After a series of satellite assimilation upgrades in RAP version 3 (planned for NCEP implementation in Aug. 2016), including adding additional RARS satellite data and improved channel selection and cycled bias correction, satellite radiance data are yielding a small but consistent positive impact within the Rapid Refresh (RAP) model system. The RAP uses the Gridpoint Statistical Interpolation (GSI) hybrid variational/Ensemble Kalman Filter (EnKF) data assimilation system, with ensemble information for the regional assimilation coming from the 80-member global ensemble data assimilation system. We are currently testing the next set of satellite assimilation upgrades for the coming RAP version 4, tentatively planned for late 2017 / early 2018. These upgrades include tuning of the regional radiance bias correction scheme, possible improvement in the cycling strategy, and use of new instruments/data (SEVIRI, ATMS, CrIs etc.) with lower data latency (e.g., using the direct readout data). A series of RAP retrospective runs are being conducted to evaluate the forecast impact from these changes and/or new instruments/data separately and/or combined together. At the conference, we will report on progress to date for all aspects of satellite radiance assimilation upgrade for the RAP version 4 implementation. This presentation will include assessment of forecast impact for individual satellite datasets and conbined impacts from all the new satellite data.
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