net radiation showing a notable increase at night.(3) The monthly average diurnal variation of surface albedo presents a "U"-shaped curve, decreasing first and then increasing. The seasonal variation follows the order of winter > autumn > spring > summer, with the maximum and minimum monthly averages occurring in February and June, at 0.25 and 0.14, respectively.
Utilizing the surface radiation data from Nyingchi Airport in the typical river valley of the lower reaches of the Brahmaputra River in 2014, and combining it with the clear-sky index to identify sunny and cloudy days, this study analyzed the monthly variations of surface radiation components, surface albedo, and diurnal variations under typical sunny and cloudy conditions in different seasons at that location. The results show that: (1) The monthly average variations in the components of surface radiation show that, except for shortwave radiation, all other components exhibit distinct unimodal monthly changes. The monthly maximum averages of surface longwave radiation, atmospheric longwave radiation, and net radiation occur from June to August, at 414.1 W/m2, 371.2 W/m2, and 151.4 W/m2 respectively. The monthly average maximum of reflected shortwave radiation occurs in March, at 98.4 W/m2. Due to the higher cloud cover during the summer months and a significantly higher number of overcast days compared to the average for the other 14 years, the monthly maximum of total solar radiation occurs in October, at 560.3 W/m2 .(2) The diurnal variations of radiation components on typical sunny days exhibit a smooth single-peak shape, while on cloudy days, they show an irregular multi-peak shape. Compared to sunny days, cloudy days show enhanced atmospheric longwave radiation, which decreases in the afternoon due to local circulations. Other radiation intensities significantly weaken during the day, with surface longwave radiation and net radiation showing a notable increase at night.(3) The monthly average diurnal variation of surface albedo presents a "U"-shaped curve, decreasing first and then increasing. The seasonal variation follows the order of winter > autumn > spring > summer, with the maximum and minimum monthly averages occurring in February and June, at 0.25 and 0.14, respectively.
Abstract:
This article proposes a combined Long Short Term Memory Network(LSTM) and K-Nearest Neighbor (KNN) model for predicting hydrological flow, and analyzes the daily runoff of the Jimai,Jungong and Tangnaihai hydrological sections in the source area of the Yellow River.First,the dynamic attributes of the watershed are constructed by using meteorological factors such as temperature and precipitation,Using historical meteorological and hydrological and geographic information data to build the static attribute characteristics of river basin,The LSTM model is used for feature optimization,Determine the optimal model TOPO_ CLIM_ SOIL-LSTM, it is used for actual daily runoff forecast,Then the KNN algorithm is used to correct the prediction results in real time.The results show that,Model TOPO_CLIM_SOIL-LSTM with river basin attribute characteristics can better learn the relationship between rainfall and runoff,It can effectively solve the problem of predicting runoff jump in low flow section,After revising the predicted flow with KNN model,The accuracy rate of daily runoff forecast at Jimai,Jungong and Tangnaihai stations in the next day has reached over 93%,Nash coefficient increased by 6.45%,12.5% and 18.07% respectively,Effectively improve the accuracy of daily runoff forecast.
This article proposes a combined Long Short Term Memory Network(LSTM) and K-Nearest Neighbor (KNN) model for predicting hydrological flow, and analyzes the daily runoff of the Jimai,Jungong and Tangnaihai hydrological sections in the source area of the Yellow River.First,the dynamic attributes of the watershed are constructed by using meteorological factors such as temperature and precipitation,Using historical meteorological and hydrological and geographic information data to build the static attribute characteristics of river basin,The LSTM model is used for feature optimization,Determine the optimal model TOPO_ CLIM_ SOIL-LSTM, it is used for actual daily runoff forecast,Then the KNN algorithm is used to correct the prediction results in real time.The results show that,Model TOPO_CLIM_SOIL-LSTM with river basin attribute characteristics can better learn the relationship between rainfall and runoff,It can effectively solve the problem of predicting runoff jump in low flow section,After revising the predicted flow with KNN model,The accuracy rate of daily runoff forecast at Jimai,Jungong and Tangnaihai stations in the next day has reached over 93%,Nash coefficient increased by 6.45%,12.5% and 18.07% respectively,Effectively improve the accuracy of daily runoff forecast.
Abstract:
Based on multi-source new-type detection data from S-band dual-polarization weather radar, millimeter wave cloud radar, microwave radiometer and laser aerosol radar, environmental background and structure characteristics of the precipitation cloud in a local short time rainstorm occurred in Zhejiang Jinhua on 6 August 2023 were diagnosed. The results show that: (1) Temperature and humidity stratification of cold and dry air above but warm and wet air below provides the unstable condition; Surface medium scale cold front and cyclonic vortex provide favorable dynamic and thermodynamic trigger mechanisms. (2) Both differential reflectivity (ZDR) and specific differential phase (KDP) increase rapidly, leading to the formation of ZDR and KDP columns with extended height close to 0 ℃ layer, which indicate the existence of strong updraft and precipitation intensity and can provide an important reference for short time rainstorm warning. (3) Millimeter wave cloud radar can detect development of the convective cloud 20 min in advance; Rapid extension of echo top height to 12 km, rapid increase of reflectivity factor to more than 30 dBZ, and rapid increase of radial velocity to 10 m·s-1 in the upper layer have certain indicative significance for short time rainstorm. (4) Integrated Water Vapor and Integrated Liquid Water Content of microwave radiometer jump to 90 kg·m-2 and 10 g·m-2 respectively and maintain for a long time, which can be used as a reference index for short time rainstorm warning. (5) Laser aerosol radar with “high extinction and high depolarization” spectra of extinction coefficient greater than 2 and depolarization ratio greater than 0.3 can indicate short time rainstorm well.
Based on multi-source new-type detection data from S-band dual-polarization weather radar, millimeter wave cloud radar, microwave radiometer and laser aerosol radar, environmental background and structure characteristics of the precipitation cloud in a local short time rainstorm occurred in Zhejiang Jinhua on 6 August 2023 were diagnosed. The results show that: (1) Temperature and humidity stratification of cold and dry air above but warm and wet air below provides the unstable condition; Surface medium scale cold front and cyclonic vortex provide favorable dynamic and thermodynamic trigger mechanisms. (2) Both differential reflectivity (ZDR) and specific differential phase (KDP) increase rapidly, leading to the formation of ZDR and KDP columns with extended height close to 0 ℃ layer, which indicate the existence of strong updraft and precipitation intensity and can provide an important reference for short time rainstorm warning. (3) Millimeter wave cloud radar can detect development of the convective cloud 20 min in advance; Rapid extension of echo top height to 12 km, rapid increase of reflectivity factor to more than 30 dBZ, and rapid increase of radial velocity to 10 m·s-1 in the upper layer have certain indicative significance for short time rainstorm. (4) Integrated Water Vapor and Integrated Liquid Water Content of microwave radiometer jump to 90 kg·m-2 and 10 g·m-2 respectively and maintain for a long time, which can be used as a reference index for short time rainstorm warning. (5) Laser aerosol radar with “high extinction and high depolarization” spectra of extinction coefficient greater than 2 and depolarization ratio greater than 0.3 can indicate short time rainstorm well.
Abstract:
Based on the hourly precipitation data of 3,795 national and regional meteorological stations in the Eastern Sichuan Basin from April to September in 2016-2022, we used the percentile method to determine the threshold of extreme heavy precipitation at each station"s sub-daily scale (1、3、6、12 h), analyzing and studying the characteristics of extreme heavy precipitation at the sub-daily scale in this region. The results indicated that: (1) Due to significant differences in terrain and landforms in the region, there were significant differences in the extreme heavy rainfall areas on the sub-daily scale. The average threshold values for the 98.5th percentile at 1, 3, 6, and 12 h were 42 mm, 68, 92, and 118 mm. (2) The short-term extreme heavy precipitation in the region mainly occurred from June to August, especially in July, followed by August and June. In the aspect of diurnal variation, the extreme heavy rainfall was more likely to occur in the second half of the night (2:00-8:00) than other time periods, and regional extreme heavy rainfall weather processes had the same characteristics. (3) In the central and northern regions of Sichuan and north of the Yangtze River in Chongqing, there was a high incidence rate of sub-daily scale extreme heavy precipitation. The main center of regional short-term extreme heavy precipitation weather processes was located in the central eastern part of Sichuan to the western part of Chongqing. The main influence systems that produced the regional short-term extreme heavy rainfall weather process in the eastern Sichuan basin included the southwest vortex and the surface cold front. (4) The threshold for extreme heavy rainfall on sub-daily scale in the region gradually increased from the ground to an altitude of 400～500 meters, and then generally decreased with changes in altitude, with weak fluctuations around 800 meters and 1500 meters.
Based on the hourly precipitation data of 3,795 national and regional meteorological stations in the Eastern Sichuan Basin from April to September in 2016-2022, we used the percentile method to determine the threshold of extreme heavy precipitation at each station"s sub-daily scale (1、3、6、12 h), analyzing and studying the characteristics of extreme heavy precipitation at the sub-daily scale in this region. The results indicated that: (1) Due to significant differences in terrain and landforms in the region, there were significant differences in the extreme heavy rainfall areas on the sub-daily scale. The average threshold values for the 98.5th percentile at 1, 3, 6, and 12 h were 42 mm, 68, 92, and 118 mm. (2) The short-term extreme heavy precipitation in the region mainly occurred from June to August, especially in July, followed by August and June. In the aspect of diurnal variation, the extreme heavy rainfall was more likely to occur in the second half of the night (2:00-8:00) than other time periods, and regional extreme heavy rainfall weather processes had the same characteristics. (3) In the central and northern regions of Sichuan and north of the Yangtze River in Chongqing, there was a high incidence rate of sub-daily scale extreme heavy precipitation. The main center of regional short-term extreme heavy precipitation weather processes was located in the central eastern part of Sichuan to the western part of Chongqing. The main influence systems that produced the regional short-term extreme heavy rainfall weather process in the eastern Sichuan basin included the southwest vortex and the surface cold front. (4) The threshold for extreme heavy rainfall on sub-daily scale in the region gradually increased from the ground to an altitude of 400～500 meters, and then generally decreased with changes in altitude, with weak fluctuations around 800 meters and 1500 meters.
Abstract:
This study investigates the retrieval of atmospheric precipitable water vapor (PWV) through the application of the Precise Point Positioning (PPP) algorithm utilizing the Global Navigation Satellite System (GNSS) data from Hechi, Baoshan, and Haikou stations. We conducted six experimental tests to analyze the effects of satellite data quality control on PWV retrieval accuracy, comparing our findings with sounding data and operational PWV products from the China Meteorological Administration. The results indicate that implementing effective quality control substantially improves inversion accuracy, eliminating satellite data with residual error more than 3 times before entering the filter and residual sigma values greater than 2 after entering the filter, which enhances correlation coefficients with sounding or PWV products by 0.03 to 0.25 while decreasing root mean square error by 0.54 to 10.7 mm. Optimal inversion accuracy is obtained by filtering out satellites with residual errors exceeding three times the threshold prior to analysis, resulting in an average correlation coefficient above 0.93 and a mean error ranging from -1.26 to -1.91 mm. This approach successfully mitigates the challenges associated with the low temporal resolution of conventional PWV data. The PWV retrieved via the PPP method demonstrates a enhanced sensitivity to short-term heavy precipitation events compared to other products, exhibiting rapid changes of 10 to 15 mm within 10 to 30 minutes before and after the rainfall,which can be used as an auxiliary discriminating condition for local short-term heavy precipitation forecast.
This study investigates the retrieval of atmospheric precipitable water vapor (PWV) through the application of the Precise Point Positioning (PPP) algorithm utilizing the Global Navigation Satellite System (GNSS) data from Hechi, Baoshan, and Haikou stations. We conducted six experimental tests to analyze the effects of satellite data quality control on PWV retrieval accuracy, comparing our findings with sounding data and operational PWV products from the China Meteorological Administration. The results indicate that implementing effective quality control substantially improves inversion accuracy, eliminating satellite data with residual error more than 3 times before entering the filter and residual sigma values greater than 2 after entering the filter, which enhances correlation coefficients with sounding or PWV products by 0.03 to 0.25 while decreasing root mean square error by 0.54 to 10.7 mm. Optimal inversion accuracy is obtained by filtering out satellites with residual errors exceeding three times the threshold prior to analysis, resulting in an average correlation coefficient above 0.93 and a mean error ranging from -1.26 to -1.91 mm. This approach successfully mitigates the challenges associated with the low temporal resolution of conventional PWV data. The PWV retrieved via the PPP method demonstrates a enhanced sensitivity to short-term heavy precipitation events compared to other products, exhibiting rapid changes of 10 to 15 mm within 10 to 30 minutes before and after the rainfall,which can be used as an auxiliary discriminating condition for local short-term heavy precipitation forecast.
Abstract:
Ground-level O3 is a major component of photochemical pollution and poses significant risks to human health and ecosystems. To accurately predict O3 concentration variations in Shanghai, this study proposed a random forest prediction model for O3 concentrations optimized through the fuzzy C-means clustering algorithm, based on monitoring data of six air pollutant and weather forecast data from 2014 to 2020 in Shanghai. Firstly, two clustering factors were selected using cross-correlation analysis. Then, O3 concentration was categorized into three types using the fuzzy C-means clustering algorithm. Finally, a random forest model was established to predict O3 concentration, and the predictive performance before and after clustering was compared. The results show that the O3 concentration and PM10 concentration of the previous one day have the greatest influence on the O3 concentration of the prediction day, and O3 concentration variation is notably affected by the month. After fuzzy C-means clustering, the mean absolute error and root mean square error of the predicted O3_8h concentration decreased by 10.5% and 8.8%, respectively. The random forest model improves the accuracy of O3 concentration prediction, and the coefficient of determination R2 increases after clustering, demonstrating that this model has high practical value for predicting O3 pollution in Shanghai.
Ground-level O3 is a major component of photochemical pollution and poses significant risks to human health and ecosystems. To accurately predict O3 concentration variations in Shanghai, this study proposed a random forest prediction model for O3 concentrations optimized through the fuzzy C-means clustering algorithm, based on monitoring data of six air pollutant and weather forecast data from 2014 to 2020 in Shanghai. Firstly, two clustering factors were selected using cross-correlation analysis. Then, O3 concentration was categorized into three types using the fuzzy C-means clustering algorithm. Finally, a random forest model was established to predict O3 concentration, and the predictive performance before and after clustering was compared. The results show that the O3 concentration and PM10 concentration of the previous one day have the greatest influence on the O3 concentration of the prediction day, and O3 concentration variation is notably affected by the month. After fuzzy C-means clustering, the mean absolute error and root mean square error of the predicted O3_8h concentration decreased by 10.5% and 8.8%, respectively. The random forest model improves the accuracy of O3 concentration prediction, and the coefficient of determination R2 increases after clustering, demonstrating that this model has high practical value for predicting O3 pollution in Shanghai.
Abstract:
An analysis of a high-voltage power line icing event in Shanxi province was conducted using conventional meteorological observation data, FNL and EAR5 reanalysis data. The icing thickness was simulated using the Jones icing model coupled with the mesoscale numerical model WRF. The results showed that: (1) This icing event was a typical precipitation-type icing event caused by freezing rain, with a "cold-warm-cold" stratification structure formed by the interaction of cold and warm air masses serving as the meteorological background. (2) Overall, the simulated precipitation and surface wind fields by WRF show good agreement with the observations, indicating their suitability as input values for the icing model.(3)The Jones icing model simulation showed that icing on the power lines began at 00:00 on the 13th, with ice thickness rapidly increasing between 06:00—10:00 and 16:00—19:00, reaching a maximum thickness of 16.35 mm at 19:00.(4) Although the ice thickness simulated by the Jones icing model coupled with WRF model was slightly less than observed, the timing of ice thickness exceeding the equipment threshold matched the actual power outage times, demonstrating the model"s relevance and potential accuracy in forecasting such icing events.
An analysis of a high-voltage power line icing event in Shanxi province was conducted using conventional meteorological observation data, FNL and EAR5 reanalysis data. The icing thickness was simulated using the Jones icing model coupled with the mesoscale numerical model WRF. The results showed that: (1) This icing event was a typical precipitation-type icing event caused by freezing rain, with a "cold-warm-cold" stratification structure formed by the interaction of cold and warm air masses serving as the meteorological background. (2) Overall, the simulated precipitation and surface wind fields by WRF show good agreement with the observations, indicating their suitability as input values for the icing model.(3)The Jones icing model simulation showed that icing on the power lines began at 00:00 on the 13th, with ice thickness rapidly increasing between 06:00—10:00 and 16:00—19:00, reaching a maximum thickness of 16.35 mm at 19:00.(4) Although the ice thickness simulated by the Jones icing model coupled with WRF model was slightly less than observed, the timing of ice thickness exceeding the equipment threshold matched the actual power outage times, demonstrating the model"s relevance and potential accuracy in forecasting such icing events.
Abstract:
Based on the average hourly wind speed at a height of 10m of four representative meteorological stations in northern Ningxia, including Yinchuan, Shizuishan, Taole, and Qingtongxia, and the hourly total irradiance of Yinchuan station from 2007 to 2020, analyzed the changes in the occurrence duration and frequency of three specific weather types: little wind, little sunlight, little wind with little sunlight. We obtained the climate characteristics as follows: 1) The average daily duration of little wind with little sunlight is 14.3 h, which is basically normal distribution. Compared with a single little wind or little sunlight duration, they have decreased by nearly 4 hours and 3 hours respectively, which indicates that the complementarity of wind and solar energy resources is good in the area. 2) The average duration of little wind with little sunlight is the lowest from March to May, which is most conducive to wind and solar complementary power generation. And it is the highest from September to January of the following year, which is adverse to new energy generation. 3) The occurrence frequency of three types of weather decreases significantly with the duration increasing. Autumn and winter are their long-term and frequent seasons. According to the above characteristics, different reference suggestions are proposed for new energy planning, consumption, and storage configuration to reduce the risk of power shortage caused by long-term lack of wind and solar resources due to little wind with little sunlight weather.
Based on the average hourly wind speed at a height of 10m of four representative meteorological stations in northern Ningxia, including Yinchuan, Shizuishan, Taole, and Qingtongxia, and the hourly total irradiance of Yinchuan station from 2007 to 2020, analyzed the changes in the occurrence duration and frequency of three specific weather types: little wind, little sunlight, little wind with little sunlight. We obtained the climate characteristics as follows: 1) The average daily duration of little wind with little sunlight is 14.3 h, which is basically normal distribution. Compared with a single little wind or little sunlight duration, they have decreased by nearly 4 hours and 3 hours respectively, which indicates that the complementarity of wind and solar energy resources is good in the area. 2) The average duration of little wind with little sunlight is the lowest from March to May, which is most conducive to wind and solar complementary power generation. And it is the highest from September to January of the following year, which is adverse to new energy generation. 3) The occurrence frequency of three types of weather decreases significantly with the duration increasing. Autumn and winter are their long-term and frequent seasons. According to the above characteristics, different reference suggestions are proposed for new energy planning, consumption, and storage configuration to reduce the risk of power shortage caused by long-term lack of wind and solar resources due to little wind with little sunlight weather.
Abstract:
Based on the data from Heyuan meteorological station and the observation data of "Huinantian" in Dongyuan from 2015 to 2021, a recurrent neural networks (RNN) regression prediction model is constructed to predict the indoor surface temperatures for the next 24 and 48 hours , and evaluated on the data from 2022. By combining artificial intelligence with numerical forecasting products, the level of "Huinantian" prediction is improved. The verification results show that the Gated Recurrent Unit (GRU) performs better than traditional linear model. Sensitivity experiments demonstrate that more accurate numerical forecast results enhance the robustness of the GRU model. This method combines artificial intelligence and numerical forecasting, whose accuracy depends on the precision of numerical forecasts for dew point temperature and air temperature.
Based on the data from Heyuan meteorological station and the observation data of "Huinantian" in Dongyuan from 2015 to 2021, a recurrent neural networks (RNN) regression prediction model is constructed to predict the indoor surface temperatures for the next 24 and 48 hours , and evaluated on the data from 2022. By combining artificial intelligence with numerical forecasting products, the level of "Huinantian" prediction is improved. The verification results show that the Gated Recurrent Unit (GRU) performs better than traditional linear model. Sensitivity experiments demonstrate that more accurate numerical forecast results enhance the robustness of the GRU model. This method combines artificial intelligence and numerical forecasting, whose accuracy depends on the precision of numerical forecasts for dew point temperature and air temperature.
Abstract:
Using FY-4A satellite and radar data, regional automatic station data, European Center ERA-5 reanalysis data, the organizational structure characteristics of the mesoscale convective system at the edge of the subtropical high in the northeast of Guanzhong, Shaanxi Province on July 14-15, 2022 and the causes of the local special heavy rainstorm were studied. The results indicated that the extreme precipitation was caused by α,β and γ mesoscale convective cells. The northeast of Guanzhong is located in the warm zone of the Subtropical High. The shear of the 700 hPa low-vortex was maintained in the central and northern parts of Shaanxi, with unstable environmental conditions of high temperature, high humidity near the surface. The strengthening of low-level easterly wind brought about continuous water vapor convergence, the maintenance and enhancement of medium intensity vertical wind shear caused helicity growth, and the maintenance of strong vortex movement were important mechanisms for the consolidation and enhancement of rainstorm cloud clusters. The backward propagation of mesoscale convective cells was caused by the cyclonic convergence and maintenance of radar wind fields, resulting in the "train effect" of the backward propagation of inclined deep moist convective cells with low centroids and high cloud tops. The continuous and efficient precipitation was the direct cause of the heavy precipitation in Pucheng, northeastern Guanzhong, Shaanxi.
Using FY-4A satellite and radar data, regional automatic station data, European Center ERA-5 reanalysis data, the organizational structure characteristics of the mesoscale convective system at the edge of the subtropical high in the northeast of Guanzhong, Shaanxi Province on July 14-15, 2022 and the causes of the local special heavy rainstorm were studied. The results indicated that the extreme precipitation was caused by α,β and γ mesoscale convective cells. The northeast of Guanzhong is located in the warm zone of the Subtropical High. The shear of the 700 hPa low-vortex was maintained in the central and northern parts of Shaanxi, with unstable environmental conditions of high temperature, high humidity near the surface. The strengthening of low-level easterly wind brought about continuous water vapor convergence, the maintenance and enhancement of medium intensity vertical wind shear caused helicity growth, and the maintenance of strong vortex movement were important mechanisms for the consolidation and enhancement of rainstorm cloud clusters. The backward propagation of mesoscale convective cells was caused by the cyclonic convergence and maintenance of radar wind fields, resulting in the "train effect" of the backward propagation of inclined deep moist convective cells with low centroids and high cloud tops. The continuous and efficient precipitation was the direct cause of the heavy precipitation in Pucheng, northeastern Guanzhong, Shaanxi.
Abstract:
The occurrence and impact of extreme drought events are spatiotemporal differences. Expanding the information on extreme drought events on the spatio-temporal scale is helpful to understand their occurrence characteristics and accurately assess their impact. In this study, tree-ring samples of Picea schrenkiana Fisch.et Mey were collected in Xiaerxili, Xinjiang. The tree-ring width chronology was established, the relationship between radial growth and climate factors was analyzed to explore historical extreme climate events and their impacts. The results showed as follows: (1) There was a significant negative correlation between radial growth and vapor pressure deficit (VPD) in April, and this relationship was significantly enhanced recently; (2) A major forest growth decline occurred from 1850 to 1870, during which the radial growth rate of trees was the lowest over the past 300 years; (3) In the late period of forest growth decline event, some trees exhibited growth release phenomenon. These results indicate that the Xiaerxili experienced a super persistent drought event in the 1850s and 1860s, characterized primarily by atmospheric drought, which resulted in the radial growth of trees was inhibited or some trees even died. With the increasing trend of regional VPD, the risk of extreme drought events in Xiaerxili will also increase, and the risk of growth decline events and even large-scale death of Picea schrenkiana will further increase. It is suggested to strengthen the real-time monitoring of forest growth in Xiaerxili, accurately assess the health risks to forest growth, and develop corresponding measures for drought and disaster prevention.
The occurrence and impact of extreme drought events are spatiotemporal differences. Expanding the information on extreme drought events on the spatio-temporal scale is helpful to understand their occurrence characteristics and accurately assess their impact. In this study, tree-ring samples of Picea schrenkiana Fisch.et Mey were collected in Xiaerxili, Xinjiang. The tree-ring width chronology was established, the relationship between radial growth and climate factors was analyzed to explore historical extreme climate events and their impacts. The results showed as follows: (1) There was a significant negative correlation between radial growth and vapor pressure deficit (VPD) in April, and this relationship was significantly enhanced recently; (2) A major forest growth decline occurred from 1850 to 1870, during which the radial growth rate of trees was the lowest over the past 300 years; (3) In the late period of forest growth decline event, some trees exhibited growth release phenomenon. These results indicate that the Xiaerxili experienced a super persistent drought event in the 1850s and 1860s, characterized primarily by atmospheric drought, which resulted in the radial growth of trees was inhibited or some trees even died. With the increasing trend of regional VPD, the risk of extreme drought events in Xiaerxili will also increase, and the risk of growth decline events and even large-scale death of Picea schrenkiana will further increase. It is suggested to strengthen the real-time monitoring of forest growth in Xiaerxili, accurately assess the health risks to forest growth, and develop corresponding measures for drought and disaster prevention.
Abstract:
Wind damage is one of the major natural disasters during the cotton seeding stage in Xinjiang. Clarifying the evolution characteristics of wind disaster in cotton seedling stage in this region can provide a scientific basis for refined cotton meteorological services and disaster prevention and mitigation strategies. Based on the daily maximum wind speed of 40 national basic meteorological stations in Xinjiang from 2005 to 2022， this study analyzed the variation trend and spatial-temporal distribution of the daily maximum wind speed， the cumulative number of days with winds ≥ force 5， and the number of days with winds at different grades during the cotton seeding stage. The results showed that from 2005 to 2022， the daily maximum wind speed and the cumulative number of days with winds ≥ force 5 during the cotton seeding stage in Xinjiang showed an overall upward trend， particularly evident in southern Xinjiang. Wind damage during the cotton seedling stage was primarily caused by force 5 wind events， followed by force 6 wind events， while events with winds ≥ force 7 occurred less frequently， with high incidence areas were concentrated in the cotton regions of northern and eastern Xinjiang. Given the threat of wind damage to cotton production， it is suggested to implement targeted disaster prevention and mitigation measures， including strengthening the construction of shelter forests， setting up windbreak isolation belt， and timely responding to meteorological early warnings， to ensure the safety and stability of cotton industry.
Wind damage is one of the major natural disasters during the cotton seeding stage in Xinjiang. Clarifying the evolution characteristics of wind disaster in cotton seedling stage in this region can provide a scientific basis for refined cotton meteorological services and disaster prevention and mitigation strategies. Based on the daily maximum wind speed of 40 national basic meteorological stations in Xinjiang from 2005 to 2022， this study analyzed the variation trend and spatial-temporal distribution of the daily maximum wind speed， the cumulative number of days with winds ≥ force 5， and the number of days with winds at different grades during the cotton seeding stage. The results showed that from 2005 to 2022， the daily maximum wind speed and the cumulative number of days with winds ≥ force 5 during the cotton seeding stage in Xinjiang showed an overall upward trend， particularly evident in southern Xinjiang. Wind damage during the cotton seedling stage was primarily caused by force 5 wind events， followed by force 6 wind events， while events with winds ≥ force 7 occurred less frequently， with high incidence areas were concentrated in the cotton regions of northern and eastern Xinjiang. Given the threat of wind damage to cotton production， it is suggested to implement targeted disaster prevention and mitigation measures， including strengthening the construction of shelter forests， setting up windbreak isolation belt， and timely responding to meteorological early warnings， to ensure the safety and stability of cotton industry.
Abstract:
Using NCEP (National Centers for Environmental Prediction) atmospheric reanalysis data and the monthly occurrence records of floating dust days in the Tarim River Basin from 1988 to 2021, this research investigates the variation characteristics of the subtropical westerly jet stream (20°-40°N, 70°-95°E) and its relationship with the floating dust weather in the basin during spring. The results show that, there has been a northward shift in the axis of the subtropical westerly jet stream during spring, with a weakening trend in the strength of the jet over these years. The interannual zonal position of the jet stream axis was significantly negatively correlated with the interannual days of the floating dust in the basin. In the years with the more floating dust events in the basin during spring, compared with the less floating dust year, the subtropical westerly jet stream shifts southward, and the zonal wind speed at 200 hPa on the northern side of the jet is relatively high, particularly over the Tarim River Basin, where the wind speed increase is more obvious， the distribution of wind speed field and geopotential height fields at 500 hPa and 850 hPa is also conducive to an increase in surface wind speeds in the basin. As the upper-level westerly wind speed increases, momentum is transferred downward, causing strong surface winds in the Tarim River Basin, which lead to the frequent occurrence of floating dust weather.
Using NCEP (National Centers for Environmental Prediction) atmospheric reanalysis data and the monthly occurrence records of floating dust days in the Tarim River Basin from 1988 to 2021, this research investigates the variation characteristics of the subtropical westerly jet stream (20°-40°N, 70°-95°E) and its relationship with the floating dust weather in the basin during spring. The results show that, there has been a northward shift in the axis of the subtropical westerly jet stream during spring, with a weakening trend in the strength of the jet over these years. The interannual zonal position of the jet stream axis was significantly negatively correlated with the interannual days of the floating dust in the basin. In the years with the more floating dust events in the basin during spring, compared with the less floating dust year, the subtropical westerly jet stream shifts southward, and the zonal wind speed at 200 hPa on the northern side of the jet is relatively high, particularly over the Tarim River Basin, where the wind speed increase is more obvious， the distribution of wind speed field and geopotential height fields at 500 hPa and 850 hPa is also conducive to an increase in surface wind speeds in the basin. As the upper-level westerly wind speed increases, momentum is transferred downward, causing strong surface winds in the Tarim River Basin, which lead to the frequent occurrence of floating dust weather.
Abstract:
Based on daily data from 12 meteorological stations in Zunyi (1981-2023), obtained AET and PET data, Analyzed using trend analysis, change point tests, and PCA, Studying Zunyi"s drought patterns under global warming and its agricultural impacts to inform drought mitigation strategies. Results show central Zunyi becoming "warmer and drier," while edges trend "warmer and wetter" over 43 years. Before 2019, non-drought; post-2019, drought characteristics, intensified post-2016, with deepening impacts expected.Spatially, Zunyi shows non-drought traits; AET and PET difference decreases from SW to NE and NW to SE, trending downward.Zunyi"s drought mainly hurts maize production now, worsening with climate change, necessitating proactive measures.
Based on daily data from 12 meteorological stations in Zunyi (1981-2023), obtained AET and PET data, Analyzed using trend analysis, change point tests, and PCA, Studying Zunyi"s drought patterns under global warming and its agricultural impacts to inform drought mitigation strategies. Results show central Zunyi becoming "warmer and drier," while edges trend "warmer and wetter" over 43 years. Before 2019, non-drought; post-2019, drought characteristics, intensified post-2016, with deepening impacts expected.Spatially, Zunyi shows non-drought traits; AET and PET difference decreases from SW to NE and NW to SE, trending downward.Zunyi"s drought mainly hurts maize production now, worsening with climate change, necessitating proactive measures.
Abstract:
Through the combination of shadow operation effect assessment and long time series remote sensing data， the precipitation of Shiyang River Basin from 2010 to 2020 was deeply analyzed， and the effect of artificial rainfall enhancement after increasing the operation point and operation amount was evaluated. At the same time， based on the long-term Landsat remote sensing data of Google Earth Engine platform， a pixel binary model was established to quantitatively analyze the vegetation cover and its spatio-temporal dynamic changes in Shiyang River Basin before and after artificial rainfall enhancement. The results showed that the average relative rainfall enhancement effect was 20.8% （P<0.1%）. During the period of 2010-2020， 1017.56 km2 of sandy or bare land will be transformed into grassland. Through the combined effect of artificial rain enhancement and natural precipitation， the vegetation coverage area of Shiyang River Basin increased from 20.2% before rain enhancement to 27.24% after rain enhancement in 2010， and the improvement was more obvious. Artificial rain enhancement technology has played a positive role in improving the ecological environment of the Shiyang River basin， and has made important contributions to the local ecological balance and sustainable development.
Through the combination of shadow operation effect assessment and long time series remote sensing data， the precipitation of Shiyang River Basin from 2010 to 2020 was deeply analyzed， and the effect of artificial rainfall enhancement after increasing the operation point and operation amount was evaluated. At the same time， based on the long-term Landsat remote sensing data of Google Earth Engine platform， a pixel binary model was established to quantitatively analyze the vegetation cover and its spatio-temporal dynamic changes in Shiyang River Basin before and after artificial rainfall enhancement. The results showed that the average relative rainfall enhancement effect was 20.8% （P<0.1%）. During the period of 2010-2020， 1017.56 km2 of sandy or bare land will be transformed into grassland. Through the combined effect of artificial rain enhancement and natural precipitation， the vegetation coverage area of Shiyang River Basin increased from 20.2% before rain enhancement to 27.24% after rain enhancement in 2010， and the improvement was more obvious. Artificial rain enhancement technology has played a positive role in improving the ecological environment of the Shiyang River basin， and has made important contributions to the local ecological balance and sustainable development.
Abstract:
[Introduction] Wind disaster has strong sudden occurrence and great harm. It is of great significance to carry out risk assessment and regionalization research of Wind disaster for disaster prevention in various regions. [Method] Based on the disaster risk theory, using the wind observation data of 97 national weather stations in Shaanxi Province from 1978 to 2022, combined with socio-economic data and geographic information data, the index system of wind meteorological disaster risk assessment was constructed to quantitatively evaluate the wind disaster risk in Shaanxi Province. [Result] The disaster-inducing risk of wind disaster is mainly low and lower, accounting for 72.8% of the total area of the province, while the high and higher risk account for a relatively small proportion, accounting for 9.8% of the total area of the province. The wind disaster-inducing risk is highest in northern Shaanxi, followed by the high altitude area of Qinling Mountains. However, considering the environmental sensitivity, vulnerability of disaster bearing bodies and disaster prevention and mitigation ability, the wind disaster risk is mainly medium and above risk, the medium, high and higher risk all account for more than 20% of the total area of the province. The wind disaster risk is highest in northern Shaanxi, most of Guanzhong and a small part of northeast Shangluo, followed by southern Shaanxi and northern Guanzhong. According to the index distribution of risk zoning, the high risk in the northern part of Northern Shaanxi is mainly caused by the high sensitivity of disaster factors and disaster pregnancy environment, the high risk in Guanzhong is mainly caused by the highest vulnerability of disaster bearing body, and the northern Shangluo is caused by the high sensitivity of disaster pregnancy environment. [Conclusion] Densely populated areas, industrial agglomerations and high altitude areas are prone to wind disaster, and measures can be taken according to the main risk indicators that cause high risk of wind disasters to reduce the social and economic losses caused by wind disasters.
[Introduction] Wind disaster has strong sudden occurrence and great harm. It is of great significance to carry out risk assessment and regionalization research of Wind disaster for disaster prevention in various regions. [Method] Based on the disaster risk theory, using the wind observation data of 97 national weather stations in Shaanxi Province from 1978 to 2022, combined with socio-economic data and geographic information data, the index system of wind meteorological disaster risk assessment was constructed to quantitatively evaluate the wind disaster risk in Shaanxi Province. [Result] The disaster-inducing risk of wind disaster is mainly low and lower, accounting for 72.8% of the total area of the province, while the high and higher risk account for a relatively small proportion, accounting for 9.8% of the total area of the province. The wind disaster-inducing risk is highest in northern Shaanxi, followed by the high altitude area of Qinling Mountains. However, considering the environmental sensitivity, vulnerability of disaster bearing bodies and disaster prevention and mitigation ability, the wind disaster risk is mainly medium and above risk, the medium, high and higher risk all account for more than 20% of the total area of the province. The wind disaster risk is highest in northern Shaanxi, most of Guanzhong and a small part of northeast Shangluo, followed by southern Shaanxi and northern Guanzhong. According to the index distribution of risk zoning, the high risk in the northern part of Northern Shaanxi is mainly caused by the high sensitivity of disaster factors and disaster pregnancy environment, the high risk in Guanzhong is mainly caused by the highest vulnerability of disaster bearing body, and the northern Shangluo is caused by the high sensitivity of disaster pregnancy environment. [Conclusion] Densely populated areas, industrial agglomerations and high altitude areas are prone to wind disaster, and measures can be taken according to the main risk indicators that cause high risk of wind disasters to reduce the social and economic losses caused by wind disasters.
Abstract:
Based on FY-4A satellite data, ERA5 reanalysis data and multi-source observation data, the rainfall characteristics and occurrence conditions of two southwest vortex rainstorm processes in the east of Sichuan Chongqing Basin on June 22 and 26, 2022 are analyzed,and the mechanism for the development and maintenance of the southwest vortex is diagnosed through the analysis of thermal conditions and dynamic effects. The results show that there is a certain similarity between the two processes,and the strong downfall areas are located near the low-level shear line on the east side of the low vortex and the southwest northeast direction. From the difference between the two processes, it can be seen that the "6.22" process is more driven by thermal effects, and the main reasons for the development of the southwest vortex are surface sensible heating, sensible heating in the upper and middle troposphere, and the release of latent heat from condensation. The "6.26" process is dominated by dynamic action, and its circulation characteristics are clearer than the former, with better water vapor and energy conditions. The convergence of the horizontal wind field promotes the increase of local vorticity, leading to stronger development intensity and longer maintenance time of the southwest vortex, resulting in a slightly stronger rainstorm weather process than the "6.22" process.
Based on FY-4A satellite data, ERA5 reanalysis data and multi-source observation data, the rainfall characteristics and occurrence conditions of two southwest vortex rainstorm processes in the east of Sichuan Chongqing Basin on June 22 and 26, 2022 are analyzed,and the mechanism for the development and maintenance of the southwest vortex is diagnosed through the analysis of thermal conditions and dynamic effects. The results show that there is a certain similarity between the two processes,and the strong downfall areas are located near the low-level shear line on the east side of the low vortex and the southwest northeast direction. From the difference between the two processes, it can be seen that the "6.22" process is more driven by thermal effects, and the main reasons for the development of the southwest vortex are surface sensible heating, sensible heating in the upper and middle troposphere, and the release of latent heat from condensation. The "6.26" process is dominated by dynamic action, and its circulation characteristics are clearer than the former, with better water vapor and energy conditions. The convergence of the horizontal wind field promotes the increase of local vorticity, leading to stronger development intensity and longer maintenance time of the southwest vortex, resulting in a slightly stronger rainstorm weather process than the "6.22" process.
