Impact of satellite rainfall assimilation on Weather Research and Forecasting model predictions over the Indian region

摘要: Rainfall is probably the most important parameter that predicted by numerical weather prediction models, though skill of rainfall poorest compared to other parameters, e.g., temperature and humidity. In this study, impact assimilation on mesoscale model forecasts evaluated during Indian summer monsoon 2011. The Weather Research Forecasting (WRF) its four-dimensional variational data system are used assimilate Tropical Measuring Mission 3B42 Japan Aerospace Exploration Agency Global Satellite Mapping Precipitation retrieved rainfall. A total five experiments performed daily with without entire month July Separate assess sensitivity WRF forecast strict less quality control. Assimilation improves temperature, specific humidity, wind speed. Domain average improvement also improved over landmass when NOAA Climate Prediction Center Morphing technique Meteorological Department gridded