新疆春季气温前后反相变化及其环流异常特征

Characteristics of temperature inversion and circulation anomaly in spring in Xinjiang

摘要:

基于1961—2023年新疆春季逐月气温、NCEP/NCAR再分析资料及环流指数，研究了新疆春季气温季节内变化的主导模态及其对应的环流异常特征。结果表明：近60a来，新疆春季气温上升显著，季节内存在一致变化和前后反相两个主要模态。当春季气温一致偏暖（冷）时，对流层高层纬向风北正南负（北负南正），中层呈类东大西洋/西俄罗斯遥相关型（EA/WR）正（负）位相，低层乌拉尔山为异常气旋（反气旋），地面欧亚冷高压偏弱（偏强）。当气温发生季节内冷暖转换时，影响气温波动的副热带西风急流、中高纬环流经向度、乌拉尔山与西西伯利亚位势高度以及低层异常气旋-反气旋的偶极分布、欧亚冷高压等关键环流系统的维持和变化是气温同相与反相演变的重要原因。因此，斯堪的纳维亚遥相关型指数（SCA）、亚洲纬向环流指数（AZC）、北大西洋-欧洲区极涡强度指数（AEPVI）、东大西洋/西俄罗斯遥相关型（EA/WR）、亚洲区极涡面积指数(APVA)、东大西洋遥相关型指数(EA)均对气温的季节内变化有重要影响，可作为预测春季气温季节内变化的重要指标。

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.