Improving assimilation of advanced IR sounder radiances in NWP with cloud detection from collocated imager cloud mask

Reliable forecasts of tropical cyclones (TCs) such as Isaac and Sandy which made landfall on the continental United States (CONUS) during 2012 are critical for decision making and better preparation. Obtaining good TC forecasts remains one of the most challenging aspects. Accurate cloud detection is very important for infrared (IR) radiance assimilation; improved cloud detection could reduce cloud contamination and hence improve the assimilation. Although operational numerical weather prediction (NWP) centers are using IR sounder radiance data for cloud detection, collocated high spatial resolution imager data could help sounder sub-pixel cloud detection and characterization. IR sounder radiances with improved cloud detection using AIRS/MODIS were assimilated for Hurricane Sandy (2012) and Hurricane Irene (2011). Forecast experiments were run with WRF (Weather Research and Forecasting) as the forecast model and the 3DVAR-based GSI (Gridpoint Statistical Interpolation) as the analysis system. Results indicate that forecasts of both hurricane track and intensity are substantially improved when the collocated high spatial resolution MODIS cloud mask is used for AIRS sub-pixel cloud detection for assimilating radiances. This methodology can be applied to process CrIS/VIIRS onboard Suomi-NPP/JPSS and IASI/AVHRR onboard the Metop series for improved radiance assimilation in NWP.