Abstract:
The apparent temperature（AT）， primarily influenced by air temperature， humidity， wind speed and solar radiation.In scenarios such as direct sunlight， high humidity and extreme high（low） temperature， AT can vary significantly even when air temperature remains constant. Taking Jiangxi Province as an example， two AT calculation methods were employed to analyze the differences of meteorological factors affecting AT under various scenarios.The result indicates that there are pronounced seasonal variations between AT and air temperature. From May to September， AT exhibits significant amplification relative to air temperature， peaking in mid-summer （July） at levels 5 to 6°C higher than air temperature. In winter， AT exerts a significant negative effect relative to air temperature， with AT lower than air temperature， reaching a trough in December and January， approximately 3°C below the air temperature. Conversely， in March and October， AT and air temperature show negligible differences. Under extreme meteorological conditions （temperatures of -10 ℃ and 35 ℃）， it is observed that regions with lower AT values correspond closely with areas of higher wind speeds and humidity levels.The discrepancy in AT during the colder months can reach up to 6℃ under identical air temperature conditions， with AT potentially being as much as 10 ℃ lower than the daily average air temperature. In warmer seasons， the rate of increase in AT outpaces that of air temperature. Under the same air temperature conditions， AT can be up to 8℃ higher， with area of high AT correlating well with low wind speed. In humid and hot summer conditions， wind speed emerges as a dominant driving factor of influencing the divergence between temperature and AT trends. In regions with solar radiation measurements， particularly Nanchang and Ganzhou method 2 was applied to assess the contribution of solar radiation to AT. The results demonstrate that AT values exceed air temperature by 3～5 ℃ and AT values with radiation are consistently higher than those without，contributing approximately 0.5～1.5°C in the warm season and 0.7～1.1°C in the cold season ， respectively.Hence， leveraging the distinctive characteristics of AT in contrast to air temperature， and selecting appropriate AT calculation methods in different scenarios，can provide a technical references for forecasting health-related meteorological risks in urban environments during humid and hot summers as well as humid and cold winters.
The apparent temperature（AT）， primarily influenced by air temperature， humidity， wind speed and solar radiation.In scenarios such as direct sunlight， high humidity and extreme high（low） temperature， AT can vary significantly even when air temperature remains constant. Taking Jiangxi Province as an example， two AT calculation methods were employed to analyze the differences of meteorological factors affecting AT under various scenarios.The result indicates that there are pronounced seasonal variations between AT and air temperature. From May to September， AT exhibits significant amplification relative to air temperature， peaking in mid-summer （July） at levels 5 to 6°C higher than air temperature. In winter， AT exerts a significant negative effect relative to air temperature， with AT lower than air temperature， reaching a trough in December and January， approximately 3°C below the air temperature. Conversely， in March and October， AT and air temperature show negligible differences. Under extreme meteorological conditions （temperatures of -10 ℃ and 35 ℃）， it is observed that regions with lower AT values correspond closely with areas of higher wind speeds and humidity levels.The discrepancy in AT during the colder months can reach up to 6℃ under identical air temperature conditions， with AT potentially being as much as 10 ℃ lower than the daily average air temperature. In warmer seasons， the rate of increase in AT outpaces that of air temperature. Under the same air temperature conditions， AT can be up to 8℃ higher， with area of high AT correlating well with low wind speed. In humid and hot summer conditions， wind speed emerges as a dominant driving factor of influencing the divergence between temperature and AT trends. In regions with solar radiation measurements， particularly Nanchang and Ganzhou method 2 was applied to assess the contribution of solar radiation to AT. The results demonstrate that AT values exceed air temperature by 3～5 ℃ and AT values with radiation are consistently higher than those without，contributing approximately 0.5～1.5°C in the warm season and 0.7～1.1°C in the cold season ， respectively.Hence， leveraging the distinctive characteristics of AT in contrast to air temperature， and selecting appropriate AT calculation methods in different scenarios，can provide a technical references for forecasting health-related meteorological risks in urban environments during humid and hot summers as well as humid and cold winters.
Abstract:
The study is based on the hourly PM2.5 concentration data from January 2017 to December 2024 at the Anshan City environmental monitoring station, as well as the surface meteorological element values during the same period. By using surface wind field data and the HYSPLIT backward trajectory model, the study explores the regional transport impact mechanism and potential source distribution of PM2.5 concentrations in Anshan City. The results show that the annual PM2.5 concentration in Anshan City exhibits an overall fluctuating downward trend. The annual variation trend presents a double “U” shape, with the highest levels in winter and the lowest in summer, and the pollution trend in spring and winter is significantly worse than in summer and autumn. From January to August, the PM2.5 mass concentration decreases monthly, while from August to December, it increases monthly. The daily average concentration shows a “bimodal” pattern, with peaks generally occurring around 8 am and 10 pm, and troughs around 4 pm. The PM2.5 concentration in the Anshan area is significantly affected by regional transport. In spring, summer, and autumn, the surface winds from the southwest direction lift the observed PM2.5 concentration, while in winter, the northerly winds correspond to higher PM2.5 concentrations, with the maximum lift coming from the northerly direction. In spring and summer, the PM2.5 concentration in Anshan is mainly influenced by medium-distance air masses from the northern land and sea, in autumn by short-distance air mass transport from the southwest within the province, and in winter by medium-distance air mass transport from the northern land and short-distance airflow from the west within the province. The potential source areas of PM2.5 are mainly distributed in the northern part of Liaoning, the central urban agglomeration of Liaoning, the southern part of Liaoning, the Bohai Bay area, as well as the Xing’an League of Inner Mongolia, the southwestern part of Jilin, and the Yantai area near the Shandong?Peninsula.
The study is based on the hourly PM2.5 concentration data from January 2017 to December 2024 at the Anshan City environmental monitoring station, as well as the surface meteorological element values during the same period. By using surface wind field data and the HYSPLIT backward trajectory model, the study explores the regional transport impact mechanism and potential source distribution of PM2.5 concentrations in Anshan City. The results show that the annual PM2.5 concentration in Anshan City exhibits an overall fluctuating downward trend. The annual variation trend presents a double “U” shape, with the highest levels in winter and the lowest in summer, and the pollution trend in spring and winter is significantly worse than in summer and autumn. From January to August, the PM2.5 mass concentration decreases monthly, while from August to December, it increases monthly. The daily average concentration shows a “bimodal” pattern, with peaks generally occurring around 8 am and 10 pm, and troughs around 4 pm. The PM2.5 concentration in the Anshan area is significantly affected by regional transport. In spring, summer, and autumn, the surface winds from the southwest direction lift the observed PM2.5 concentration, while in winter, the northerly winds correspond to higher PM2.5 concentrations, with the maximum lift coming from the northerly direction. In spring and summer, the PM2.5 concentration in Anshan is mainly influenced by medium-distance air masses from the northern land and sea, in autumn by short-distance air mass transport from the southwest within the province, and in winter by medium-distance air mass transport from the northern land and short-distance airflow from the west within the province. The potential source areas of PM2.5 are mainly distributed in the northern part of Liaoning, the central urban agglomeration of Liaoning, the southern part of Liaoning, the Bohai Bay area, as well as the Xing’an League of Inner Mongolia, the southwestern part of Jilin, and the Yantai area near the Shandong?Peninsula.
Abstract:
Used gale data from 1984 to 2020 of 142 national meteorological stations, the climatic characteristics of gale in Hebei province were analyzed. Based on the disaster risk assessment theory, we chosen gale days and daily extreme wind speed as risky indexes and assessed the gale disaster risk. It is concluded that the average maximum wind speed tends to decrease, whose peak value appeared in 1978. The average extreme wind speed tends to increase in 2014—2020, which is similar to the trend of the maximum wind speed during this period. Gale days in April is peak while it is valley in September. Gale days tend to decline from the northwest to the southeast part of Hebei Province, while they increase in coastal region of Cangzhou. The average maximum wind speed is high in northwest and low in northeast. The average extreme wind speed is high in northwest and southwest while low in southeast. Both of the highest region of these two speeds appear in Bashang region in Zhangjiakou. The trend of the gale disaster risk is high in northwest and low in northeast and southwest. The highest risk parts are the Bashang region in Zhangjiakou and Fengning, a county in Chengde.
Used gale data from 1984 to 2020 of 142 national meteorological stations, the climatic characteristics of gale in Hebei province were analyzed. Based on the disaster risk assessment theory, we chosen gale days and daily extreme wind speed as risky indexes and assessed the gale disaster risk. It is concluded that the average maximum wind speed tends to decrease, whose peak value appeared in 1978. The average extreme wind speed tends to increase in 2014—2020, which is similar to the trend of the maximum wind speed during this period. Gale days in April is peak while it is valley in September. Gale days tend to decline from the northwest to the southeast part of Hebei Province, while they increase in coastal region of Cangzhou. The average maximum wind speed is high in northwest and low in northeast. The average extreme wind speed is high in northwest and southwest while low in southeast. Both of the highest region of these two speeds appear in Bashang region in Zhangjiakou. The trend of the gale disaster risk is high in northwest and low in northeast and southwest. The highest risk parts are the Bashang region in Zhangjiakou and Fengning, a county in Chengde.
Abstract:
Based on meteorological observation data of temperature and precipitation in the Shaanxi section of the Yellow River Basin from 1961 to 2022， along with estimated data of temperature and precipitation under the CIMP6 climate scenario model， we analyzed and projected the climate change characteristics in the Shaanxi section of the Yellow River Basin by trend analysis， M-K test， and Morlet wavelet analysis methods. The results indicated that over the past 62 years， the annual mean temperature in the Shaanxi section of the Yellow River Basin showed a significant increasing trend， while the annual precipitation exhibited a non-significant decreasing trend， with the 400mm isohyet continuously shifting northward. The frequency and intensity of extreme climate events in the basin have increased， particularly over the last two decades. Under the SSP1-2.6， SSP2-4.5， and SSP5-8.5 scenarios， both the annual mean temperature and annual precipitation in the basin show increasing trends. The overall characteristic of the Shaanxi Yellow River Basin is a transition towards a warmer and more humid climate， which may lead to positive ecological developments in some areas， and optimization of agroclimatic resources， but also an increasing risk of meteorological disasters. Therefore， it is necessary to take positively respond measures by maximizing benefits and minimizing harms.
Based on meteorological observation data of temperature and precipitation in the Shaanxi section of the Yellow River Basin from 1961 to 2022， along with estimated data of temperature and precipitation under the CIMP6 climate scenario model， we analyzed and projected the climate change characteristics in the Shaanxi section of the Yellow River Basin by trend analysis， M-K test， and Morlet wavelet analysis methods. The results indicated that over the past 62 years， the annual mean temperature in the Shaanxi section of the Yellow River Basin showed a significant increasing trend， while the annual precipitation exhibited a non-significant decreasing trend， with the 400mm isohyet continuously shifting northward. The frequency and intensity of extreme climate events in the basin have increased， particularly over the last two decades. Under the SSP1-2.6， SSP2-4.5， and SSP5-8.5 scenarios， both the annual mean temperature and annual precipitation in the basin show increasing trends. The overall characteristic of the Shaanxi Yellow River Basin is a transition towards a warmer and more humid climate， which may lead to positive ecological developments in some areas， and optimization of agroclimatic resources， but also an increasing risk of meteorological disasters. Therefore， it is necessary to take positively respond measures by maximizing benefits and minimizing harms.
Abstract:
The characteristics and causes of the extreme rain and snow brought by strong cold wave in China from November 5 to 8, 2021 are comprehensively analyzed by using multi-source observations and forecast data. The results show that: the accumulated amount and intensity of rain and snow in Northern China were both historical rare in the early winter, meanwhile the rain and snow lasted for much a long time, with rather thick snow depth in Northeast China, the total precipitation, snowfall and snow depth in many stations reached or exceeded its historical extreme value in November. The extreme rain and snow were caused by several combined factors, one was the continuous and profound updraft coupled by high-level divergence, mid-level convergence and low-level frontogenesis under unusually strong atmospheric barocline environment, another was the unusually strong water vapor transported by the low-level southerly jet and the easterly jet near northern part of the Western Pacific tropical disturbance, the other ones were the local atmospheric unstable convection and the slow movement of surface cyclones. The dynamics and water vapor conditions are obviously stronger than most heavy rain and snow processes in Northern China. Regional differences were founded in the formation of heavy precipitation centers, the strong rain and snow centers in the southern part of North China, the northern part of Huanghuai region and the southern part of Northeast China were caused by a combination of large-scale dynamic uplift, abundant water vapor transport and unstable convection, while heavy snow centers in the southeast part of Inner Mongolia were mainly caused by long-term stable and large-scale precipitation synoptic circulation. The numerical models provided a good forecasting ability for extreme rain and snow, while the forecast deviations still existed. Therefore, this analysis of the formation causes and threshold values of the heavy rain and snow can partly give some guidance to improve the future similar forecasts in some coming extreme precipitation in Northern China.
The characteristics and causes of the extreme rain and snow brought by strong cold wave in China from November 5 to 8, 2021 are comprehensively analyzed by using multi-source observations and forecast data. The results show that: the accumulated amount and intensity of rain and snow in Northern China were both historical rare in the early winter, meanwhile the rain and snow lasted for much a long time, with rather thick snow depth in Northeast China, the total precipitation, snowfall and snow depth in many stations reached or exceeded its historical extreme value in November. The extreme rain and snow were caused by several combined factors, one was the continuous and profound updraft coupled by high-level divergence, mid-level convergence and low-level frontogenesis under unusually strong atmospheric barocline environment, another was the unusually strong water vapor transported by the low-level southerly jet and the easterly jet near northern part of the Western Pacific tropical disturbance, the other ones were the local atmospheric unstable convection and the slow movement of surface cyclones. The dynamics and water vapor conditions are obviously stronger than most heavy rain and snow processes in Northern China. Regional differences were founded in the formation of heavy precipitation centers, the strong rain and snow centers in the southern part of North China, the northern part of Huanghuai region and the southern part of Northeast China were caused by a combination of large-scale dynamic uplift, abundant water vapor transport and unstable convection, while heavy snow centers in the southeast part of Inner Mongolia were mainly caused by long-term stable and large-scale precipitation synoptic circulation. The numerical models provided a good forecasting ability for extreme rain and snow, while the forecast deviations still existed. Therefore, this analysis of the formation causes and threshold values of the heavy rain and snow can partly give some guidance to improve the future similar forecasts in some coming extreme precipitation in Northern China.
Abstract:
The system inspection and evaluation the official weather radar software of china (Radar Operational Software Engineering version 2.1, ROSE2.1) is helpful to refine the short-term forecast and early warning and to improve the quantitative precipitation estimation algorithm. For the four types of quantitative precipitation estimation ROSE2.1 products named 078, 079, 169, 170, through spatio-temporal matching and recalculation evaluation index method, the spatial, seasonal, precipitation levels and precipitation properties were discussed by hourly analysis from 2021 to 2023. The results show: for quantitative precipitation estimation capabilities, dual polarization products are better than single polarization, OHP is better than THP, Precipitations with smaller levels and closer distances are better; In the radius of 50 ~ 150 km, the effect of dual polarization on single polarization product is the greatest, the accuracy of OHP and THP products can increase by 25-34% and 18-32% respectively, which may be related to the improvement of ground echo and building occlusion by dual polarization; the accuracy of OHP169 and THP170 products is higher than 80% in the area of 30,000 km2 around Nanchang radar station; spring is the best, followed by summer and autumn, winter is worse; convective precipitation is better than stable precipitation.
The system inspection and evaluation the official weather radar software of china (Radar Operational Software Engineering version 2.1, ROSE2.1) is helpful to refine the short-term forecast and early warning and to improve the quantitative precipitation estimation algorithm. For the four types of quantitative precipitation estimation ROSE2.1 products named 078, 079, 169, 170, through spatio-temporal matching and recalculation evaluation index method, the spatial, seasonal, precipitation levels and precipitation properties were discussed by hourly analysis from 2021 to 2023. The results show: for quantitative precipitation estimation capabilities, dual polarization products are better than single polarization, OHP is better than THP, Precipitations with smaller levels and closer distances are better; In the radius of 50 ~ 150 km, the effect of dual polarization on single polarization product is the greatest, the accuracy of OHP and THP products can increase by 25-34% and 18-32% respectively, which may be related to the improvement of ground echo and building occlusion by dual polarization; the accuracy of OHP169 and THP170 products is higher than 80% in the area of 30,000 km2 around Nanchang radar station; spring is the best, followed by summer and autumn, winter is worse; convective precipitation is better than stable precipitation.
Abstract:
Using regional automatic station data, ERA5 reanalysis data, FY-4A data, and Doppler radar data, the weather background, environmental conditions, trigger mechanism, and evolution causation of the Shandong double squall line process on June 13, 2022 were analyzed. The results showed that: 1) This strong convective process was generated by the influence of two consecutive squall lines under cold vortex background, by the continuous influence of a locally developed squall line in Shandong (squall line A) and the squall line generated in Shanxi and Hebei that moved into Shandong (squall line B). The strong northwest airflow behind the cold vortex carried dry and cold air overlaid on the low-level warm ridge, establishing a strong thermal instability layer. The environment had large CAPE and total index, providing favorable environmental conditions for the occurrence of squall lines. 2) The surface convergence line in the northwest of Shandong, the 850 hPa dry line, and the gust front on the southern side of the Bohai convective storm were the triggering mechanisms of the initial convection of squall line A. The triggering of squall line B was related to the surface sub cold front and solar radiation heating. 3) In the vertical direction, the warm and humid inflow at the front of the system rose diagonally to the top of the storm, causing divergence, while the sinking airflow at the back converged in front of the squall line.In the horizontal direction, it exhibited a self-organizing structure where environmental inflow and storm outflow were interdependent and staggered, allowing squall line A to develop and maintain under weak vertical wind shear conditions in northern Shandong. The water vapor and energy conditions in the southern region of Mid-Shandong were conducive to the maintenance and development of squall line A, and the range of the posterior stratiform cloud area increases. 4) After the impact of squall line A from eastern Henan to southwestern Shandong, the rapid reconstruction of low-level convective conditions and moderate vertical wind shear provided favorable conditions for the maintenance of squall line B in the later stage.
Using regional automatic station data, ERA5 reanalysis data, FY-4A data, and Doppler radar data, the weather background, environmental conditions, trigger mechanism, and evolution causation of the Shandong double squall line process on June 13, 2022 were analyzed. The results showed that: 1) This strong convective process was generated by the influence of two consecutive squall lines under cold vortex background, by the continuous influence of a locally developed squall line in Shandong (squall line A) and the squall line generated in Shanxi and Hebei that moved into Shandong (squall line B). The strong northwest airflow behind the cold vortex carried dry and cold air overlaid on the low-level warm ridge, establishing a strong thermal instability layer. The environment had large CAPE and total index, providing favorable environmental conditions for the occurrence of squall lines. 2) The surface convergence line in the northwest of Shandong, the 850 hPa dry line, and the gust front on the southern side of the Bohai convective storm were the triggering mechanisms of the initial convection of squall line A. The triggering of squall line B was related to the surface sub cold front and solar radiation heating. 3) In the vertical direction, the warm and humid inflow at the front of the system rose diagonally to the top of the storm, causing divergence, while the sinking airflow at the back converged in front of the squall line.In the horizontal direction, it exhibited a self-organizing structure where environmental inflow and storm outflow were interdependent and staggered, allowing squall line A to develop and maintain under weak vertical wind shear conditions in northern Shandong. The water vapor and energy conditions in the southern region of Mid-Shandong were conducive to the maintenance and development of squall line A, and the range of the posterior stratiform cloud area increases. 4) After the impact of squall line A from eastern Henan to southwestern Shandong, the rapid reconstruction of low-level convective conditions and moderate vertical wind shear provided favorable conditions for the maintenance of squall line B in the later stage.
Abstract:
This study focuses on a severe pollution event in Hubei Province from February 4th to 7th, 2023. Conventional meteorological observation data, air quality data, ERA-5 reanalysis data, and Global Data Assimilation System (GDAS) meteorological data were utilized for analysis of synoptic circulation patterns, atmospheric dynamic and thermal conditions, local meteorological element variations, and air mass trajectories. Results indicate that during this event, six cities experienced severe pollution, with Xiangyang being the first affected and Jingzhou recording the highest pollution level with an AQI of 215. Based on the development of ρ (PM2.5) and surface weather situations, the process was divided into three stages: "transportation-accumulation and local transportation-dissipation." These stages correspond respectively to the formation stage (transportation before cold front), the accumulation and persistence stage (affected by synoptic situation, troughs, ridges, and fireworks emissions during the Lantern Festival), and the dissipation stage (affected by the southward intrusion of the Baikal cold high and front precipitation). Xiangyang's PM2.5 mainly originates from the southern part of Henan Province, while Jingzhou's PM2.5 mainly comes from the nearby city of Suizhou in Hubei Province, indicating the significant role of upstream cities within the province in pollutant transportation.
This study focuses on a severe pollution event in Hubei Province from February 4th to 7th, 2023. Conventional meteorological observation data, air quality data, ERA-5 reanalysis data, and Global Data Assimilation System (GDAS) meteorological data were utilized for analysis of synoptic circulation patterns, atmospheric dynamic and thermal conditions, local meteorological element variations, and air mass trajectories. Results indicate that during this event, six cities experienced severe pollution, with Xiangyang being the first affected and Jingzhou recording the highest pollution level with an AQI of 215. Based on the development of ρ (PM2.5) and surface weather situations, the process was divided into three stages: "transportation-accumulation and local transportation-dissipation." These stages correspond respectively to the formation stage (transportation before cold front), the accumulation and persistence stage (affected by synoptic situation, troughs, ridges, and fireworks emissions during the Lantern Festival), and the dissipation stage (affected by the southward intrusion of the Baikal cold high and front precipitation). Xiangyang's PM2.5 mainly originates from the southern part of Henan Province, while Jingzhou's PM2.5 mainly comes from the nearby city of Suizhou in Hubei Province, indicating the significant role of upstream cities within the province in pollutant transportation.
Abstract:
Using the hourly data of net radiation flux and soil heat flux in gravel-mulched fields and desert grassland in 2021, based on conventional meteorological statistical methods, the change characteristics of net radiation flux and soil heat flux at different time scales were compared and analyzed, and the change rules of energy balance components of different underlying surfaces were discussed. The results indicate that: (1) the net radiation flux of gravel-mulched fields and grassland is lower at two ends and higher in the middle, and the net radiation flux of gravel-mulched fields is higher than that of grassland. The soil heat flux of the two types of underlying surface changes gently, and the soil heat flux of the gravel-mulched fields in spring and summer is lower than that of the grassland, but it is just the opposite in autumn and winter. (2) The monthly total net radiation flux of gravel-mulched fields and grassland shows a trend of first increasing and then decreasing, with the maximum value appearing in July and the minimum value appearing in December and January, respectively. The variation of soil heat flux is gentle, with the maximum value appearing in May and the minimum value appearing in November and December respectively. (3) The monthly average daily changes of net radiation flux and soil heat flux in different months are unimodal, and the daily peak value of soil heat flux lags behind the net radiation flux by 1 ~ 2 hours. The daily peak value of net radiation flux in gravel-mulched fields is higher than that in grassland, and the difference is great in different months, while the daily peak value of soil heat flux is small. (4) Under different weather conditions, the net radiation flux and soil heat flux of gravel-mulched fields and grassland have different diurnal variation characteristics, and the diurnal variation trend and amplitude have obvious seasonal differences. In addition, the fluctuation amplitude of net radiation flux and soil heat flux of the two types of underlying surface is the largest in sunny days, followed by cloudy days, sand blowing/sandstorm, and the smallest in rain/snow days.
Using the hourly data of net radiation flux and soil heat flux in gravel-mulched fields and desert grassland in 2021, based on conventional meteorological statistical methods, the change characteristics of net radiation flux and soil heat flux at different time scales were compared and analyzed, and the change rules of energy balance components of different underlying surfaces were discussed. The results indicate that: (1) the net radiation flux of gravel-mulched fields and grassland is lower at two ends and higher in the middle, and the net radiation flux of gravel-mulched fields is higher than that of grassland. The soil heat flux of the two types of underlying surface changes gently, and the soil heat flux of the gravel-mulched fields in spring and summer is lower than that of the grassland, but it is just the opposite in autumn and winter. (2) The monthly total net radiation flux of gravel-mulched fields and grassland shows a trend of first increasing and then decreasing, with the maximum value appearing in July and the minimum value appearing in December and January, respectively. The variation of soil heat flux is gentle, with the maximum value appearing in May and the minimum value appearing in November and December respectively. (3) The monthly average daily changes of net radiation flux and soil heat flux in different months are unimodal, and the daily peak value of soil heat flux lags behind the net radiation flux by 1 ~ 2 hours. The daily peak value of net radiation flux in gravel-mulched fields is higher than that in grassland, and the difference is great in different months, while the daily peak value of soil heat flux is small. (4) Under different weather conditions, the net radiation flux and soil heat flux of gravel-mulched fields and grassland have different diurnal variation characteristics, and the diurnal variation trend and amplitude have obvious seasonal differences. In addition, the fluctuation amplitude of net radiation flux and soil heat flux of the two types of underlying surface is the largest in sunny days, followed by cloudy days, sand blowing/sandstorm, and the smallest in rain/snow days.
Abstract:
如何用多源气象资料监测突发森林火灾并分析机理,是大气探测与大气遥感面临的挑战。以2019年3月31日18时四川省凉山州木里县雅砻江镇立尔村的森林火灾因突发山火爆燃导致31名救火人员牺牲的事件为例,研究了天气背景、卫星云图、风矢-位温(V-3)图以及卫星遥感甲烷含量的垂直分布等特征。结果表明:林火区域前期很干燥,没有云和降水,大气的垂直结构显示了中层以下明显的热力不稳定。根据地下排气的作用,烃类气体的强大喷发改变了大气对流层的温湿结构。利用Aqua卫星AIRS传感器的甲烷资料,可监测地球排气现象。地下气体喷发在离地面不远处发生爆炸,造成爆燃。本研究从大气和地质的交叉学科视野进行探索,提出了用多源气象资料监测山火爆燃与地球排气的关系,旨在为保护生态环境防火减灾的科学决策提供依据。
如何用多源气象资料监测突发森林火灾并分析机理,是大气探测与大气遥感面临的挑战。以2019年3月31日18时四川省凉山州木里县雅砻江镇立尔村的森林火灾因突发山火爆燃导致31名救火人员牺牲的事件为例,研究了天气背景、卫星云图、风矢-位温(V-3)图以及卫星遥感甲烷含量的垂直分布等特征。结果表明:林火区域前期很干燥,没有云和降水,大气的垂直结构显示了中层以下明显的热力不稳定。根据地下排气的作用,烃类气体的强大喷发改变了大气对流层的温湿结构。利用Aqua卫星AIRS传感器的甲烷资料,可监测地球排气现象。地下气体喷发在离地面不远处发生爆炸,造成爆燃。本研究从大气和地质的交叉学科视野进行探索,提出了用多源气象资料监测山火爆燃与地球排气的关系,旨在为保护生态环境防火减灾的科学决策提供依据。
Abstract:
The threshold phenomenon of impervious surfaces affecting the environmental hydrology of rivers has reference value for watershed planning and environmental management, but current studies are mostly limited to the description of the phenomenon and static assessment based on statistical methods, with less attention paid to its formation mechanism and influencing factors. This paper proposes the threshold effect of impervious surfaces on river environmental hydrology and its formation mechanism under a single rainfall event, tries to establish a nonlinear pressure response function between surface pollution loads and rainfall runoff with impervious surfaces as the core parameter, and theoretically demonstrates the existence conditions and influencing factors of the threshold effect. It is argued that the immediate threshold value of impervious surfaces affecting river hydrological and water quality indicators under a single rainfall event can be investigated by carrying out field monitoring and surveys of river environmental hydrology under different rainfall conditions. The coupled system of MIKE-URBAN stormwater management and MIKE11 water quality simulation is further established to demonstrate the theoretical basis for the existence of the threshold phenomenon from the process mechanism. MIKE-LID and LTHIA-LID model simulation techniques are applied to seek the impervious surface threshold constraints for the effectiveness of LID in urbanized areas at different scales, with a view to providing a reference basis for decision-making to promote the construction of sponge cities.
The threshold phenomenon of impervious surfaces affecting the environmental hydrology of rivers has reference value for watershed planning and environmental management, but current studies are mostly limited to the description of the phenomenon and static assessment based on statistical methods, with less attention paid to its formation mechanism and influencing factors. This paper proposes the threshold effect of impervious surfaces on river environmental hydrology and its formation mechanism under a single rainfall event, tries to establish a nonlinear pressure response function between surface pollution loads and rainfall runoff with impervious surfaces as the core parameter, and theoretically demonstrates the existence conditions and influencing factors of the threshold effect. It is argued that the immediate threshold value of impervious surfaces affecting river hydrological and water quality indicators under a single rainfall event can be investigated by carrying out field monitoring and surveys of river environmental hydrology under different rainfall conditions. The coupled system of MIKE-URBAN stormwater management and MIKE11 water quality simulation is further established to demonstrate the theoretical basis for the existence of the threshold phenomenon from the process mechanism. MIKE-LID and LTHIA-LID model simulation techniques are applied to seek the impervious surface threshold constraints for the effectiveness of LID in urbanized areas at different scales, with a view to providing a reference basis for decision-making to promote the construction of sponge cities.
Abstract:
The diurnal variation of precipitation in Sichuan Basin is very distinctive, and the saying "Bashan Night Rain" has existed in ancient times, but the research on the difficulties in the study of the diurnal variation of topographic heavy precipitation and the diurnal variation of disastrous mountain rainstorm is still rare. In this paper, several recent advances in the field of mountain rainstorm events in Sichuan are reviewed from the perspectives of climatic characteristics, spatio-temporal fine distribution (including dependence on altitude) and synthesis characteristics, and dynamic-thermal structures and topographic effects, the transport of water vapor by boundary layer jets, the role of surface and atmospheric heat sources, the Synchronous contribution of the Southwest Vortex, the evolution of mesoscale convective systems (MCSs), and the impact of topographic gravity waves. Finally, some important issues that still exist were pointed out, and looked forward to the main research directions in the future.
The diurnal variation of precipitation in Sichuan Basin is very distinctive, and the saying "Bashan Night Rain" has existed in ancient times, but the research on the difficulties in the study of the diurnal variation of topographic heavy precipitation and the diurnal variation of disastrous mountain rainstorm is still rare. In this paper, several recent advances in the field of mountain rainstorm events in Sichuan are reviewed from the perspectives of climatic characteristics, spatio-temporal fine distribution (including dependence on altitude) and synthesis characteristics, and dynamic-thermal structures and topographic effects, the transport of water vapor by boundary layer jets, the role of surface and atmospheric heat sources, the Synchronous contribution of the Southwest Vortex, the evolution of mesoscale convective systems (MCSs), and the impact of topographic gravity waves. Finally, some important issues that still exist were pointed out, and looked forward to the main research directions in the future.
Abstract:
The Ertix River, the second largest river in Xinjiang and an international watercourse, is crucial for the socio-economic development of Xinjiang, China, as well as Mongolia and Kazakhstan. With global climate warming, spring snowmelt floods in the Ertix River Basin are increasing in frequency, posing severe threats to local communities, agricultural production, infrastructure, and the ecological environment. This study identifies six key factors influencing snowmelt flood occurrence: snow depth, elevation, topographic ruggedness, slope, distance to water systems, and land use types. By integrating historical disaster data with an information quantity model, we quantitatively evaluated and zoned the hazard of spring snowmelt floods. The findings indicate: 1) Spring snowmelt floods predominantly occur in the piedmont plains below 1500 meters elevation and near rivers, particularly in grasslands, farmlands, and residential areas; 2) Snow depth and distance to water systems are critical factors, with areas having snow depths between 40-50 cm and distances to water systems between 1-2 km exhibiting the highest flood risks; 3) The average AUC value of 0.86 from five sets of random experimental models confirms the effectiveness of the information quantity model in evaluating the hazard of spring snowmelt floods based on the six selected key indicators. This study provides a scientific basis for developing flood prevention measures and water resource management strategies in the Ertix River Basin and offers a reference for assessing snowmelt flood hazards in similar regions.
The Ertix River, the second largest river in Xinjiang and an international watercourse, is crucial for the socio-economic development of Xinjiang, China, as well as Mongolia and Kazakhstan. With global climate warming, spring snowmelt floods in the Ertix River Basin are increasing in frequency, posing severe threats to local communities, agricultural production, infrastructure, and the ecological environment. This study identifies six key factors influencing snowmelt flood occurrence: snow depth, elevation, topographic ruggedness, slope, distance to water systems, and land use types. By integrating historical disaster data with an information quantity model, we quantitatively evaluated and zoned the hazard of spring snowmelt floods. The findings indicate: 1) Spring snowmelt floods predominantly occur in the piedmont plains below 1500 meters elevation and near rivers, particularly in grasslands, farmlands, and residential areas; 2) Snow depth and distance to water systems are critical factors, with areas having snow depths between 40-50 cm and distances to water systems between 1-2 km exhibiting the highest flood risks; 3) The average AUC value of 0.86 from five sets of random experimental models confirms the effectiveness of the information quantity model in evaluating the hazard of spring snowmelt floods based on the six selected key indicators. This study provides a scientific basis for developing flood prevention measures and water resource management strategies in the Ertix River Basin and offers a reference for assessing snowmelt flood hazards in similar regions.
Abstract:
Northwest China is one of the most serious drought areas in China, and the study of precipitation in this region is of great scientific significance. The high temporal and spatial resolution of the GPM (Global Precipitation Measurement) satellite precipitation data provides a useful scientific supplement to the in-depth study of the precipitation process in the Northwest China region under sparse and complex terrain conditions. In this paper, the intensive surface observations within Gansu Province in the Qilian Mountains region were utilized to objectively assess the GPM precipitation using TS (Threat Score) scores, consistency indices and CSI (Critical Success Index) etc. The results show that: (1) the GPM data can characterize the main fallout areas of precipitation in different seasons in the Qilianshan region, and at the same time, the data underestimates the amount of weak precipitation areas and overestimates the amount of strong precipitation areas; (2) the observation data show that the Qilianshan region has the highest frequency of forming drizzle, which is 85.95%, and the frequencies of medium rain, heavy rain and heavy rain are less frequent, which are 12.04%, 1.89% and 0.1%, respectively; The GPM data detection results are more consistent with the observations; (3) the GPM data can also well characterize the daily change of precipitation in the Qilian Mountain region, and the data can better capture the characteristics of summer and autumn seasons when precipitation is mainly concentrated in the morning and at night, and the effect is the worst in winter. Overall, the GPM data can detect the precipitation process under the complex terrain of Northwest China with high accuracy
Northwest China is one of the most serious drought areas in China, and the study of precipitation in this region is of great scientific significance. The high temporal and spatial resolution of the GPM (Global Precipitation Measurement) satellite precipitation data provides a useful scientific supplement to the in-depth study of the precipitation process in the Northwest China region under sparse and complex terrain conditions. In this paper, the intensive surface observations within Gansu Province in the Qilian Mountains region were utilized to objectively assess the GPM precipitation using TS (Threat Score) scores, consistency indices and CSI (Critical Success Index) etc. The results show that: (1) the GPM data can characterize the main fallout areas of precipitation in different seasons in the Qilianshan region, and at the same time, the data underestimates the amount of weak precipitation areas and overestimates the amount of strong precipitation areas; (2) the observation data show that the Qilianshan region has the highest frequency of forming drizzle, which is 85.95%, and the frequencies of medium rain, heavy rain and heavy rain are less frequent, which are 12.04%, 1.89% and 0.1%, respectively; The GPM data detection results are more consistent with the observations; (3) the GPM data can also well characterize the daily change of precipitation in the Qilian Mountain region, and the data can better capture the characteristics of summer and autumn seasons when precipitation is mainly concentrated in the morning and at night, and the effect is the worst in winter. Overall, the GPM data can detect the precipitation process under the complex terrain of Northwest China with high accuracy
Abstract:
In this study, we utilized the temperature and wind speed forecast products from the Rapid-update Multi-scale Analysis and Forecasting System in Central Asia (RMAPS-CA), along with weather station data for Gwadar Port, spanning from June 1, 2020, to June 30, 2021, to form our training dataset. Three distinct machine learning models—Support Vector Machine (SVM), Gradient Boosting Regression (GBR), and Random Forest (RDF) were applied to correct the forecast products of RMAPS-CA for Gwadar Port's near-surface temperature and 10 m wind speed from July 1 to September 30, 2021. The results indicate that the SVM, GBR, and RDF model has led to a notable reduction in the root mean square error (RMSE) for RMAPS-CA forecasted T-2m initialized at 00:00 UTC and 12:00 UTC, with a decrease more than 54%. Concurrently, there was a substantial increase in the correlation coefficient, which exceeded 0.85. In terms of the 10 m wind speed forecast initialized at 00:00 UTC and 12:00 UTC, the RMSE was reduced by more than 63%, and the correlation coefficient increased to above 0.68. The three machine learning models exhibited significant improvements in the accuracy of T-2m and wind speed forecasts for the Gwadar Port station. Notably, the RDF model demonstrated the most effective corrections for T-2m forecasts, while the GBR model outperformed in the correction of 10 m wind speed forecasts. These machine learning models hold considerable potential for the refinement of numerical weather prediction products in the Central Asian region.
In this study, we utilized the temperature and wind speed forecast products from the Rapid-update Multi-scale Analysis and Forecasting System in Central Asia (RMAPS-CA), along with weather station data for Gwadar Port, spanning from June 1, 2020, to June 30, 2021, to form our training dataset. Three distinct machine learning models—Support Vector Machine (SVM), Gradient Boosting Regression (GBR), and Random Forest (RDF) were applied to correct the forecast products of RMAPS-CA for Gwadar Port's near-surface temperature and 10 m wind speed from July 1 to September 30, 2021. The results indicate that the SVM, GBR, and RDF model has led to a notable reduction in the root mean square error (RMSE) for RMAPS-CA forecasted T-2m initialized at 00:00 UTC and 12:00 UTC, with a decrease more than 54%. Concurrently, there was a substantial increase in the correlation coefficient, which exceeded 0.85. In terms of the 10 m wind speed forecast initialized at 00:00 UTC and 12:00 UTC, the RMSE was reduced by more than 63%, and the correlation coefficient increased to above 0.68. The three machine learning models exhibited significant improvements in the accuracy of T-2m and wind speed forecasts for the Gwadar Port station. Notably, the RDF model demonstrated the most effective corrections for T-2m forecasts, while the GBR model outperformed in the correction of 10 m wind speed forecasts. These machine learning models hold considerable potential for the refinement of numerical weather prediction products in the Central Asian region.
