Assimilation of AMSU-A Surface-Sensitive Channels in CMA_GFS 4D-Var System over Land

Abstract

Abstract The assimilation of two surface-sensitive channels of the AMSU-A instruments on board the NOAA-15/NOAA-18/NOAA-19 and MetOp-A/MetOp-B satellites over land was achieved in the China Meteorological Administration Global Forecast System (CMA_GFS). The land surface emissivity was calculated by 1) the window channel retrieval method and 2) the Tool to Estimate Land Surface Emissivities at Microwave frequencies (TELSEM2). Quality controls for these satellite microwave observations over land were conducted. The predictors and regression coefficients used for oceanic satellite data were retained during the bias correction over land and found to perform well. Three batch experiments were implemented in CMA_GFS with 4D-Var: 1) assimilating only the default data, and adding the above data over land with land surface emissivity obtained from 2) TELSEM2 and 3) the window channel retrieval method. The results indicated that the window channel retrieval method can better reduce the departure between the observed and simulated brightness temperature. Over most land types, the positive impacts of this method exceed those of TELSEM2. Both TELSEM2 and the window channel retrieval method improve the humidity analysis near the ground, as well as the forecast capability globally, particularly in those regions where the land coverage is greater, such as in the Northern Hemisphere. The data utilization of the two surface-sensitive channels increase by 6% and 12%, respectively, and the additional data every 6 h can cover most land, where there was no surface-sensitive data assimilated before. This study marks the beginning of near-surface channel assimilation over land in CMA_GFS and represents a breakthrough in the assimilation of other surface-sensitive channels in other satellite instruments. Significance Statement Surface-sensitive microwave channels are difficult to assimilate in NWP due to the lack of both direct measurement and appropriate modeling for instantaneous land surface emissivity. This paper discusses a method that improves the surface emissivity estimates, which has allowed the utilization of surface-sensitive microwave channels in CMA_GFS. Those capabilities have resulted in better data utilization, improved forecasts of temperature, geopotential height, and winds in the Northern Hemisphere at 3–7 days, and represent an incremental and important improvement to CMA_GFS.