Impact of Assimilation of MADRAS Geophysical Parameters on Short Range WRF Model Forecasts

This research paper presents the assimilation of ocean surface precipitable water (TPW) and wind speed obtained from Microwave Analysis and Detection of Rain and Atmospheric Structures (MADRAS) onboard Megha-Tropics satellite retrievals into the Weather Research and Forecasting Model (WRF) model to assess their impact on short-range precipitation forecasts. Two parallel experiments are performed daily with and without assimilation of the MADRAS geophysical parameters during the entire month of the July 2012. Initially, MADRAS retrieved TPW and wind speed are compared with the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) retrieved geophysical parameters and European Centre for Medium-Range Weather Forecasts (ECMWF) global model analyses. This comparison shows a root mean square difference (RMSD) of similar to 1.8 ms(-1) and similar to 0.3 gcm(-2), and mean difference (BIAS) of similar to-1.0 ms(-1) and similar to 0.15 gcm(-2) in wind speed and TPW, respectively. Results show that the assimilation of MADRAS retrieved geophysical parameters improved the TPW and wind speed by about 20% and 10% reduction in RMSD, respectively. Six-hourly WRF model forecasts are also improved with the assimilation of MADRAS retrievals. The Forecast Impact (FI) parameter shows larger than 10 mm improvement in 24 h rainfall forecasts over the Indian Ocean.