Abstract:
The purpose of this study is to evaluate the climatic potential suitable zones and disaster risks distribution for apple cultivation in Mizhi County from 1991 to 2020. Based on the meteorological observation data, the digital elevation model data and the land confirmation rights data, the changing trends for heat and water resource of Mizhi County from 1971 to 2023 were analyzed by methods such as climate tendency rate and M-K test. By integrating climatic conditions, site characteristics, and available agricultural land resources, this study conducted a quantitative analysis and assessment of the climatic potential suitable regions for apple cultivation in Mizhi County, evaluated their cultivation development potential, and identified risk-sensitive areas of major meteorological disasters. The results indicate: (1) Mizhi County has exhibited a warming and moistening trend over the past 53 years, enhancing the suitability of hydrothermal conditions for apple growth. (2) The potential climate suitability regions are mainly distributed in sun-facing gentle slopes of hilly-gully areas at elevations of 870~1 240 m, covering approximately 20 064.0 hm2 (53.2% of available agricultural land). (3) Climate risk assessment revealed: 11 752.2 hm2 of low-risk areas and 8 311.8 hm2 of moderate-risk areas for flowering-period frost damage; 4 675.3 hm2 of moderate-risk and 15 388.7 hm2 of high-risk areas for drought during sprouting-young fruit stages. These findings provide direct references for optimizing regional apple industry layout and enhancing meteorological disaster prevention strategies.
The purpose of this study is to evaluate the climatic potential suitable zones and disaster risks distribution for apple cultivation in Mizhi County from 1991 to 2020. Based on the meteorological observation data, the digital elevation model data and the land confirmation rights data, the changing trends for heat and water resource of Mizhi County from 1971 to 2023 were analyzed by methods such as climate tendency rate and M-K test. By integrating climatic conditions, site characteristics, and available agricultural land resources, this study conducted a quantitative analysis and assessment of the climatic potential suitable regions for apple cultivation in Mizhi County, evaluated their cultivation development potential, and identified risk-sensitive areas of major meteorological disasters. The results indicate: (1) Mizhi County has exhibited a warming and moistening trend over the past 53 years, enhancing the suitability of hydrothermal conditions for apple growth. (2) The potential climate suitability regions are mainly distributed in sun-facing gentle slopes of hilly-gully areas at elevations of 870~1 240 m, covering approximately 20 064.0 hm2 (53.2% of available agricultural land). (3) Climate risk assessment revealed: 11 752.2 hm2 of low-risk areas and 8 311.8 hm2 of moderate-risk areas for flowering-period frost damage; 4 675.3 hm2 of moderate-risk and 15 388.7 hm2 of high-risk areas for drought during sprouting-young fruit stages. These findings provide direct references for optimizing regional apple industry layout and enhancing meteorological disaster prevention strategies.
Abstract:
Artificial intelligence (AI) has become an indispensable tool in the field of meteorological forecasting, showcasing its prowess in deciphering the complex dynamics of weather systems. This article delves into the application of AI in meteorological prediction, outlining both its current successes and the challenges that lie ahead. Firstly, traditional machine learning algorithms such as random forests, XGBoost, and support vector machines are introduced, which, despite performing better than conventional methods in certain aspects, exhibit inherent limitations. Secondly, deep learning models, leveraging their powerful feature extraction and pattern recognition capabilities, have excelled in analyzing and predicting meteorological variables, particularly neural networks, convolutional neural networks, and recurrent neural networks. Furthermore, the text underscores the significant potential of large-scale models like Pangu, FuXi, and GraphCAST in bolstering the accuracy of weather predictions. In conclusion, the study proposes key areas for future research, emphasizing the need for model optimization, algorithmic enhancement, data quality and diversity improvements, and interdisciplinary collaboration. These efforts are crucial for laying the groundwork and providing the technological support necessary to propel meteorological forecasting into a new era of sophistication and reliability.
Artificial intelligence (AI) has become an indispensable tool in the field of meteorological forecasting, showcasing its prowess in deciphering the complex dynamics of weather systems. This article delves into the application of AI in meteorological prediction, outlining both its current successes and the challenges that lie ahead. Firstly, traditional machine learning algorithms such as random forests, XGBoost, and support vector machines are introduced, which, despite performing better than conventional methods in certain aspects, exhibit inherent limitations. Secondly, deep learning models, leveraging their powerful feature extraction and pattern recognition capabilities, have excelled in analyzing and predicting meteorological variables, particularly neural networks, convolutional neural networks, and recurrent neural networks. Furthermore, the text underscores the significant potential of large-scale models like Pangu, FuXi, and GraphCAST in bolstering the accuracy of weather predictions. In conclusion, the study proposes key areas for future research, emphasizing the need for model optimization, algorithmic enhancement, data quality and diversity improvements, and interdisciplinary collaboration. These efforts are crucial for laying the groundwork and providing the technological support necessary to propel meteorological forecasting into a new era of sophistication and reliability.
Abstract:
Precipitation data from May-September 2019-2023 from national meteorological stations (national stations) and regional automatic meteorological stations (regional stations) in Xinjiang are applied to compare and analyze the effectiveness of the two in describing the precipitation characteristics in Xinjiang. The results are as follows. The correlation between precipitation at national and regional stations is significant. The average precipitation of regional and national stations in the summer half-year is 103.2 mm and 89.0 mm respectively, and the maximum precipitation is 451.2 mm and 395.7 mm respectively. The average monthly maximum precipitation of regional and national stations is 67.4 mm and 56.3 mm respectively, and the maximum precipitation is 335.5 mm and 167.6 mm respectively. The average precipitation at the regional station is higher than that at the national station, and the skewed character of precipitation is more pronounced than that at the national station. Precipitation at regional stations is distributed in bands along the mountain system, and national stations are sporadically distributed in the mountains.The precipitation concentration intervals are consistent between the two types of stations, but the discrete and localized nature of precipitation is not sufficiently described by the national stations to characterize in detail the spatial distribution of precipitation extremes of less than 25 mm and more than 100 mm. The spatial distribution of extreme precipitation events in Xinjiang is closely related to the topography, with national stations higher than regional stations in the basin and the opposite in the mountains. The difference in precipitation levels between the two types of stations under different terrain conditions is significant, with regional stations having an advantage in complex terrain areas with large elevation differences. Regional station data can monitor more and stronger extreme precipitation events, providing more refined real-time information for forecast prediction and disaster prevention and mitigation services.
Precipitation data from May-September 2019-2023 from national meteorological stations (national stations) and regional automatic meteorological stations (regional stations) in Xinjiang are applied to compare and analyze the effectiveness of the two in describing the precipitation characteristics in Xinjiang. The results are as follows. The correlation between precipitation at national and regional stations is significant. The average precipitation of regional and national stations in the summer half-year is 103.2 mm and 89.0 mm respectively, and the maximum precipitation is 451.2 mm and 395.7 mm respectively. The average monthly maximum precipitation of regional and national stations is 67.4 mm and 56.3 mm respectively, and the maximum precipitation is 335.5 mm and 167.6 mm respectively. The average precipitation at the regional station is higher than that at the national station, and the skewed character of precipitation is more pronounced than that at the national station. Precipitation at regional stations is distributed in bands along the mountain system, and national stations are sporadically distributed in the mountains.The precipitation concentration intervals are consistent between the two types of stations, but the discrete and localized nature of precipitation is not sufficiently described by the national stations to characterize in detail the spatial distribution of precipitation extremes of less than 25 mm and more than 100 mm. The spatial distribution of extreme precipitation events in Xinjiang is closely related to the topography, with national stations higher than regional stations in the basin and the opposite in the mountains. The difference in precipitation levels between the two types of stations under different terrain conditions is significant, with regional stations having an advantage in complex terrain areas with large elevation differences. Regional station data can monitor more and stronger extreme precipitation events, providing more refined real-time information for forecast prediction and disaster prevention and mitigation services.
Abstract:
利用高空、地面、区域自动气象站和风廓线雷达、激光雷达观测资料,采用HYSPLIT模型,对2024年4月12—14日哈密市一次强沙尘暴天气过程特征进行分析,并采用HYSPLIT模型对沙尘轨迹进行模拟。结果表明:500hPa西西伯利亚低槽快速东移南下、极地强冷空气向南爆发是此次强大风沙尘暴发生的影响系统,地面冷锋后强偏北大风是产生强沙尘暴的主要原因。激光雷达1.0—6.0km-1,退偏振比在0.11—0.20,风廓线雷达低空风场出现切变和风向转为偏东风时,分别对应哈密站沙尘暴天气的开始和强沙尘暴的开始。前期温高雨少,时值北疆春播期,沙尘自哈萨克斯坦阿斯塔纳,沿西北路径途经巴尔喀什湖北部、天山山区等地,从哈密市西部翻越天山进入哈密南部,为沙尘暴的发生提供了丰富的沙源。
利用高空、地面、区域自动气象站和风廓线雷达、激光雷达观测资料,采用HYSPLIT模型,对2024年4月12—14日哈密市一次强沙尘暴天气过程特征进行分析,并采用HYSPLIT模型对沙尘轨迹进行模拟。结果表明:500hPa西西伯利亚低槽快速东移南下、极地强冷空气向南爆发是此次强大风沙尘暴发生的影响系统,地面冷锋后强偏北大风是产生强沙尘暴的主要原因。激光雷达1.0—6.0km-1,退偏振比在0.11—0.20,风廓线雷达低空风场出现切变和风向转为偏东风时,分别对应哈密站沙尘暴天气的开始和强沙尘暴的开始。前期温高雨少,时值北疆春播期,沙尘自哈萨克斯坦阿斯塔纳,沿西北路径途经巴尔喀什湖北部、天山山区等地,从哈密市西部翻越天山进入哈密南部,为沙尘暴的发生提供了丰富的沙源。
Abstract:
Based on the national multi-source analysis products by the National Meteorological Information Center of CMA and ground automatic stations observation data in 2023,the applicability of hourly temperature, relative humidity, wind and precipitation in Fujian were evaluated by the error statistical analysis,skill score and other methods.The result show that the quality of temperature product is good,the mean error is between -0.5 and 0.5℃,correlation coefficient is 0.999.The mean absolute error of relative humidity is 0.646%,correlation coefficient is 0.997,which means that it has a high accuracy.The wind product are consistent with automatic station observations,with the mean error is between -0.2 and 0 m/s,Inland areas perform better than coastal areas.The TS score of precipitation products for light rain is higher than those in other classes,and as the rainfall magnitude increases,the false alarm rates and missing report rate increase in general.For Typhoon Doksuri,the precipitation product are consistent with automatic station observations with respect to the precipitation intensity and the precipitation area,but there are deviations in the reproduction capabilities of precipitation peak .
Based on the national multi-source analysis products by the National Meteorological Information Center of CMA and ground automatic stations observation data in 2023,the applicability of hourly temperature, relative humidity, wind and precipitation in Fujian were evaluated by the error statistical analysis,skill score and other methods.The result show that the quality of temperature product is good,the mean error is between -0.5 and 0.5℃,correlation coefficient is 0.999.The mean absolute error of relative humidity is 0.646%,correlation coefficient is 0.997,which means that it has a high accuracy.The wind product are consistent with automatic station observations,with the mean error is between -0.2 and 0 m/s,Inland areas perform better than coastal areas.The TS score of precipitation products for light rain is higher than those in other classes,and as the rainfall magnitude increases,the false alarm rates and missing report rate increase in general.For Typhoon Doksuri,the precipitation product are consistent with automatic station observations with respect to the precipitation intensity and the precipitation area,but there are deviations in the reproduction capabilities of precipitation peak .
Abstract:
The objective test and evaluation of the model forecast effect provide an important reference for improving the model forecast performance and improving the forecaster"s localization correction. Using the refined grid precipitation forecast guidance product SCMOC and the three-source fusion grid live precipitation analysis data (CMPAS) of the National Meteorological Center from May to September 2019-2022, based on the classical test and the MODE spatial test method, the precipitation forecast performance of the intelligent grid forecast SCMOC in the Hexi Corridor was tested and analyzed. Results showed: (1) The TS of precipitation forecast by SCMOC varies with the magnitude of precipitation. The smaller the magnitude is, the larger the TS is, the larger the magnitude is, the larger the deviation is, and the smaller the hit rate is. (2) The target similarity of SCMOC for precipitation forecast below rainstorm reaches 0.71 ~ 0.75, and the target similarity of rainstorm is 0 ~ 0.49. (3) The target axis attribute test shows that SCMOC has expanded the length and width of the target axis of each magnitude of precipitation. The rain bands of moderate rain and below are more obvious in the northwest-southeast than in the northeast-southwest, and the heavy rain and rainstorm rain bands are close to the actual situation. (4) The target surface attribute test shows that the forecast area of SCMOC for each magnitude of precipitation is larger than the actual area (except rainstorm), and the larger the magnitude, the greater the degree of bias ; the forecast intensity of light rain is stronger, and the forecast intensity of moderate rain and above is weaker. The light rain forecast is more westward and southward than the actual situation, and the moderate rain and above are more westward and northward. (5) The typical case test shows that SCMOC can better grasp the spatial distribution pattern of precipitation below heavy rain, and the forecast of rain belt and rain intensity is better, but the forecast ability of rain belt and rain intensity of heavy rain and above is weak, and the position is north and west, and the intensity is weak.
The objective test and evaluation of the model forecast effect provide an important reference for improving the model forecast performance and improving the forecaster"s localization correction. Using the refined grid precipitation forecast guidance product SCMOC and the three-source fusion grid live precipitation analysis data (CMPAS) of the National Meteorological Center from May to September 2019-2022, based on the classical test and the MODE spatial test method, the precipitation forecast performance of the intelligent grid forecast SCMOC in the Hexi Corridor was tested and analyzed. Results showed: (1) The TS of precipitation forecast by SCMOC varies with the magnitude of precipitation. The smaller the magnitude is, the larger the TS is, the larger the magnitude is, the larger the deviation is, and the smaller the hit rate is. (2) The target similarity of SCMOC for precipitation forecast below rainstorm reaches 0.71 ~ 0.75, and the target similarity of rainstorm is 0 ~ 0.49. (3) The target axis attribute test shows that SCMOC has expanded the length and width of the target axis of each magnitude of precipitation. The rain bands of moderate rain and below are more obvious in the northwest-southeast than in the northeast-southwest, and the heavy rain and rainstorm rain bands are close to the actual situation. (4) The target surface attribute test shows that the forecast area of SCMOC for each magnitude of precipitation is larger than the actual area (except rainstorm), and the larger the magnitude, the greater the degree of bias ; the forecast intensity of light rain is stronger, and the forecast intensity of moderate rain and above is weaker. The light rain forecast is more westward and southward than the actual situation, and the moderate rain and above are more westward and northward. (5) The typical case test shows that SCMOC can better grasp the spatial distribution pattern of precipitation below heavy rain, and the forecast of rain belt and rain intensity is better, but the forecast ability of rain belt and rain intensity of heavy rain and above is weak, and the position is north and west, and the intensity is weak.
Abstract:
Hour-by-hour precipitation data and ERA5 reanalysis data from May to September 2018-2022 are used to study the characteristics of short-term heavy precipitation in the warm season in Harbin area under the background of cold vortex. Statistics and the following conclusions are drawn from the analysis of individual cases: (1) There is significantly more short-duration heavy precipitation in the northwestern and central parts of the region than in the eastern part. (2) The frequency of weak and medium-intensity heavy precipitation occurs most frequently in July, and increases month by month from May to August, with extreme heavy precipitation occurring most frequently in August. (3) The cold vortex that produces short-term heavy precipitation accounts for 61% in the development period, 14% in the maturity period, and 24% in the weakening period; among them, the number of stations with short-term heavy precipitation is the most in the development period, the maturity period is less than the development period, and the weakening period is the least. (4) The development period is dominated by moderate intensity and stronger short-term heavy precipitation, the maturity period is dominated by weaker and moderate intensity short-term heavy precipitation, and the weakening period is dominated by moderate intensity and extreme short-term heavy precipitation, with heavy rainfall scattered and localized. (5) There is a good correspondence between the upward movement and the area of heavy precipitation in the developmental period, with strong coupling of high and low level rapids; the upward movement in the weakening period is weaker than that in the developmental period, and the weakest in the maturation period. (6) The best water vapor conditions are found in the developmental period, the whole layer specific humidity is larger and stably maintained, and the specific humidity in the weakening period is the second largest and the smallest in the maturation period.
Hour-by-hour precipitation data and ERA5 reanalysis data from May to September 2018-2022 are used to study the characteristics of short-term heavy precipitation in the warm season in Harbin area under the background of cold vortex. Statistics and the following conclusions are drawn from the analysis of individual cases: (1) There is significantly more short-duration heavy precipitation in the northwestern and central parts of the region than in the eastern part. (2) The frequency of weak and medium-intensity heavy precipitation occurs most frequently in July, and increases month by month from May to August, with extreme heavy precipitation occurring most frequently in August. (3) The cold vortex that produces short-term heavy precipitation accounts for 61% in the development period, 14% in the maturity period, and 24% in the weakening period; among them, the number of stations with short-term heavy precipitation is the most in the development period, the maturity period is less than the development period, and the weakening period is the least. (4) The development period is dominated by moderate intensity and stronger short-term heavy precipitation, the maturity period is dominated by weaker and moderate intensity short-term heavy precipitation, and the weakening period is dominated by moderate intensity and extreme short-term heavy precipitation, with heavy rainfall scattered and localized. (5) There is a good correspondence between the upward movement and the area of heavy precipitation in the developmental period, with strong coupling of high and low level rapids; the upward movement in the weakening period is weaker than that in the developmental period, and the weakest in the maturation period. (6) The best water vapor conditions are found in the developmental period, the whole layer specific humidity is larger and stably maintained, and the specific humidity in the weakening period is the second largest and the smallest in the maturation period.
Abstract:
Based on precipitation forecast data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasting system (IFS), this study employs Empirical Orthogonal Function (EOF) and Affinity Propagation Clustering (AP) methods to construct the EOF_AP clustering model. The model is applied to analyze and classify three major heavy precipitation events in the Beijing-Tianjin-Hebei region during the winters of 2019–2021, focusing on medium-range forecast features. The results shows: firstly, the EOF_AP clustering model demonstrates excellent performance, effectively identifying and classifying the primary types of cumulative precipitation forecasts in ensemble models and their occurrence probabilities. It is particularly adept at extracting low-probability extreme precipitation forecast types with high clustering credibility. Then, the ECMWF ensemble forecasting system exhibits a certain capability for predicting extreme heavy precipitation in winter. Around 168 hours in advance, a small number of ensemble members start to stably predict extreme precipitation types close to actual observations. At approximately 72 hours in advance, a turning point occurs, and the number of members capable of identifying extreme precipitation increases significantly. Finally, the ensemble model shows greater predictability for precipitation location than for precipitation intensity, with more ensemble members providing accurate forecasts for longer lead times.
Based on precipitation forecast data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasting system (IFS), this study employs Empirical Orthogonal Function (EOF) and Affinity Propagation Clustering (AP) methods to construct the EOF_AP clustering model. The model is applied to analyze and classify three major heavy precipitation events in the Beijing-Tianjin-Hebei region during the winters of 2019–2021, focusing on medium-range forecast features. The results shows: firstly, the EOF_AP clustering model demonstrates excellent performance, effectively identifying and classifying the primary types of cumulative precipitation forecasts in ensemble models and their occurrence probabilities. It is particularly adept at extracting low-probability extreme precipitation forecast types with high clustering credibility. Then, the ECMWF ensemble forecasting system exhibits a certain capability for predicting extreme heavy precipitation in winter. Around 168 hours in advance, a small number of ensemble members start to stably predict extreme precipitation types close to actual observations. At approximately 72 hours in advance, a turning point occurs, and the number of members capable of identifying extreme precipitation increases significantly. Finally, the ensemble model shows greater predictability for precipitation location than for precipitation intensity, with more ensemble members providing accurate forecasts for longer lead times.
Abstract:
Abstract:From the afternoon to night on June 12,2022, multi-disaster convective weather including extreme heavy precipitation，thunderstorm wind and hail occurred in eastern Beijing．Using the ground automatic encryption observation station data、ERA5 reanalysis data、GPS/MET water vapor data and the dual-polarization radar data in Beijing, causes of a severe convective weather and the dual-polarization radar characteristics are analyzed. The results show that：(1) This severe convective weather occurs in the area where the Northeast China Cold Vortex superimposes on the low-level warm ridge. The near surface water vapor transport and strong vertical wind shear further enhance the convective potential. (2) Cold air accumulates in front of the mountain after convection occurs.The front of the cold air zone continuously triggers new convection, leading to the long-term maintenance of strong convective weather. (3) The low elevation ZDR of the dual polarization radar is close to 0 dB, and the CC drops to 0.85~0.95, showing obvious hail cloud characteristics. The ZDR column extends to -20 ℃ isothermal line. The low level of CC and the hole of KDP appear in this area. The strong upward airflow at this location is conducive to the growth of hail. Strong wind appears at the forefront of low elevation velocity high value areas and reflectivity factor and KDP gradient high value areas. The rapid decline in the height of the center of mass has intensified strong winds on the ground. During the period of heavy rainfall, both ZDR and KDP show an increasing trend with the increase of Z. The rainfall intensity rapidly increases with the leap of low-level KDP.
Abstract:From the afternoon to night on June 12,2022, multi-disaster convective weather including extreme heavy precipitation，thunderstorm wind and hail occurred in eastern Beijing．Using the ground automatic encryption observation station data、ERA5 reanalysis data、GPS/MET water vapor data and the dual-polarization radar data in Beijing, causes of a severe convective weather and the dual-polarization radar characteristics are analyzed. The results show that：(1) This severe convective weather occurs in the area where the Northeast China Cold Vortex superimposes on the low-level warm ridge. The near surface water vapor transport and strong vertical wind shear further enhance the convective potential. (2) Cold air accumulates in front of the mountain after convection occurs.The front of the cold air zone continuously triggers new convection, leading to the long-term maintenance of strong convective weather. (3) The low elevation ZDR of the dual polarization radar is close to 0 dB, and the CC drops to 0.85~0.95, showing obvious hail cloud characteristics. The ZDR column extends to -20 ℃ isothermal line. The low level of CC and the hole of KDP appear in this area. The strong upward airflow at this location is conducive to the growth of hail. Strong wind appears at the forefront of low elevation velocity high value areas and reflectivity factor and KDP gradient high value areas. The rapid decline in the height of the center of mass has intensified strong winds on the ground. During the period of heavy rainfall, both ZDR and KDP show an increasing trend with the increase of Z. The rainfall intensity rapidly increases with the leap of low-level KDP.
Abstract:
Based on the precipitation data from more than 600 new rainfall stations in Shangluo City and the results of the National Geological Disaster Survey in 2020, the threshold of rainfall-type geological disaster in Shangluo City was re-studied and compared with the research results in 2010. The results showed that the threshold starting value and range of each prone area determined by this time had obvious changes, and the threshold value tended to concentrate in the middle. That is, the threshold initial value of the high-prone region increases, the threshold initial value of the non-prone region decreases, and the threshold ranges of three levels in each prone region show a decreasing trend. The initial threshold of debris flow decreases, and the threshold range of the three levels also decreases significantly. The main reason for this change is that the rainfall data corresponding to the geological disaster obtained this time is denser than that in 2010, and the matching rainfall range is also refined from 5 km to 3 km, and the data quality is improved. Based on the SWAN system of Shangluo Meteorological Observatory, the actual rainfall and the threshold value calculated by the 3-hour grid (3 km × 3 km) rainfall forecast, the geological hazard level forecast, and early warning application are carried out, and the effect is good.
Based on the precipitation data from more than 600 new rainfall stations in Shangluo City and the results of the National Geological Disaster Survey in 2020, the threshold of rainfall-type geological disaster in Shangluo City was re-studied and compared with the research results in 2010. The results showed that the threshold starting value and range of each prone area determined by this time had obvious changes, and the threshold value tended to concentrate in the middle. That is, the threshold initial value of the high-prone region increases, the threshold initial value of the non-prone region decreases, and the threshold ranges of three levels in each prone region show a decreasing trend. The initial threshold of debris flow decreases, and the threshold range of the three levels also decreases significantly. The main reason for this change is that the rainfall data corresponding to the geological disaster obtained this time is denser than that in 2010, and the matching rainfall range is also refined from 5 km to 3 km, and the data quality is improved. Based on the SWAN system of Shangluo Meteorological Observatory, the actual rainfall and the threshold value calculated by the 3-hour grid (3 km × 3 km) rainfall forecast, the geological hazard level forecast, and early warning application are carried out, and the effect is good.
Abstract:
Based on conventional observation data, ERA5 reanalysis data, wind profile of Doppler weather radar data, five southwest jet stream type warm-sector rainstorms were analyzed, and a conceptual model of this kind rainstorm is preliminarily established. The occurrence conditions and jet stream pulses are also analyzed. The results showed that: The rainstorm has two vapor transport channels of Bay of Bengal and South China Sea, and the main water vapor transport altitude is around 850 hPa; The strengthened 850 hPa southwesterly jet intensified the "upper cool and lower warm" stratification. Vertical wind shear between 800 hPa and 1000 hPa shows enhanced features when the rainstorm occurred and developed. The atmosphere is moderately unstable; Moderate to weak Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN) would also lead to rainstorms. 1 to 2 hours before the rainstorm, the jet stream pulses spread upward. The wind speed and thickness of jet stream at an altitude of 1.0 to 3.4 km had a certain relationship with precipitation.
Based on conventional observation data, ERA5 reanalysis data, wind profile of Doppler weather radar data, five southwest jet stream type warm-sector rainstorms were analyzed, and a conceptual model of this kind rainstorm is preliminarily established. The occurrence conditions and jet stream pulses are also analyzed. The results showed that: The rainstorm has two vapor transport channels of Bay of Bengal and South China Sea, and the main water vapor transport altitude is around 850 hPa; The strengthened 850 hPa southwesterly jet intensified the "upper cool and lower warm" stratification. Vertical wind shear between 800 hPa and 1000 hPa shows enhanced features when the rainstorm occurred and developed. The atmosphere is moderately unstable; Moderate to weak Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN) would also lead to rainstorms. 1 to 2 hours before the rainstorm, the jet stream pulses spread upward. The wind speed and thickness of jet stream at an altitude of 1.0 to 3.4 km had a certain relationship with precipitation.
Abstract:
Numerical weather prediction is an essential component of core technologies that safeguard national economy, people's livelihood, and national defense security. In order to enhance the meteorological service level along the "Belt and Road" regions, the Urumqi Desert Meteorological Research Institute of the China Meteorological Administration has been advancing the development of the Central Asia Regional Rapid Update Multi-scale Analysis and Forecast System (RMAPS-CA) since 2017. Significant research achievements have been made in the joint assimilation of multi-source data, optimization of parameterization schemes, and adjustment of the dynamic framework. Based on a review of the operational development history of RMAPS-CA, this paper focuses on summarizing the research achievements in the assimilation of radar reflectivity, the separation of sub-grid physical processes such as gravity wave drag due to high-altitude sub-grid terrain and near-surface blocking drag, the hybrid terrain-following coordinate dynamic framework, and the correction of forecast products based on the Bayesian model averaging (BMA) method. In response to the characteristics of sparse conventional observations and extensive desert surfaces in Central Asia, suggestions are proposed to strengthen the operational development and application of numerical weather prediction in the Central Asia region, especially on the assimilation of satellite ground channels.
Numerical weather prediction is an essential component of core technologies that safeguard national economy, people's livelihood, and national defense security. In order to enhance the meteorological service level along the "Belt and Road" regions, the Urumqi Desert Meteorological Research Institute of the China Meteorological Administration has been advancing the development of the Central Asia Regional Rapid Update Multi-scale Analysis and Forecast System (RMAPS-CA) since 2017. Significant research achievements have been made in the joint assimilation of multi-source data, optimization of parameterization schemes, and adjustment of the dynamic framework. Based on a review of the operational development history of RMAPS-CA, this paper focuses on summarizing the research achievements in the assimilation of radar reflectivity, the separation of sub-grid physical processes such as gravity wave drag due to high-altitude sub-grid terrain and near-surface blocking drag, the hybrid terrain-following coordinate dynamic framework, and the correction of forecast products based on the Bayesian model averaging (BMA) method. In response to the characteristics of sparse conventional observations and extensive desert surfaces in Central Asia, suggestions are proposed to strengthen the operational development and application of numerical weather prediction in the Central Asia region, especially on the assimilation of satellite ground channels.
Abstract:
To optimize the agricultural cultivation structure and promote the healthy and stable development of the seed maize industry in the Ili River Valley. Based on the meteorological data from 10 national meteorological observation stations in the Ili River Valley from 1991 to 2020, meteorological factors that have a significant impact on seed maize cultivation in the Ili river valley were selected in combination with practical production. These factors include ≥10℃ active accumulated temperature, late spring coldness, high temperature days, and gale days. The spatiotemporal distribution characteristics of each meteorological factor in various counties and cities were analyzed, along with their impact on seed maize cultivation. Additionally, climatic suitability values for each meteorological factor were provided for these counties and cities. The principal component analysis method was used to determine the influence weights of each meteorological factor, and the comprehensive climate suitability for seed maize cultivation in each county and city was calculated. The results showed that Xinyuan County has the highest comprehensive climate suitability value for seed maize cultivation, reaching 9.83. Its climate is highly conducive to the growth and development of seed maize, with fewer disasters, making it the most ideal region for the development of seed maize industry in the Ili River Valley. The western valley areas such as Qapqal, along with two other counties and cities, have favorable thermal conditions. However, there are more weather disasters that affect the growth and development of seed maize cultivation, leading to higher costs for disaster prevention and mitigation. The cultivation benefits in these areas are lower than in counties and cities like Xinyuan, and thus, the scale of seed maize cultivation should be limited.
To optimize the agricultural cultivation structure and promote the healthy and stable development of the seed maize industry in the Ili River Valley. Based on the meteorological data from 10 national meteorological observation stations in the Ili River Valley from 1991 to 2020, meteorological factors that have a significant impact on seed maize cultivation in the Ili river valley were selected in combination with practical production. These factors include ≥10℃ active accumulated temperature, late spring coldness, high temperature days, and gale days. The spatiotemporal distribution characteristics of each meteorological factor in various counties and cities were analyzed, along with their impact on seed maize cultivation. Additionally, climatic suitability values for each meteorological factor were provided for these counties and cities. The principal component analysis method was used to determine the influence weights of each meteorological factor, and the comprehensive climate suitability for seed maize cultivation in each county and city was calculated. The results showed that Xinyuan County has the highest comprehensive climate suitability value for seed maize cultivation, reaching 9.83. Its climate is highly conducive to the growth and development of seed maize, with fewer disasters, making it the most ideal region for the development of seed maize industry in the Ili River Valley. The western valley areas such as Qapqal, along with two other counties and cities, have favorable thermal conditions. However, there are more weather disasters that affect the growth and development of seed maize cultivation, leading to higher costs for disaster prevention and mitigation. The cultivation benefits in these areas are lower than in counties and cities like Xinyuan, and thus, the scale of seed maize cultivation should be limited.
Abstract:
Based on climate observation data from 105 national meteorological stations in Xinjiang during 1991-2020 under the new climatic normals, this study employed a GIS-based spatial fine-grid interpolation model to analyze the spatial distribution of key climatic factors influencing cotton growth, including ≥10℃ accumulated temperature, frost-free period, and July mean temperature. By integrating the climate suitability zoning index system for cotton varieties with different maturity groups and applying spatial overlay analysis, we classified the cotton cultivation regions in Xinjiang into five climate suitability categories: The mid-maturing cotton zone, predominantly concentrated in the Turpan and Hami basins of the eastern Tianshan Mountains; The early-mid-maturing cotton zone, mainly distributed along the northern, northwestern, western, and southwestern margins of the Tarim Basin; The early-maturing cotton zone, primarily located in the piedmont sloping plains south of the Gurbantünggüt Desert and the southern margin of the Junggar Basin, extending to the northern foothills of the Tianshan Mountains; The ultra-early-maturing cotton zone, distributed across the Ili River Valley, Tacheng Basin, Yanqi Basin, and parts of the Bortala Mongol Autonomous Prefecture and Kizilsu Kirghiz Autonomous Prefecture; The non-suitable cotton zone, extensively covering the Altai, Tianshan, and Kunlun Mountains and their high-altitude, high-latitude foothills. This zoning framework provides a scientific basis for optimizing cotton production layout in Xinjiang, facilitating the concentration of cotton cultivation in advantageous regions, while offering climatological support for scientific planning of coordinated grain-cotton development.
Based on climate observation data from 105 national meteorological stations in Xinjiang during 1991-2020 under the new climatic normals, this study employed a GIS-based spatial fine-grid interpolation model to analyze the spatial distribution of key climatic factors influencing cotton growth, including ≥10℃ accumulated temperature, frost-free period, and July mean temperature. By integrating the climate suitability zoning index system for cotton varieties with different maturity groups and applying spatial overlay analysis, we classified the cotton cultivation regions in Xinjiang into five climate suitability categories: The mid-maturing cotton zone, predominantly concentrated in the Turpan and Hami basins of the eastern Tianshan Mountains; The early-mid-maturing cotton zone, mainly distributed along the northern, northwestern, western, and southwestern margins of the Tarim Basin; The early-maturing cotton zone, primarily located in the piedmont sloping plains south of the Gurbantünggüt Desert and the southern margin of the Junggar Basin, extending to the northern foothills of the Tianshan Mountains; The ultra-early-maturing cotton zone, distributed across the Ili River Valley, Tacheng Basin, Yanqi Basin, and parts of the Bortala Mongol Autonomous Prefecture and Kizilsu Kirghiz Autonomous Prefecture; The non-suitable cotton zone, extensively covering the Altai, Tianshan, and Kunlun Mountains and their high-altitude, high-latitude foothills. This zoning framework provides a scientific basis for optimizing cotton production layout in Xinjiang, facilitating the concentration of cotton cultivation in advantageous regions, while offering climatological support for scientific planning of coordinated grain-cotton development.
Abstract:
MODIS data from April to September were used to build EVI (Enhanced Vegetation Index)-LST (Land Surface Temperature) feature space and calculate temperature vegetation drought index (TVDI) which modified by digital elevation Model (DEM). Based on the correlation between modified TVDI (MTVDI), relative soil moisture and precipitation, the applicability of MTVDI in monitoring drought in Hebei was discussed. The results showed that: (1) the modified EVI-LST feature space was more in line with the triangle relationship and closer to the TVDI Schematic diagram by DEM. (2) The correlation between MTVDI and soil moisture were 0.09 higher than TVDI and soil moisture and the spatial matching degree was above 0.9, indicating MTVDI has the ability to reflect the dry and wet conditions of soil. (3) MTVDI had negative correlation with precipitation, and it showed that MTVDI can represent drought in Hebei to a certain extent from the meteorological view. (4) From the perspective of the 2019 drought event, MTVDI can show the development of drought from northeast to all area of Hebei. In conclusion, MTVDI can reflect the agricultural drought in Hebei. Our study can provide scientific reference for the operation of drought monitoring and the strategy of drought relief.
MODIS data from April to September were used to build EVI (Enhanced Vegetation Index)-LST (Land Surface Temperature) feature space and calculate temperature vegetation drought index (TVDI) which modified by digital elevation Model (DEM). Based on the correlation between modified TVDI (MTVDI), relative soil moisture and precipitation, the applicability of MTVDI in monitoring drought in Hebei was discussed. The results showed that: (1) the modified EVI-LST feature space was more in line with the triangle relationship and closer to the TVDI Schematic diagram by DEM. (2) The correlation between MTVDI and soil moisture were 0.09 higher than TVDI and soil moisture and the spatial matching degree was above 0.9, indicating MTVDI has the ability to reflect the dry and wet conditions of soil. (3) MTVDI had negative correlation with precipitation, and it showed that MTVDI can represent drought in Hebei to a certain extent from the meteorological view. (4) From the perspective of the 2019 drought event, MTVDI can show the development of drought from northeast to all area of Hebei. In conclusion, MTVDI can reflect the agricultural drought in Hebei. Our study can provide scientific reference for the operation of drought monitoring and the strategy of drought relief.
Abstract:
Using the daily ground data from 105 stations in Xinjiang， climate indices such as Arctic Oscillation （AO）， NOAA satellite outgoing long-wave radiation （OLR） data， and Global Data Assimilation System （GDAS） data， we analyzed the changes in climate patterns before and after the cold wave process， tracked the source of cold air during the cold wave process， and explored the characteristics of the cold wave process in Xinjiang during the winter of 2023/2024. The results indicate that Xinjiang experienced 2 cold wave events during the 2023/2024 winter， which is 0.4 more than the long-term average. The average intensity of these cold waves was 2.39， 0.65 stronger than the long-term average.The negative anomaly of AO， the enhancement of meridional circulation， and the decrease of OLR are all conducive to the occurrence and development of cold wave processes in Xinjiang. The cold air path of the cold wave process in Xinjiang in the winter of 2023/2024 is divided into westward and northwestward paths. Through the three-dimensional spatial distribution of cold air trajectories at different heights， it is found that the cold air is mainly concentrated at 400 hPa and 750 hPa. Paying attention to its changes is of great significance for guiding the prediction of the winter cold wave process in the extended period.
Using the daily ground data from 105 stations in Xinjiang， climate indices such as Arctic Oscillation （AO）， NOAA satellite outgoing long-wave radiation （OLR） data， and Global Data Assimilation System （GDAS） data， we analyzed the changes in climate patterns before and after the cold wave process， tracked the source of cold air during the cold wave process， and explored the characteristics of the cold wave process in Xinjiang during the winter of 2023/2024. The results indicate that Xinjiang experienced 2 cold wave events during the 2023/2024 winter， which is 0.4 more than the long-term average. The average intensity of these cold waves was 2.39， 0.65 stronger than the long-term average.The negative anomaly of AO， the enhancement of meridional circulation， and the decrease of OLR are all conducive to the occurrence and development of cold wave processes in Xinjiang. The cold air path of the cold wave process in Xinjiang in the winter of 2023/2024 is divided into westward and northwestward paths. Through the three-dimensional spatial distribution of cold air trajectories at different heights， it is found that the cold air is mainly concentrated at 400 hPa and 750 hPa. Paying attention to its changes is of great significance for guiding the prediction of the winter cold wave process in the extended period.
