Optimal Use of Satellite Sounding Products for Numerical Weather Prediction

The numerical weather prediction (NWP) and simulation model has been developed for decades. It has received substantial improvement in term of predictability. On the other hand, satellite observations and retrieved products may provide critical assistant over ocean than conventional observation. In particular, the combined sounding retrievals from Advanced Microwave Sounding Unit and Atmospheric Infrared Sounder (AMSU/AIRS) suggest a high quality estimation of atmospheric temperature and moisture profiles. Meanwhile, a higher spatial resolution from single field-of-view (SFOV) of AIRS sounding was developed followed by the previous combined AMSU/AIRS product. It is believe that finer spatial resolution retrievals could retain a better gradient structure in a weather system. 　　In this study, we propose to use combined AMSU/AIRS and AIRS SFOV soundings to evaluate the performance for introducing these two different data sets. A heavy precipitation MCS case associated with a Mei-Yu frontal system during early June 2012 in the vicinity area of Taiwan is selected to demonstrate this concept. Weather Research Forecasting (WRF) and its three-dimensional variational module (3D-Var) is used to evaluate the forecast performance due to assimilating of NASA EOS AMSU and AIRS products. The preliminary result suggests that AIRS SFOV data set have better performance over combined AIRS/AMSU in temperature and mixing ratio forecast when both data are selected in the same spatial coverage. However, assimilating AMSU/AIRS data can improve the front location. Therefore, combine AMSU/AIRS and AIRS SFOV these two products may enhance the forecast capability.