All-Sky assimilation of AMSU-A window channel radiances using Gain-form of Local Ensemble Transform Kalman filter within MPAS-JEDI

The Gain-form of Local Ensemble Transform Kalman Filter (LGETKF) has been implemented in the Joint Effort for Data assimilation Integration (JEDI) with the Model for Prediction Across Scales - Atmosphere (MPAS-A) (i.e., MPAS-JEDI). LGETKF applies vertical localization in model space and is particularly suitable for the assimilation of satellite radiance data, which does not have an explicit vertical height assigned for each channel. The quality control, bias correction, all-sky observation error model, and cloudy observation operator within the JEDI framework are employed to enable the MPAS-JEDI’s LGETKF to assimilate satellite radiances in all-weather situations, in addition to conventional observations and clear-sky radiances. To optimize the assimilation configurations in LGETKF, a series of sensitivity experiments are conducted to evaluate the impacts of adding all-sky window channel AMSU-A radiances above the conventional observations and clear-sky radiances from the AMSU-A temperature sounding channels and MHS humidity sounding channels. It is found that a combination of relaxation to prior perturbation (RTPP) and relaxation to prior spread (RTPS) aids LGETKF in maintaining the ensemble spread across cycles, and a smaller horizontal localization scale proves preferable for all-sky AMSU-A radiance assimilation. The performance of all-sky radiance assimilation in LGETKF is evaluated through two one-month global cycling experiments with 80 ensemble members at 60-km cell spacing, with and without the all-sky assimilation of AMSU-A window channel radiances. Verification against Global Forecast System (GFS) analyses illustrates the benefits of all-sky assimilation in reducing short-term and 7-day forecast errors of almost all variables, despite some slight degradations for temperature. Further observation space verification demonstrates that the all-sky assimilation can improve the forecasts with a better fit to satellite winds and all-sky radiances, with positive impacts lasting for 5 to 6 days. Overall, the MPAS-JEDI LGETKF shows robust and stable performance in all-sky radiance assimilation and holds great potential for both research and operation applications. Active research is underway to explore the added value of assimilating all-sky radiances from Advanced Technology Microwave Sounder (ATMS) window channels at a higher temporal resolution (i.e. 30 km). Results will be presented at the conference.