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Abstract:
This research employed daily meteorological observations and outpatient visit records for respiratory ailments in Yinchuan from 2015 to 2022. By utilizing the Generalized Additive Model (GAM) and the Distributed Lag Nonlinear Model (DLNM), with inhalable particulate matter concentration in Yinchuan serving as the primary exposure variable and NO?, SO?, CO, wind speed, mean temperature, and maximum temperature as covariates, it quantitatively assessed the lagged and cumulative impacts of inhalable particulate matter concentration on outpatient visits for respiratory diseases in Yinchuan. The findings are as follows:(1) Between 2015 and 2022, the number of outpatient consultations for respiratory diseases exhibited a fluctuating yet upward trend. A notable positive correlation was observed between the concentration of inhalable particulate matter and the number of outpatient visits, with both reaching their zenith during winter and spring.(2) During the same period, both PM?.? and PM?? concentrations demonstrated a marginal decline. The proportion of days categorized as "mild pollution" or worse for PM2.5 ranged from 10% to 40%, predominantly occurring in spring and winter. For PM??, this proportion varied between 10% and 30%.(3) The concentration of inhalable particulate matter exerted both lagged and cumulative effects on the number of outpatient visits for respiratory diseases. On the day of disease onset, the likelihood of respiratory illness escalated with increasing PM?? levels. Furthermore, the risk persisted above baseline (RR > 1) within a two-day lag period.(4) The exposure-response relationship between inhalable particulate matter concentration and outpatient visits for respiratory diseases displayed minimal overall variance across genders. However, variations in sensitivity and lagged effects were evident among different age groups: individuals aged 65 and above exhibited heightened susceptibility to particulate matter concentrations. When PM?.? remained below 175 μg/m3, the risk of disease onset peaked on the same day for all demographic groups. For the elderly, this risk persisted until the tenth day post-exposure, whereas for those under 65, it lasted until the 4th day.
This research employed daily meteorological observations and outpatient visit records for respiratory ailments in Yinchuan from 2015 to 2022. By utilizing the Generalized Additive Model (GAM) and the Distributed Lag Nonlinear Model (DLNM), with inhalable particulate matter concentration in Yinchuan serving as the primary exposure variable and NO?, SO?, CO, wind speed, mean temperature, and maximum temperature as covariates, it quantitatively assessed the lagged and cumulative impacts of inhalable particulate matter concentration on outpatient visits for respiratory diseases in Yinchuan. The findings are as follows:(1) Between 2015 and 2022, the number of outpatient consultations for respiratory diseases exhibited a fluctuating yet upward trend. A notable positive correlation was observed between the concentration of inhalable particulate matter and the number of outpatient visits, with both reaching their zenith during winter and spring.(2) During the same period, both PM?.? and PM?? concentrations demonstrated a marginal decline. The proportion of days categorized as "mild pollution" or worse for PM2.5 ranged from 10% to 40%, predominantly occurring in spring and winter. For PM??, this proportion varied between 10% and 30%.(3) The concentration of inhalable particulate matter exerted both lagged and cumulative effects on the number of outpatient visits for respiratory diseases. On the day of disease onset, the likelihood of respiratory illness escalated with increasing PM?? levels. Furthermore, the risk persisted above baseline (RR > 1) within a two-day lag period.(4) The exposure-response relationship between inhalable particulate matter concentration and outpatient visits for respiratory diseases displayed minimal overall variance across genders. However, variations in sensitivity and lagged effects were evident among different age groups: individuals aged 65 and above exhibited heightened susceptibility to particulate matter concentrations. When PM?.? remained below 175 μg/m3, the risk of disease onset peaked on the same day for all demographic groups. For the elderly, this risk persisted until the tenth day post-exposure, whereas for those under 65, it lasted until the 4th day.
Abstract:
In this paper, the mesoscale model WRF and microscale weather model calmet were interoduced to simulate the near ground wind speed in Jiangxi Province,using WRF-3DVAR assimilation system to assimilate conventional meteorological observation data. The influence of conventional observation data assimilation on wind speed simulation is tested using data from meteorological stations and wind measurement towers of typical wind farms in Jiangxi Province. The results show that: The results show that after assimilating conventional observation data, the annual average wind speed at various altitudes of 10-70m in most areas of Jiangxi Province is 0.3～1.6 m/s lower than that of the non assimilating scheme. The assimilation of conventional observation data has improved the simulation of near-surface wind speed in Jiangxi. Compared to before assimilation, after assimilation, the correlation coefficient between simulated and measured wind speeds at meteorological stations has increased by 0 to 0.28, with the deviation reduction of 0.13 to 0.9 m/s and the standard deviation reduction of 0.03 to 1.08 m/s. The simulation effect of the wind speed assimilation experiment at the lower level (10m) of the wind towers in Poyang Lake area is better than that of the non assimilation experiment, but with the increase of the height, the error between the wind speed simulated in the assimilation experiment and the observation value gradually increases. For the wind towers in the mountainous areas of Gannan with higher altitudes, the simulation effect of non assimilation experiments from 10 to 70 meters is better than that of assimilation experiments.
In this paper, the mesoscale model WRF and microscale weather model calmet were interoduced to simulate the near ground wind speed in Jiangxi Province,using WRF-3DVAR assimilation system to assimilate conventional meteorological observation data. The influence of conventional observation data assimilation on wind speed simulation is tested using data from meteorological stations and wind measurement towers of typical wind farms in Jiangxi Province. The results show that: The results show that after assimilating conventional observation data, the annual average wind speed at various altitudes of 10-70m in most areas of Jiangxi Province is 0.3～1.6 m/s lower than that of the non assimilating scheme. The assimilation of conventional observation data has improved the simulation of near-surface wind speed in Jiangxi. Compared to before assimilation, after assimilation, the correlation coefficient between simulated and measured wind speeds at meteorological stations has increased by 0 to 0.28, with the deviation reduction of 0.13 to 0.9 m/s and the standard deviation reduction of 0.03 to 1.08 m/s. The simulation effect of the wind speed assimilation experiment at the lower level (10m) of the wind towers in Poyang Lake area is better than that of the non assimilation experiment, but with the increase of the height, the error between the wind speed simulated in the assimilation experiment and the observation value gradually increases. For the wind towers in the mountainous areas of Gannan with higher altitudes, the simulation effect of non assimilation experiments from 10 to 70 meters is better than that of assimilation experiments.
Abstract:
Heavy rainfall and flash floods pose severe threats to people’s lives, property, and social and economic development. This study focuses on the Xigou reservoir basin in Yiwu County, Hami City, using historical precipitation data from 1961 to 2023. The FloodArea model and return period functions were employed to estimate the areal rainfall of extreme precipitation events under different return periods and to simulate flood inundation risks. The results show that the maximum daily precipitation in the Xigou basin has significantly increased from 1961 to 2023, with an average increase of 2.1 mm per decade, especially evident since the late 1980s. During the major rainfall event in the Hami mountainous area on July 31, 2018, the precipitation peaked around 6:00 AM, leading to rapid surface runoff and a significant expansion of the inundation range and depth. Using SPSS and MuDFiT tools, the areal rainfall for return periods of 100, 50, 30, 20, 10, and 5 years were determined to be 51.83 mm, 34.94 mm, 26.23 mm, 20.62 mm, 13.70 mm, and 8.93 mm, respectively. The simulation results indicate that the inundation range and depth increase significantly with the return period, and the areal rainfall for 30 years or more reaches the heavy rainfall standard of Xinjiang. The vulnerability assessment of disaster-bearing bodies shows that vulnerability increases significantly with the increase in flood return period. For a 100-year flood with a inundation depth exceeding 1.8 meters, the affected population and GDP proportions are as high as 60.87% and 54.03%, respectively. These findings highlight the far-reaching impact of severe floods on society and the economy, emphasizing the need for more stringent disaster prevention and mitigation measures.
Heavy rainfall and flash floods pose severe threats to people’s lives, property, and social and economic development. This study focuses on the Xigou reservoir basin in Yiwu County, Hami City, using historical precipitation data from 1961 to 2023. The FloodArea model and return period functions were employed to estimate the areal rainfall of extreme precipitation events under different return periods and to simulate flood inundation risks. The results show that the maximum daily precipitation in the Xigou basin has significantly increased from 1961 to 2023, with an average increase of 2.1 mm per decade, especially evident since the late 1980s. During the major rainfall event in the Hami mountainous area on July 31, 2018, the precipitation peaked around 6:00 AM, leading to rapid surface runoff and a significant expansion of the inundation range and depth. Using SPSS and MuDFiT tools, the areal rainfall for return periods of 100, 50, 30, 20, 10, and 5 years were determined to be 51.83 mm, 34.94 mm, 26.23 mm, 20.62 mm, 13.70 mm, and 8.93 mm, respectively. The simulation results indicate that the inundation range and depth increase significantly with the return period, and the areal rainfall for 30 years or more reaches the heavy rainfall standard of Xinjiang. The vulnerability assessment of disaster-bearing bodies shows that vulnerability increases significantly with the increase in flood return period. For a 100-year flood with a inundation depth exceeding 1.8 meters, the affected population and GDP proportions are as high as 60.87% and 54.03%, respectively. These findings highlight the far-reaching impact of severe floods on society and the economy, emphasizing the need for more stringent disaster prevention and mitigation measures.
Abstract:
Based on the theory of regional disaster risk, ten evaluation indicators were selected from three aspects: the hazard-inducing risk of wind and hail disasters, vulnerability of disaster-bearing bodies, and environmental sensitivity. The AHP-entropy weight combination method was used to determine the weights of each evaluation indicator. A risk assessment model for wind and hail disasters was established to conduct a risk assessment study of wind and hail disasters in Hebei Province. The results indicate that the high-risk and higher-risk areas for wind and hail disasters in Hebei Province account for 9.3% and 22.6% of the total area, respectively. The high-risk areas are mainly concentrated in the northern and central-western parts of Zhangjiakou, southern Hengshui, northwestern Xingtai, and central-eastern Shijiazhuang, while the central and northern parts of Baoding, Tangshan, and Qinhuangdao have lower risks. The assessment results can well reflect the risk level of wind and hail disasters in Hebei Province.
Based on the theory of regional disaster risk, ten evaluation indicators were selected from three aspects: the hazard-inducing risk of wind and hail disasters, vulnerability of disaster-bearing bodies, and environmental sensitivity. The AHP-entropy weight combination method was used to determine the weights of each evaluation indicator. A risk assessment model for wind and hail disasters was established to conduct a risk assessment study of wind and hail disasters in Hebei Province. The results indicate that the high-risk and higher-risk areas for wind and hail disasters in Hebei Province account for 9.3% and 22.6% of the total area, respectively. The high-risk areas are mainly concentrated in the northern and central-western parts of Zhangjiakou, southern Hengshui, northwestern Xingtai, and central-eastern Shijiazhuang, while the central and northern parts of Baoding, Tangshan, and Qinhuangdao have lower risks. The assessment results can well reflect the risk level of wind and hail disasters in Hebei Province.
Abstract:
Using temperature, precipitation, Normalized Difference Vegetation Index (NDVI) and Net Primary Productivity (NPP), three drought indices, namely the Temperature Condition Index (TCI), Vegetation Condition Index (VCI) and Vegetation Health Index (VHI), are calculated. The Theil-Sen median trend analysis and Mann-Kendall test methods were adopted to study the spatio-temporal variation characteristics of drought in the three provinces of Yunnan, Guizhou, and Guangxi in Southwest China from 1961 to 2023. The relationship between NPP and various droughts, as well as the causes of drought and NPP changes, were explored. The results show that: (1) The three drought indices, TCI, VCI, and VHI, all show upward trends of varying degrees. Although there are differences in the regional drought evaluated by different indices, they all show that the drought has gradually eased during the study period. (2) From 1982 to 2018, the overall NPP level in the three provinces was 885.4 gC?m-2?a-1, with an overall growth trend of 2.053 gC?m-2?a-1, and there were large differences among different provinces. The response of NPP to TCI, VCI, and VHI indicates that there are significant correlations among them. Among them, the correlation between VCI and NPP is the best (r=0.687, p<0.01), indicating that VCI has a good effect in indicating drought and reflecting NPP changes. (3) Comprehensive correlation analysis and wavelet analysis results indicate that regional drought mitigation is an important driver of NPP growth; the monsoon promotes gradual drought mitigation by regulating water vapor transport processes.
Using temperature, precipitation, Normalized Difference Vegetation Index (NDVI) and Net Primary Productivity (NPP), three drought indices, namely the Temperature Condition Index (TCI), Vegetation Condition Index (VCI) and Vegetation Health Index (VHI), are calculated. The Theil-Sen median trend analysis and Mann-Kendall test methods were adopted to study the spatio-temporal variation characteristics of drought in the three provinces of Yunnan, Guizhou, and Guangxi in Southwest China from 1961 to 2023. The relationship between NPP and various droughts, as well as the causes of drought and NPP changes, were explored. The results show that: (1) The three drought indices, TCI, VCI, and VHI, all show upward trends of varying degrees. Although there are differences in the regional drought evaluated by different indices, they all show that the drought has gradually eased during the study period. (2) From 1982 to 2018, the overall NPP level in the three provinces was 885.4 gC?m-2?a-1, with an overall growth trend of 2.053 gC?m-2?a-1, and there were large differences among different provinces. The response of NPP to TCI, VCI, and VHI indicates that there are significant correlations among them. Among them, the correlation between VCI and NPP is the best (r=0.687, p<0.01), indicating that VCI has a good effect in indicating drought and reflecting NPP changes. (3) Comprehensive correlation analysis and wavelet analysis results indicate that regional drought mitigation is an important driver of NPP growth; the monsoon promotes gradual drought mitigation by regulating water vapor transport processes.
Abstract:
Based on the wire icing data and related meteorological data in Xinjiang from 1985 to 2015, a wire ice accumulation forecasting model for Xinjiang was established based on the multiple regression method. Through analysis, the following conclusions were drawn: (1) Xinjiang’s wire icing days are generally more in northern Xinjiang than in southern Xinjiang, and more mountainous areas than basins, with the most along the Tianshan Mountains (including the east, west, and central Tianshan Mountains). The maximum standard ice accretion thickness is the largest in the northern part of northern Xinjiang; followed by the western part of southern Xinjiang. The number of days of ice accumulation and the maximum standard ice thickness on the southern margin of the Tarim Basin are the smallest areas in Xinjiang. (2) The two-class Logistics regression model was used to predict the occurrence of ice accretion on electric wires, the accuracy rate is 89.49%, and the model effect was good; then multiple regression model was used to predict the thickness of ice accretion. The average absolute error of thickness prediction of the typical ice accretion weather process was 0.98mm, and the model effect was good. (3) The calculation results of the return period show that the ice thickness was big in the northern part of northern Xinjiang, the Tacheng area, the central and western regions along the Tianshan Mountains, the western part of southern Xinjiang; the ice thickness was small in the Tarim Basin and surrounding areas, and most of the eastern Xinjiang.
Based on the wire icing data and related meteorological data in Xinjiang from 1985 to 2015, a wire ice accumulation forecasting model for Xinjiang was established based on the multiple regression method. Through analysis, the following conclusions were drawn: (1) Xinjiang’s wire icing days are generally more in northern Xinjiang than in southern Xinjiang, and more mountainous areas than basins, with the most along the Tianshan Mountains (including the east, west, and central Tianshan Mountains). The maximum standard ice accretion thickness is the largest in the northern part of northern Xinjiang; followed by the western part of southern Xinjiang. The number of days of ice accumulation and the maximum standard ice thickness on the southern margin of the Tarim Basin are the smallest areas in Xinjiang. (2) The two-class Logistics regression model was used to predict the occurrence of ice accretion on electric wires, the accuracy rate is 89.49%, and the model effect was good; then multiple regression model was used to predict the thickness of ice accretion. The average absolute error of thickness prediction of the typical ice accretion weather process was 0.98mm, and the model effect was good. (3) The calculation results of the return period show that the ice thickness was big in the northern part of northern Xinjiang, the Tacheng area, the central and western regions along the Tianshan Mountains, the western part of southern Xinjiang; the ice thickness was small in the Tarim Basin and surrounding areas, and most of the eastern Xinjiang.
Abstract:
Abstract: This study evaluates the performance of the China Meteorological Administration Land Data Assimilation System (CLDAS) 5-km hourly fused analysis products by comparing them with ground meteorological station observations, which located in Urumqi City and Changji Hui Autonomous Prefecture region from January to December 2023. The methodology employs bilinear interpolation for spatial matching and calculates statistical metrics, including the correlation coefficient (COR), mean error (ME), mean absolute error (MAE), mean relative error (MRE), and root mean square error (RMSE). Spatial heterogeneity of errors in temperature, relative humidity, and wind speed products is further analyzed using the Moran’s I index and local indicators of spatial association (LISA) cluster analysis. The key findings are as follows: ⑴ The diurnal variations of CLDAS temperature, relative humidity, and wind speed align closely with station observations, indicating strong capability in capturing spatiotemporal patterns under synoptic-scale weather conditions. ⑵ On an hourly scale, temperature (COR > 0.95) and relative humidity (COR > 0.88) exhibit high consistency with observations, whereas wind speed shows weaker correlations (COR = 0.65–0.83), particularly in southern mountainous areas where terrain-induced parameterization limitations result in significant errors (RMSE ≥ 1.56 m/s). ⑶ While temperature products demonstrate reliability in plains (MAE ≤ 0.76°C), higher independent validation errors (ME = 0.53–0.67°C) suggest inadequate adaptability to local microclimates. Additionally, relative humidity products systematically underestimate values in oasis irrigation zones (ME = -0.83% to -1.24%), likely due to insufficient evapotranspiration coupling. ⑷ Spatially, temperature errors are minimal in the Junggar Basin, relative humidity errors dominate southwestern mountainous and oasis areas, and wind speed errors escalate in urban and complex terrain regions. In conclusion, CLDAS products effectively support macro-scale meteorological analysis in the Wuchang region; however, localized microclimate adaptability in complex terrains (e.g., Tianshan Mountains, oasis-desert transition zones) requires further optimization of parameterization schemes and multi-source data integration.
Abstract: This study evaluates the performance of the China Meteorological Administration Land Data Assimilation System (CLDAS) 5-km hourly fused analysis products by comparing them with ground meteorological station observations, which located in Urumqi City and Changji Hui Autonomous Prefecture region from January to December 2023. The methodology employs bilinear interpolation for spatial matching and calculates statistical metrics, including the correlation coefficient (COR), mean error (ME), mean absolute error (MAE), mean relative error (MRE), and root mean square error (RMSE). Spatial heterogeneity of errors in temperature, relative humidity, and wind speed products is further analyzed using the Moran’s I index and local indicators of spatial association (LISA) cluster analysis. The key findings are as follows: ⑴ The diurnal variations of CLDAS temperature, relative humidity, and wind speed align closely with station observations, indicating strong capability in capturing spatiotemporal patterns under synoptic-scale weather conditions. ⑵ On an hourly scale, temperature (COR > 0.95) and relative humidity (COR > 0.88) exhibit high consistency with observations, whereas wind speed shows weaker correlations (COR = 0.65–0.83), particularly in southern mountainous areas where terrain-induced parameterization limitations result in significant errors (RMSE ≥ 1.56 m/s). ⑶ While temperature products demonstrate reliability in plains (MAE ≤ 0.76°C), higher independent validation errors (ME = 0.53–0.67°C) suggest inadequate adaptability to local microclimates. Additionally, relative humidity products systematically underestimate values in oasis irrigation zones (ME = -0.83% to -1.24%), likely due to insufficient evapotranspiration coupling. ⑷ Spatially, temperature errors are minimal in the Junggar Basin, relative humidity errors dominate southwestern mountainous and oasis areas, and wind speed errors escalate in urban and complex terrain regions. In conclusion, CLDAS products effectively support macro-scale meteorological analysis in the Wuchang region; however, localized microclimate adaptability in complex terrains (e.g., Tianshan Mountains, oasis-desert transition zones) requires further optimization of parameterization schemes and multi-source data integration.
Abstract:
Under the background of global promotion of carbon neutrality, new energy represented by photovoltaic power generation will gradually change from auxiliary energy to main energy. In recent years, extreme weather and climate events have occurred frequently. With the completion and operation of a large number of photovoltaic power stations, the disaster cases of photovoltaic power stations are common. In-depth understanding of the impact mechanism of extreme weather on the development of photovoltaic power stations will help to take effective prevention and control measures in time to ensure the healthy and safe development of the photovoltaic industry. By reviewing relevant literature, high-impact weather affecting the development of photovoltaic (PV) power stations is categorized into two major categories: extreme weather and adverse weather. The effects of various high-impact weather on different stages of photovoltaic power station development are summarized. The results show that in the planning and design stage, it is necessary to identify and evaluate the high-impact weather risk, and carry out scientific site selection and parameter design. In the construction stage, rainstorm leads to instability of pile foundation, soil erosion, strong wind affects lifting operation, sea fog and lightning affect the construction safety of offshore photovoltaic power station, etc. In the production and operation stage, high-impact weather can damage photovoltaic component facilities, reduce the power output of photovoltaic generation, cause drastic fluctuations in the output of photovoltaic power stations, and even threaten the safety and stability of the power grid. Finally, the measures to deal with high-impact weather are proposed, including improving extreme weather risk assessment and modeling techniques, strengthening emergency management and monitoring and early warning of high-impact weather, and considering the impact of high-impact weather on photovoltaic power generation prediction.
Under the background of global promotion of carbon neutrality, new energy represented by photovoltaic power generation will gradually change from auxiliary energy to main energy. In recent years, extreme weather and climate events have occurred frequently. With the completion and operation of a large number of photovoltaic power stations, the disaster cases of photovoltaic power stations are common. In-depth understanding of the impact mechanism of extreme weather on the development of photovoltaic power stations will help to take effective prevention and control measures in time to ensure the healthy and safe development of the photovoltaic industry. By reviewing relevant literature, high-impact weather affecting the development of photovoltaic (PV) power stations is categorized into two major categories: extreme weather and adverse weather. The effects of various high-impact weather on different stages of photovoltaic power station development are summarized. The results show that in the planning and design stage, it is necessary to identify and evaluate the high-impact weather risk, and carry out scientific site selection and parameter design. In the construction stage, rainstorm leads to instability of pile foundation, soil erosion, strong wind affects lifting operation, sea fog and lightning affect the construction safety of offshore photovoltaic power station, etc. In the production and operation stage, high-impact weather can damage photovoltaic component facilities, reduce the power output of photovoltaic generation, cause drastic fluctuations in the output of photovoltaic power stations, and even threaten the safety and stability of the power grid. Finally, the measures to deal with high-impact weather are proposed, including improving extreme weather risk assessment and modeling techniques, strengthening emergency management and monitoring and early warning of high-impact weather, and considering the impact of high-impact weather on photovoltaic power generation prediction.
Abstract:
The wind shear exponent has a significant impact on the selection of wind turbines, hub height, and other factors. To investigate the characteristics of the wind shear exponent in northern Bazhou, according to 96 months of continuous, high time-resolution observational data from southeastern Bosten Lake wind measurement tower from January 2017 to December 2024, the average wind speed, wind speed deviation coefficient, and wind shear exponent at different heights were calculated, and the spatiotemporal distribution characteristics of the wind shear exponent, as well as the relationship between wind shear exponent and wind speed were analyzed. The study revealed that: (1) As the height increases, the overall wind shear exponent shows a segmented decreasing trend with a breakpoint at 70 m. The wind speed difference is greatest at heights of 70 to 80 m, with significant wind speed shear and relatively poor stability. (2) From spring to autumn, the wind shear exponent decreases in segments with increasing height. In winter, minimal variation is observed in the height range of 10 to 70 m, while significant differences emerge in the height range of 70 to 100 m. The diurnal variation of the wind shear exponent at all heights presents a 'bimodal' distribution characteristic, and the diurnal variation characteristic of the wind shear exponent shows a inverse correlation with the diurnal variation of wind speed. (3) There is a wind speed inversion zone in the height range of 35 to 70 m when the wind speed exceeds 8 m·s-1. In the height range of 70 to 100 m, the wind shear exponent shows an inverted V-shaped distribution with a wind speed of 10 m·s-1 as the axis of symmetry. (4) The averages and standard deviations of the wind speed bins generally show that the entire wind speed segment is the largest, followed by the ≥3 m·s-1 startup wind speed segment, and the ≥17.2 m·s-1 strong wind speed segment is the smallest. Wind field stability increases with rising wind speeds, concomitantly resulting in a reduction of the wind shear exponent.
The wind shear exponent has a significant impact on the selection of wind turbines, hub height, and other factors. To investigate the characteristics of the wind shear exponent in northern Bazhou, according to 96 months of continuous, high time-resolution observational data from southeastern Bosten Lake wind measurement tower from January 2017 to December 2024, the average wind speed, wind speed deviation coefficient, and wind shear exponent at different heights were calculated, and the spatiotemporal distribution characteristics of the wind shear exponent, as well as the relationship between wind shear exponent and wind speed were analyzed. The study revealed that: (1) As the height increases, the overall wind shear exponent shows a segmented decreasing trend with a breakpoint at 70 m. The wind speed difference is greatest at heights of 70 to 80 m, with significant wind speed shear and relatively poor stability. (2) From spring to autumn, the wind shear exponent decreases in segments with increasing height. In winter, minimal variation is observed in the height range of 10 to 70 m, while significant differences emerge in the height range of 70 to 100 m. The diurnal variation of the wind shear exponent at all heights presents a 'bimodal' distribution characteristic, and the diurnal variation characteristic of the wind shear exponent shows a inverse correlation with the diurnal variation of wind speed. (3) There is a wind speed inversion zone in the height range of 35 to 70 m when the wind speed exceeds 8 m·s-1. In the height range of 70 to 100 m, the wind shear exponent shows an inverted V-shaped distribution with a wind speed of 10 m·s-1 as the axis of symmetry. (4) The averages and standard deviations of the wind speed bins generally show that the entire wind speed segment is the largest, followed by the ≥3 m·s-1 startup wind speed segment, and the ≥17.2 m·s-1 strong wind speed segment is the smallest. Wind field stability increases with rising wind speeds, concomitantly resulting in a reduction of the wind shear exponent.
Abstract:
In this study,the spatial-temporal distributionin,variation rate,abrupt changes and periodic patterns of extreme cold weather in Hulunbuir were analyzed based on daily minimum temperature data from 16 national meteorological stations in Hulunbuir during 1960-2024,by means of integrated climate statistical methods,Mann-Kendall tests,and Morlet wavelet method.The results indicate that:(1)The spatial distribution of extreme cold days is highly uneven,mainly concentrated in the northern Greater Hinggan Mountains region, with a significant decrease from north to southwest and southeast.The annual average days of extreme cold weather is highest in Tulihe station (17.20 d), while no extreme cold weather occurred in the southeast stations such as Zhalantun, Arongqi, and Boketu.The frequency of extreme cold weather is highest in January (47.8%) and lowest in November (0.8%). The interannual variation of extreme cold weather shows a significant decreasing trend as -2.23 d?(10 a)-1. After the abrupt change in 1971, the average days of extreme cold weather significantly decreased..During the study period, there is a 12-15 year periodicity of extreme cold days,which is more pronounced before 1990 and after 2000, with a slight weakening of the periodic variation between 1990 and 2000.Additionally, a 6-7 year periodicity exists from 1960 to 1970.(2) The average extreme minimum temperature over 65 years is -45.3°C, with the lowest temperature recorded on February 22, 1966, at Tulihe station (-50.2°C),where 69% of extreme cold weather occurred, other 22% occurred at Genhe station.In addition,58.5% of extreme cold weather occurred in January.The interannual variation shows an upward trend at the rate of 0.21°C?(10 a)-1. After the abrupt change in 1971, the extreme minimum temperature significantly rose, but the warming trend slowed down after 2016. The cyclical variation characteristics of the annual extreme minimum temperature are not obvious. (3) The impact area and duration of extreme cold weather both show a decreasing trend, with trend rates of -1.5 d?(10 a)-1 and -0.6 d?(10 a)-1, respectively. The longest duration of extreme cold weather reached 28 days, occurring from December 19, 1976, to January 15, 1977. The study indicates that extreme cold weather in Hulunbuir is significantly affected by global warming, but still occurs frequently in recent years. It is necessary to strengthen monitoring and early warning to provide scientific support for regional disaster prevention and mitigation and the utilization of cold resources.
In this study,the spatial-temporal distributionin,variation rate,abrupt changes and periodic patterns of extreme cold weather in Hulunbuir were analyzed based on daily minimum temperature data from 16 national meteorological stations in Hulunbuir during 1960-2024,by means of integrated climate statistical methods,Mann-Kendall tests,and Morlet wavelet method.The results indicate that:(1)The spatial distribution of extreme cold days is highly uneven,mainly concentrated in the northern Greater Hinggan Mountains region, with a significant decrease from north to southwest and southeast.The annual average days of extreme cold weather is highest in Tulihe station (17.20 d), while no extreme cold weather occurred in the southeast stations such as Zhalantun, Arongqi, and Boketu.The frequency of extreme cold weather is highest in January (47.8%) and lowest in November (0.8%). The interannual variation of extreme cold weather shows a significant decreasing trend as -2.23 d?(10 a)-1. After the abrupt change in 1971, the average days of extreme cold weather significantly decreased..During the study period, there is a 12-15 year periodicity of extreme cold days,which is more pronounced before 1990 and after 2000, with a slight weakening of the periodic variation between 1990 and 2000.Additionally, a 6-7 year periodicity exists from 1960 to 1970.(2) The average extreme minimum temperature over 65 years is -45.3°C, with the lowest temperature recorded on February 22, 1966, at Tulihe station (-50.2°C),where 69% of extreme cold weather occurred, other 22% occurred at Genhe station.In addition,58.5% of extreme cold weather occurred in January.The interannual variation shows an upward trend at the rate of 0.21°C?(10 a)-1. After the abrupt change in 1971, the extreme minimum temperature significantly rose, but the warming trend slowed down after 2016. The cyclical variation characteristics of the annual extreme minimum temperature are not obvious. (3) The impact area and duration of extreme cold weather both show a decreasing trend, with trend rates of -1.5 d?(10 a)-1 and -0.6 d?(10 a)-1, respectively. The longest duration of extreme cold weather reached 28 days, occurring from December 19, 1976, to January 15, 1977. The study indicates that extreme cold weather in Hulunbuir is significantly affected by global warming, but still occurs frequently in recent years. It is necessary to strengthen monitoring and early warning to provide scientific support for regional disaster prevention and mitigation and the utilization of cold resources.
Abstract:
Conventional meteorological data, ERA5 reanalysis data, wind profile radar data, and forecast products from four numerical models (European Centre for Medium-Range Weather Forecasts, China Meteorological Administration Mesoscale Model, China Meteorological Administration Global Data, and China Meteorological Administration - Southern Region - 9 km resolution) were used to analyze the causes of the false alarm of heavy rainfall in the northeastern Guangxi region on the night of May 26, 2024. Results show that (1) on the night of May 26, the northeastern Guangxi region had the synoptic background and energy conditions for heavy precipitation, but the rapid eastward movement of the upper - level short - wave trough led to insufficient dynamic uplift, with no deep ascending motion formed; (2) the wind speed divergence in the southwestern jet stream at 850 hPa led to insufficient low - level water vapor convergence, preventing the development of discrete convective cells into a large - scale strong convective system; (3) The forecasting performance of various models in this process was poor. The three mesoscale models—CMA-MESO, CMA-GD, and CMA-SH9—all showed significant discrepancies from the actual conditions in their forecasts of echo intensity and rainfall intensity in the northeastern Guangxi region on the night of the 26th. Forecasters relied on the circulation pattern forecasts from the ECMWF model, leading to an overestimation of the depth of the upper-level shortwave trough and an overestimation of the southward movement speed of the low-level shear line and boundary layer front.
Conventional meteorological data, ERA5 reanalysis data, wind profile radar data, and forecast products from four numerical models (European Centre for Medium-Range Weather Forecasts, China Meteorological Administration Mesoscale Model, China Meteorological Administration Global Data, and China Meteorological Administration - Southern Region - 9 km resolution) were used to analyze the causes of the false alarm of heavy rainfall in the northeastern Guangxi region on the night of May 26, 2024. Results show that (1) on the night of May 26, the northeastern Guangxi region had the synoptic background and energy conditions for heavy precipitation, but the rapid eastward movement of the upper - level short - wave trough led to insufficient dynamic uplift, with no deep ascending motion formed; (2) the wind speed divergence in the southwestern jet stream at 850 hPa led to insufficient low - level water vapor convergence, preventing the development of discrete convective cells into a large - scale strong convective system; (3) The forecasting performance of various models in this process was poor. The three mesoscale models—CMA-MESO, CMA-GD, and CMA-SH9—all showed significant discrepancies from the actual conditions in their forecasts of echo intensity and rainfall intensity in the northeastern Guangxi region on the night of the 26th. Forecasters relied on the circulation pattern forecasts from the ECMWF model, leading to an overestimation of the depth of the upper-level shortwave trough and an overestimation of the southward movement speed of the low-level shear line and boundary layer front.
Abstract:
Based on the daily data from 16 wire icing observation stations in Shanxi Province between 1980 and 2019, a comprehensive wire icing intensity index using icing days, average standard ice thickness, longest continuous icing duration, and maximum standard ice thickness was constructed for four regions such as Wutai Mountain, northern, central, and southern areas. On this basis, trend tests, ensemble empirical mode decomposition, time-lag correlation, and linear discriminant analysis were employed to examine the trends in icing changes and their response characteristics to 24 circulation factors. The results indicated that: except for Wutai Mountain where icing occurred across many months of the year, icing in other regions was primarily concentrated in winter months, particularly January and December. Additionally, Wutai Mountain exhibited higher icing intensity. The icing intensity in the northern, central, and Wutai Mountain regions showed a weakening trend, while the southern region displayed a significant increasing trend. Significant time-lag correlations existed between icing intensity and circulation factors. Notably, a linear discriminant model driven by characteristic values of multiple key circulation indices from preceding periods demonstrated effective predictive performance for the intensity levels in critical months.
Based on the daily data from 16 wire icing observation stations in Shanxi Province between 1980 and 2019, a comprehensive wire icing intensity index using icing days, average standard ice thickness, longest continuous icing duration, and maximum standard ice thickness was constructed for four regions such as Wutai Mountain, northern, central, and southern areas. On this basis, trend tests, ensemble empirical mode decomposition, time-lag correlation, and linear discriminant analysis were employed to examine the trends in icing changes and their response characteristics to 24 circulation factors. The results indicated that: except for Wutai Mountain where icing occurred across many months of the year, icing in other regions was primarily concentrated in winter months, particularly January and December. Additionally, Wutai Mountain exhibited higher icing intensity. The icing intensity in the northern, central, and Wutai Mountain regions showed a weakening trend, while the southern region displayed a significant increasing trend. Significant time-lag correlations existed between icing intensity and circulation factors. Notably, a linear discriminant model driven by characteristic values of multiple key circulation indices from preceding periods demonstrated effective predictive performance for the intensity levels in critical months.
Abstract:
To reveal the spatiotemporal evolution patterns and transport mechanisms of dust pollution in the Hexi region, this study utilized continuous monitoring data from a ground-based remote sensing vertical observation system, including aerosol lidar, L-band wind profiler, and microwave radiometer. Machine learning algorithms and the HYSPLIT model were employed to comprehensively analyze a typical dust event occurring from March 13 to March 22, 2023. The results indicated that dry and warm meteorological conditions combined with short-term strong winds facilitated the occurrence and transport of dust, with four dust events observed during this period. The machine learning model achieved high-accuracy inversion of the vertical distribution of particulate matter concentrations. The analysis revealed significant stratification in the first and second dust processes, while particulate matter mainly accumulated in the lower atmosphere during the third process. The fourth dust process exhibited strong transport intensity, with high concentrations of particulates uniformly distributed from the surface to high altitude. By analyzing transmission fluxes and backward trajectories, it was found that the Xinjiang region west of Jiuquan is a major dust source, contributing to regional severe dust weather and high-altitude dust transport. Additionally, the Inner Mongolia region to the northeast is also an important source area, but its impact on Jiuquan was limited to the lower atmosphere due to the dominance of upper-level westerly winds.
To reveal the spatiotemporal evolution patterns and transport mechanisms of dust pollution in the Hexi region, this study utilized continuous monitoring data from a ground-based remote sensing vertical observation system, including aerosol lidar, L-band wind profiler, and microwave radiometer. Machine learning algorithms and the HYSPLIT model were employed to comprehensively analyze a typical dust event occurring from March 13 to March 22, 2023. The results indicated that dry and warm meteorological conditions combined with short-term strong winds facilitated the occurrence and transport of dust, with four dust events observed during this period. The machine learning model achieved high-accuracy inversion of the vertical distribution of particulate matter concentrations. The analysis revealed significant stratification in the first and second dust processes, while particulate matter mainly accumulated in the lower atmosphere during the third process. The fourth dust process exhibited strong transport intensity, with high concentrations of particulates uniformly distributed from the surface to high altitude. By analyzing transmission fluxes and backward trajectories, it was found that the Xinjiang region west of Jiuquan is a major dust source, contributing to regional severe dust weather and high-altitude dust transport. Additionally, the Inner Mongolia region to the northeast is also an important source area, but its impact on Jiuquan was limited to the lower atmosphere due to the dominance of upper-level westerly winds.
Abstract:
This paper based on the total solar radiation data from 1991~2023, the air quality monitoring data of Xi"an from 2014 to 2020 and the corresponding hourly radiation simulation data, defined the percentage of greater than 80% as a sunny day, introduced the solar radiation reduction, reduction rate and scattering coefficient, analyzed the interannual variation of solar radiation and the influence of ambient air quality on solar radiation. (1)There are good simulation effect of Simulation of total solar radiation, direct radiation, scattered radiation number used the first-generation Global Atmospheric Reanalysis 40-year product of China (CMA-RA), it can solve the problem of incomplete radiation observation projects at national stations.(2)Since 1991, the total solar radiation in the three different climatic regions of Shaanxi Province has shown a fluctuating increasing trend, and the spatial distribution of total solar radiation has increased from south to north.(3)Under sunny conditions, atmospheric pollution is one of the important factors affecting the solar radiation reaching the Earth"s surface. There are great difference of average total radiation between PM2.5 pollution days and non-pollution days,the radiation reduction amount, reduction ratet and scattering coefficien on polluted days are greater than those on clean days.On sunny days, latgest of reduction amount and reduction ratet occured in Ankang, respectively were 12.1MJ/m2 and 0.44, smallest in Xi "an respectively were 12.1MJ/m2 and 0.44. In addition, the average scattering coefficient of PM2.5 polluted day in Yan"an and Xi"an respectively was 0.50 and 0.39, while in Ankang was 0.23. It is consistent with that the ambient air quality of Xi "an and Yan "an is worse than that of Ankang, further verified that the scattering radiation increases due to the higher concentration of polluted particles.(4)Compared the relationship between pollutants and scattering coefficient in Xi "an on the same day or adjacent days, it can be seen that PM2.5 has a significant impact on solar radiation reduction when there is little difference in meteorological factors, the radiation reduction rate increases significantly with the increase of PM2.5 concentration.
