Study on the influence of ECMWF short-term forecast field assimilation on regional mesoscale model forecast

The forecast of the global numerical weather prediction model is often used as the background field to drive the regional mesoscale weather models, and its forecast quality has an important impact on the prediction skill of regional models. The mesoscale operational model in Central China uses the Global Forecast Field (NCEP GFS) of the US Center for Environmental Prediction as the background field, and its forecast accuracy needs to be improved. This paper proposes a method to improve the initial field of the model by using the three-dimensional variational method to assimilate the high-quality European Centre for Medium-range Weather Forecasts (ECMWF) fine-grid forecast field to improve the short-term forecasting ability of the model. At first, the error characters of the 12 h forecast products of NCEP GFS and ECMWF were analyzed by using sounding observations. The RMSE (root mean square error) of temperature, horizontal wind field and relative humidity of ECMWF 12 h forecast are smaller than those of NCEP