Cyclone(编程语言)
气候学
位势高度
温带气旋
中国
大气环流
循环(流体动力学)
异常(物理)
东亚
地质学
降水
气象学
地理
物理
考古
凝聚态物理
现场可编程门阵列
计算机科学
计算机硬件
热力学
作者
Jing Wang,Lei Chen,Shuanglin Li
摘要
Abstract Based on the fifth‐generation reanalysis (ERA5) data of the European Centre for Medium Range Weather Forecasts (ECMWF), spring Mongolian cyclones were examined from 1950 to 2023. Then, based on the feature parameters of activity path information, machine learning method (k‐means) is used to classify the trajectories of spring Mongolian cyclone. Subsequently, the atmospheric circulation configurations of the three categories of Mongolian cyclones and their influence on the weather in China verify the reasonability of the classification method. Specifically: (1) eastward moving type, affecting Inner Mongolia and Northeast China (Clus‐1). The circulation background of the Clus‐1 cyclone displays a broad negative geopotential height anomaly centre over East Asia; (2) northeastward moving type, affecting northeast part of Northeast China (Clus‐2). The circulation background of the Clus‐2 cyclones shows a “positive–negative–positive” distribution of circulation anomalies in the European Plain, Lake Baikal and the Sea of Japan; (3) southeastward moving type, this type can move to the south of China (Clus‐3). The circulation background of the Clus‐3 cyclones is opposite to that of the Clus‐2 cyclones. The three categories of Mongolian cyclones will cause dust weather and strong winds in different regions of China, mainly affecting Inner Mongolia and Northeast China.
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