This paper based on the total solar radiation data from 1991~2023, the air quality monitoring data of Xi"an from 2014 to 2020 and the corresponding hourly radiation simulation data, defined the percentage of greater than 80% as a sunny day, introduced the solar radiation reduction, reduction rate and scattering coefficient, analyzed the interannual variation of solar radiation and the influence of ambient air quality on solar radiation. (1)There are good simulation effect of Simulation of total solar radiation, direct radiation, scattered radiation number used the first-generation Global Atmospheric Reanalysis 40-year product of China (CMA-RA), it can solve the problem of incomplete radiation observation projects at national stations.(2)Since 1991, the total solar radiation in the three different climatic regions of Shaanxi Province has shown a fluctuating increasing trend, and the spatial distribution of total solar radiation has increased from south to north.(3)Under sunny conditions, atmospheric pollution is one of the important factors affecting the solar radiation reaching the Earth"s surface. There are great difference of average total radiation between PM2.5 pollution days and non-pollution days,the radiation reduction amount, reduction ratet and scattering coefficien on polluted days are greater than those on clean days.On sunny days, latgest of reduction amount and reduction ratet occured in Ankang, respectively were 12.1MJ/m2 and 0.44, smallest in Xi "an respectively were 12.1MJ/m2 and 0.44. In addition, the average scattering coefficient of PM2.5 polluted day in Yan"an and Xi"an respectively was 0.50 and 0.39, while in Ankang was 0.23. It is consistent with that the ambient air quality of Xi "an and Yan "an is worse than that of Ankang, further verified that the scattering radiation increases due to the higher concentration of polluted particles.(4)Compared the relationship between pollutants and scattering coefficient in Xi "an on the same day or adjacent days, it can be seen that PM2.5 has a significant impact on solar radiation reduction when there is little difference in meteorological factors, the radiation reduction rate increases significantly with the increase of PM2.5 concentration.
Abstract:
Xichang, celebrated for its year-round spring-like climate, has become a prominent destination for seasonal migrants seeking health-oriented lifestyles. This study investigates the dual nature of meteorological impacts on respiratory health by analyzing daily hospital admissions for respiratory diseases (July 1, 2019–June 30, 2022) and concurrent meteorological data from Xichang. Integrating interpretable SHAP (SHapley Additive exPlanations) modeling, biometeorological comfort indices, and distributed lag nonlinear models (DLNM), we evaluate season- and solar-term-specific health risks and benefits through a harm-mitigation and advantage-utilization lens. Key findings include: (1) Temperature emerged as the dominant driver of respiratory morbidity (SHAP value: 0.42), followed by atmospheric pressure (0.31), relative humidity (0.28), wind speed (0.19), and precipitation (0.12). (2) During the Yang Qi phase (February–August, ascending thermal energy), respiratory admissions decreased progressively by 51% from the November peak to the August trough, reaching the annual minimum at the Chushu solar term (61% reduction vs. Lidong peak). Summer exhibited 74% generalized comfort days, correlating with sustained low-risk health conditions. (3) The Yin Qi phase (September–January, descending thermal energy) showed morbidity escalation peaking in November, with prolonged high-risk intervals until January. DLNM analyses revealed synergistic "high-pressure effects under mild cold stress" (relative risk [RR] = 1.24, 95% CI: 1.12–1.38) from combined temperature-pressure interactions. Notably, winter climate demonstrates duality: while posing elevated respiratory risks for local residents (RR = 1.67 during extreme cold spells) necessitating targeted prevention, it concurrently offers cold-avoidance benefits for northern migrants due to milder temperatures (mean >10°C vs. <0°C in northern China). These findings advocate spatially stratified health advisories—prioritizing cold-season protection for locals while leveraging climate advantages for seasonal migrants—providing a paradigm for adaptive health governance in transitional climate zones.
Xichang, celebrated for its year-round spring-like climate, has become a prominent destination for seasonal migrants seeking health-oriented lifestyles. This study investigates the dual nature of meteorological impacts on respiratory health by analyzing daily hospital admissions for respiratory diseases (July 1, 2019–June 30, 2022) and concurrent meteorological data from Xichang. Integrating interpretable SHAP (SHapley Additive exPlanations) modeling, biometeorological comfort indices, and distributed lag nonlinear models (DLNM), we evaluate season- and solar-term-specific health risks and benefits through a harm-mitigation and advantage-utilization lens. Key findings include: (1) Temperature emerged as the dominant driver of respiratory morbidity (SHAP value: 0.42), followed by atmospheric pressure (0.31), relative humidity (0.28), wind speed (0.19), and precipitation (0.12). (2) During the Yang Qi phase (February–August, ascending thermal energy), respiratory admissions decreased progressively by 51% from the November peak to the August trough, reaching the annual minimum at the Chushu solar term (61% reduction vs. Lidong peak). Summer exhibited 74% generalized comfort days, correlating with sustained low-risk health conditions. (3) The Yin Qi phase (September–January, descending thermal energy) showed morbidity escalation peaking in November, with prolonged high-risk intervals until January. DLNM analyses revealed synergistic "high-pressure effects under mild cold stress" (relative risk [RR] = 1.24, 95% CI: 1.12–1.38) from combined temperature-pressure interactions. Notably, winter climate demonstrates duality: while posing elevated respiratory risks for local residents (RR = 1.67 during extreme cold spells) necessitating targeted prevention, it concurrently offers cold-avoidance benefits for northern migrants due to milder temperatures (mean >10°C vs. <0°C in northern China). These findings advocate spatially stratified health advisories—prioritizing cold-season protection for locals while leveraging climate advantages for seasonal migrants—providing a paradigm for adaptive health governance in transitional climate zones.
Abstract:
Vegetation carbon use efficiency (CUE) is an important indicator to evaluate the carbon sequestration capacity and efficiency of vegetation. It is of great significance to explore its response to climate change and human activities for monitoring regional ecological environment quality and studying carbon cycle. Here, Sen slope estimation and Mann-Kendall significance test were used to analyze the temporal and spatial variation characteristics of vegetation CUE based on MODIS remote sensing data in Zhejiang Province from 2001 to 2020. Furthermore, we conducted correlation analysis and multiple regression residual method based on the data of ground meteorological observation stations to quantify the effects of climate change and human activities on vegetation CUE. The results showed that the vegetation CUE in Zhejiang Province showed a weak downward trend from 2001 to 2020, and the average rate was 0.0008 a-1 (p=0.08). The spatial distribution range of vegetation CUE was 0.20 to 0.67, and the average was 0.50±0.08. The trend rate of vegetation CUE was -0.017-0.018 a-1, and the area showing an increasing trend accounted for 10.5%, and the area showing a decreasing trend accounted for 23.9%. The influence trend of climate change on vegetation CUE change was -0.007-0.010 a-1, vegetation CUE was mainly negatively correlated with temperature and positively correlated with precipitation. The influence of human activities on vegetation CUE change was -0.015-0.017 a-1. The decrease areas caused by climate change and human activities accounted for 50.7%. Among them, human activities were the main driving factors, and climate change was the secondary driving factor. The relative contribution rates of climate change and human activities to vegetation CUE changes were 33% and 67%, respectively. In summary, the vegetation CUE in Zhejiang Province showed a weak downward trend in the past 20 years, and the spatial distribution was quite different. Human activities had a stronger impact on the vegetation CUE in Zhejiang Province, primarily causing them to lower.
Vegetation carbon use efficiency (CUE) is an important indicator to evaluate the carbon sequestration capacity and efficiency of vegetation. It is of great significance to explore its response to climate change and human activities for monitoring regional ecological environment quality and studying carbon cycle. Here, Sen slope estimation and Mann-Kendall significance test were used to analyze the temporal and spatial variation characteristics of vegetation CUE based on MODIS remote sensing data in Zhejiang Province from 2001 to 2020. Furthermore, we conducted correlation analysis and multiple regression residual method based on the data of ground meteorological observation stations to quantify the effects of climate change and human activities on vegetation CUE. The results showed that the vegetation CUE in Zhejiang Province showed a weak downward trend from 2001 to 2020, and the average rate was 0.0008 a-1 (p=0.08). The spatial distribution range of vegetation CUE was 0.20 to 0.67, and the average was 0.50±0.08. The trend rate of vegetation CUE was -0.017-0.018 a-1, and the area showing an increasing trend accounted for 10.5%, and the area showing a decreasing trend accounted for 23.9%. The influence trend of climate change on vegetation CUE change was -0.007-0.010 a-1, vegetation CUE was mainly negatively correlated with temperature and positively correlated with precipitation. The influence of human activities on vegetation CUE change was -0.015-0.017 a-1. The decrease areas caused by climate change and human activities accounted for 50.7%. Among them, human activities were the main driving factors, and climate change was the secondary driving factor. The relative contribution rates of climate change and human activities to vegetation CUE changes were 33% and 67%, respectively. In summary, the vegetation CUE in Zhejiang Province showed a weak downward trend in the past 20 years, and the spatial distribution was quite different. Human activities had a stronger impact on the vegetation CUE in Zhejiang Province, primarily causing them to lower.
Abstract:
The study of regional precipitation change under the background of climate warming is of great significance to economic and social development. Based on the daily precipitation data in Shanxi flood season during 1981-2023 from 108 meteorological stations in Shanxi Province, the temporal and spatial variations of days and precipitation on different precipitation grades and extreme precipitation in Shanxi flood season were studied by using statistical methods of climate trend coefficient, linear tendency estimation and similarity coefficient. The results show that: The regional average of total rain days, light rain days and light rain precipitation all show linear decreasing trend, while the regional average of heavy rain days, rainstorm days and total precipitation, precipitation of heavy rain and above grades all show increasing trend in Shanxi flood season during 1981-2023, among them, the rainstorm days increases significantly, the light rain precipitation decreases relatively significant, and the precipitation of heavy rain and above grades increases relatively significant; The regional average days and precipitation of moderate rain exhibit negligible linear trend change. In Shanxi flood season, the days of precipitation is mainly determined by the light rain days, and the total precipitation is mainly determined by the precipitation of heavy rain and above grads. In Shanxi flood season, the significantly decreasing areas of the light rain days and light rain precipitation locate mainly in the basins areas, the significantly increasing areas on the rainstorm days and the precipitation of heavy rain and above grads mainly locate among Xinzhou, Jinzhong and Lvliang; The extreme precipitation days has increased and the extreme precipitation intensity has strengthened in most areas in Shanxi during flood season from 1981-2023.
The study of regional precipitation change under the background of climate warming is of great significance to economic and social development. Based on the daily precipitation data in Shanxi flood season during 1981-2023 from 108 meteorological stations in Shanxi Province, the temporal and spatial variations of days and precipitation on different precipitation grades and extreme precipitation in Shanxi flood season were studied by using statistical methods of climate trend coefficient, linear tendency estimation and similarity coefficient. The results show that: The regional average of total rain days, light rain days and light rain precipitation all show linear decreasing trend, while the regional average of heavy rain days, rainstorm days and total precipitation, precipitation of heavy rain and above grades all show increasing trend in Shanxi flood season during 1981-2023, among them, the rainstorm days increases significantly, the light rain precipitation decreases relatively significant, and the precipitation of heavy rain and above grades increases relatively significant; The regional average days and precipitation of moderate rain exhibit negligible linear trend change. In Shanxi flood season, the days of precipitation is mainly determined by the light rain days, and the total precipitation is mainly determined by the precipitation of heavy rain and above grads. In Shanxi flood season, the significantly decreasing areas of the light rain days and light rain precipitation locate mainly in the basins areas, the significantly increasing areas on the rainstorm days and the precipitation of heavy rain and above grads mainly locate among Xinzhou, Jinzhong and Lvliang; The extreme precipitation days has increased and the extreme precipitation intensity has strengthened in most areas in Shanxi during flood season from 1981-2023.
Abstract:
Abstract: Understanding the heterogeneous evolution and threshold coupling mechanisms of dust devils and sand-dust weather is of critical scientific importance for ecological security in arid regions, sand-dust disaster prevention, and global desertification control. Based on meteorological observations and intensive observation campaigns at the northern edge of the Taklimakan Desert from 1992 to 2024, this study reveals the heterogeneous evolution of dust devils and sand-dust weather, as well as their thermal-dynamic coupling mechanisms. The number of dust devil days peaked at 104 days in 1994, then fluctuated and declined (55 days in 2020), while sand-dust weather events decreased sharply due to ecological restoration (20 sandstorm days in 2024). Monthly, dust devils exhibited a single summer peak (peaking in July), driven by thermal thresholds (land-air temperature difference ≥20°C, wind speed 3.0–3.5 m/s, humidity <25%); sand-dust weather showed dual spring peaks (March–May), dependent on dynamic thresholds (wind speed ≥8 m/s, humidity <35%). During the transitional period (May–June), enhanced thermal conditions increased dust devil days to 11 days while reducing sandstorm days to 8 days, reflecting spatiotemporal competition. Regression models indicate that dust devils are synergistically driven by temperature difference (+1°C increases frequency by 0.86 times, R2=0.82-0.77) and wind speed (+1 m/s increases frequency by 1.32 times), with low humidity (≤30%: 22 events) and low pressure (898.6 hPa) as facilitators. Sand-dust weather is dominated by wind speed (≥8 m/s: 22.12 events, R2=0.69-0.78), enhanced by low humidity (≤20%: 20.24 events). Mechanistically, dust devils are small-scale thermal-turbulence phenomena relying on local thermal convection, while dusty weather is governed by large-scale dynamic transport. By quantifying thermo-dynamic threshold disparities, these findings provide multiscale regulatory insights for sand-dust early warning systems, ecological engineering optimization, and climate adaptation strategies, thereby supporting practical desertification control in arid regions.
Abstract: Understanding the heterogeneous evolution and threshold coupling mechanisms of dust devils and sand-dust weather is of critical scientific importance for ecological security in arid regions, sand-dust disaster prevention, and global desertification control. Based on meteorological observations and intensive observation campaigns at the northern edge of the Taklimakan Desert from 1992 to 2024, this study reveals the heterogeneous evolution of dust devils and sand-dust weather, as well as their thermal-dynamic coupling mechanisms. The number of dust devil days peaked at 104 days in 1994, then fluctuated and declined (55 days in 2020), while sand-dust weather events decreased sharply due to ecological restoration (20 sandstorm days in 2024). Monthly, dust devils exhibited a single summer peak (peaking in July), driven by thermal thresholds (land-air temperature difference ≥20°C, wind speed 3.0–3.5 m/s, humidity <25%); sand-dust weather showed dual spring peaks (March–May), dependent on dynamic thresholds (wind speed ≥8 m/s, humidity <35%). During the transitional period (May–June), enhanced thermal conditions increased dust devil days to 11 days while reducing sandstorm days to 8 days, reflecting spatiotemporal competition. Regression models indicate that dust devils are synergistically driven by temperature difference (+1°C increases frequency by 0.86 times, R2=0.82-0.77) and wind speed (+1 m/s increases frequency by 1.32 times), with low humidity (≤30%: 22 events) and low pressure (898.6 hPa) as facilitators. Sand-dust weather is dominated by wind speed (≥8 m/s: 22.12 events, R2=0.69-0.78), enhanced by low humidity (≤20%: 20.24 events). Mechanistically, dust devils are small-scale thermal-turbulence phenomena relying on local thermal convection, while dusty weather is governed by large-scale dynamic transport. By quantifying thermo-dynamic threshold disparities, these findings provide multiscale regulatory insights for sand-dust early warning systems, ecological engineering optimization, and climate adaptation strategies, thereby supporting practical desertification control in arid regions.
Abstract:
Wind energy resources are abundant in cold mountainous areas, but wind turbine blades are prone to ice in this area. An analysis of blade icing variation with the 2-minute average wind speed was conducted based on the ice observation records of the Jieshan wind farm in Hubei Province. Utilizing the blade element momentum theory and the FLUENT Eulerian model, water droplet collisions and icing behavior on wind turbine blades was investigated under various meteorological conditions. The findings indicate: water droplet collision position is mainly distributed in the leading edge of airfoil. Within attack angle ranging form 5° to 25°, the center position of water droplet collision moves to lower edge with attack angle increasing, and calculated ice thickness also reflects this pattern. Within a range form 30μm to 50μm of droplet median diameter, the position of droplet collision center remains essentially unchanged as median diameter increases, while both peak droplet collision coefficient and icing thickness increase. The liquid water content in the air has a minor impact on the collision characteristics. As the wind speed increases, both the peak droplet collision coefficient and the collision range increase, leading to a corresponding increase in the ice thickness on the blades. Additionally, the reasons for the reduced probability of ice accumulation on wind turbine blades when the wind speed exceeds a certain threshold, based on data from the Jieshan Wind Farm, are analyzed. Within the temperature range of -5°C to -1°C, as the temperature decreases, the ice thickness increases. Meanwhile, the rate of increase in ice thickness first accelerates, then slows down, and eventually stabilizes. This is mainly due to the influence of temperature on the freezing coefficient of the blades.
Wind energy resources are abundant in cold mountainous areas, but wind turbine blades are prone to ice in this area. An analysis of blade icing variation with the 2-minute average wind speed was conducted based on the ice observation records of the Jieshan wind farm in Hubei Province. Utilizing the blade element momentum theory and the FLUENT Eulerian model, water droplet collisions and icing behavior on wind turbine blades was investigated under various meteorological conditions. The findings indicate: water droplet collision position is mainly distributed in the leading edge of airfoil. Within attack angle ranging form 5° to 25°, the center position of water droplet collision moves to lower edge with attack angle increasing, and calculated ice thickness also reflects this pattern. Within a range form 30μm to 50μm of droplet median diameter, the position of droplet collision center remains essentially unchanged as median diameter increases, while both peak droplet collision coefficient and icing thickness increase. The liquid water content in the air has a minor impact on the collision characteristics. As the wind speed increases, both the peak droplet collision coefficient and the collision range increase, leading to a corresponding increase in the ice thickness on the blades. Additionally, the reasons for the reduced probability of ice accumulation on wind turbine blades when the wind speed exceeds a certain threshold, based on data from the Jieshan Wind Farm, are analyzed. Within the temperature range of -5°C to -1°C, as the temperature decreases, the ice thickness increases. Meanwhile, the rate of increase in ice thickness first accelerates, then slows down, and eventually stabilizes. This is mainly due to the influence of temperature on the freezing coefficient of the blades.
Abstract:
This research calculated the remote sensing ecological index (RSEI) of Jilin Province based on MOD09A1, MOD11A2, and MOD13A1 products from 2000 to 2022, combined with ecological functional zoning, trend analysis, Mann Kendall significance analysis, and other methods were used to research the spatial and temporal changes in ecological quality; At the same time, partial derivatives were used to quantify the impact of climate change and human activities on RSEI, and the driving factors affecting RSEI changes in Jilin Province were explored. The results indicate that: The average annual RSEI of Jilin Province from 2000 to 2022 is 0.562, the overall trend is slowly fluctuating upward trend,among which the western grassland wetland ecological zone has the fastest growth rate, while the eastern coniferous and broad-leaved mixed forest ecological zone has the slowest growth rate. The contributions of human activities and climate change to the RSEI changes in Jilin Province are roughly equivalent, with human activities contributing positively and climate change contributing negatively.From the perspective of different ecological zones, the positive contribution of climate factors to RSEI in the western grassland wetland ecological zone and the central farmland ecological zone is greater than that of human activities, precipitation is the main factor affecting the change of RSEI in the western grassland wetland ecological zone, while solar radiation is the main factor affecting the change of RSEI in the central farmland ecological zone.The positive contribution of climate factors to RSEI in the eastern coniferous and broad-leaved mixed forest ecological zone is less than that of human activities, indicating that ecological engineering construction is the main factor to promote the improvement of RSEI.
This research calculated the remote sensing ecological index (RSEI) of Jilin Province based on MOD09A1, MOD11A2, and MOD13A1 products from 2000 to 2022, combined with ecological functional zoning, trend analysis, Mann Kendall significance analysis, and other methods were used to research the spatial and temporal changes in ecological quality; At the same time, partial derivatives were used to quantify the impact of climate change and human activities on RSEI, and the driving factors affecting RSEI changes in Jilin Province were explored. The results indicate that: The average annual RSEI of Jilin Province from 2000 to 2022 is 0.562, the overall trend is slowly fluctuating upward trend,among which the western grassland wetland ecological zone has the fastest growth rate, while the eastern coniferous and broad-leaved mixed forest ecological zone has the slowest growth rate. The contributions of human activities and climate change to the RSEI changes in Jilin Province are roughly equivalent, with human activities contributing positively and climate change contributing negatively.From the perspective of different ecological zones, the positive contribution of climate factors to RSEI in the western grassland wetland ecological zone and the central farmland ecological zone is greater than that of human activities, precipitation is the main factor affecting the change of RSEI in the western grassland wetland ecological zone, while solar radiation is the main factor affecting the change of RSEI in the central farmland ecological zone.The positive contribution of climate factors to RSEI in the eastern coniferous and broad-leaved mixed forest ecological zone is less than that of human activities, indicating that ecological engineering construction is the main factor to promote the improvement of RSEI.
Abstract:
The health risk effects of the synergistic action of temperature and humidity in Chengdu are currently unclear. Based on this, this study collected the death data of Cardio-cerebrovascular diseases (CVD) in Chengdu from 2010 to 2016 and the meteorological data in the same period, and combined the generalized additive model and the distributed lag non-linear model to conduct a study on the impact of local average temperature (T) and relative humidity (RH) on the number of deaths from CVD. The results show that in the winter-half year, the associations between T, RH and the death of cardiovascular and cerebrovascular diseases are both in an inverted "J" shape, and the thresholds of T and RH are 14.8°C and 74% respectively. In the winter-half year, the relative risk (RR) of the impact of cold days alone (T<14.8°C) on the death of cardiovascular and cerebrovascular diseases is 1.24, resulting in 13,184 cases of CVD deaths; the RRs corresponding to wet-cold and dry-cold are 1.30 and 1.15 respectively, resulting in 12,623 cases and 1,998 cases of CVD deaths. The number of disease deaths jointly caused by wet-cold and dry-cold days is higher than that caused by cold days alone. The risks of the impact of wet-cold and dry-cold on the death of CVD both have a synergistic effect, and the compound exposure risk of wet-cold is more significant. This study reminds us that in the study of the health risk effects of meteorological elements, we should fully consider the compound exposure of meteorological elements and their synergistic effects on the health of relevant populations.
The health risk effects of the synergistic action of temperature and humidity in Chengdu are currently unclear. Based on this, this study collected the death data of Cardio-cerebrovascular diseases (CVD) in Chengdu from 2010 to 2016 and the meteorological data in the same period, and combined the generalized additive model and the distributed lag non-linear model to conduct a study on the impact of local average temperature (T) and relative humidity (RH) on the number of deaths from CVD. The results show that in the winter-half year, the associations between T, RH and the death of cardiovascular and cerebrovascular diseases are both in an inverted "J" shape, and the thresholds of T and RH are 14.8°C and 74% respectively. In the winter-half year, the relative risk (RR) of the impact of cold days alone (T<14.8°C) on the death of cardiovascular and cerebrovascular diseases is 1.24, resulting in 13,184 cases of CVD deaths; the RRs corresponding to wet-cold and dry-cold are 1.30 and 1.15 respectively, resulting in 12,623 cases and 1,998 cases of CVD deaths. The number of disease deaths jointly caused by wet-cold and dry-cold days is higher than that caused by cold days alone. The risks of the impact of wet-cold and dry-cold on the death of CVD both have a synergistic effect, and the compound exposure risk of wet-cold is more significant. This study reminds us that in the study of the health risk effects of meteorological elements, we should fully consider the compound exposure of meteorological elements and their synergistic effects on the health of relevant populations.
Abstract:
In order to better carry out the online monitoring of particulate matter in Akedala Atmospheric Background Station (hereinafter referred to as Akedala Station), this paper is based on the 2019-2020 and 2023-2024 PM10 and PM2.5 monitored by three particulate matter online monitoring instruments GRIMM180, TEMO1405DF, and DXC1 at Akedala Station and the meteorological data in the same period, we have characterized the temporal distribution of the PM10 and PM2.5 mass concentration data of the three online monitoring instruments and The differences of PM10 and PM2.5 mass concentration data monitored by instruments with different principles were explored. The results show that the seasonal variation of particulate matter mass concentrations at Akedala Station was obvious, with high levels in spring and winter and low levels in summer and fall. The deviation of PM10 mass concentration data monitored by the three instruments was large, while the deviation of PM2.5 mass concentration was small.The correlation coeffic
In order to better carry out the online monitoring of particulate matter in Akedala Atmospheric Background Station (hereinafter referred to as Akedala Station), this paper is based on the 2019-2020 and 2023-2024 PM10 and PM2.5 monitored by three particulate matter online monitoring instruments GRIMM180, TEMO1405DF, and DXC1 at Akedala Station and the meteorological data in the same period, we have characterized the temporal distribution of the PM10 and PM2.5 mass concentration data of the three online monitoring instruments and The differences of PM10 and PM2.5 mass concentration data monitored by instruments with different principles were explored. The results show that the seasonal variation of particulate matter mass concentrations at Akedala Station was obvious, with high levels in spring and winter and low levels in summer and fall. The deviation of PM10 mass concentration data monitored by the three instruments was large, while the deviation of PM2.5 mass concentration was small.The correlation coeffic
Abstract:
Short-term extreme precipitation can trigger localized flooding, while multi-day extreme events may lead to soil saturation, flash floods, and significant agricultural losses. Using daily precipitation data from 374 stations in Northwest China (1961—2024), and considering the region's arid and semi-arid climate, extreme precipitation events were defined using the 90th percentile daily precipitation and a 20 mm absolute threshold. The analysis revealed that 2-day extreme events were concentrated in western Xinjiang, central-eastern Qinghai, and southwestern Gansu, with over 60 occurrences. Longer events (3-4 days) were less frequent, mainly occurring in high-altitude areas like the Tianshan and Bayan Har mountains. Events peaked from May to September, with a summer maximum in July-August. While the frequency of 2-day events increased significantly from 1961—1983, it declined in 1983—1997 before rising again in 1997—2024, though at a slower rate. Longer events remained relatively rare, primarily in specific mountainous regions. These findings highlight a rising trend in extreme precipitation frequency, providing a basis for disaster prevention and policy formulation.
Short-term extreme precipitation can trigger localized flooding, while multi-day extreme events may lead to soil saturation, flash floods, and significant agricultural losses. Using daily precipitation data from 374 stations in Northwest China (1961—2024), and considering the region's arid and semi-arid climate, extreme precipitation events were defined using the 90th percentile daily precipitation and a 20 mm absolute threshold. The analysis revealed that 2-day extreme events were concentrated in western Xinjiang, central-eastern Qinghai, and southwestern Gansu, with over 60 occurrences. Longer events (3-4 days) were less frequent, mainly occurring in high-altitude areas like the Tianshan and Bayan Har mountains. Events peaked from May to September, with a summer maximum in July-August. While the frequency of 2-day events increased significantly from 1961—1983, it declined in 1983—1997 before rising again in 1997—2024, though at a slower rate. Longer events remained relatively rare, primarily in specific mountainous regions. These findings highlight a rising trend in extreme precipitation frequency, providing a basis for disaster prevention and policy formulation.
Abstract:
Based on the historical disaster and meteorological data of wind and hail disasters in Hebei Province from 1984 to 2024, an agricultural economic loss assessment model with maximum wind speed, hail diameter, and hail duration was constructed using regression analysis and advantage analysis methods. The model was used to improve the historical disaster loss sequence, then five disaster intensity levels were divided by optimal segmentation method, and the critical thresholds for each level were established accordingly. Finally, the model was used for wind and hail disaster assessment in Hebei Province on May 3, 2020 as an example. The results show that: 1) Agricultural economic losses from wind and hail disasters are significantly positively correlated with the maximum hail diameter and the maximum wind force grade. 2) The constructed evaluation model can accurately assess the economic losses of crop caused by wind and hail disasters, which can be used for disaster prevention and reduction.
Based on the historical disaster and meteorological data of wind and hail disasters in Hebei Province from 1984 to 2024, an agricultural economic loss assessment model with maximum wind speed, hail diameter, and hail duration was constructed using regression analysis and advantage analysis methods. The model was used to improve the historical disaster loss sequence, then five disaster intensity levels were divided by optimal segmentation method, and the critical thresholds for each level were established accordingly. Finally, the model was used for wind and hail disaster assessment in Hebei Province on May 3, 2020 as an example. The results show that: 1) Agricultural economic losses from wind and hail disasters are significantly positively correlated with the maximum hail diameter and the maximum wind force grade. 2) The constructed evaluation model can accurately assess the economic losses of crop caused by wind and hail disasters, which can be used for disaster prevention and reduction.
Abstract:
As a typical ecologically fragile area in northwest China, the border region of Shanxi, Shaanxi, and Inner Mongolia is of great significance for soil and water conservation and ecological restoration to study the spatio-temporal variation characteristics of evapotranspiration (ET) and its response mechanism to meteorological factors in this area. In this study, we used MODIS ET data as data sources, and analyzed the spatio-temporal variation characteristics of ET and its relationship with meteorological factors by using trend analysis, correlation analysis, and the geographic detector method. The results showed that the spatial distribution of ET in the border region had significant differences, and was greatly affected by the terrain. ET in the southern Luliang Mountains and the northern Yinshan Mountains was significantly higher than that in the central region. In terms of time, affected by the coincidence of rainfall and heat, the monthly ET in the border region was high in summer and autumn, and low in winter and spring, and its maximum value occured in July-August. The explanatory power of meteorological factors on ET in the border region was in the order of precipitation, vapor pressure, temperature, wind speed, sunshine, and relative humidity, and they mainly had a synergistic effect. The synergistic effect of precipitation and temperature was the strongest, while the direct effect of wind speed and sunshine on ET was weak, mainly through affecting precipitation and temperature, and indirectly affecting ET.
As a typical ecologically fragile area in northwest China, the border region of Shanxi, Shaanxi, and Inner Mongolia is of great significance for soil and water conservation and ecological restoration to study the spatio-temporal variation characteristics of evapotranspiration (ET) and its response mechanism to meteorological factors in this area. In this study, we used MODIS ET data as data sources, and analyzed the spatio-temporal variation characteristics of ET and its relationship with meteorological factors by using trend analysis, correlation analysis, and the geographic detector method. The results showed that the spatial distribution of ET in the border region had significant differences, and was greatly affected by the terrain. ET in the southern Luliang Mountains and the northern Yinshan Mountains was significantly higher than that in the central region. In terms of time, affected by the coincidence of rainfall and heat, the monthly ET in the border region was high in summer and autumn, and low in winter and spring, and its maximum value occured in July-August. The explanatory power of meteorological factors on ET in the border region was in the order of precipitation, vapor pressure, temperature, wind speed, sunshine, and relative humidity, and they mainly had a synergistic effect. The synergistic effect of precipitation and temperature was the strongest, while the direct effect of wind speed and sunshine on ET was weak, mainly through affecting precipitation and temperature, and indirectly affecting ET.
Abstract:
Based on the ADTD lightning location data (2015-2023), DEM terrain elevation data and land use type data in the Ili River Valley, the temporal and spatial distribution characteristics of cloud-to-ground (CG) lightning activities and their correlation with topography and land use type were studied. The results showed that: CG lightning in the Ili River Valley mainly occurred in the warm season (April-September), with the highest frequency in June. The diurnal variation of CG lightning frequency demonstrated a unimodal pattern, with the most active period between 17:00 and 22:00, which simultaneously corresponded to the weakest CG lightning intensity observed within a day. The CG lightning activities in the Ili River Valley predominantly occurred in mountainous terrain or transitional zones between plains and mountains, with three high-frequency regions located in the southern mountains of Tekes County, the southern and northern slopes of Wusun Mountain, and the northern mountainous region from Huocheng County to Yining County. June constituted the most active month for CG lightning in 51.2% of the study area, while July predominated in 43.8% of the territory. The diurnal peak occurrence time of CG lightning frequency exhibited a pronounced eastward delay, with plains regions demonstrating later peak times than mountainous regions. The frequency and density of CG lightning initially increased then decreased with rising elevation, reaching maximum values at 1500-2500 m. Regarding slope effects, CG lightning density followed a unimodal pattern peaking at 18-21°, while CG lightning frequency and intensity demonstrated statistically significant negative correlations with increasing slope angles. North-facing slopes exhibited the highest frequency of CG lightning, while east-facing slopes showed the greatest density. Among land use types, grasslands recorded the highest CG lightning frequency, whereas forested areas demonstrated the maximum density.
Based on the ADTD lightning location data (2015-2023), DEM terrain elevation data and land use type data in the Ili River Valley, the temporal and spatial distribution characteristics of cloud-to-ground (CG) lightning activities and their correlation with topography and land use type were studied. The results showed that: CG lightning in the Ili River Valley mainly occurred in the warm season (April-September), with the highest frequency in June. The diurnal variation of CG lightning frequency demonstrated a unimodal pattern, with the most active period between 17:00 and 22:00, which simultaneously corresponded to the weakest CG lightning intensity observed within a day. The CG lightning activities in the Ili River Valley predominantly occurred in mountainous terrain or transitional zones between plains and mountains, with three high-frequency regions located in the southern mountains of Tekes County, the southern and northern slopes of Wusun Mountain, and the northern mountainous region from Huocheng County to Yining County. June constituted the most active month for CG lightning in 51.2% of the study area, while July predominated in 43.8% of the territory. The diurnal peak occurrence time of CG lightning frequency exhibited a pronounced eastward delay, with plains regions demonstrating later peak times than mountainous regions. The frequency and density of CG lightning initially increased then decreased with rising elevation, reaching maximum values at 1500-2500 m. Regarding slope effects, CG lightning density followed a unimodal pattern peaking at 18-21°, while CG lightning frequency and intensity demonstrated statistically significant negative correlations with increasing slope angles. North-facing slopes exhibited the highest frequency of CG lightning, while east-facing slopes showed the greatest density. Among land use types, grasslands recorded the highest CG lightning frequency, whereas forested areas demonstrated the maximum density.
Abstract:
On 18 February 2018, one of the strongest snowfall weather processes in the history of February occurred in Linxia Prefecture, and the strong snowfall was accompanied by a strong temperature drop, which adversely affected facility agriculture, traffic and travel, electricity, animal husbandry and people's lives. In this paper, this extreme snowstorm weather process was diagnosed and analysed using routine observations at high altitude and on the ground, and ERA5 (0.25ox0.25o) global reanalysis grid point data. The results show that the Indian trough and the cold trough of Lake Balkhash are the main influencing systems of this extreme snowfall weather, the Indian trough lifts north and moves east, the trough of Lake Balkhash moves east and presses south, and forms a northeast-southwest oriented shear line from the Qinghai Plateau to Linxia Prefecture, and the formation of this shear line has an increasing effect on the strong snowfall in Linxia Prefecture; the water vapour mainly comes from the Bay of Bengal region, and with the Indian trough lifting north and moving east, the water vapour increases along the Bay of Bengal. As the Indian trough lifts northward and moves eastward, the water vapour is transported to the southeast side of the Tibetan Plateau along the southwestern airflow in front of the trough, and then passes through the Sichuan Basin, forming an obvious water vapour convergence zone in Linxia Prefecture, and there is a very good correspondence between the convergence zone and the main snowfall area of Linxia Prefecture, with the water vapour channel mainly concentrating at 650hPa～350hPa, and the water vapour convergence zone is located at 650hPa～400hPa. The isotropic θe line is steeply and densely packed over Linxia Prefecture before precipitation. Before the precipitation, the isotropic θe lines were steep and dense over Linxiazhou, the wet obliquity pressure was enhanced, the vertical vorticity developed significantly, accompanied by a strong upward movement, leading to the release of unstable energy from atmospheric convection, which was conducive to the occurrence of strong precipitation in Linxiazhou in the short term; the dense zone of wet vortex isotropic contours is the transition zone of cold and warm airflow, and the centre of the blizzard in Linxiazhou was located in the area where the positive value of MPV1 isotropic contour was dense and negative value of MPV2 got a large growth, and the negative value of MPV2 was enlarged. The increase of MPV2 negative value and the development of downward tilted vorticity is another important reason for the formation of this blizzard.
On 18 February 2018, one of the strongest snowfall weather processes in the history of February occurred in Linxia Prefecture, and the strong snowfall was accompanied by a strong temperature drop, which adversely affected facility agriculture, traffic and travel, electricity, animal husbandry and people's lives. In this paper, this extreme snowstorm weather process was diagnosed and analysed using routine observations at high altitude and on the ground, and ERA5 (0.25ox0.25o) global reanalysis grid point data. The results show that the Indian trough and the cold trough of Lake Balkhash are the main influencing systems of this extreme snowfall weather, the Indian trough lifts north and moves east, the trough of Lake Balkhash moves east and presses south, and forms a northeast-southwest oriented shear line from the Qinghai Plateau to Linxia Prefecture, and the formation of this shear line has an increasing effect on the strong snowfall in Linxia Prefecture; the water vapour mainly comes from the Bay of Bengal region, and with the Indian trough lifting north and moving east, the water vapour increases along the Bay of Bengal. As the Indian trough lifts northward and moves eastward, the water vapour is transported to the southeast side of the Tibetan Plateau along the southwestern airflow in front of the trough, and then passes through the Sichuan Basin, forming an obvious water vapour convergence zone in Linxia Prefecture, and there is a very good correspondence between the convergence zone and the main snowfall area of Linxia Prefecture, with the water vapour channel mainly concentrating at 650hPa～350hPa, and the water vapour convergence zone is located at 650hPa～400hPa. The isotropic θe line is steeply and densely packed over Linxia Prefecture before precipitation. Before the precipitation, the isotropic θe lines were steep and dense over Linxiazhou, the wet obliquity pressure was enhanced, the vertical vorticity developed significantly, accompanied by a strong upward movement, leading to the release of unstable energy from atmospheric convection, which was conducive to the occurrence of strong precipitation in Linxiazhou in the short term; the dense zone of wet vortex isotropic contours is the transition zone of cold and warm airflow, and the centre of the blizzard in Linxiazhou was located in the area where the positive value of MPV1 isotropic contour was dense and negative value of MPV2 got a large growth, and the negative value of MPV2 was enlarged. The increase of MPV2 negative value and the development of downward tilted vorticity is another important reason for the formation of this blizzard.
