The impact of an improved land cloud detection method on cold‐vortex precipitation forecasting

Abstract The Northeast China Cold Vortex (NCCV) is an important land‐bound large‐scale weather system affecting Northeast China. Microwave temperature sounders onboard polar‐orbiting satellites provide uniform and consistent spatiotemporal observations of the NCCV. However, the assimilation of microwave temperature sounding observations is hindered by the insufficient accuracy of cloud detection over land. Herein, a concurrent microwave temperature and humidity sounder cloud detection method was introduced into the Gridpoint Statistical Interpolation (GSI) assimilation system. This method not only enhances the accuracy of cloud detection using microwave temperature sounding data but also enhances the prediction accuracy of the NCCV and the associated precipitation. The assimilation and forecast experimental results indicate that the concurrent cloud detection method effectively improves the cloud detection accuracy of the GSI system by retaining more observations in land areas and eliminating more observations in cloudy ocean areas. These improvements enable better adjustment of the temperature structure and intensity of the NCCV system. Moreover, this approach improves the accuracy of forecasts of typhoon positions in ocean areas. A more reasonable configuration of cold‐vortex and typhoon systems can yield improved forecasts of heavy precipitation in cold‐vortex regions. Additionally, several NCCV forecast experiments revealed that the use of the concurrent microwave temperature and humidity sounder cloud detection method effectively improved NCCV forecasting, indicating its practical application.