基于大数据聚类方法的我国夏季极端气候事件时空演变特征

Analysis of spatio-temporal evolution characteristics of summer extremeweather event in China based on big data clustering method

近年来,受到全球气候变化影响,我国极端天气频发多发,尤其是2022年川渝等地极端高温干旱天气持续时间长,严重影响经济、社会和人民生活,有必要对极端天气发生、发展态势开展研究.本文基于1962—2022年,近60年我国213个气象监测站点逐日气象数据,利用聚类方法对极端天气时空演变特征及预测展开研究.结果显示,近年来我国夏季气温呈波动上升态势,极端高温、暴雨、干旱等恶劣天气愈加频发,波及范围已从基准年份的东南局部地区大幅向北扩展,近3年已经波及至秦岭淮河沿线、长江中下游流域的大部分地区,预计未来极端天气发生更为常态化.

In recent years,affected by global climate change,extreme weather has occurred frequently in China,especially that the extreme heat and drought have lasted for a long time in Sichuan,Chongqing and other areas in 2022,which has seriously affected the economy,society and people's lives.As a result,it is necessary to conduct researches on the occurrence and development of extreme weather.Based on the 60 years daily meteorological data of 213 meteorological monitoring stations in China from 1962 to 2022,the clustering method was used to study the temporal and spatial evolution characteristics and prediction of extreme weather.The results showed that in recent years,summer temperature in China saw a wavelike rise,severe weather such as extreme heat,heavy rain,and drought took place more frequently,and had spread from parts of the southeastern areas of the base year substantially towards north,and had already influenced the most areas of the Qinling Huaihe River and the middle and lower reaches of the Yangtze River in the past 3 years.It was expected that extreme weather will become more normal in the future.