Abstract:
Based on the monthly air temperature, NCEP/NCAR reanalysis data, and circulation indices of spring in Xinjiang from 1961 to 2023, we studied the dominant modes of seasonal temperature change in Xinjiang and their corresponding circulation anomalies. The results show that: Over the past 60 years, the spring temperature in Xinjiang has increased significantly, with two main modes of variation: uniform change and inverse phase. When the temperature in spring is uniformly warm (cold), the zonal winds in the upper troposphere are negative north to south (positive north to negative south), the middle layer is positive (negative) like the East Atlantic-West Russia Pattern (EA/WR), the lower Ural Mountains are abnormal cyclones (anticyclones), and the surface Eurasian cold high is weak (strong). When the temperature changes during the season, the key circulation systems, such as the subtropical westerly jet, the longitude of the middle and high latitude circulation, the geopotential height of the Ural Mountains and Western Siberia, the abnormal cyclon-anticyclone dipole distribution in the lower level, and the maintenance and change of the Eurasian cold high, which affect the temperature fluctuation, are the important reasons for the evolution of the temperature in phase and phase. The analysis shows that the Scandinavia Pattern (SCA), Asian Zonal Circulation Index (AZC), Atlantic-European Polar Vortex Intensity Index (AEPVI), East Atlantic-West Russia Pattern (EA/WR), Asia Polar Vortex Area Index (APVA), and East Atlantic Pattern (EA) have important effects on the intra-seasonal change of air temperatures. They can be used as important indicators for predicting the intra-seasonal variation of spring temperatures.
Based on the monthly air temperature, NCEP/NCAR reanalysis data, and circulation indices of spring in Xinjiang from 1961 to 2023, we studied the dominant modes of seasonal temperature change in Xinjiang and their corresponding circulation anomalies. The results show that: Over the past 60 years, the spring temperature in Xinjiang has increased significantly, with two main modes of variation: uniform change and inverse phase. When the temperature in spring is uniformly warm (cold), the zonal winds in the upper troposphere are negative north to south (positive north to negative south), the middle layer is positive (negative) like the East Atlantic-West Russia Pattern (EA/WR), the lower Ural Mountains are abnormal cyclones (anticyclones), and the surface Eurasian cold high is weak (strong). When the temperature changes during the season, the key circulation systems, such as the subtropical westerly jet, the longitude of the middle and high latitude circulation, the geopotential height of the Ural Mountains and Western Siberia, the abnormal cyclon-anticyclone dipole distribution in the lower level, and the maintenance and change of the Eurasian cold high, which affect the temperature fluctuation, are the important reasons for the evolution of the temperature in phase and phase. The analysis shows that the Scandinavia Pattern (SCA), Asian Zonal Circulation Index (AZC), Atlantic-European Polar Vortex Intensity Index (AEPVI), East Atlantic-West Russia Pattern (EA/WR), Asia Polar Vortex Area Index (APVA), and East Atlantic Pattern (EA) have important effects on the intra-seasonal change of air temperatures. They can be used as important indicators for predicting the intra-seasonal variation of spring temperatures.
Abstract:
Based on the geological disaster data of mountain torrents in the east of Hexi corridor from 1971 to 2023 and the hourly precipitation data of 83 meteorological stations with complete data from May to September of the main flood season in the east of Hexi corridor from 2016 to 2023, the characteristics of geological disasters of rainstorm mountain torrents in the east of Hexi corridor are analyzed by using statistics, main cause analysis, secondary attenuation model and other methods, and the prediction and early warning technology is studied. The results show that: (1) the distribution of mountain flood geological hazards in the east of Hexi corridor shows a gradually increasing trend from north to south, with a decreasing trend from southwest to northeast from low altitude to high altitude, which is consistent with the distribution pattern of precipitation during the flood season; (2) The refined risk zoning of mountain flood geological disasters in the east of Hexi corridor established by multiple factors provides technical support for accurate prediction of local mountain flood geological disasters and disaster prevention and reduction; (3) Using the comprehensive disaster causing ability assessment Ri index, comparing with the risk zoning map of mountain flood geological disasters, and combining with the climate and terrain characteristics , the risk level of mountain flood geological disasters in the east of Hexi corridor was determined. The relationship between mountain flood disasters and rainfall was quantitatively described more accurately, playing an important role in the prediction and early warning of mountain flood geological disasters; (4) The determined meteorological forecast and early warning grade of rainstorm and mountain torrent geological disasters in the east of Hexi corridor and the forecast and early warning model constructed need to be further optimized and improved by using longer time data
Based on the geological disaster data of mountain torrents in the east of Hexi corridor from 1971 to 2023 and the hourly precipitation data of 83 meteorological stations with complete data from May to September of the main flood season in the east of Hexi corridor from 2016 to 2023, the characteristics of geological disasters of rainstorm mountain torrents in the east of Hexi corridor are analyzed by using statistics, main cause analysis, secondary attenuation model and other methods, and the prediction and early warning technology is studied. The results show that: (1) the distribution of mountain flood geological hazards in the east of Hexi corridor shows a gradually increasing trend from north to south, with a decreasing trend from southwest to northeast from low altitude to high altitude, which is consistent with the distribution pattern of precipitation during the flood season; (2) The refined risk zoning of mountain flood geological disasters in the east of Hexi corridor established by multiple factors provides technical support for accurate prediction of local mountain flood geological disasters and disaster prevention and reduction; (3) Using the comprehensive disaster causing ability assessment Ri index, comparing with the risk zoning map of mountain flood geological disasters, and combining with the climate and terrain characteristics , the risk level of mountain flood geological disasters in the east of Hexi corridor was determined. The relationship between mountain flood disasters and rainfall was quantitatively described more accurately, playing an important role in the prediction and early warning of mountain flood geological disasters; (4) The determined meteorological forecast and early warning grade of rainstorm and mountain torrent geological disasters in the east of Hexi corridor and the forecast and early warning model constructed need to be further optimized and improved by using longer time data
Abstract:
Against the context of climate change, with rising temperature and uneven distribution of precipitation, the production of highland barley in Ganzi is increasingly affected by drought. Based on the daily meteorological data of 12 meteorological stations in the main barley planting areas of Ganzi from 1981 to 2022, the daily Meteorological drought Comprehensive Index (MCI) was calculated. The Mann-Kendall mutation test, Morlet wavelet analysis, and Hurst exponent based on ReScaled range (R/S) analysis were employed to examine the spatial-temporal distribution and change trends of drought intensity across various growth stages in Ganzi. This analysis aims to further comprehend the impact of drought intensity on various growth stages of highland barley. The results showed that: (1) Drought intensity exhibited a decreasing trend during the tiller-heading stage, while it increased during other growth stages. Drought intensity during the head-maturity stage was significantly higher than that during the sow-tillering stage and the entire growth stage. (2) Drought intensity in each growth stage experienced abrupt mutations in both the 1990s and the 2020s, while exhibited a significant decrease during the sow-tillering stage in 1985 and the tiller-heading stage in 2002. (3) The regions with the strongest drought intensity across different growth stages were located in Derong, the southwestern part of Ganzi, followed by surrounding counties such as Batang, Xiangcheng, and Daocheng, showing a distribution pattern that increases from the northeast to the southwest. (4) Over the next decade, drought intensity was projected to show a continuous drying trend during the sow-tillering stage, head-maturity stage and the entire growth stage, while the tiller-heading stage was expected to experience a continuous wetting trend. The temporal variation characteristics of drought intensity during different growth stages of highland barley in Ganzi show significant differences, while the spatial distribution characteristics exhibit similarities.
Against the context of climate change, with rising temperature and uneven distribution of precipitation, the production of highland barley in Ganzi is increasingly affected by drought. Based on the daily meteorological data of 12 meteorological stations in the main barley planting areas of Ganzi from 1981 to 2022, the daily Meteorological drought Comprehensive Index (MCI) was calculated. The Mann-Kendall mutation test, Morlet wavelet analysis, and Hurst exponent based on ReScaled range (R/S) analysis were employed to examine the spatial-temporal distribution and change trends of drought intensity across various growth stages in Ganzi. This analysis aims to further comprehend the impact of drought intensity on various growth stages of highland barley. The results showed that: (1) Drought intensity exhibited a decreasing trend during the tiller-heading stage, while it increased during other growth stages. Drought intensity during the head-maturity stage was significantly higher than that during the sow-tillering stage and the entire growth stage. (2) Drought intensity in each growth stage experienced abrupt mutations in both the 1990s and the 2020s, while exhibited a significant decrease during the sow-tillering stage in 1985 and the tiller-heading stage in 2002. (3) The regions with the strongest drought intensity across different growth stages were located in Derong, the southwestern part of Ganzi, followed by surrounding counties such as Batang, Xiangcheng, and Daocheng, showing a distribution pattern that increases from the northeast to the southwest. (4) Over the next decade, drought intensity was projected to show a continuous drying trend during the sow-tillering stage, head-maturity stage and the entire growth stage, while the tiller-heading stage was expected to experience a continuous wetting trend. The temporal variation characteristics of drought intensity during different growth stages of highland barley in Ganzi show significant differences, while the spatial distribution characteristics exhibit similarities.
Abstract:
Based on the high-resolution hourly precipitation intensity and frequency, topography, vegetation index (NDVI) and socio-economic data, integrated GIS and analytic hierarchy Process (AHP) and other methods, this paper analyzes the risk of flood disaster causing factors, disaster-induced environmental sensitivity and the vulnerability of disaster bearing bodies. The detailed characteristics of rainstorm and flood disaster risk in Yili River basin are given and risk zoning is carried out. The results showed as follows: 1) In the Ili River Basin, the area of high risk area (risk index ≥3.96) accounted for the largest proportion, about 40.74%, the area of medium risk area accounted for 27%, the area of high risk area and low risk area accounted for 25.04% and 5.76%, respectively, while the area of very low risk area accounted for the least, about 1.617%. 2) The flood hazard, sensitivity, vulnerability and risk levels all showed a decreasing trend from northwest to southeast. Precipitation intensity and frequency, NDVI and social and economic development are the key factors that determine the degree of flood risk in the Ili River basin, which should be paid attention to in disaster prevention and reduction planning and design. The areas with high and extremely high flood risk are mainly concentrated in the western and eastern sections of the northern mountainous area of the Ili River basin and the southern mountainous area, that is, Horgos City, Huocheng County, Yining County, eastern Nilek County, Xinyuan County and Zhaosu County, which is consistent with the historical disaster distribution.
Based on the high-resolution hourly precipitation intensity and frequency, topography, vegetation index (NDVI) and socio-economic data, integrated GIS and analytic hierarchy Process (AHP) and other methods, this paper analyzes the risk of flood disaster causing factors, disaster-induced environmental sensitivity and the vulnerability of disaster bearing bodies. The detailed characteristics of rainstorm and flood disaster risk in Yili River basin are given and risk zoning is carried out. The results showed as follows: 1) In the Ili River Basin, the area of high risk area (risk index ≥3.96) accounted for the largest proportion, about 40.74%, the area of medium risk area accounted for 27%, the area of high risk area and low risk area accounted for 25.04% and 5.76%, respectively, while the area of very low risk area accounted for the least, about 1.617%. 2) The flood hazard, sensitivity, vulnerability and risk levels all showed a decreasing trend from northwest to southeast. Precipitation intensity and frequency, NDVI and social and economic development are the key factors that determine the degree of flood risk in the Ili River basin, which should be paid attention to in disaster prevention and reduction planning and design. The areas with high and extremely high flood risk are mainly concentrated in the western and eastern sections of the northern mountainous area of the Ili River basin and the southern mountainous area, that is, Horgos City, Huocheng County, Yining County, eastern Nilek County, Xinyuan County and Zhaosu County, which is consistent with the historical disaster distribution.
Abstract:
Abstract:The Fengyun meteorological satellites play an important role in global disaster prevention and reduction. With the development of remote sensing technology and the expansion of application fields, there is an increasing demand for the authenticity of remote sensing data. In this study, we used hourly data of Ground Surface Temperature (GST) measured by 93 national basic meteorological stations in Jiangxi province and MYD11A1 daily products, as well as considered the complex underlying surface and cloud cover conditions, the authenticity verification and error analysis of FY-3D land surface temperature (LST) products were conducted. The results showed that there was a significant positive correlation (P < 0.001) between the FY-3D LST and the observed GST by meteorological stations, and the FY-3D LST was generally slightly lower than GST, it indicated that there was an obviously underestimation phenomenon. Clouds had a great influence on the LST retrieval results from satellites, and the accuracy of FY-3D LST was significantly improved after cloud removal. FY-3D LST and MYD11A had high consistency in spatial distribution, but the FY-3D LST retrieval results were slightly higher than MYD11A1, besides, the two LST products had the greatest difference in the underlying surface of water bodies and the smallest difference in the underlying surface of cultivated land.
Abstract:The Fengyun meteorological satellites play an important role in global disaster prevention and reduction. With the development of remote sensing technology and the expansion of application fields, there is an increasing demand for the authenticity of remote sensing data. In this study, we used hourly data of Ground Surface Temperature (GST) measured by 93 national basic meteorological stations in Jiangxi province and MYD11A1 daily products, as well as considered the complex underlying surface and cloud cover conditions, the authenticity verification and error analysis of FY-3D land surface temperature (LST) products were conducted. The results showed that there was a significant positive correlation (P < 0.001) between the FY-3D LST and the observed GST by meteorological stations, and the FY-3D LST was generally slightly lower than GST, it indicated that there was an obviously underestimation phenomenon. Clouds had a great influence on the LST retrieval results from satellites, and the accuracy of FY-3D LST was significantly improved after cloud removal. FY-3D LST and MYD11A had high consistency in spatial distribution, but the FY-3D LST retrieval results were slightly higher than MYD11A1, besides, the two LST products had the greatest difference in the underlying surface of water bodies and the smallest difference in the underlying surface of cultivated land.
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By the conventional meteorological observation data, ERA5 hourly reanalysis data, and other sources, a comprehensive analysis was conducted on an extreme rainfall event that occurred in northern Guangdong from June 22 to June 24, 2023. This analysis focused on the circulation background field, dynamic causes, water vapor environment, and moisture transportation characteristics associated with the heavy rain. The results indicated that the 500 hPa upper-level trough, 850 hPa low vortex shear, and anomalously strong southwest monsoon were the direct influencing systems for this precipitation event. The divergence in the upper atmosphere and strong upward motion facilitated the upward transport of water vapor in the rain-affected area. The southwestern water vapor channel was established early, and the later addition of water vapor from the South China Sea provided a continuous supply of moisture for the sustained extreme heavy precipitation. The trajectory clustering analysis conducted 120 hours later revealed that the moisture transport paths below 500 hPa are relatively similar across various layers, primarily comprising three channels: the eastern Pacific, the southern South China Sea, and the western Indian Ocean-Bay of Bengal. Among these, the moisture originating from the eastern Pacific contributes the most.Throughout the heavy rain event, the southern and western boundaries at the lower levels exhibited net inflow, whereas the eastern and northern boundaries demonstrated net outflow. Notably, during both the peak and the weakening periods of the heavy rain, the moisture inflow from the southern boundary was at its highest.
By the conventional meteorological observation data, ERA5 hourly reanalysis data, and other sources, a comprehensive analysis was conducted on an extreme rainfall event that occurred in northern Guangdong from June 22 to June 24, 2023. This analysis focused on the circulation background field, dynamic causes, water vapor environment, and moisture transportation characteristics associated with the heavy rain. The results indicated that the 500 hPa upper-level trough, 850 hPa low vortex shear, and anomalously strong southwest monsoon were the direct influencing systems for this precipitation event. The divergence in the upper atmosphere and strong upward motion facilitated the upward transport of water vapor in the rain-affected area. The southwestern water vapor channel was established early, and the later addition of water vapor from the South China Sea provided a continuous supply of moisture for the sustained extreme heavy precipitation. The trajectory clustering analysis conducted 120 hours later revealed that the moisture transport paths below 500 hPa are relatively similar across various layers, primarily comprising three channels: the eastern Pacific, the southern South China Sea, and the western Indian Ocean-Bay of Bengal. Among these, the moisture originating from the eastern Pacific contributes the most.Throughout the heavy rain event, the southern and western boundaries at the lower levels exhibited net inflow, whereas the eastern and northern boundaries demonstrated net outflow. Notably, during both the peak and the weakening periods of the heavy rain, the moisture inflow from the southern boundary was at its highest.
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Based on the Baseline Surface Radiation Network (BSRN) data quality control norm and the national standards such as "Assessment method of solar energy resource" and "Specification for data inspection and correction of wind power plant meteorological observation", a integrity and validity inspection was conducted on 7 items in 4 categories of meteorological observation data, including the solar radiation, the wind, the temperature and the relative humidity, for 8 photovoltaic power stations in Shaanxi Province. The integrity rate of the valid data was divided into 5 grades to assess the data quality. The results indicate that: (1) The integrity rate of radiation data is higher than that of wind, temperature and relative humidity. The overall ranking is total radiation > scattering radiation > direct radiation > relative humidity > temperature > wind. (2) The integrity rate of valid radiation data is lower than that of wind, temperature and relative humidity. The overall ranking is temperature > relative humidity > wind > total radiation > direct radiation > scattering radiation, with only the temperature meeting the national standard. (3) The data quality of the three radiation items is relatively poor. The total proportion of stations with radiation data quality meeting the national standard (combined grades 1-2) is only 0%-12.5%, and the proportion of poor and extremely poor grades (combined grades 4-5) account for 50%-75%. (4) The overall quality of the wind, temperature and relative humidity data is respectively poor, good, and average. The compliance rates are 25%, 62.5%, and 50% respectively, and the combined proportion of poor and extremely poor grades account for 50%, 12.5%, and 37.5% respectively. (5) The variation coefficient of radiation reveals that the radiation data quality of 4 stations such as Lianhuachi Station in winter is worse than that in summer. Only the radiation data quality of Mingshuo Station is relatively stable each month.
Based on the Baseline Surface Radiation Network (BSRN) data quality control norm and the national standards such as "Assessment method of solar energy resource" and "Specification for data inspection and correction of wind power plant meteorological observation", a integrity and validity inspection was conducted on 7 items in 4 categories of meteorological observation data, including the solar radiation, the wind, the temperature and the relative humidity, for 8 photovoltaic power stations in Shaanxi Province. The integrity rate of the valid data was divided into 5 grades to assess the data quality. The results indicate that: (1) The integrity rate of radiation data is higher than that of wind, temperature and relative humidity. The overall ranking is total radiation > scattering radiation > direct radiation > relative humidity > temperature > wind. (2) The integrity rate of valid radiation data is lower than that of wind, temperature and relative humidity. The overall ranking is temperature > relative humidity > wind > total radiation > direct radiation > scattering radiation, with only the temperature meeting the national standard. (3) The data quality of the three radiation items is relatively poor. The total proportion of stations with radiation data quality meeting the national standard (combined grades 1-2) is only 0%-12.5%, and the proportion of poor and extremely poor grades (combined grades 4-5) account for 50%-75%. (4) The overall quality of the wind, temperature and relative humidity data is respectively poor, good, and average. The compliance rates are 25%, 62.5%, and 50% respectively, and the combined proportion of poor and extremely poor grades account for 50%, 12.5%, and 37.5% respectively. (5) The variation coefficient of radiation reveals that the radiation data quality of 4 stations such as Lianhuachi Station in winter is worse than that in summer. Only the radiation data quality of Mingshuo Station is relatively stable each month.
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The boundary layer is a critical region in the atmosphere for the transport of momentum, heat, and matter, and its meteorological variations are essential for understanding convective processes. Using sounding data from rotary-wing unmanned aerial vehicles (UAVs), lidar measurements, and wind tower observations, a comparative analysis was conducted, and the mesoscale meteorological model WRF was employed to simulate and validate the accuracy of the observational and modeled results. The study found that increased forest cover enhances surface roughness, reduces near-surface wind speed, and disrupts vertical mixing, resulting in a clear wind speed gradient. During the daytime, solar heating and plant transpiration increase near-surface relative humidity, raising the boundary layer height to approximately 900m, with air temperatures reaching 18°C and relative humidity dropping to 35%, indicating vertical mixing. At night, radiative cooling and canopy shielding accelerate surface cooling, forming an inversion layer, suppressing turbulence, increasing relative humidity to over 50%, and lowering the boundary layer height to 100~200m, resulting in a stable layer. The WRF model’s simulations of temperature, relative humidity, and boundary layer height closely matched the observational results, demonstrating the accuracy of high-resolution numerical models in simulating low-level boundary layer meteorological elements in regions with complex terrain. These findings provide important scientific insights for understanding the characteristics of the boundary layer under plateau complex terrain conditions and its response to climate change.
The boundary layer is a critical region in the atmosphere for the transport of momentum, heat, and matter, and its meteorological variations are essential for understanding convective processes. Using sounding data from rotary-wing unmanned aerial vehicles (UAVs), lidar measurements, and wind tower observations, a comparative analysis was conducted, and the mesoscale meteorological model WRF was employed to simulate and validate the accuracy of the observational and modeled results. The study found that increased forest cover enhances surface roughness, reduces near-surface wind speed, and disrupts vertical mixing, resulting in a clear wind speed gradient. During the daytime, solar heating and plant transpiration increase near-surface relative humidity, raising the boundary layer height to approximately 900m, with air temperatures reaching 18°C and relative humidity dropping to 35%, indicating vertical mixing. At night, radiative cooling and canopy shielding accelerate surface cooling, forming an inversion layer, suppressing turbulence, increasing relative humidity to over 50%, and lowering the boundary layer height to 100~200m, resulting in a stable layer. The WRF model’s simulations of temperature, relative humidity, and boundary layer height closely matched the observational results, demonstrating the accuracy of high-resolution numerical models in simulating low-level boundary layer meteorological elements in regions with complex terrain. These findings provide important scientific insights for understanding the characteristics of the boundary layer under plateau complex terrain conditions and its response to climate change.
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This study investigates the characteristics and impacts of the seasonally consecutive drought in Guizhou Province during 2022-2023 with using the data of station observation, atmospheric reanalysis and sea surface temperature and the identification methods of high temperature processes, meteorological drought composite index (MCI), and regional drought processes and discuss the potential issues in drought monitoring services. Main results are as follows. The seasonally consecutive drought from August 13 of 2022 to February 21 of 2023 is the most intense one with the second longest duration and the greatest impact in Guizhou since 1961. The temperatures in summer and autumn of 2022 are both the highest during the same period since 1961 and also the high temperature processes are the strongest and most frequent since 1961. The precipitation from July of 2022 to February of 2023 is the lowest during the corresponding historical period.The western Pacific subtropical high was stronger and located more westward in summer and autumn of 2022, and temporarily connected with the Iranian high to form a high-pressure dam, under which Guizhou was controlled and influenced. The La Ni?a-like cold SST anomaly was conducive to a stronger summer monsoon and a northerly shift of the rain belt, resulting in less precipitation in Guizhou Province. The drought has significantly affected power supply and water usage for production and daily life.Both the MCI and the agricultural drought index provide good indications for the initial occurrence and development stage of drought. For persistent drought, especially starting from the rainy season, it is necessary for both indices to supplement and re-correct the previous water balance calculation. Severe droughts occurring in main rainy season have a more profound impact than those in other seasons.
This study investigates the characteristics and impacts of the seasonally consecutive drought in Guizhou Province during 2022-2023 with using the data of station observation, atmospheric reanalysis and sea surface temperature and the identification methods of high temperature processes, meteorological drought composite index (MCI), and regional drought processes and discuss the potential issues in drought monitoring services. Main results are as follows. The seasonally consecutive drought from August 13 of 2022 to February 21 of 2023 is the most intense one with the second longest duration and the greatest impact in Guizhou since 1961. The temperatures in summer and autumn of 2022 are both the highest during the same period since 1961 and also the high temperature processes are the strongest and most frequent since 1961. The precipitation from July of 2022 to February of 2023 is the lowest during the corresponding historical period.The western Pacific subtropical high was stronger and located more westward in summer and autumn of 2022, and temporarily connected with the Iranian high to form a high-pressure dam, under which Guizhou was controlled and influenced. The La Ni?a-like cold SST anomaly was conducive to a stronger summer monsoon and a northerly shift of the rain belt, resulting in less precipitation in Guizhou Province. The drought has significantly affected power supply and water usage for production and daily life.Both the MCI and the agricultural drought index provide good indications for the initial occurrence and development stage of drought. For persistent drought, especially starting from the rainy season, it is necessary for both indices to supplement and re-correct the previous water balance calculation. Severe droughts occurring in main rainy season have a more profound impact than those in other seasons.
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Based on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Level 2 5 km Aerosol Layer and Level 3 Aerosol Profile products for the decade (2014—2023), the spatio-temporal distribution and aerosol optical properties in Guizhou are analyzed. The results showed that: (1) The high values of aerosol optical depth in Guizhou are mainly concentrated in Qianxinan, Qiannan (significant in spring and summer) and Guiyang (significant in winter); (2) Between 2014 and 2023, AOD in Zunyi and Qiannan showed an upward trend, while AOD in Qiandongnan and Tongren showed a downward trend, and the overall trend of AOD in Guiyang over the past decade was not significant; (3) The aerosol extinction coefficient in Guizhou decreases with increasing height. The annual extinction contributions of dust, polluted dust, and elevated smoke are 8%, 29%, and 21%, respectively; (4) In the longitudinal distribution, the height of the aerosol extinction layer rises gradually from east to west as the altitude increases; In the latitudinal distribution, the weak extinction layer lifts higher in lower latitudes; (5) The larger particulate depolarization ratio (0.0~1.0) indicates stronger irregularity of particles, the particulate depolarization ratio of aerosol particles in Guizhou is relatively small (mean value 0.098), indicating weaker irregularity. The color ratio (0.0~4.0) increases as particle size increases, and the color ratio of aerosol particles in Guizhou is relatively small (mean value 0.738), indicating smaller particle size.
Based on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Level 2 5 km Aerosol Layer and Level 3 Aerosol Profile products for the decade (2014—2023), the spatio-temporal distribution and aerosol optical properties in Guizhou are analyzed. The results showed that: (1) The high values of aerosol optical depth in Guizhou are mainly concentrated in Qianxinan, Qiannan (significant in spring and summer) and Guiyang (significant in winter); (2) Between 2014 and 2023, AOD in Zunyi and Qiannan showed an upward trend, while AOD in Qiandongnan and Tongren showed a downward trend, and the overall trend of AOD in Guiyang over the past decade was not significant; (3) The aerosol extinction coefficient in Guizhou decreases with increasing height. The annual extinction contributions of dust, polluted dust, and elevated smoke are 8%, 29%, and 21%, respectively; (4) In the longitudinal distribution, the height of the aerosol extinction layer rises gradually from east to west as the altitude increases; In the latitudinal distribution, the weak extinction layer lifts higher in lower latitudes; (5) The larger particulate depolarization ratio (0.0~1.0) indicates stronger irregularity of particles, the particulate depolarization ratio of aerosol particles in Guizhou is relatively small (mean value 0.098), indicating weaker irregularity. The color ratio (0.0~4.0) increases as particle size increases, and the color ratio of aerosol particles in Guizhou is relatively small (mean value 0.738), indicating smaller particle size.
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Based on hourly precipitation data from 178 meteorological stations in Kashgar Region from April to October in 2012-2023,the temporal and spatial distribution characteristics of short-term heavy rainfall of different grades are statistically analyzed. The results shows that:the frequency of short-term heavy rainfall in Kashgar region distributed in the pattern of north > south>east,shallow mountain area more then plain area.The terrain is closely related to short-term heavy rainfall.The short-term heavy rainfall mainly occurred near the complex terrain, such as the windward slope in front of the mountain, the valley, the steep terrain, the horn estuary terrain, and the junction area between oasis and Gobi desert..The inter-annual variation of short-term heavy rainfall is very different.2016-2018 is the year with the highest frequency of short-time heavy rainfall, with the highest frequency in 2017 (155 times) and the lowest frequency in 2012 (10 times). The annual variation characteristics of short-time heavy rainfall frequency of different grades are roughly the same as the total frequency, and the maximum frequency all appeared in 2017. The frequency changes of monthly and ten-day periods are unimodal. The high-frequency period of short-term heavy rainfall occurred from July to August, and the cumulative frequency reached the highest (140 times) in mid-July, while the maximum of extreme rainfall intensity appeared in early August (87.9 mm/h). The diurnal variation shows a bimodal pattern, with the highest frequency from around evening to midnight, followed by from midnight to morning, and the lowest from morning to noon: from 19:00 to 1:00 PM were the high frequency periods of short-time heavy rainfall of different magnitudes.
Based on hourly precipitation data from 178 meteorological stations in Kashgar Region from April to October in 2012-2023,the temporal and spatial distribution characteristics of short-term heavy rainfall of different grades are statistically analyzed. The results shows that:the frequency of short-term heavy rainfall in Kashgar region distributed in the pattern of north > south>east,shallow mountain area more then plain area.The terrain is closely related to short-term heavy rainfall.The short-term heavy rainfall mainly occurred near the complex terrain, such as the windward slope in front of the mountain, the valley, the steep terrain, the horn estuary terrain, and the junction area between oasis and Gobi desert..The inter-annual variation of short-term heavy rainfall is very different.2016-2018 is the year with the highest frequency of short-time heavy rainfall, with the highest frequency in 2017 (155 times) and the lowest frequency in 2012 (10 times). The annual variation characteristics of short-time heavy rainfall frequency of different grades are roughly the same as the total frequency, and the maximum frequency all appeared in 2017. The frequency changes of monthly and ten-day periods are unimodal. The high-frequency period of short-term heavy rainfall occurred from July to August, and the cumulative frequency reached the highest (140 times) in mid-July, while the maximum of extreme rainfall intensity appeared in early August (87.9 mm/h). The diurnal variation shows a bimodal pattern, with the highest frequency from around evening to midnight, followed by from midnight to morning, and the lowest from morning to noon: from 19:00 to 1:00 PM were the high frequency periods of short-time heavy rainfall of different magnitudes.
Temporal and spatial distributions of the diurnal cycle of summer precipitation in Altay of Xinjiang
Abstract:
Based on the summer (June to August) hourly precipitation data covering 8 meteorological stations in Altay region during 2011-2020. The spatial and temporal distribution characteristics of diurnal variation of precipitation characteristics are discussed, The main conclusions are as follows: The peak values of total precipitation amount and total precipitation intensity occur from 16:00 to 19:00 Beijing time, The amount and intensity of total precipitation shows an increasing trend in day (09:00-20:00), while the total precipitation frequency is opposite. and the valley values of total precipitation characteristics occur from 23:00 to 02:00 of the next day. The precipitation main occur in day and the drizzle is more frequent than other levels. precipitation lasting for two hours contributed the maximum precipitation amount to the total precipitation, precipitation lasting for one hours occurred most and the duration is negatively correlated with precipitation frequency. There is a spatial distribution of the total precipitation maximum that is "the west is more than l the east, the north more than the south", the three different precipitation categories events generally show a decreasing trend from the mountainous areas and foothills to river valley plain, the three different durations precipitation events mainly are contributed by short-term precipitation with duration of one to six hours.
Based on the summer (June to August) hourly precipitation data covering 8 meteorological stations in Altay region during 2011-2020. The spatial and temporal distribution characteristics of diurnal variation of precipitation characteristics are discussed, The main conclusions are as follows: The peak values of total precipitation amount and total precipitation intensity occur from 16:00 to 19:00 Beijing time, The amount and intensity of total precipitation shows an increasing trend in day (09:00-20:00), while the total precipitation frequency is opposite. and the valley values of total precipitation characteristics occur from 23:00 to 02:00 of the next day. The precipitation main occur in day and the drizzle is more frequent than other levels. precipitation lasting for two hours contributed the maximum precipitation amount to the total precipitation, precipitation lasting for one hours occurred most and the duration is negatively correlated with precipitation frequency. There is a spatial distribution of the total precipitation maximum that is "the west is more than l the east, the north more than the south", the three different precipitation categories events generally show a decreasing trend from the mountainous areas and foothills to river valley plain, the three different durations precipitation events mainly are contributed by short-term precipitation with duration of one to six hours.
Gong Yan Duo, Liu Xing Guang, Wu Xia, Wang Cheng Wei, Han Ji Liang, Deng Wen Jia, Meng Ting Ting, Liu Yang, Pan Xue
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In order to accurately evaluate the restoration benefits of artificial precipitation operations on the ecological quality of forest vegetation in the Daxing'anling Prefecture, the net primary productivity of vegetation was obtained according to the light energy utilization model based on monthly NDVI data from EOS/MODIS. Combined with vegetation coverage, the Vegetation Ecological Quality Index was calculated to evaluate the ecological effects of forest ecological restoration type artificial precipitation stimulation carried out since 2012. Results showed that: (1) during the growing season from 2000 to 2022, the overall ecological quality of forest vegetation showed an improvement trend. The proportion of regions with vegetation ecological quality evaluation grades of "good" and "medium" had shown a significant increasing trend. (2) the average values of forest Vegetation Ecological Quality Index in the high-frequency, medium-frequency and low-frequency areas of the artificial precipitation operation from 2012 to 2022 were 7.9 %, 5.5 % and 4.9 % higher than the average values from 2000 to 2011, respectively. Therefore, the artificial precipitation enhancement operation carried out in spring in the Daxing'anling Prefecture had a significant effect on forest vegetation restoration and ecological improvement.
In order to accurately evaluate the restoration benefits of artificial precipitation operations on the ecological quality of forest vegetation in the Daxing'anling Prefecture, the net primary productivity of vegetation was obtained according to the light energy utilization model based on monthly NDVI data from EOS/MODIS. Combined with vegetation coverage, the Vegetation Ecological Quality Index was calculated to evaluate the ecological effects of forest ecological restoration type artificial precipitation stimulation carried out since 2012. Results showed that: (1) during the growing season from 2000 to 2022, the overall ecological quality of forest vegetation showed an improvement trend. The proportion of regions with vegetation ecological quality evaluation grades of "good" and "medium" had shown a significant increasing trend. (2) the average values of forest Vegetation Ecological Quality Index in the high-frequency, medium-frequency and low-frequency areas of the artificial precipitation operation from 2012 to 2022 were 7.9 %, 5.5 % and 4.9 % higher than the average values from 2000 to 2011, respectively. Therefore, the artificial precipitation enhancement operation carried out in spring in the Daxing'anling Prefecture had a significant effect on forest vegetation restoration and ecological improvement.
Abstract:
Abstract: In order to effectively play the important role of artificial precipitation enhancement in agricultural drought resistance, taking Chibi city in Hubei Province as the research area,using the daily temperature and precipitation observation data from 2014 to 2023, based on the crop water requirement formula and crop water deficit index (CWDI),determined the identification and grade standard of crop drought process,and constructed the artificial precipitation enhancement demand index and grade standard. We deeply analyzed the spatial and temporal distribution characteristics of crop water requirement, agricultural drought and artificial precipitation demand. The results showed that:(1) The crop water requirement in Chibi City showed a unimodal distribution, with a peak in late July. The period during which the crop water requirement exceeds 20 mm is concentrated from early April to early October.The cumulative crop water requirement showed an 'X'-shaped high - and - low - scattered spatial distribution.The high - value area between740 mm and 800 mm was distributed in the towns such as Zhonghuopu, Guantangyi, Xindian, etc. (2) The light, medium and heavy crop drought processes last an average of 8 - 10days, 18 - 20days, 25 - 35days respectively, and the extreme drought process is more than 60days. Light drought occurs from December to May, and moderate and above -level droughts mostly occur in June - October. The frequency and intensity of drought among townships are significantly different; and the extremely high intensity areas are distributed in Chibi,Liushanhu,Zhonghuopu and other towns.(3)The seasonal characteristics of artificial precipitation demand are obvious. In winter to spring ( December-May ), the grade is low and the frequency is low. In summer to autumn (June-November), the grade is high and the frequency is high. The demand degree shows a spatial distribution of ' high in the angle area and low in the middle area ', with high to extremely high demand areas are distributed in the northeast, northwest and southwest angle areas.(4) The emergence of low level artificial precipitation enhancement demand is an important signal to trigger the artificial precipitation enhancement operation, and the development period of demand degree from low level to medium and high level is the effective operation period of artificial rain enhancement. The practice has proved many times that the artificial precipitation enhancement demand index can help the operation unit make the artificial precipitation enhancement operation plan for agricultural drought resistance more effectively and reasonably.
Abstract: In order to effectively play the important role of artificial precipitation enhancement in agricultural drought resistance, taking Chibi city in Hubei Province as the research area,using the daily temperature and precipitation observation data from 2014 to 2023, based on the crop water requirement formula and crop water deficit index (CWDI),determined the identification and grade standard of crop drought process,and constructed the artificial precipitation enhancement demand index and grade standard. We deeply analyzed the spatial and temporal distribution characteristics of crop water requirement, agricultural drought and artificial precipitation demand. The results showed that:(1) The crop water requirement in Chibi City showed a unimodal distribution, with a peak in late July. The period during which the crop water requirement exceeds 20 mm is concentrated from early April to early October.The cumulative crop water requirement showed an 'X'-shaped high - and - low - scattered spatial distribution.The high - value area between740 mm and 800 mm was distributed in the towns such as Zhonghuopu, Guantangyi, Xindian, etc. (2) The light, medium and heavy crop drought processes last an average of 8 - 10days, 18 - 20days, 25 - 35days respectively, and the extreme drought process is more than 60days. Light drought occurs from December to May, and moderate and above -level droughts mostly occur in June - October. The frequency and intensity of drought among townships are significantly different; and the extremely high intensity areas are distributed in Chibi,Liushanhu,Zhonghuopu and other towns.(3)The seasonal characteristics of artificial precipitation demand are obvious. In winter to spring ( December-May ), the grade is low and the frequency is low. In summer to autumn (June-November), the grade is high and the frequency is high. The demand degree shows a spatial distribution of ' high in the angle area and low in the middle area ', with high to extremely high demand areas are distributed in the northeast, northwest and southwest angle areas.(4) The emergence of low level artificial precipitation enhancement demand is an important signal to trigger the artificial precipitation enhancement operation, and the development period of demand degree from low level to medium and high level is the effective operation period of artificial rain enhancement. The practice has proved many times that the artificial precipitation enhancement demand index can help the operation unit make the artificial precipitation enhancement operation plan for agricultural drought resistance more effectively and reasonably.
