Characteristics of large-scale atmospheric circulation patterns conducive to severe spring and winter wind events over beijing in china based on a machine learning categorizing method

Abstract

Severe wind events which occur in the metropolis of Beijing in China bring major catastrophes. Characteristics of severe winter and spring wind events over Beijing during the past 40 years have been analyzed. An artificial intelligence-based method is adopted to categorize the favorable large-scale circulation patterns and dominant weather systems. Four categories are concluded and compared to each other in terms of distributions of geopotential height at 500 hPa, temperature at 500 hPa, sea level pressure and their corresponding anomalies in 1979–2019. It is found that the first category (T1) which is dominated by strong cold trough at upper levels with strong cold-core high locating at surface is the most conducive circulation pattern, while the fourth category (T4) which is controlled by weak trough and strong ridge with strong low cyclone at surface is the least one. The second and third categories, represented by T2 and T3, are under the control of strong cold trough and warm ridge at upper levels with weak high at surface, and of weak trough and strong ridge with strong low cyclone at surface, respectively. Characteristics and differences under different backgrounds of global temperatures are analyzed by separating the past 40years into two distinct periods. The decreasing trends of intensities of the trough and ridge, the temperature at 500hPa, together with the surface systems, are found to be responsible for the decrease in severe wind events in T1, T2 and T3 in the last 20 years, while T4 is distinct to the other three categories with little change in its circulation pattern, and thus continues contributing to the severe wind events over Beijing. The results found in this study with the usage of an AI-based algorithm will benefit for the operational forecasting for extreme wind events over Beijing.