Exploring the Satellite Radiance Impact via Ensemble Forecast Sensitivity to Observation Impact (EFSOI) Within RRFS

Satellite radiance observations have been commonly assimilated within NOAA’s regional forecast systems, such as the Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR)-Alaska as well as their successor, the Rapid Refresh Forecast System (RRFS) prototype, the convective version of the Unified Forecast System (UFS). Those systems include a workflow of both deterministic and ensemble data analysis. However, up to date, the assimilation of radiances is performed mainly within the deterministic data analysis in RAP, HRRR, and the RRFS prototype, while it has not been added and tested within the ensemble data analysis components of these systems. To address this gap, this work has implemented a radiance data assimilation capability into the RRFS Ensemble Kalman Filter data assimilation (hereafter, RRFS-EnKF) workflow. The specification of the assimilated satellite sensors/channels in RRFS-EnKF is identical to the deterministic data analysis in RRFS, and the RRFS-EnKF bias correction coefficients are updated and cycled hourly.

To quantify the impact of radiance data assimilation, we enhance the Gridpoint Statistical Interpolation (GSI)-EnKF based ensemble forecast sensitivity to observation impact (EFSOI) package with RRFS. This GSI-EFSOI package has been experimentally implemented within various Finite-Volume Cubed-Sphere (FV3) based systems, with different cycling strategies. With Global Forecast System (GFS) v.16, the GSI-EFSOI adopts 1) a cycling frequency of 6 hours and 2) 24h and 30h forecasts that are valid at the same time and verified against ensemble analyses. Prior to this study, the GSI-EFSOI with RRFS used a cycling frequency of 3 hours and 6h and 9h forecasts valid at the same time for the regional EFSOI calculation, considering that the impact of assimilated observations from a longer forecast could propagate outside of the domain boundary. This study further tests the use of hourly cycling for our RRFS-EnKF EFSOI experiments, for a configuration that is comparable to the RRFS hourly cycling design. The preliminary investigation of continuous hourly cycling RRFS-EnKF experiments over the CONUS domain indicates that the radiances from the Cross-track Infrared Sounder (CrIS) on NOAA-20 show a stronger data impact than other assimilated satellite data.