Variational Assimilation Of ATOVS Data And Its Application For Numerical Prediction Of Heavy Rainfall

GRAPES three-dimensional variational data assimilation system, developed by China, is used in this paper to assimilate ATOVS data, then a process of a heavy rainstorm in 02-03 July 2005 is forecasted through the WRF mesoscal model, in order to find the impact of ATOVS data on numerical forecast of heavy rainfall in our country. By comparing and analyzing the results of assimilation and forecast respectively, the main conclusions to be drawn from this paper are as follows: 1) By Assimilating AMSU-B data, the elements of initial fields' middle and upper are adjusted mainly, especially humidity;2) If there was raining at the beginning of assimilation, assimilating HIRS data contributes to the upper elements of the initial fields, but no good influence on precipitation forecast;3) From the adjusting extent to the results of 6hr. precipitation forecast, the contribution of conventional observations are superior to AMSU-B data and HIRS data at the areas of the conventional observations' distribution denseness. The analyses above show that AMSU-B data may advance the quality of the initial fields and increase the accuracy of heavy rainfall NWP in our country, and manifest enough the advantage of microwave radiance data. Else, in order to evaluate the forecast abilities of WRF model, WRF model's and MM5 model's precipitation forecast results have been compared. The most important results of this part are as follows: For the forecast of heavy rains centers' location, WRF model's results are better than MM5 model's. But for its intensity, WRF model's results are worse than MM5 model's.