The unique data assimilation features of the RUC (digital filter-based radar reflectivity assimilation and cloud analysis using METAR and satellite data) have been ported to the RR system. The RR cloud analysis will benefit from use of a GOES-based special NASA Langley cloud product, which provides extended spatial coverage over both northern and southern portions of the RR domain. A new feature for the data assimilation system is the use of a partial cycling mechanism to prevent drift of the RR atmospheric state away from the parent GFS model atmosphere. The RR also retains the use of physical parameterizations used in the RUC: the RUC-Smirnova land surface model, the Thompson mixed-phase microphysics scheme with 2-moment treatment of rain and cloud ice, and the Grell-Devenyi ensemble cumulus scheme . Each of those parameterizations has been updated significantly over versions in the current RUC model, and all are available within the community WRF repository.
The RR system has undergone extensive testing; first on the ESRL GSD linux-based supercomputer system and more recently on the NCEP IBM system. This testing has lead to a significant improvement in the interoperability of both the GSI and ARW systems and enhancements to the ARW for application as a cycled operational model. Upper-level and surface verification comparisons between the RR and RUC indicate RR superiority for nearly all variables and levels. RR precipitation forecasts are similar to the RUC. At the conference, we will provide a full statistical assessment of the RR, present case-study examples and discuss issues related to its implementation at NCEP (expected around the time of the conference).