Diagnostic analysis of the extreme rain-snow process in Liaoning province from November 7-9,2021
The conventional meteorological observation data,artificially enhanced observation data and NCEP/NCAR(the National Centers for Environmental Prediction and the National Center for Atmospheric Research)grid data were used to analyze the extreme rain and snow weather in Liaoning province from November 7-9,2021.The results show that the Northeast China Cold Vortex(NCCV)and the surface cyclone are the main influence systems of the extreme rain and snow weather.The convergence of the middle and lower troposphere,the diver-gence of the upper troposphere and the convergence of the strong cold and warm air flow are the main causes of the extreme rain and snow weather.The coupling of the high and low level jet and the high level divergence suc-tion,together with the dynamic lifting effect of the NCCV,the warm and wet low level jet climb along the cold pad,which further strengthen the upward motion.The warm moist jet provides abundant water vapor conditions for the extreme rain and snow weather,and the strengthening of the warm moist jet corresponds to the strengthening of water vapor convergence,combined with the dynamic lifting effect of the low-level cold pad and the NCCV,and the ground convergence line distributes along the terrain,which triggers the extreme heavy snow weather.Terrain blocking leads to the accumulation of cold air on the ground to form cold air cushion,which is an important reason for extreme snowfall.The difference of temperature stratification is the main reason for the difference of rain and snow phase between Anshan and Xiuyan.The low layer cold air cushion with the characteristics of freezing layer provides favorable temperature stratification conditions for the extreme snowstorm in Anshan.The melting layer thickness and ground temperature are the key factors for the occurrence of freezing rain in Xiuyan.
Northeast China Cold Vortex(NCCV)Warm moist jet streamCold air cushionTemperature stratifi-cation
国家科技期刊平台
NSTL
万方数据
