气候学
罗斯比波
反气旋
环境科学
纬度
海面温度
热带大西洋
沃克循环
纬向和经向
海洋学
地质学
大地测量学
作者
Jilan Jiang,Yimin Liu,Jiangyu Mao,Guoxiong Wu
标识
DOI:10.1088/1748-9326/acc5fb
摘要
Abstract Eastern China experienced persistent regional extreme heatwaves in the summer of 2022, with disparate spatial features and formation mechanisms in different months. We quantitatively assessed the relative contributions of three oceans, i.e. tropical Indian Ocean and Pacific and North Atlantic, and the local soil moisture–temperature feedback using linear regression. The results showed that the monthly mean atmospheric circulation anomalies failed to explain the extreme heatwave in June 2022. The combined contribution of the tropical Indo-Pacific and North Atlantic sea surface temperature anomalies (SSTAs), together with the local soil moisture–temperature feedback, explaining approximately 10% of the temperature anomalies. In July, the tropical Indo-Pacific SSTAs promoted anomalous atmospheric circulation and extreme heat via meridional circulation originating in the Maritime Continent, accounting for approximately 10% of the temperature anomalies, with North Atlantic SSTAs contributing the same percentage by a mid-latitude steady Rossby wave. Local soil moisture–temperature feedback accounted for 42% of the anomalies. The tropical Indo-Pacific SSTAs produced a strong western North Pacific anticyclone in August, but their direct contribution to the temperature anomalies was negligible. The North Atlantic SSTAs contributed 9% of the total via the mid-latitude steady Rossby wave. Local soil moisture–temperature feedback contributed 66%, suggesting that the July heatwave and drought exerted a significant impact on the subsequent August extreme heatwave. Global warming has greatly facilitated extreme heatwaves, accounting for about 30%–40% of these events in summer 2022. These results also suggest that the climatic effects of tropical Indo-Pacific and North Atlantic SSTAs on Eastern China are evident in the month-to-month variation in summer. Our results thus contribute to the understanding and prediction of extreme heatwaves in Eastern China.
科研通智能强力驱动
Strongly Powered by AbleSci AI