Assimilation of cloud affected radiances in NCEP GDAS

One of 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 cloudy radiance components in NOAA data assimilation systems.

Radiance data assimilation in cloudy regions requires rapid and accurate radiative transfer and radiance gradient models. 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 under all weather conditions.

Clouds and precipitation are generated by grid-scale condensation process and subgrid convection (Simplified Arakawa Schubert method) in the NOAA NCEP Global Forecast System (GFS). Implementing cloudy radiance assimilations requires the tangent-linear models and adjoint models of these schemes. However, cloud schemes usually have strong nonlinearities/discontinuities. Therefore, it is challenging to use these scheme in data assimilation systems.

This presentation introduces the moisture process parameterization schemes and discusses their linearization processes to assimilate satellite observed cloud and precipitation information in NCEP global data assimilation system (GDAS). The current NCEP operational GDAS assimilates TMI and SSMI retrieved surface rain rate. Revisiting cloud and precipitation parameterizations of NCEP Global Forecast System (GFS) and building new tangent linear (TL) and adjoint (AD) models are the part of efforts to directly assimilate cloud and precipitation affected microwave radiances in NCEP GDAS in near future.