One of the major challenges of data assimilation is incorporating the satellite measurements over cloudy regions. Radiance measurements over cloudy regions possibly provide us with the atmospheric total liquid/ice water content, humidity, and temperature. This additional information could help to improve the numerical weather forecast skill. NOAA is currently working to include components to assimilate cloud- and precipitation-affected radiance components in NCEP numerical weather prediction models.

Assimilating cloud- and precipitation-affected radiances requires rapid and accurate radiative transfer and radiance gradient models and forward and adjoint models including moisture physics processes. For a vertically stratified scattering and emitting atmosphere, the Community Radiative Transfer Model (CRTM) was developed at the Joint Center for Satellite Data Assimilation (JCSDA). This CRTM is employed in this study to calculate radiances and Jacobians at various wavelengths for radiance assimilation. Clouds and precipitation generated by grid-scale condensation process and subgrid convection (Simplified Arakawa Schubert method) schemes of the NOAA NCEP Global Forecast System (GFS) model are included in the observational operators. The adjoint models of these moisture physics are used to add the effect of clouds and precipitation to the CRTM computed Jacobians for cloudy radiance assimilation.

This presentation begins with describing the current operational NCEP Global Data Assimilation System (GDAS) which utilizes radiance data only in clear sky conditions. Methodologies and development progress to assimilate cloud- and precipitation-affected radiances in the NCEP GDAS are discussed. Finally, preliminary results from the impact study to directly assimilate cloud- and precipitation-affected AMSU-A radiances in NCEP GDAS are presented.