Abstract:
By using the MODIS land use in 2022 and based on the vegetation coverage data retrieved from the MODIS NDVI (Normalized Difference Vegetation Index) in 2022, this study assesses the impact of land surface information on the performance of the Weather Research and Forecasting Model (WRF) over Chenzhou in summer. Results indicated that using the new high-resolution and high-timely land surface data can improve the simulated results of 2 m temperature and 2 m relative humidity, and 70% of stations experienced significant enhancement, with the hit rate increased by 8.21% and 7.80% in summer over Chenzhou; the 2 m temperature and 2 m relative humidity were very sensitive to the land surface data resolution. Specifically, the decrease in vegetation coverage, changes in vegetation types, and expansion of urban areas, as evidenced by new data, lead to a reduction in latent heat and an increase in sensible heat, which resulted in simulated higher 2 m temperatures and lower 2 m relative humidity in Chenzhou.
By using the MODIS land use in 2022 and based on the vegetation coverage data retrieved from the MODIS NDVI (Normalized Difference Vegetation Index) in 2022, this study assesses the impact of land surface information on the performance of the Weather Research and Forecasting Model (WRF) over Chenzhou in summer. Results indicated that using the new high-resolution and high-timely land surface data can improve the simulated results of 2 m temperature and 2 m relative humidity, and 70% of stations experienced significant enhancement, with the hit rate increased by 8.21% and 7.80% in summer over Chenzhou; the 2 m temperature and 2 m relative humidity were very sensitive to the land surface data resolution. Specifically, the decrease in vegetation coverage, changes in vegetation types, and expansion of urban areas, as evidenced by new data, lead to a reduction in latent heat and an increase in sensible heat, which resulted in simulated higher 2 m temperatures and lower 2 m relative humidity in Chenzhou.
Abstract:
Using multiple sources such as high-altitude, ground-based meteorological observatories and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis data ERA5, two warm season elevated thunderstorms were analyzed in the southern and central parts of Beijing-Tianjin-Hebei on 25 June, 2008 and 21 July, 2017. The stability and triggering mechanism of the atmosphere when convection occurred were discussed. The results are as follows. (1) In warm season, elevated convection occurred in the relatively cold and stable stratification state of the lower atmosphere. In the case of conditioned instability over strong ininversion, the convective intensity was stronger than that over weak ininversion. (2) The convective instability layer in the middle and upper atmosphere was established 8 hours before the elevated thunderstorm. The instability of the elevated thunderstorm with strong inversion was higher, which was conducive to the generation of severe thunderstorm winds, while the convective instability for precipitation was relatively weak. K index had a stronger response to elevated thunderstorms in the warm season, the SI index and T85 were more sensitive to the occurrence of severe thunderstorm winds, and the LI index was better for the application of severe precipitation forecast. (3) The two elevated thunderstorms occurred under different weather backgrounds, which were in the southeast quadrant of the vortex and under the subtropical high. The atmosphere near or above the inversion layer showed the characteristics of symmetrical instability, it indicated slanting updraft development. (4) The frontogenesis between 925 and 700 hPa and the latitudinal wind shear at 850 hPa had a significant triggering effect on the formation of strong convection. The faster the height of frontogenesis falled and the stronger the intensity was, the more favorable the gale would appear. If the frontogenesis duration was long, the heavy precipitation would persist. If the vertical wind shear on the cold mat was maintained for a long time, the development and propagation of heavy precipitation thunderstorm cells were predicted.
Using multiple sources such as high-altitude, ground-based meteorological observatories and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis data ERA5, two warm season elevated thunderstorms were analyzed in the southern and central parts of Beijing-Tianjin-Hebei on 25 June, 2008 and 21 July, 2017. The stability and triggering mechanism of the atmosphere when convection occurred were discussed. The results are as follows. (1) In warm season, elevated convection occurred in the relatively cold and stable stratification state of the lower atmosphere. In the case of conditioned instability over strong ininversion, the convective intensity was stronger than that over weak ininversion. (2) The convective instability layer in the middle and upper atmosphere was established 8 hours before the elevated thunderstorm. The instability of the elevated thunderstorm with strong inversion was higher, which was conducive to the generation of severe thunderstorm winds, while the convective instability for precipitation was relatively weak. K index had a stronger response to elevated thunderstorms in the warm season, the SI index and T85 were more sensitive to the occurrence of severe thunderstorm winds, and the LI index was better for the application of severe precipitation forecast. (3) The two elevated thunderstorms occurred under different weather backgrounds, which were in the southeast quadrant of the vortex and under the subtropical high. The atmosphere near or above the inversion layer showed the characteristics of symmetrical instability, it indicated slanting updraft development. (4) The frontogenesis between 925 and 700 hPa and the latitudinal wind shear at 850 hPa had a significant triggering effect on the formation of strong convection. The faster the height of frontogenesis falled and the stronger the intensity was, the more favorable the gale would appear. If the frontogenesis duration was long, the heavy precipitation would persist. If the vertical wind shear on the cold mat was maintained for a long time, the development and propagation of heavy precipitation thunderstorm cells were predicted.
Abstract:
Based on the precipitation data from the national meteorological observatory, the FY-4A satellite cloud map data and the ERA5 reanalysis data for a rainstorm that occurred in the western part of Chongqing from July 26 to 28, 2023, through the principle of the decomposition of the creeping and circling currents to explore the dynamics of flow over and flow around currents inspired by the topography and to analyze the thermal characteristics of the rainstorm process by using moist potential vorticity as the entry point, the following conclusions are obtained: (1) The rainstorm mainly occurred at night and developed in a “bimodal” pattern with long duration, high intensity and wide coverage. The mesoscale convective system (MCS) controlled western Chongqing, while the coexistence of Tibetan Plateau vortics and southwestern vortex, as well as the northward movement of super typhoon Doksuri and the transport of its residual circulation provided sufficient water vapor for the rainstorm, thus promoting the enhancement of the intensity of precipitation and its persistence. (2) The contribution of the flow over current movement to the rainstorm is more significant than that of the cirrus movement, and the development trend and distribution range of the flow over current intensity and precipitation intensity over time are basically the same, and the vertical movement caused by the flow over current has an increase in atmospheric suction effect. (3) The positive pressure component (MPV1) and the oblique pressure component (MPV2) of the moist potential vorticity have important significance in the process of rainstorm formation, and the negative MPV1 and positive MPV2 zones in the middle and lower troposphere correspond well with the precipitation zone, especially the intensity changes of the negative MPV1 and positive MPV2 centers match the trend of the changes of the precipitation intensity.
Based on the precipitation data from the national meteorological observatory, the FY-4A satellite cloud map data and the ERA5 reanalysis data for a rainstorm that occurred in the western part of Chongqing from July 26 to 28, 2023, through the principle of the decomposition of the creeping and circling currents to explore the dynamics of flow over and flow around currents inspired by the topography and to analyze the thermal characteristics of the rainstorm process by using moist potential vorticity as the entry point, the following conclusions are obtained: (1) The rainstorm mainly occurred at night and developed in a “bimodal” pattern with long duration, high intensity and wide coverage. The mesoscale convective system (MCS) controlled western Chongqing, while the coexistence of Tibetan Plateau vortics and southwestern vortex, as well as the northward movement of super typhoon Doksuri and the transport of its residual circulation provided sufficient water vapor for the rainstorm, thus promoting the enhancement of the intensity of precipitation and its persistence. (2) The contribution of the flow over current movement to the rainstorm is more significant than that of the cirrus movement, and the development trend and distribution range of the flow over current intensity and precipitation intensity over time are basically the same, and the vertical movement caused by the flow over current has an increase in atmospheric suction effect. (3) The positive pressure component (MPV1) and the oblique pressure component (MPV2) of the moist potential vorticity have important significance in the process of rainstorm formation, and the negative MPV1 and positive MPV2 zones in the middle and lower troposphere correspond well with the precipitation zone, especially the intensity changes of the negative MPV1 and positive MPV2 centers match the trend of the changes of the precipitation intensity.
Abstract:
Based on the lightning location data of Inner Mongolia from 2014 to 2023, the spatial characteristics of lightning activity and its hazard in Inner Mongolia were studied by using spss mathematical statistics analysis method, percentile method, analytic hierarchy process and spatial analysis method in AcrGIS.The results show that the flash days shows an upward trend, the total flash and negative flash density show a downward trend, and the positive flash density shows an upward trend. Through the T test, it is significant above the 0.05 confidence level. May-September is the high incidence period of lightning, and the lightning is the most active in July. The lightning is the weakest at 7-10 a.m., and the lightning is the most active at 13-19 p.m. The trend of the average peak current of lightning is opposite to the trend of lightning activity. The peak current of positive flashes is significantly higher than that of negative flashes. From the lower quartile to the upper quartile, the ratio of positive and negative flash peak current increases from about 1.7 times to 2.0 times, and the median and average positive flashes are about 1.8 times that of negative flashes. The lightning disaster-causing risk is gradually increasing from the plain-valley-mountain area in the east-west direction of the Yinshan Mountains to the south and the north-south direction of the daxing"an mountains to the east.
Based on the lightning location data of Inner Mongolia from 2014 to 2023, the spatial characteristics of lightning activity and its hazard in Inner Mongolia were studied by using spss mathematical statistics analysis method, percentile method, analytic hierarchy process and spatial analysis method in AcrGIS.The results show that the flash days shows an upward trend, the total flash and negative flash density show a downward trend, and the positive flash density shows an upward trend. Through the T test, it is significant above the 0.05 confidence level. May-September is the high incidence period of lightning, and the lightning is the most active in July. The lightning is the weakest at 7-10 a.m., and the lightning is the most active at 13-19 p.m. The trend of the average peak current of lightning is opposite to the trend of lightning activity. The peak current of positive flashes is significantly higher than that of negative flashes. From the lower quartile to the upper quartile, the ratio of positive and negative flash peak current increases from about 1.7 times to 2.0 times, and the median and average positive flashes are about 1.8 times that of negative flashes. The lightning disaster-causing risk is gradually increasing from the plain-valley-mountain area in the east-west direction of the Yinshan Mountains to the south and the north-south direction of the daxing"an mountains to the east.
Abstract:
Based on the hail observation data in western Shandong during 1978 - 2020, the characteristics of hail variation was analyzed. Furthermore, hail clouds tracks was studied by using K-means clustering algorithm. The results show that: (1) The hail in western Shandong present obvious spatial-temporal characteristics. Compare to before 2000, the total hail days show decreasing trend after 2000. The spatial distribution characteristics of hail tend to be higher in the north, but lower in the south. (2) There are five main hail paths, including north path, northwest path, west path, southwest path and local generation path. Among the five types of hail paths, northwest path account for the largest portion, southwest path take the lowest portion. The west path produce the longest duration, southwest path produce the shortest duration. (3)There are five synoptic-scale circulation patterns, namely low vortex, low trough, transverse trough, northwest current and the edge of the subtropical high, which low vortex type has the largest share.
Based on the hail observation data in western Shandong during 1978 - 2020, the characteristics of hail variation was analyzed. Furthermore, hail clouds tracks was studied by using K-means clustering algorithm. The results show that: (1) The hail in western Shandong present obvious spatial-temporal characteristics. Compare to before 2000, the total hail days show decreasing trend after 2000. The spatial distribution characteristics of hail tend to be higher in the north, but lower in the south. (2) There are five main hail paths, including north path, northwest path, west path, southwest path and local generation path. Among the five types of hail paths, northwest path account for the largest portion, southwest path take the lowest portion. The west path produce the longest duration, southwest path produce the shortest duration. (3)There are five synoptic-scale circulation patterns, namely low vortex, low trough, transverse trough, northwest current and the edge of the subtropical high, which low vortex type has the largest share.
Abstract:
By using conventional observations data and ERA5 reanalysis data, the causes and extremes of the two rainstorms in Northern Shaanxi, which occurred on July 11 (“7·11”) and August 9 (“8·9”), were analyzed based on the background of abnormally high precipitation in 2022. Results showed that: (1) The low-level jet provided continuous water vapor transport and the wet layer is deep during “7·11” rainstorm. The development of deep mesoscale vortex system provided favorable dynamic conditions for large-scale rainstorm.Rainstorms with a long duration and low intensity. (2) Northern Shaanxi was controlled by the subtropical high and with strong convective effective potential energy and large whole layer precipitable water vapor during “8·9” rainstorm. The surface convergence line triggered the release of unstable energy and resulted in convective rainstorms which had intense hourly precipitation and short duration of single station precipitation.The maintenance of theβmesoscale convective complex resulted in rainfall intensity greater than 80 mm·h-1. (3) The water vapor flux standardized deviation (SD) exceeded 3σ at 700 and 850 hPa during “7·11” rainstorm and many physical quantities representing the water vapor and dynamic conditions reached or approached the maximum value of extremely strong rainstorm process, which indicated strong extremity. The whole layer precipitable water vapor SD exceeded 3 σ in “8·9” rainstorm and the convective effective potential energy reached the upper quartile value of extremely strong rainstorm process. The large value region of physical quantities with high SD had good indication significance for extreme rainfall prediction.
By using conventional observations data and ERA5 reanalysis data, the causes and extremes of the two rainstorms in Northern Shaanxi, which occurred on July 11 (“7·11”) and August 9 (“8·9”), were analyzed based on the background of abnormally high precipitation in 2022. Results showed that: (1) The low-level jet provided continuous water vapor transport and the wet layer is deep during “7·11” rainstorm. The development of deep mesoscale vortex system provided favorable dynamic conditions for large-scale rainstorm.Rainstorms with a long duration and low intensity. (2) Northern Shaanxi was controlled by the subtropical high and with strong convective effective potential energy and large whole layer precipitable water vapor during “8·9” rainstorm. The surface convergence line triggered the release of unstable energy and resulted in convective rainstorms which had intense hourly precipitation and short duration of single station precipitation.The maintenance of theβmesoscale convective complex resulted in rainfall intensity greater than 80 mm·h-1. (3) The water vapor flux standardized deviation (SD) exceeded 3σ at 700 and 850 hPa during “7·11” rainstorm and many physical quantities representing the water vapor and dynamic conditions reached or approached the maximum value of extremely strong rainstorm process, which indicated strong extremity. The whole layer precipitable water vapor SD exceeded 3 σ in “8·9” rainstorm and the convective effective potential energy reached the upper quartile value of extremely strong rainstorm process. The large value region of physical quantities with high SD had good indication significance for extreme rainfall prediction.
Abstract:
Using X-band dual-polarization phased-array radar data, ERA5 reanalysis data, and conventional observation data, the observation characteristics of a hail cloud (without artificial hail suppression operation) that occurred in Weining, Guizhou on July 1, 2023 is analyzed. The results show that hail cloud cell develop rapidly, with a significant increase in VIL. During the developmental stage of hail cloud, the ZDR column and KDP column exceed the -20℃ layer. While during the mature hail stage, there are strong ZH values (greater than 60 dBZ), low ZDR values (0~2 dB) above the 0℃ layer, and large ZDR values (0.5~4 dB) below the 0℃ layer, strong KDP values (greater than 3.1 °/km), low CC values (0.85~0.94) with dual polarization parameter characteristics. The horizontal wind field of hail cloud is influenced by the background field of mesoscale circulation, with southwest and southerly winds dominating in the middle and lower layers. There is convergence at the strong center of hail cloud cell in the middle layer, and northwest dry and cold air invading in the upper layers. The rear side of the vertical wind field of hail cloud is the inflow area of upward airflow, and the front side is the outflow area of downward airflow. At the mature stage of development, the storm top divergence feature appears at 12~14 km above the strong center of the hail cloud, and the downdrafts from 10 km above the strong center to the ground correspond to hail falling areas. The main mechanism for hail formation in this process is that the upwelling airflow brings hail particles to the accumulation area of ice water mixture and grows into hail particles. The research results can provide reference for the application of X-band dual-polarization radar in hail weather monitoring and warning.
Using X-band dual-polarization phased-array radar data, ERA5 reanalysis data, and conventional observation data, the observation characteristics of a hail cloud (without artificial hail suppression operation) that occurred in Weining, Guizhou on July 1, 2023 is analyzed. The results show that hail cloud cell develop rapidly, with a significant increase in VIL. During the developmental stage of hail cloud, the ZDR column and KDP column exceed the -20℃ layer. While during the mature hail stage, there are strong ZH values (greater than 60 dBZ), low ZDR values (0~2 dB) above the 0℃ layer, and large ZDR values (0.5~4 dB) below the 0℃ layer, strong KDP values (greater than 3.1 °/km), low CC values (0.85~0.94) with dual polarization parameter characteristics. The horizontal wind field of hail cloud is influenced by the background field of mesoscale circulation, with southwest and southerly winds dominating in the middle and lower layers. There is convergence at the strong center of hail cloud cell in the middle layer, and northwest dry and cold air invading in the upper layers. The rear side of the vertical wind field of hail cloud is the inflow area of upward airflow, and the front side is the outflow area of downward airflow. At the mature stage of development, the storm top divergence feature appears at 12~14 km above the strong center of the hail cloud, and the downdrafts from 10 km above the strong center to the ground correspond to hail falling areas. The main mechanism for hail formation in this process is that the upwelling airflow brings hail particles to the accumulation area of ice water mixture and grows into hail particles. The research results can provide reference for the application of X-band dual-polarization radar in hail weather monitoring and warning.
Abstract:
Using temperature and precipitation observation data from 17 national meteorological stations in the Hexi Corridor region of Gansu Province from 1961 to 2022, this study employed ensemble empirical mode decomposition (EEMD) and the least squares linear fitting method to investigate the spatiotemporal variations in temperature and precipitation in this area. The results indicate that over the past 62 years, the average temperature in the Hexi Corridor has shown a continuous upward trend, with an annual average temperature increase rate of 0.36°C/10 years (P<0.01), particularly notable since the 1990s. Both the annual maximum and minimum temperatures also exhibit upward trends, with the most significant warming occurring in winter, which is substantially higher than the other three seasons. Over the same period, annual precipitation has generally increased, with seasonal precipitation rising in the order of summer > autumn > spring > winter, with summer contributing the most to the annual precipitation. EEMD analysis revealed a significant quasi-3-year periodic oscillation in the annual average temperature, while annual precipitation exhibited a significant quasi-2-year periodic oscillation. Compared to the temperature series, the decadal-scale changes and long-term trend contributions in the precipitation series were notably smaller. Spatially, the warming trend in the central and eastern parts of the Hexi Corridor was significantly higher than in the western part, and warming in the northern part was greater than in the southern part. Precipitation increased the most in the eastern part, followed by the central part, with the least increase observed in the western part. Additionally, precipitation increased more in the southern part compared to the northern part.
Using temperature and precipitation observation data from 17 national meteorological stations in the Hexi Corridor region of Gansu Province from 1961 to 2022, this study employed ensemble empirical mode decomposition (EEMD) and the least squares linear fitting method to investigate the spatiotemporal variations in temperature and precipitation in this area. The results indicate that over the past 62 years, the average temperature in the Hexi Corridor has shown a continuous upward trend, with an annual average temperature increase rate of 0.36°C/10 years (P<0.01), particularly notable since the 1990s. Both the annual maximum and minimum temperatures also exhibit upward trends, with the most significant warming occurring in winter, which is substantially higher than the other three seasons. Over the same period, annual precipitation has generally increased, with seasonal precipitation rising in the order of summer > autumn > spring > winter, with summer contributing the most to the annual precipitation. EEMD analysis revealed a significant quasi-3-year periodic oscillation in the annual average temperature, while annual precipitation exhibited a significant quasi-2-year periodic oscillation. Compared to the temperature series, the decadal-scale changes and long-term trend contributions in the precipitation series were notably smaller. Spatially, the warming trend in the central and eastern parts of the Hexi Corridor was significantly higher than in the western part, and warming in the northern part was greater than in the southern part. Precipitation increased the most in the eastern part, followed by the central part, with the least increase observed in the western part. Additionally, precipitation increased more in the southern part compared to the northern part.
Abstract:
The role of clouds in regulating temperature and humidity is pivotal for various sectors such as agriculture, urban development, and aviation. Despite this, the precise forecasting of cloud cover remains a formidable challenge. This paper introduces a novel cloud prediction model that leverages the time-adaptive method, dynamic variable parameter method, and random forest method, along with data from the GRAPES (Global/Regional Assimilation and Prediction System) model and FY-4A satellite. The objective is to enhance the precision of cloud amount predictions. The study reveals that the daily fluctuations in total cloud cover in the Jiuquan region and its vicinity are relatively minor, yet they exhibit pronounced seasonal patterns, peaking in spring and summer and diminishing in autumn and winter. A spatial analysis indicates a gradient from fewer clouds in the northern areas to a higher concentration in the south. The cloud cover at various grid points is influenced by a multitude of factors. Employing the dynamic variable parameter method, this paper dynamically selects forecast variables based on their correlation with cloud cover at different grid points, which are then used to refine the random forest model. The model demonstrates an accuracy range of 0.55 to 0.80, thereby significantly elevating the precision of cloud amount forecasts. Furthermore, the incorporation of a time-adaptive method allows for the continuous updating of the random forest model. However, the cloud prediction accuracy hovers around 0.55, which may be attributed in part to the scarcity of comprehensive data, thereby impacting the model’s predictive capabilities for cloud amounts.
The role of clouds in regulating temperature and humidity is pivotal for various sectors such as agriculture, urban development, and aviation. Despite this, the precise forecasting of cloud cover remains a formidable challenge. This paper introduces a novel cloud prediction model that leverages the time-adaptive method, dynamic variable parameter method, and random forest method, along with data from the GRAPES (Global/Regional Assimilation and Prediction System) model and FY-4A satellite. The objective is to enhance the precision of cloud amount predictions. The study reveals that the daily fluctuations in total cloud cover in the Jiuquan region and its vicinity are relatively minor, yet they exhibit pronounced seasonal patterns, peaking in spring and summer and diminishing in autumn and winter. A spatial analysis indicates a gradient from fewer clouds in the northern areas to a higher concentration in the south. The cloud cover at various grid points is influenced by a multitude of factors. Employing the dynamic variable parameter method, this paper dynamically selects forecast variables based on their correlation with cloud cover at different grid points, which are then used to refine the random forest model. The model demonstrates an accuracy range of 0.55 to 0.80, thereby significantly elevating the precision of cloud amount forecasts. Furthermore, the incorporation of a time-adaptive method allows for the continuous updating of the random forest model. However, the cloud prediction accuracy hovers around 0.55, which may be attributed in part to the scarcity of comprehensive data, thereby impacting the model’s predictive capabilities for cloud amounts.
Abstract:
To evaluate the optimization effect of variable speed on the detection performance of the Very low frequency long-range lightning location network, this paper presents a preliminary assessment of the station network error within the core area. By comparing lightning localization results obtained using variable speed versus the speed of light against actual lightning strikes, it is found that assigning an individual variable speed to each observation station achieves optimal lightning location accuracy. Further anal-ysis focuses on the impact of station quantity and layout within the network's core area, it reveals that the localization error can generally be contained within 3 km when synchronized by more than six stations. As evidenced by the superimposition results of lightning with Cloud Top Temperature and radar echoes, the location network exhibits excellent recognition of thunderstorm activities of different scales, both within and outside the network. This underscores the capability of the variable speed algorithm in minimizing location errors stemming from propagation paths, station quantity, and layout, thereby enabling long-range and high-precision lightning detection.
To evaluate the optimization effect of variable speed on the detection performance of the Very low frequency long-range lightning location network, this paper presents a preliminary assessment of the station network error within the core area. By comparing lightning localization results obtained using variable speed versus the speed of light against actual lightning strikes, it is found that assigning an individual variable speed to each observation station achieves optimal lightning location accuracy. Further anal-ysis focuses on the impact of station quantity and layout within the network's core area, it reveals that the localization error can generally be contained within 3 km when synchronized by more than six stations. As evidenced by the superimposition results of lightning with Cloud Top Temperature and radar echoes, the location network exhibits excellent recognition of thunderstorm activities of different scales, both within and outside the network. This underscores the capability of the variable speed algorithm in minimizing location errors stemming from propagation paths, station quantity, and layout, thereby enabling long-range and high-precision lightning detection.
Abstract:
Based on the hourly precipitation observation data of 70 stations and the observation data of dual polarization radar in Suizhou City, Hubei Province, the distribution characteristics of short-time heavy rainfall and the characteristics of dual polarization radar parameters of different levels of rainfall intensity from 2019 to 2023 were statistically analyzed. The results show that: (1) The short-time heavy rainfall is concentrated in June to August, with the most frequent in June to July. The daily variation characteristics show a three peak distribution, with the highest occurrence occurring from 05:00 to 08:00, followed by 22:00 to 01:00, and the third occurring from 13:00 to 18:00. From the perspective of regional distribution, the south of Suizhou is more prone to short-time heavy rainfall than the north, and the south of Suixian is the most prone area. (2) The radar parameters with high correlation with rain intensity are combined reflectivity(CR), vertical integrated liquid water content (VIL), and differential reflectivity(ZDR), specific differential phase (KDP) below 2.5 km. With the increase of rainfall intensity, the general trends of horizontal reflectivity(ZH), KDP, CR and VIL increase slightly, while the correlation between rainfall intensity and ZDR, correlation coefficient(CC), echo top height(ET) and maximum echo height(DBZM HT) is not obvious. (3) The higher the rain intensity, the greater ET and ZDR, indicating that the higher the echo top, the stronger the convection development, the larger the particle diameter. (4) The early warning index values of ZH, ZDR, KDP, CC at low levels and CR, ET, DBZM HT and VIL corresponding to rainfall intensity of 20~40 mm·h-1 and ≥40 mm·h-1 are respectively 37 dBZ and 41.2 dBZ、0.77 dB and 0.92 dB、0.34 deg·km-1 and 0.65 deg·km-1、0.95 and 0.96、39.2 dBZ and 43.3 dBZ、6.5 km and 7.6 km、1.8 km and 1.8 km、2.9 kg·m-2 and 4.5 kg·m-2.
Based on the hourly precipitation observation data of 70 stations and the observation data of dual polarization radar in Suizhou City, Hubei Province, the distribution characteristics of short-time heavy rainfall and the characteristics of dual polarization radar parameters of different levels of rainfall intensity from 2019 to 2023 were statistically analyzed. The results show that: (1) The short-time heavy rainfall is concentrated in June to August, with the most frequent in June to July. The daily variation characteristics show a three peak distribution, with the highest occurrence occurring from 05:00 to 08:00, followed by 22:00 to 01:00, and the third occurring from 13:00 to 18:00. From the perspective of regional distribution, the south of Suizhou is more prone to short-time heavy rainfall than the north, and the south of Suixian is the most prone area. (2) The radar parameters with high correlation with rain intensity are combined reflectivity(CR), vertical integrated liquid water content (VIL), and differential reflectivity(ZDR), specific differential phase (KDP) below 2.5 km. With the increase of rainfall intensity, the general trends of horizontal reflectivity(ZH), KDP, CR and VIL increase slightly, while the correlation between rainfall intensity and ZDR, correlation coefficient(CC), echo top height(ET) and maximum echo height(DBZM HT) is not obvious. (3) The higher the rain intensity, the greater ET and ZDR, indicating that the higher the echo top, the stronger the convection development, the larger the particle diameter. (4) The early warning index values of ZH, ZDR, KDP, CC at low levels and CR, ET, DBZM HT and VIL corresponding to rainfall intensity of 20~40 mm·h-1 and ≥40 mm·h-1 are respectively 37 dBZ and 41.2 dBZ、0.77 dB and 0.92 dB、0.34 deg·km-1 and 0.65 deg·km-1、0.95 and 0.96、39.2 dBZ and 43.3 dBZ、6.5 km and 7.6 km、1.8 km and 1.8 km、2.9 kg·m-2 and 4.5 kg·m-2.
Abstract:
Using the daily precipitation data of Gannan 2015-2021 automatic station, regional station, and the 2015-2021 geological disaster data, based on the precipitation data, the second generation display statistical early-warning model of geological hazards in Gannan Prefecture is established to study the possibility of geological hazards induced by dynamic precipitation, it can also provide technical reference for the prevention and control of geological disasters, and reduce the economic losses and casualties caused by sudden geological disasters such as collapse, landslide and debris flow, which are mainly induced by precipitation, is of great significance. Method 1: to quantitatively evaluate the geological background risk of Gannan Prefecture by using information quantity method, taking the effective precipitation before the disaster, the maximum and minimum precipitation on the same day, and the accumulated precipitation on the same day as the independent variables, by fitting different linear equations to different risk areas, the meteorological risk early-warning model of geological hazards in Gannan Prefecture was established. Method 2: take the slope, aspect, relief degree, stratum lithology, fault structure, river system and human engineering activity as evaluation indexes, and use machine learning method, by using BP neural network algorithm program and setting the learning step, the probability quantization value of geological hazard potential degree is obtained, and coupled with precipitation factor, the geological hazard meteorological risk early-warning model of Gannan Prefecture is established.
Using the daily precipitation data of Gannan 2015-2021 automatic station, regional station, and the 2015-2021 geological disaster data, based on the precipitation data, the second generation display statistical early-warning model of geological hazards in Gannan Prefecture is established to study the possibility of geological hazards induced by dynamic precipitation, it can also provide technical reference for the prevention and control of geological disasters, and reduce the economic losses and casualties caused by sudden geological disasters such as collapse, landslide and debris flow, which are mainly induced by precipitation, is of great significance. Method 1: to quantitatively evaluate the geological background risk of Gannan Prefecture by using information quantity method, taking the effective precipitation before the disaster, the maximum and minimum precipitation on the same day, and the accumulated precipitation on the same day as the independent variables, by fitting different linear equations to different risk areas, the meteorological risk early-warning model of geological hazards in Gannan Prefecture was established. Method 2: take the slope, aspect, relief degree, stratum lithology, fault structure, river system and human engineering activity as evaluation indexes, and use machine learning method, by using BP neural network algorithm program and setting the learning step, the probability quantization value of geological hazard potential degree is obtained, and coupled with precipitation factor, the geological hazard meteorological risk early-warning model of Gannan Prefecture is established.
Abstract:
The 2023 heat and drought event in eastern Hexi Corridor, the worst in 60 years, caused significant economic losses. In order to accurately forecast and mitigate the effects of extreme weather events, based on daily meteorological data at the basic national meteorological stations in the eastern Hexi Corridor and the El Ni?o events records from the National Climate Center from 1961 to 2020, the meteorological drought composite index (MCI) was used to analyze the drought days and the characteristics of the drought process at different scales by the climatic statistics method, and the response of the meteorological drought composite index to El Ni?o was discussed.?The results showed that light drought days were the most frequent in the region, accounting for 62.0% of the total days, the least was extreme drought, accounting for 3.5%. The maximum number of days above moderate?drought was 51.6 days in Gulang and the least was 19.3 days in Minqin. May has the highest number of dry days at 5.1 days, January has the lowest at 2.1 days, April has the highest number of days with moderate drought or above at 2.2 days, and January has the lowest at 0.5 days. The average annual drought process was 1.0 days, the most was 1.3 days in Gulang and the least was 0.7 days in Minqin.The average duration of a drought process was 64.3 days, the longest in Minqin was 78.2 days, and the shortest in Tianzhu was 51.8 days. The drought process intensity was characterized by general drought?accounted for the largest 47.9% and the lowest proportion of extreme drought was 5.2%, Stronger than the drought accounted for the largest 56.7% in Liangzhou and Minqin and the lowest was 47.3% in Gulang. During the continuous period of El Ni?o, the temperature in the area is mainly normal, and the probability of climate anomalies occurring in higher years is higher; Precipitation is mainly low, and climate anomalies are prone to occur in years with high precipitation; The number of dry days is relatively high, with more moderate and above days in the southern mountainous areas, El Ni?o was one of the main causes of severe drought in the study area.
The 2023 heat and drought event in eastern Hexi Corridor, the worst in 60 years, caused significant economic losses. In order to accurately forecast and mitigate the effects of extreme weather events, based on daily meteorological data at the basic national meteorological stations in the eastern Hexi Corridor and the El Ni?o events records from the National Climate Center from 1961 to 2020, the meteorological drought composite index (MCI) was used to analyze the drought days and the characteristics of the drought process at different scales by the climatic statistics method, and the response of the meteorological drought composite index to El Ni?o was discussed.?The results showed that light drought days were the most frequent in the region, accounting for 62.0% of the total days, the least was extreme drought, accounting for 3.5%. The maximum number of days above moderate?drought was 51.6 days in Gulang and the least was 19.3 days in Minqin. May has the highest number of dry days at 5.1 days, January has the lowest at 2.1 days, April has the highest number of days with moderate drought or above at 2.2 days, and January has the lowest at 0.5 days. The average annual drought process was 1.0 days, the most was 1.3 days in Gulang and the least was 0.7 days in Minqin.The average duration of a drought process was 64.3 days, the longest in Minqin was 78.2 days, and the shortest in Tianzhu was 51.8 days. The drought process intensity was characterized by general drought?accounted for the largest 47.9% and the lowest proportion of extreme drought was 5.2%, Stronger than the drought accounted for the largest 56.7% in Liangzhou and Minqin and the lowest was 47.3% in Gulang. During the continuous period of El Ni?o, the temperature in the area is mainly normal, and the probability of climate anomalies occurring in higher years is higher; Precipitation is mainly low, and climate anomalies are prone to occur in years with high precipitation; The number of dry days is relatively high, with more moderate and above days in the southern mountainous areas, El Ni?o was one of the main causes of severe drought in the study area.
Abstract:
Using the conventional sounding data and ground observation data, the key environmental parameters of the summer cold vortex heavy rainfall cases occurring in Shandong province in recent 10 years were analyzed. The results show that: (1) Cold vortex heavy rainfall mainly occurs from June to July in Shandong province, one month later than that in Northeast China. It is mainly distributed in the northwest and central mountainous areas of Shandong, with strong inter-monthly variation. (2) It has the stratification characteristics of high humidity in the low layer, and does not require strong static instability conditions and tends to occur under high PW conditions. The potential prediction of cold vortex heavy rainfall should pay attention to the whole atmospheric precipitable water and low layer high humidity water vapor conditions. (3)The threshold values of the key parameters of ΔT850-500, PW and (T-Td)850 are 22-27 ℃,40-65mm and 1-7 ℃ respectively. The threshold of warm cloud thickness is 3000-4500m, the thicker the better. The thresholds of K index, CAPE and CIN are 30-40 ℃, 1000-2300J ?kg-1 and >-100J?kg-1 respectively. The deep vertical wind shears of most cases are weak to moderate intensity in Shandong province, and the minimum threshold is 6 m?s-1. (4) It is different monthly for the key environmental parameters of cold vortex heavy rainfall in Shandong province summer, and the moderate intensity deep vertical wind shear and a certain degree of weak convection simulation may play more obvious role on it. The above work constitutes the foundation for the forecast of cold vortex heavy rainfall, and provides a reference.
Using the conventional sounding data and ground observation data, the key environmental parameters of the summer cold vortex heavy rainfall cases occurring in Shandong province in recent 10 years were analyzed. The results show that: (1) Cold vortex heavy rainfall mainly occurs from June to July in Shandong province, one month later than that in Northeast China. It is mainly distributed in the northwest and central mountainous areas of Shandong, with strong inter-monthly variation. (2) It has the stratification characteristics of high humidity in the low layer, and does not require strong static instability conditions and tends to occur under high PW conditions. The potential prediction of cold vortex heavy rainfall should pay attention to the whole atmospheric precipitable water and low layer high humidity water vapor conditions. (3)The threshold values of the key parameters of ΔT850-500, PW and (T-Td)850 are 22-27 ℃,40-65mm and 1-7 ℃ respectively. The threshold of warm cloud thickness is 3000-4500m, the thicker the better. The thresholds of K index, CAPE and CIN are 30-40 ℃, 1000-2300J ?kg-1 and >-100J?kg-1 respectively. The deep vertical wind shears of most cases are weak to moderate intensity in Shandong province, and the minimum threshold is 6 m?s-1. (4) It is different monthly for the key environmental parameters of cold vortex heavy rainfall in Shandong province summer, and the moderate intensity deep vertical wind shear and a certain degree of weak convection simulation may play more obvious role on it. The above work constitutes the foundation for the forecast of cold vortex heavy rainfall, and provides a reference.
Abstract:
A regional severe thunderstorm on March 25, 2020 in Guangxi province was investigated based on multi-source observations and reanalysis data. The results are as follows. (1)The severe thunderstorm occurred in a warm area, and the trough at 500hPa and low-level south jet provided favorable conditions for the formation of the thunderstorm. (2)The severe thunderstorm was caused by two bow echoes and a super cell. The first squall line had the characteristics of a low barycenter in warm cloud. The reflectivity gradient of the front of the second squall line was high, and the second squall line had characteristics of front inflow and momentum downward. The super cell led to hail in southeast of Guangxi.(3) The cold advection was superimposed with the warm advection over northern Vietnam, forming a persistent strong unstable zone, where two squall lines were triggered by surface convergence lines. The main mechanism for the development and maintenance of squall lines was the interaction between the cold pool outflow and low-level environmental wind fields.
A regional severe thunderstorm on March 25, 2020 in Guangxi province was investigated based on multi-source observations and reanalysis data. The results are as follows. (1)The severe thunderstorm occurred in a warm area, and the trough at 500hPa and low-level south jet provided favorable conditions for the formation of the thunderstorm. (2)The severe thunderstorm was caused by two bow echoes and a super cell. The first squall line had the characteristics of a low barycenter in warm cloud. The reflectivity gradient of the front of the second squall line was high, and the second squall line had characteristics of front inflow and momentum downward. The super cell led to hail in southeast of Guangxi.(3) The cold advection was superimposed with the warm advection over northern Vietnam, forming a persistent strong unstable zone, where two squall lines were triggered by surface convergence lines. The main mechanism for the development and maintenance of squall lines was the interaction between the cold pool outflow and low-level environmental wind fields.
Display Method:
2014,8(1):32-38
Abstract:
Abstract: This article applies ECMWF refined net numerical forecast data(0.25白0.25? from NMC in September 2011 ,the data of AWOS ,wind profiler data as well as regular data to southeast gale forecasting and diagnostic analyzing in Urumqi southern suburbs in spring, in order to reveal the occurrence and the maintaining of southeast gale, so we can understand the meaning of the ECMWF refined net numerical forecast data for southeast gale forecasting and raise accuracy rate of southeast gale forecasting. The analysis indicates: southeast gale in Urumqi southern suburbs to Dabancheng is caused by Mongolian high pressure moving southward. The refluent gale forms from the east-west pressure gradient, terrain of Urumqi with narrow tube direction, also decline in the slow slope gravity together. The 850hPa wind, 10-meter wind, sea level pressure, 2-meter temperature etc are very useful for southeast gale forecasting in the start and end of gale, wind scale and falling area. ECMWF refined net numerical forecast data make up the spatial and temporal distribution, that let the forecasters understand the occurrence and the development of the weather system more clearer. It is also helpful in predicting the generation, development and dissipation of southeast gale and could reduce the damage caused by the southeast gale event.
