Application Of GSI-3DVAR Technique On Precipitation Forecast

With the rapid development and constant improvement of Global Satellite Observation System, more and more abundant and credible satellite radiance data can be obtained. Due to the characteristic of wide coverage, high temporal and spatial resolution and all-weather, the problem of lack of conventional observation data over the ocean and plateau can be made up by the satellite radiance data to a large extent. In recent weather forecast operation, precipitation forecast has been the focus of concerned problem in forecasting. China is located in the area of East Asian Monsoon (EAM) and frequently influenced by the rainstorm or other strong precipitation weather after the summer monsoon onsets every year. Therefore, it is of the great importance for making effective use of the satellite radiance data in the numerical weather prediction model to improve the accuracy of prediction or forecast of precipitation.In this paper, a rainstorm is simulated by the Advanced Weather Research and Forecasting (ARW WRF) model of NCAR. GSI-3DVAR system is employed to assimilate the conventional observation data and ATOVS bright temperature data into the WRF model directly. The event is based on a severe precipitation weather process that occurred in the middle-lower braches of Yangtze River during13-15June2011. The contrast analysis of different assimilation schemes impact on the initial field and precipitation forecasting was made. The numerical results show that by convention and ATOVS data assimilation, temperature and humidity field in the initial time are improved obviously. ATOVS data is important to improve the initial field and the only conventional observation data assimilation means limited improvement on forecasting. The assimilation of both satellite radiance data and convention data has positive effect on rainfall area and intensity of precipitation. Further more, the physical factors which affect the precipitation forecast are discussed in the paper. The comparison between the results indicate:Assimilation of both conventional data and ATOVS data modifies the dynamic structure and thermodynamic structure of the atmosphere. In rainy areas, the dynamic condition, thermodynamic condition and moisture condition are adjusted in favor of precipitation, and consequently improve the precipitation forecast.