Advanced infrared sounder cloud detection and cloud-clearing and its impact on radiance assimilation in NWP

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). 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.