Abstract: This article applies ECMWF refined net numerical forecast data(0.25白0.25? from NMC in September 2011 ,the data of AWOS ,wind profiler data as well as regular data to southeast gale forecasting and diagnostic analyzing in Urumqi southern suburbs in spring, in order to reveal the occurrence and the maintaining of southeast gale, so we can understand the meaning of the ECMWF refined net numerical forecast data for southeast gale forecasting and raise accuracy rate of southeast gale forecasting. The analysis indicates: southeast gale in Urumqi southern suburbs to Dabancheng is caused by Mongolian high pressure moving southward. The refluent gale forms from the east-west pressure gradient, terrain of Urumqi with narrow tube direction, also decline in the slow slope gravity together. The 850hPa wind, 10-meter wind, sea level pressure, 2-meter temperature etc are very useful for southeast gale forecasting in the start and end of gale, wind scale and falling area. ECMWF refined net numerical forecast data make up the spatial and temporal distribution, that let the forecasters understand the occurrence and the development of the weather system more clearer. It is also helpful in predicting the generation, development and dissipation of southeast gale and could reduce the damage caused by the southeast gale event.
2013,7(5):1-6
Abstract:
Using the NCEP 1°×1° reanalysis data, a snowstorm in northern Xinjiang from March 19 to 20 in 2009 was analyzed, and the application of wet potential vorticity was discussed specially. The results showed that there are 3 vapor source of snowstorm, and there are obvious relationship between negative divergence in lower layers, northward inclined vorticity distribution present a up negative and down positive appearance, equivalent potential temperature rise steeply intensive belt, rise velocity area and the falling area of snowstorm. This snowstorm occurred in a area of MPV1 positive and amplify distinctly, and absolute value mushroom and isoline intensive area of MPV2. MPV1 amplify down and atmosphere convective instability energy release. Absolute value of MPV2 at low level magnify and atmosphere wet baroclinicity enhance. It is a important reason that the development of down-sliding slantwise vorticity for the snowstorm formation.
Using the NCEP 1°×1° reanalysis data, a snowstorm in northern Xinjiang from March 19 to 20 in 2009 was analyzed, and the application of wet potential vorticity was discussed specially. The results showed that there are 3 vapor source of snowstorm, and there are obvious relationship between negative divergence in lower layers, northward inclined vorticity distribution present a up negative and down positive appearance, equivalent potential temperature rise steeply intensive belt, rise velocity area and the falling area of snowstorm. This snowstorm occurred in a area of MPV1 positive and amplify distinctly, and absolute value mushroom and isoline intensive area of MPV2. MPV1 amplify down and atmosphere convective instability energy release. Absolute value of MPV2 at low level magnify and atmosphere wet baroclinicity enhance. It is a important reason that the development of down-sliding slantwise vorticity for the snowstorm formation.
2014,8(4):18-25
Abstract:
By using GFS 0.5 ° x 0.5 ° reanalysis data, satellite data and Doppler radar, the torrential rain in Hong An on July 12th 2012 is analyzed, results show the complex terrain of the Dabie Mountain has significant effects on the increase of precipitation. “Influence of topographic on flow theory” provides a good explanation of the precipitation distribution. The southwest current is forced to lift by the special terrain in Hong An, and the continuously generation of "finger clouds" in the windward slope of the Dabie Mountain which promotes the backward transmission system effectively, extends the period of the heavy rain. The variation of radar radial velocity field shows that the cold and warm air channel between the Dabie Mountain and Tongpai Mountain plays an important role in the formation and development of the mesoscale system. By analyzing the radar echo characteristics, we find that the vertical stretching thickness and vertically integrated liquid water of the echo which is greater than 45 DBZ under 0 ℃ layer, has very good consistency with rainfall intensity.
By using GFS 0.5 ° x 0.5 ° reanalysis data, satellite data and Doppler radar, the torrential rain in Hong An on July 12th 2012 is analyzed, results show the complex terrain of the Dabie Mountain has significant effects on the increase of precipitation. “Influence of topographic on flow theory” provides a good explanation of the precipitation distribution. The southwest current is forced to lift by the special terrain in Hong An, and the continuously generation of "finger clouds" in the windward slope of the Dabie Mountain which promotes the backward transmission system effectively, extends the period of the heavy rain. The variation of radar radial velocity field shows that the cold and warm air channel between the Dabie Mountain and Tongpai Mountain plays an important role in the formation and development of the mesoscale system. By analyzing the radar echo characteristics, we find that the vertical stretching thickness and vertically integrated liquid water of the echo which is greater than 45 DBZ under 0 ℃ layer, has very good consistency with rainfall intensity.
2014,8(3):42-47
Abstract:
Using the wind data supplied by Wind Profiler Radar products of Urumqi, hourly rainfall data and NECP/NCAR reanalysis data, the heavy rainfall process in Urumqi from 15:00 on 19th May to 4:00 on 20th May are thoro-uhly analyzed. The results indicate that the strong vertical ascending motion produced by the coordination betwe- en the upper-level jet stream and the low-level convergence zone triggered this heavy rainfall. The northwest jet st-ream quickly passed down 2 hours before the heavy rainfall,causing the enhancement of the low -level northwest jet stream, which is corresponding to the heavy rainfall,especially below 1500m. Low-level vertical ascending speed 2m/s ca-n be used as rainfall threshold. The rain would be heavier as the low-level vertical velocity became larger. During heavy rainfall phase the whole layer of atmospheric refractive index structure constant(RISC) value detection is between -128~-120dB, which shows that water vapor is abundant. The wind profiler radar products (vertical velocity, refractive index structure constant) reflect the beginning and end and strength of the precipitation clearly, provide reference for the refine forecast.
Using the wind data supplied by Wind Profiler Radar products of Urumqi, hourly rainfall data and NECP/NCAR reanalysis data, the heavy rainfall process in Urumqi from 15:00 on 19th May to 4:00 on 20th May are thoro-uhly analyzed. The results indicate that the strong vertical ascending motion produced by the coordination betwe- en the upper-level jet stream and the low-level convergence zone triggered this heavy rainfall. The northwest jet st-ream quickly passed down 2 hours before the heavy rainfall,causing the enhancement of the low -level northwest jet stream, which is corresponding to the heavy rainfall,especially below 1500m. Low-level vertical ascending speed 2m/s ca-n be used as rainfall threshold. The rain would be heavier as the low-level vertical velocity became larger. During heavy rainfall phase the whole layer of atmospheric refractive index structure constant(RISC) value detection is between -128~-120dB, which shows that water vapor is abundant. The wind profiler radar products (vertical velocity, refractive index structure constant) reflect the beginning and end and strength of the precipitation clearly, provide reference for the refine forecast.
2014,8(1):0-0
Abstract:
Abstract: Applying the conventional meteorological observation data, the FY-2D meteorological satellite data, radar data to analyze the strong precipitation weather occurred in Weihe basin of Shaanxi province on July 28 to 29 , 2011. The results show that subtropical high strengthening northward, plateau low trough move to eastward, the merging of the edge of moist airflow of subtropical high and the plateau trough southwest airflow to provide favorable conditions for the rainstorms; The low level shear line, vortex and low-level jet were the main influencing system of rainstorm; Satellite image in low trough clouds have rainstorm cloud characteristics; Radar reflectivity factor strong echo and liquid-water content value are always corresponding with the strong precipitation.
Abstract: Applying the conventional meteorological observation data, the FY-2D meteorological satellite data, radar data to analyze the strong precipitation weather occurred in Weihe basin of Shaanxi province on July 28 to 29 , 2011. The results show that subtropical high strengthening northward, plateau low trough move to eastward, the merging of the edge of moist airflow of subtropical high and the plateau trough southwest airflow to provide favorable conditions for the rainstorms; The low level shear line, vortex and low-level jet were the main influencing system of rainstorm; Satellite image in low trough clouds have rainstorm cloud characteristics; Radar reflectivity factor strong echo and liquid-water content value are always corresponding with the strong precipitation.
2020,14(4):27-34
,DOI: 10.12057/j.issn.1002-0799.2020.04.004
Abstract:
Based on the compilation data of temperature and precipitation in Xinjiang during 1976-2017, the trend tendency was estimated by linear regression, and the average annual change rate and trend of climate elements were reflected by least square method. The results showed that: the annual and seasonal average temperatures in Xinjiang, northern Xinjiang, Tianshan Mountains and southern Xinjiang showed a consistent upward trend. The average annual warming rate in Xinjiang was 0.31 C/10a, and there has been a significant warming since the late 1990s. The warming trend was most pronounced in winter and weakest in summer. The annual and seasonal precipitation in all districts showed a consistent increasing trend, and the annual precipitation in Xinjiang increased at a rate of 10.14 mm/10a. Since the 2010s, it has increased by 30% over the 1960s. The trend of increasing precipitation in winter was the most obvious. From 1961 to 2017, climate change in Xinjiang was more obvious, and the overall change was in the direction of warm and humid.
Based on the compilation data of temperature and precipitation in Xinjiang during 1976-2017, the trend tendency was estimated by linear regression, and the average annual change rate and trend of climate elements were reflected by least square method. The results showed that: the annual and seasonal average temperatures in Xinjiang, northern Xinjiang, Tianshan Mountains and southern Xinjiang showed a consistent upward trend. The average annual warming rate in Xinjiang was 0.31 C/10a, and there has been a significant warming since the late 1990s. The warming trend was most pronounced in winter and weakest in summer. The annual and seasonal precipitation in all districts showed a consistent increasing trend, and the annual precipitation in Xinjiang increased at a rate of 10.14 mm/10a. Since the 2010s, it has increased by 30% over the 1960s. The trend of increasing precipitation in winter was the most obvious. From 1961 to 2017, climate change in Xinjiang was more obvious, and the overall change was in the direction of warm and humid.
2018,12(6):84-92
,DOI: 10.12057/j.issn.1002-0799.2018.06.011
Abstract:
Due to the shortage of traditional fossil energy and increasingly serious environmental pollution, green energy has become the development direction. Wind energy is a kind of clean and renewable energy, and the proportion of wind power generation in the national energy structure is enhancing increasingly. However, as the intermittent and volatility of wind power generation bring more and more serious impact on the power grid, the real-time power dispatch becomes particularly important. Related research works on ultra-short-term wind speed forecasting have drawn extensive attention. Firstly, the related domestic and international wind speed forecasting researches are comprehensively analyzed. Secondly, the research status of ultra-short-term wind speed forecasting methods are summarized from three aspects: physical methods, statistical and machine learning methods,and combination methods. Thirdly, the advantages and disadvantages of the main forecasting methods are compared.In addition, the uncertainty analysis and the error evaluation metrics are provided. Finally,the issues and directions that should be mainly addressed in the research of ultra-short-term wind speed forecasting are discussed.
Due to the shortage of traditional fossil energy and increasingly serious environmental pollution, green energy has become the development direction. Wind energy is a kind of clean and renewable energy, and the proportion of wind power generation in the national energy structure is enhancing increasingly. However, as the intermittent and volatility of wind power generation bring more and more serious impact on the power grid, the real-time power dispatch becomes particularly important. Related research works on ultra-short-term wind speed forecasting have drawn extensive attention. Firstly, the related domestic and international wind speed forecasting researches are comprehensively analyzed. Secondly, the research status of ultra-short-term wind speed forecasting methods are summarized from three aspects: physical methods, statistical and machine learning methods,and combination methods. Thirdly, the advantages and disadvantages of the main forecasting methods are compared.In addition, the uncertainty analysis and the error evaluation metrics are provided. Finally,the issues and directions that should be mainly addressed in the research of ultra-short-term wind speed forecasting are discussed.
2018,12(6):16-21
,DOI: 10.12057/j.issn.1002-0799.2018.06.003
Abstract:
The study of solar radiation include its characteristic and variation, is of great significance to explore regional ecology system formation and evolution. The Taklimakan Desert, the largest mobile desert in China, is located in the center of the Tarim Basin. The oasis study in this desert is important to understand ecosystem process in arid land. However, for traffic problem, the desert"s meteorology datum, especially solar radiation data (long period), are very scare, which brings difficult in related oasis ecosystem process further discuss. In this work, the Daliyaboyi, the largest isolated pristine oasis in the Taklimakan desert hinterland, was taken as a case study to simulate the solar radiation. The daily total solar radiation of the Daliyaboyi oasis cumulants in 2015 were simulated based on the H.L.Penman"s method Q=S0(a+bs). Using this formula, the simulated datum Q in the natural oasis had been derived, and then compared with observed datum to calculate the bias and absolute errors. The result shows that we selected method of climatological empirical formula successfully estimate the annual variation trend of the total radiation. Even though, there exist a slightly but relatively larger bias between simulated and measured results in calculating the solar radiation in spring. This is because the Taklimakan Desert"s sandstorm activities are more frequent in spring, which weakens radiation intensity of the sun reach the ground. Through our calculations, the relative error of simulated values was 0.77 %. The mean bias error, the mean absolute bias error and the root square error were -0.11,2.97,3.89 MJ·m-2·d-1 respectively. And the mean absolute percentage error was 21.02%. These show that the parameters of the empirical formula need to be further modified before simulating the solar radiation when applied to area around the Taklimakan desert hinter land .
The study of solar radiation include its characteristic and variation, is of great significance to explore regional ecology system formation and evolution. The Taklimakan Desert, the largest mobile desert in China, is located in the center of the Tarim Basin. The oasis study in this desert is important to understand ecosystem process in arid land. However, for traffic problem, the desert"s meteorology datum, especially solar radiation data (long period), are very scare, which brings difficult in related oasis ecosystem process further discuss. In this work, the Daliyaboyi, the largest isolated pristine oasis in the Taklimakan desert hinterland, was taken as a case study to simulate the solar radiation. The daily total solar radiation of the Daliyaboyi oasis cumulants in 2015 were simulated based on the H.L.Penman"s method Q=S0(a+bs). Using this formula, the simulated datum Q in the natural oasis had been derived, and then compared with observed datum to calculate the bias and absolute errors. The result shows that we selected method of climatological empirical formula successfully estimate the annual variation trend of the total radiation. Even though, there exist a slightly but relatively larger bias between simulated and measured results in calculating the solar radiation in spring. This is because the Taklimakan Desert"s sandstorm activities are more frequent in spring, which weakens radiation intensity of the sun reach the ground. Through our calculations, the relative error of simulated values was 0.77 %. The mean bias error, the mean absolute bias error and the root square error were -0.11,2.97,3.89 MJ·m-2·d-1 respectively. And the mean absolute percentage error was 21.02%. These show that the parameters of the empirical formula need to be further modified before simulating the solar radiation when applied to area around the Taklimakan desert hinter land .
2018,12(6):32-39
,DOI: 10.12057/j.issn.1002-0799.2018.06.005
Abstract:
Selection of xinjiang in the wind area 51495 old site (QiJiaoJing national basic weather stations) in 1956-1998 and the new site (13 rooms national basic weather stations) in 1999-2016 monthly wind days, average wind speed and wind direction data, this paper compares and analyzes the methods of linear regression, correlation analysis in analysis of wind, season, month change characteristics and trends. The results showed that: 51495 had a significant fluctuation trend in the high wind days in the preceding years, with a tendency rate of 6.74 d·(10a) -1, with the most obvious summer increase. The annual mean wind speed decreased slightly, with the trend rate of -0.01 m·s-1·(10a) -1, the most significant decline in autumn; The dominant wind direction of the year is the calm wind and the north wind (N). In the following years, the number of wind days in the relocating station was significantly decreased, and the decline rate was -6.72 d·(10a) -1, which was the most obvious in spring. The annual average wind speed decreases the trend of the moving station, and the trend rate is -0.31 m·s-1·(10a) -1, except for the other three seasons in winter. The dominant wind direction of the seasons is basically the same with the north wind (N, NNW, NNE).
Selection of xinjiang in the wind area 51495 old site (QiJiaoJing national basic weather stations) in 1956-1998 and the new site (13 rooms national basic weather stations) in 1999-2016 monthly wind days, average wind speed and wind direction data, this paper compares and analyzes the methods of linear regression, correlation analysis in analysis of wind, season, month change characteristics and trends. The results showed that: 51495 had a significant fluctuation trend in the high wind days in the preceding years, with a tendency rate of 6.74 d·(10a) -1, with the most obvious summer increase. The annual mean wind speed decreased slightly, with the trend rate of -0.01 m·s-1·(10a) -1, the most significant decline in autumn; The dominant wind direction of the year is the calm wind and the north wind (N). In the following years, the number of wind days in the relocating station was significantly decreased, and the decline rate was -6.72 d·(10a) -1, which was the most obvious in spring. The annual average wind speed decreases the trend of the moving station, and the trend rate is -0.31 m·s-1·(10a) -1, except for the other three seasons in winter. The dominant wind direction of the seasons is basically the same with the north wind (N, NNW, NNE).
2018,12(6):58-67
,DOI: 10.12057/j.issn.1002-0799.2018.06.008
Abstract:
In order to study the optimal parameterization scheme of the land surface model Noah-MP in the desert underlying surface, this paper set up three sets of simulation experiments combining different parameterization schemes according to the characteristics of the desert environment, which based on the observation data over the Taklimakan Desert Atmospheric Environment Monitoring Station (TDAEMS), and then get the best combination. The results show that the 3rd group was the best simulation effect on soil temperature of 10 cm. The main reason is that the Chen97 sensible heat exchange coefficient and the entire grid cell two-stream approximation (gap=0) radiation transfer scheme are in line with the environmental characteristics of the TDAEMS. The three groups of experiments have poor performance soil moisture simulation . The main reason is that the surface environment and soil information of TDAEMS are not reflected in the model. The second group chooses CLM scheme to have some considerations on the influence of soil type evaporation, and has a better correlation. As for the sensible heat flux, the 1st and 2nd sets of simulation values are overestimated at the peak, especially the second set of simulated values are significantly underestimated after precipitation, and the 3rd set of simulations is the best, mainly due to the choice of sense. The heat exchange coefficient Chen97 scheme could describe the Ch variation characteristics more realistically. The latent heat flux has the worst simulation effect among the four characteristic variables. The main reason is that the desert soil moisture is extremely low. There is a bias between the observed precipitation and the actual amount of water entering the soil. In addition, there is no vegetation and plant roots. The model cannot accurately calculate soil evaporation and vegetation evapotranspiration. Therefore, the calculation of latent heat flux in the desert area is not ideal. Based on the comprehensive statistical analysis and the Taylor diagram, the third set of simulations has the best performance and can better restore the land surface process in the desert area.
In order to study the optimal parameterization scheme of the land surface model Noah-MP in the desert underlying surface, this paper set up three sets of simulation experiments combining different parameterization schemes according to the characteristics of the desert environment, which based on the observation data over the Taklimakan Desert Atmospheric Environment Monitoring Station (TDAEMS), and then get the best combination. The results show that the 3rd group was the best simulation effect on soil temperature of 10 cm. The main reason is that the Chen97 sensible heat exchange coefficient and the entire grid cell two-stream approximation (gap=0) radiation transfer scheme are in line with the environmental characteristics of the TDAEMS. The three groups of experiments have poor performance soil moisture simulation . The main reason is that the surface environment and soil information of TDAEMS are not reflected in the model. The second group chooses CLM scheme to have some considerations on the influence of soil type evaporation, and has a better correlation. As for the sensible heat flux, the 1st and 2nd sets of simulation values are overestimated at the peak, especially the second set of simulated values are significantly underestimated after precipitation, and the 3rd set of simulations is the best, mainly due to the choice of sense. The heat exchange coefficient Chen97 scheme could describe the Ch variation characteristics more realistically. The latent heat flux has the worst simulation effect among the four characteristic variables. The main reason is that the desert soil moisture is extremely low. There is a bias between the observed precipitation and the actual amount of water entering the soil. In addition, there is no vegetation and plant roots. The model cannot accurately calculate soil evaporation and vegetation evapotranspiration. Therefore, the calculation of latent heat flux in the desert area is not ideal. Based on the comprehensive statistical analysis and the Taylor diagram, the third set of simulations has the best performance and can better restore the land surface process in the desert area.
2014,8(3):48-55
Abstract:
Based on the conventional observation data, automatic weather station and T639 forecast products，in terms of the synoptic principle and dynamic diagnosis，the causation of cold wave and the character of snow during 20-23 December 2012 has been analyzed。 The results are as follows：The cold wave occurred when the North European backup ridge broken up southeastwards， leading transverse trough to erect trough which moved southeastwards。Sharp edge of high temperature was about 4０癗 which brought the strong decline of temperature and snowfall。The influencing system during snowing was the shear line between cold air mass and warm air mass as well as the mesoscale wind convergence。Water vapor was derived from northwestwards which radial moved and southeastwards which latitudinal moved。There was distinct local character tail condensation snowing and overcast and snowy moment which water vapor derived from the local vertical moving。The results showed that the saturation of moisture conditions in boundary layer were very important for winter snowfall .
Based on the conventional observation data, automatic weather station and T639 forecast products，in terms of the synoptic principle and dynamic diagnosis，the causation of cold wave and the character of snow during 20-23 December 2012 has been analyzed。 The results are as follows：The cold wave occurred when the North European backup ridge broken up southeastwards， leading transverse trough to erect trough which moved southeastwards。Sharp edge of high temperature was about 4０癗 which brought the strong decline of temperature and snowfall。The influencing system during snowing was the shear line between cold air mass and warm air mass as well as the mesoscale wind convergence。Water vapor was derived from northwestwards which radial moved and southeastwards which latitudinal moved。There was distinct local character tail condensation snowing and overcast and snowy moment which water vapor derived from the local vertical moving。The results showed that the saturation of moisture conditions in boundary layer were very important for winter snowfall .
2018,12(6):1-7
,DOI: 10.12057/j.issn.1002-0799.2018.06.001
Abstract:
本文利用天山北坡中段呼图壁河流域石门水文站1956~2011年径流量数据，以及2013年9月至2014年10月逐月呼图壁河水和地下水的δD和δ18O数据，研究了呼图壁河流域地表径流变化，并结合同位素和水化学方法探讨了河水和地下水之间的转化关系。结果表明，近55年呼图壁河流域地表径流量有明显增加趋势，在90年代之后增加了13.36%，而地下水位呈持续下降趋势。流域河水和地下水水化学特征差异显著，河水受岩石风化作用控制，而地下水受蒸发-结晶沉降作用控制。呼图壁河河水和地下水出现了两次转化关系，上游地区地下水对河水的补给占到18.45%，而中下游区域地下水的补给占到92.31%。
本文利用天山北坡中段呼图壁河流域石门水文站1956~2011年径流量数据，以及2013年9月至2014年10月逐月呼图壁河水和地下水的δD和δ18O数据，研究了呼图壁河流域地表径流变化，并结合同位素和水化学方法探讨了河水和地下水之间的转化关系。结果表明，近55年呼图壁河流域地表径流量有明显增加趋势，在90年代之后增加了13.36%，而地下水位呈持续下降趋势。流域河水和地下水水化学特征差异显著，河水受岩石风化作用控制，而地下水受蒸发-结晶沉降作用控制。呼图壁河河水和地下水出现了两次转化关系，上游地区地下水对河水的补给占到18.45%，而中下游区域地下水的补给占到92.31%。
2018,12(6):8-15
,DOI: 10.12057/j.issn.1002-0799.2018.06.002
Abstract:
Based on the NCEP 1°×1°reanalysis data, the characteristics of the weather scale circulation , dynamic and water vapor transmission of the two cases of Tashkent vortex weather processes were contrasted and analyzed. The results showed that: during South Asia High center located at 70°E, the south Xinjiang Basin was in the left ahead of the 200 hPa jet export zone ,the maintenance of 500 hPa strong southwest airflow and significant easterly jet stream in the southern xinjiang basin of 700hPa maked sure that the middle and low level shear line and convergence maintained. At the same time, the water vapor in the Arabian sea transmitted by relay transmission strongly converged with the water vapor carried by the middle and lower easterly jet stream, resulting in large-scale rainstorm. The downward extension of the negative hygroscopic tongue in the upper layer and the increase of the baroclinic pressure in the lower and middle atmosphere maked convective precipitation more intense. But as the center of South Asia High maintained over 90 °E ,200hPa jet over southern Xinjiang ,the lower vortices are reduced into slots to enter the southern border. Over south Xinjiang Basin , if the easterly airflow of 700 hPa was weaker and located further west ,and high level divergence and low level convergence were weaker, it is not conducive to the development of vertical upward movement and the convergence of water vapor. As a result, it was difficult to caused precipitation, even though the influencing system was a Tashkent vortex.
Based on the NCEP 1°×1°reanalysis data, the characteristics of the weather scale circulation , dynamic and water vapor transmission of the two cases of Tashkent vortex weather processes were contrasted and analyzed. The results showed that: during South Asia High center located at 70°E, the south Xinjiang Basin was in the left ahead of the 200 hPa jet export zone ,the maintenance of 500 hPa strong southwest airflow and significant easterly jet stream in the southern xinjiang basin of 700hPa maked sure that the middle and low level shear line and convergence maintained. At the same time, the water vapor in the Arabian sea transmitted by relay transmission strongly converged with the water vapor carried by the middle and lower easterly jet stream, resulting in large-scale rainstorm. The downward extension of the negative hygroscopic tongue in the upper layer and the increase of the baroclinic pressure in the lower and middle atmosphere maked convective precipitation more intense. But as the center of South Asia High maintained over 90 °E ,200hPa jet over southern Xinjiang ,the lower vortices are reduced into slots to enter the southern border. Over south Xinjiang Basin , if the easterly airflow of 700 hPa was weaker and located further west ,and high level divergence and low level convergence were weaker, it is not conducive to the development of vertical upward movement and the convergence of water vapor. As a result, it was difficult to caused precipitation, even though the influencing system was a Tashkent vortex.
2018,12(6):40-48
,DOI: 10.12057/j.issn.1002-0799.2018.06.006
Abstract:
The Tianshan Mountain quasi-stationary front, which forms due to the effect of the steep terrain, influences the variation of temperature and precipitation on the two sides of the mountain, playing an important role in the severe weather processes over the region of central Asia. Affected by such quasi-stationary front, a severe cold weather process took place in Xinjiang on 22 April 2014, during which strong wind and temperature decline occurred in the northern Xinjiang while strong sand-dust storm appeared in southern Xinjiang. Adopting conventional observation and NCEP 1o×1o reanalysis data, this paper analyzes the 500 hPa synoptic situation and surface pressure field during this cold wave frontal process, calculates the cold and warm advections, temperature gradient and front genesis function which are closed related to the frontal surface, and also analyzes the 3-dimensional structure and evolution characteristics of three physical quantities on the horizontal plane chart and vertical cross-section in the northwest-southeast direction. The results suggest that, before the formation of the Tianshan Mountain quasi-stationary front, the 500 hPa European ridge developed quickly northward affected by warm advection while the West Siberian trough strengthened and moved southward under the influence of cold advection. Thus, the frontal cyclone over central Asia developed vigorously and the surface cold front met with the Tianshan Mountain that is high and steep with average altitude of 3000 m, causing the temperature gradient to increase, strong front genesis to break out and strong quasi-stationary front to form in the northern part of Tianshan Mountain. This frontal surface assumes the isotherms that distribute densely on the horizontal plane chart of mid-low troposphere, which means the temperature gradient is very large. Meanwhile, front genesis is seen in the Tianshan Mountains on the vertical cross-section where θ becomes vertical, and temperature gradient increases, but the width decreases.
The Tianshan Mountain quasi-stationary front, which forms due to the effect of the steep terrain, influences the variation of temperature and precipitation on the two sides of the mountain, playing an important role in the severe weather processes over the region of central Asia. Affected by such quasi-stationary front, a severe cold weather process took place in Xinjiang on 22 April 2014, during which strong wind and temperature decline occurred in the northern Xinjiang while strong sand-dust storm appeared in southern Xinjiang. Adopting conventional observation and NCEP 1o×1o reanalysis data, this paper analyzes the 500 hPa synoptic situation and surface pressure field during this cold wave frontal process, calculates the cold and warm advections, temperature gradient and front genesis function which are closed related to the frontal surface, and also analyzes the 3-dimensional structure and evolution characteristics of three physical quantities on the horizontal plane chart and vertical cross-section in the northwest-southeast direction. The results suggest that, before the formation of the Tianshan Mountain quasi-stationary front, the 500 hPa European ridge developed quickly northward affected by warm advection while the West Siberian trough strengthened and moved southward under the influence of cold advection. Thus, the frontal cyclone over central Asia developed vigorously and the surface cold front met with the Tianshan Mountain that is high and steep with average altitude of 3000 m, causing the temperature gradient to increase, strong front genesis to break out and strong quasi-stationary front to form in the northern part of Tianshan Mountain. This frontal surface assumes the isotherms that distribute densely on the horizontal plane chart of mid-low troposphere, which means the temperature gradient is very large. Meanwhile, front genesis is seen in the Tianshan Mountains on the vertical cross-section where θ becomes vertical, and temperature gradient increases, but the width decreases.
2018,12(6):49-57
,DOI: 10.12057/j.issn.1002-0799.2018.06.007
Abstract:
The forecast performance of DOGRAFS v1.0 in 2017 is objectively verified seasonally by MET. The results show that: (1) The daytime temperature is underestimated overall while the nighttime temperature at most of the sites is overestimated. The forecasted 2 m temperature is overvalued in winter and undervalued in the other three seasons as a whole. The predicted 10 m wind speed in 2017 is always higher than the corresponding observation with the maximum root mean square error in winter and followed by spring. (2) The modeled high-altitude temperature is generally colder than the observed value. It is worst simulated in winter and well predicted in summer and autumn with the RMSE less than 3 degrees centigrade. The predicted error of high-altitude geopotential height increases with the height increasing, and the RMSE is about 6.5 ~ 12.0 gpm. Furthermore, the forecasted geopotential height is lower than the actual height. The error of high-altitude U, V wind increase firstly then decrease with the height increasing in different seasons. The RMSE of high-altitude U, V wind are 2.4 ~ 6.2 m/s and 1.8 ~ 5.2 m/s respectively. The U component of wind speed is underestimated while the V component of wind speed is overestimated. (3) The missed event ratio of heavy rainfall in winter is high while the false alarm ratio of high threshold precipitation is high in autumn. In Xinjiang, the false alarm sites are more than the missed event sites from 14 to 20 BJT and 20 to 2 BJT. The false alarm ratio from 14 to 20 BJT is the highest and the missed event ratio from 02 to 08 BJT is the highest. The Ts score during daytime is higher than at night.
The forecast performance of DOGRAFS v1.0 in 2017 is objectively verified seasonally by MET. The results show that: (1) The daytime temperature is underestimated overall while the nighttime temperature at most of the sites is overestimated. The forecasted 2 m temperature is overvalued in winter and undervalued in the other three seasons as a whole. The predicted 10 m wind speed in 2017 is always higher than the corresponding observation with the maximum root mean square error in winter and followed by spring. (2) The modeled high-altitude temperature is generally colder than the observed value. It is worst simulated in winter and well predicted in summer and autumn with the RMSE less than 3 degrees centigrade. The predicted error of high-altitude geopotential height increases with the height increasing, and the RMSE is about 6.5 ~ 12.0 gpm. Furthermore, the forecasted geopotential height is lower than the actual height. The error of high-altitude U, V wind increase firstly then decrease with the height increasing in different seasons. The RMSE of high-altitude U, V wind are 2.4 ~ 6.2 m/s and 1.8 ~ 5.2 m/s respectively. The U component of wind speed is underestimated while the V component of wind speed is overestimated. (3) The missed event ratio of heavy rainfall in winter is high while the false alarm ratio of high threshold precipitation is high in autumn. In Xinjiang, the false alarm sites are more than the missed event sites from 14 to 20 BJT and 20 to 2 BJT. The false alarm ratio from 14 to 20 BJT is the highest and the missed event ratio from 02 to 08 BJT is the highest. The Ts score during daytime is higher than at night.
2018,12(6):77-83
,DOI: 10.12057/j.issn.1002-0799.2018.06.010
Abstract:
The pollution of O3 in Chengde was analyzed based on the Chengde Environmental Monitoring Station’s and Weather Station’s data from 2014 to 2016, the conclusions are as follows: The proportion of O3 pollution days has increased year by year. Monthly average concentration of O3 8h presents high in summer and low in winter, the monthly average temperature is consistent with O3 changing trend, NO2 and CO show opposite trends, expressed as high in winter and low in summer. The diurnal variation of O3 concentration in Chengde was a single peak type distribution, O3 concentration increased in the afternoon and decreased in the night, consistent with the daily temperature changes, NO2 presents the opposite trend, the CO has a three-peak distribution and the overall performance is highest at noon. O3 8h, NO2, CO and air temperature all show a spatial distribution of north lower and south high in Chengde region. O3 8h concentration negatively correlated with NO2 and CO showed a significant.
The pollution of O3 in Chengde was analyzed based on the Chengde Environmental Monitoring Station’s and Weather Station’s data from 2014 to 2016, the conclusions are as follows: The proportion of O3 pollution days has increased year by year. Monthly average concentration of O3 8h presents high in summer and low in winter, the monthly average temperature is consistent with O3 changing trend, NO2 and CO show opposite trends, expressed as high in winter and low in summer. The diurnal variation of O3 concentration in Chengde was a single peak type distribution, O3 concentration increased in the afternoon and decreased in the night, consistent with the daily temperature changes, NO2 presents the opposite trend, the CO has a three-peak distribution and the overall performance is highest at noon. O3 8h, NO2, CO and air temperature all show a spatial distribution of north lower and south high in Chengde region. O3 8h concentration negatively correlated with NO2 and CO showed a significant.
2018,12(6):22-31
,DOI: 10.12057/j.issn.1002-0799.2018.06.004
Abstract:
Based on the daily minimum temperature of 50 weather stations in Tarim basin of Southern Xinjiang during 1971-2016,,The temporal-spatial frequency distribution of the cold air process in single station and the whole area were analyzed by means of synthesis,linear propensity estimation,Morlet wavelet,Mann-kendall and Moving average and Cumulative anomaly according to "Cold Air Grate Standards"(GB/T20484-2006).The results showed that: (1) the cold air process which grade is medium and above was mostly distributed in the western plateau the basin,the northern mountainous area and the eastern windy area.the cold air process of each grade in single station showed a linear decrease trend and not obvious in the most stations,the cold air and cold wave process decreased significantly in the whole Tarim basin which the decreasing rates were 0.19 times/10a.however,the remaining grade have a little change.(2)The occurrence of cold air process was 103.2 times a year in the area,among them the weak and medium process occupied for 86.3 and 10.4times,which amount to 83.6% and 10.1% respectively.the grade above strong cold air was totally 7.0 times,accounted for 6.8% of the total number.(3) The frequency percent of each cold air grade with 1 ~ 3d was 87.4 ~ 95.4%,weak cold air with 1d duration and other process grade with 2d duration has the highest frequency.The frequency with 3d or above decreased significantly with the increase of duration.(4) The interdecadal frequency of different cold air process grades has little change.In 1970s,the stronger,strong cold air and cold wave frequency was 2.8,2.4 and 2.9 times respectively.In 1980s,the weak cold air reached 86.6 times.In the nearly 6a (2011-2016) had the most moderate cold air,up to 10.8 times.(5) The occurrence of cold air in different grades has a strong seasonality.The frequency of medium and strong cold air grades was the highest in summer,accounting for 30.1% and 57.9% respectively.In spring strong cold air was the highest,accounting for 40.1%,and the cold wave was the highest in winter,accounting for 38.9%.(6) The cold air in all grades has 8 to 10a interannual period that was not consistent,but the cold wave dramatically decreased obviously in 1979. Keywords: Cold air process; frequcency; trend; period ; sudden change;Tarim basin
Based on the daily minimum temperature of 50 weather stations in Tarim basin of Southern Xinjiang during 1971-2016,,The temporal-spatial frequency distribution of the cold air process in single station and the whole area were analyzed by means of synthesis,linear propensity estimation,Morlet wavelet,Mann-kendall and Moving average and Cumulative anomaly according to "Cold Air Grate Standards"(GB/T20484-2006).The results showed that: (1) the cold air process which grade is medium and above was mostly distributed in the western plateau the basin,the northern mountainous area and the eastern windy area.the cold air process of each grade in single station showed a linear decrease trend and not obvious in the most stations,the cold air and cold wave process decreased significantly in the whole Tarim basin which the decreasing rates were 0.19 times/10a.however,the remaining grade have a little change.(2)The occurrence of cold air process was 103.2 times a year in the area,among them the weak and medium process occupied for 86.3 and 10.4times,which amount to 83.6% and 10.1% respectively.the grade above strong cold air was totally 7.0 times,accounted for 6.8% of the total number.(3) The frequency percent of each cold air grade with 1 ~ 3d was 87.4 ~ 95.4%,weak cold air with 1d duration and other process grade with 2d duration has the highest frequency.The frequency with 3d or above decreased significantly with the increase of duration.(4) The interdecadal frequency of different cold air process grades has little change.In 1970s,the stronger,strong cold air and cold wave frequency was 2.8,2.4 and 2.9 times respectively.In 1980s,the weak cold air reached 86.6 times.In the nearly 6a (2011-2016) had the most moderate cold air,up to 10.8 times.(5) The occurrence of cold air in different grades has a strong seasonality.The frequency of medium and strong cold air grades was the highest in summer,accounting for 30.1% and 57.9% respectively.In spring strong cold air was the highest,accounting for 40.1%,and the cold wave was the highest in winter,accounting for 38.9%.(6) The cold air in all grades has 8 to 10a interannual period that was not consistent,but the cold wave dramatically decreased obviously in 1979. Keywords: Cold air process; frequcency; trend; period ; sudden change;Tarim basin
Bimonthly
Founded in 1978
- ISSN
1002-0799
- CN
65-1265/P
- Chief Editor：
CUI Caixia
- E-mail：
dom@idm.cn
- Sponsor：
Meteorological Bureau of Xinjiang Uygur Autonomous Region
- Organizer：
Meteorological Society of Xinjiang Uygur Autonomous Region Institute of Desert Meteorology , China Meteorological Administration
- Publish house：
Department of Desert and Oasis Meteorology
- Journal History：
Originally published as "Xinjiang Meteorology" in 1978 and renamed as "Desert and Oasis Meteorology" in 2007
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