Abstract:

The NCEP FNL (National Centers for Environmental Prediction Final Operational Global Analysis data) reanalysis data was used to diagnose the heavy snowfall process in the Liaoning region from February 14 to 16, 2020, and analyze the forecast deviation of the numerical model and its correlation with the affecting system.The results show that, under the influence of the upper trough in North China and the low overlying trough in the north of the Yellow Sea, the warm and humid air in the southern branch front area climbes along the cold pad of the northern wind in the northern branch front area, forming water vapor convergence and uplifting movement, which provides favorable dynamic conditions for the occurrence of the heavy snowfall process.The performance of the CMA-GFS (China Meteorological Administration Global Forecast System) model is poor in predicting the precipitation intensity of the heavy snowfall center, but the prediction of the heavy snowfall area is relatively accurate.The ECMWF (European Center for Medium-Range Weather Forecasts) model is more accurate in predicting precipitation intensity, but the forecast of heavy snowfall area is biased westward and the range looks too larger.The ECMWF model is relatively accurate in predicting the long duration (3.5 d) of this heavy snowfall process, and the precipitation forecast has a turning change and obvious forecasting biases in the short duration.The diagnostic results show that the turning change of precipitation forecast during the heavy snowfall is significantly correlated with the forecast deviation of the high and low altitude low-pressure systems.In particular, the forecast deviation of the low altitude low-pressure system is significantly correlated with the specific humidity of the two water vapor channels over the heavy snowfall area.The stronger forecast of the low-pressure system corresponds to the larger specific humidity, resulting in stronger water vapor transport over the Sea of Japan in the model.It may be the cause of the obvious deviation in the precipitation forecast.

Key words: Snowstorm, Diagnostic analysis, Forecast error analysis