Abstract
In April–May 2023, Yunnan province of Southwest China experienced a strong high-temperature event with relatively large return period and small occurrence probability, causing adverse impacts on the regional development. The possible causes for the 2023 high-temperature event are mainly involved with an upper-level high-pressure system induced by a Rossby wave train and the precipitation shortage associated with a lower-level anticyclonic circulation over the Bay of Bengal. On the one hand, the atmospheric Rossby wave train is attributed to the decreased snow depth in the North America. On the other hand, the lower-level anticyclone over the Bay of Bengal may be caused by the warming SSTs in the tropical western Indian ocean and in the tropical eastern Pacific via the excited Matsuno-Gill response and the atmospheric signals of Southern Oscillation, respectively. The mechanisms are validated by the pacemaker experiments run with CESM1 climate model. These three factors that cause the 2023 high-temperature event are highly correlated to the surface temperature anomalies in Yunnan. Hence, a physical-based multiple regression model with the leave-five-out cross validation can be constructed to perform a skilful seasonal prediction.
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