As part of an extensive upgrade to the RAP system (slated for NCEP operational implementation early in 2018), a number of enhancements have made to the satellite assimilation part of the GSI-based RAP analysis. In this study, we have used this upgraded version of the RAP system to examine the impact of direct broadcast data on RAP forecast skill, focusing on ATMS and CrIS data. Several experiments have been carried out to explore the impact of the use of direct broadcast feeds of these datasets compared to the standard satellite data feeds, which often yield little usable data for the RAP because of the very short RAP data cutoff time (~ 30 min.). Different data combinations have been tested, including use of data set from SSEC with VIIRS-based cloud clearing and NCEP direct broadcast datasets. Over a region with CrIS data coverage only, we are examining the GSI wind, moisture and temperature analyses in detail better understand the CrIS data impact relative to other datatypes. We are also examining the spatial and temporal variation of the forecast impact in an attempt to relate it to the proximity to the observed (assimilated) observed data swaths. In addition to documenting the forecast improvements from these direct broadcast data feeds, this research should provide additional insights for overcoming the unique challenges associated with regional (limited-area) satellite radiance assimilation (intermittent coverage of data swath and associated bias correction issues, low model top and channel selection issue, etc.). Additional work will focus on evaluating the downstream impact on nested HRRR forecasts from this enhanced satellite radiance assimilation.
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