Climatology of Northeast China cold vortices during the warm season: A comparison of ERA5 and MERRA‐2 reanalyses

Abstract

AbstractThe Northeast China cold vortex (NCCV) is an important type of synoptic scale system, which often induces local torrential rainfall events, strong winds, and lightning during warm seasons (May–September). By using an automatic identification method that involves a three‐step algorithm, NCCVs during warm seasons of 1980–2018 were identified based on ERA5 and MERRA‐2, the latest generation of reanalysis. Employing this recognition result and intensive surface observations, climatology of the NCCV was analysed. With respect to average climatic characteristics, the results indicate that the NCCV is most frequently located from the east of the Yablonov Mountains to the west of the Xiao Hinggan Mountains. The average rain belt and cold tongues resulting from NCCVs both mainly fall within Northeast China, Japan, Southeast Russia, and the Korean Peninsula, causing precipitation and temperature anomalies there, especially in Northeast China. Regarding interannual variation, the number of NCCV‐occurrence hours varies at a cycle of about 3 years, and has increased in the last 10 years compared to 1999–2008. The intensity of the NCCV also fluctuates in a cycle of approximately 3 years and shows a weakening trend, particularly from July to September. As for life characteristics, NCCVs usually form at the border area between China, Mongolia, and Russia, then develop and move eastwards, and finally disappear in areas of Heilongjiang in China, southeastern Russia, and the Okhotsk Sea. The NCCV moves in complex paths; among all 55 types of routes that occurred in warm seasons of 1980–2018, the most favoured paths are east, southeast, northeast, southeast‐to‐northeast, and circular. The above results based on the up‐to‐date reanalysis datasets with high resolutions are updates and supplements to previous studies, further improving our understanding of the NCCV in aspects of its cooling effects, weakening trends, and crucially, paths of movement and their occurrence frequency.