The Optimal Sounder Data Assimilation Strategy for Mesoscale Convection System

The numerical weather prediction (NWP) or simulation model has been developed for decades. It has received substantial performance in term of predictability. On the other hand, satellite observations may provide abundant useful information over ocean than conventional observation. In particular, the sounding retrievals from microwave and hyperspectral infrared observations suggest a high quality estimation of atmospheric temperature and moisture profiles. These give an opportunity for improving the numerical weather forecast or simulation by including satellite data in the model. A heavy precipitation case associated with a mesoscale convection system (Mei-Yu frontal system) during early June 2012 around 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 Aqua AMSU microwave and AIRS sounding products. The preliminary result indicates that rain bands agree with in-situ rain gauge observation, which suggests a positive feedback for assimilating satellite data in the regional NWP model.