Assessment of Forecast Impact from JPSS Direct Readout Data for the Rapid Refresh Mesoscale Model System

Use of polar orbiter satellite radiance data in rapidly updated regional models has traditionally been limited by data latency issues combined with the very short data cutoff window for these models.  For the NOAA Rapid Refresh (RAP) mesocale model system, the data cutoff time is ~ 30 min. resulting in limited data usage.  Effective use of these data is further limited by the inconsistent spatial coverage across the limited area domain for successive updates, leading to less effectiveness in the cycled bias correction procedure. The availability of direct readout data offers the potential for improvements in both the percent of total polar orbiter data being assimilated into rapidly updated regional models and the effectiveness of the data assimilation.  

The degree to which these potentials are being realized is being evaluated for the RAP model and the subsequent High-Resolution Rapid Refresh (HRRR) model (initialized from the RAP), through a series of retrospective experiments.  We are examining data usage improvements and impacts on the bias correction and overall forecast skill from the direct readout feeds of ATMS and CrIS datasets obtained from Univ. of Wisc. / SSEC.  Our initial experiments over a 7-day period with ATMS data showed only a small forecast impact, despite encouraging bias correction results.  We are further examining the details of this experiments as well as documenting the specific degree of data usage improvement and examining other aspects such as channel selection associated with the relatively low RAP model top (10 hPa).  We are also conducting further ATMS experiments and examining impacts for CrIS data.  In this presentation, we will summarize the research results, examining data coverage, bias correction, channel selection, and forecast improvement.