Quantifying the dynamic and synergistic effects of low and mid-latitudes signals on regional extreme climate events.

Unlike previous studies solely focused on the influences of low or mid-latitudes signals on regional extreme events, this paper used the three-pattern decomposition of global atmospheric circulation (3P-DGAC), taking the 2018 hot summer in East Asia for example, to quantitatively reveal the dynamic and synergistic effects of low and mid-latitudes signals on regional extreme events. By analyzing the anomalous three-dimensional structure of atmospheric circulations in 2018 hot summer, we discovered that the local meridional circulation at low latitudes and zonal circulation at mid-latitudes both produced abnormal downdrafts in East Asia, which were consistent with the anomalous anticyclone in this region. Then, we investigated the relative vorticity advection combined with 3P-DGAC to uncover the dominant circulation patterns, and found the horizontal circulation at mid-latitudes and local meridional circulation at low latitudes were the major contributor to the anomalous anticyclone, accounting for 56% and 44% respectively. This result indicated the 2018 hot summer might be influenced by the synergistic effect of low and mid-latitudes signals. Finally, by investigating sea surface temperature anomaly (SSTA) and mid-latitudes wave train, we considered the tripole-like SSTA pattern in the North Atlantic and positive SSTA in Kuroshio and its extension area (K-KE) as the main causes of horizontal circulation anomalies, and the anomalous meridional circulation was related to the extremely late onset of South China Sea summer monsoon (SCSSM). This study provided a novel way to quantitatively study synergistic effects of low and mid-latitudes signals on regional extreme events. • East Asia was hit by extreme heat event in the summer of 2018. • Horizontal circulations at mid-latitudes and meridional circulations at low latitudes contributed greatly to this event. • The combination of 3P-DGAC and dynamic variables can be applied to the study of dynamic causes of extreme climate events. [ABSTRACT FROM AUTHOR]