Northeast cold vortex detection algorithm based on reanalysis data prediction

The Northeast Cold Vortex (NECV) is a significant atmospheric phenomenon characterized by a large-scale, high-altitude cold low-pressure system that predominantly influences the northeastern region of China and its adjacent areas. This persistent weather system typically maintains its activity for periods ranging from 3 to 4 days or longer, exhibiting substantial meteorological impacts. Current methodologies for determining the spatial extent of the NECV primarily rely on extensive data analysis, which involves substantial computational resources and prolonged data processing time. Based on the above reasons, this paper proposes a method to detect the northeast cold vortex by forecasting and reanalyzing data and combining it with satellite cloud images, which solves the problem of poor timeliness of detecting the northeast cold vortex by using ERA5, and improves the detection capability of the northeast cold vortex. Compared with the single use of satellite cloud image to detect the northeast cold vortex, its effect is significantly improved, and it has guiding significance for the detection methods of the northeast cold vortex.