The Assimilation of Satellite Data in the GRAPES (Global and Regional Assimilation Prediction System)

Liu Yan and Xue Jishan
State Key-laboratory of Severs Weather,
Chinese Academy of Meteorological Sciences, China

GRAPES (Global and Regional Assimilation Prediction System) is the Chinese new generation NWP system for which the pre-operational tests are being conducted currently in the national operational NWP centers. Sparseness of conventional data is the biggest challenge in upgrading NWP in China . Application of satellite observations is the most effective way to solve the problem of data sparseness, therefore the assimilation of satellite radiances into GRAPES analysis system is the first priority in the development of GRAPES model. In the end of 2005 the assimilation of radiance data from the Advanced TIROS Operational Vertical Sounder (ATOVS) into the GRAPES-3DVar analysis system has been implemented. Several procedures have also been developed, including advanced thinning, identification of cloud/rain-affected radiances, removal of radiance data which are erroneous or not well simulated using a current fast radiative transfer model and/or numerical weather prediction model, selection of adequate channels and correction of radiance biases. After a brief description of these schemes, results of a series of validations of GRAPES analyses against the observation data and analyses derived from other operational NWP center to assess its performance are presented in this paper.

Key words: data assimilation, satellite data