TOPOGRAPHIC DEPENDENT HORIZONTAL LOCALIZATION SCALE SCHEME IN GRAPES-MESO HYBRID EN-3DVAR ASSIMILATION SYSTEM

Abstract:

Based on the GRAPES-MESO hybrid En-3DVAR (Ensemble three-dimension hybrid data assimilation for Global/Regional Assimilation and Prediction system) constructed by China Meteorological Administration, a 7-day simulation (from 10 July 2015 to 16 July 2015) is conducted for horizontal localization scales. 48h forecasts have been designed for each test, and seven different horizontal localization scales of 250, 500, 750, 1000, 1250, 1500 and 1750 km are set. The 7-day simulation results show that the optimal horizontal localization scales over the Tibetan Plateau and the plain area are 1500 km and 1000 km, respectively. As a result, based on the GRAPES-MESO hybrid En-3DVAR, a topography- dependent horizontal localization scale scheme (hereinafter referred to as GRAPES-MESO hybrid En-3DVAR-TD-HLS) has been constructed. The data assimilation and forecast experiments have been implemented by GRAPES-MESO hybrid En-3DVAR, 3DVAR and GRAPES-MESO hybrid En-3DVAR-TD-HLS, and then the analysis and forecast field of these three systems are compared. The results show that the analysis field and forecast field within 30h of GRAPES-MESO hybrid En-3DVAR-TD-HLS are better than those of the other two data assimilation systems. Particularly in the analysis field, the root mean square error (RMSE) of u_wind and v_wind in the entire vertical levels is significantly less than that of the other two systems. The time series of total RMSE indicate, in the 6-30h forecast range, that the forecast result of En-3DVAR-TD-HLS is better than that of the other two systems, but the En-3DVAR and 3DVAR are equivalent in terms of their forecast skills. The 36-48h forecasts of three data assimilation systems have similar forecast skill.