In order for NWP models to forecast tropical cyclone structure, size and intensity changes with fidelity, the inner core structure of these storms must be resolved at 1-3 km horizontal grid spacing. Currently, the NWS relies on both coarse-scale global models and regional scale higher resolution models to provide numerical guidance for tropical cyclone forecasters. Primary models used for numerical guidance are the GFS at 13-km equivalent grid spacing and the HWRF, which runs in a storm-centric mode with a single set of telescopic domains at 18-, 6-, and 2-km over each storm. When multiple storms are present, multiple instantiations of the operational HWRF model are run, which hinders representation of multi-scale interactions, post landfall applications and Tropical Cyclone genesis. Global non-hydrostatic models are being envisioned by the NWS to be run at higher resolutions by the end of this decade. However, it remains to be seen whether these models can routinely operate at a 1-3 km resolution, providing reliable forecasts with the refreshing frequency needed to support the creation of operational forecast products. In the absence of a very high-resolution global model in all basins, grid nesting over individual storms could be a practical approach for the hurricane-forecasting problem, both at the regional and global scales. To investigate the technical and scientific challenges and merits of a multi-storm configuration, NOAA's Hurricane Forecast Improvement Project (HFIP) supported HRD/AOML, along with its partners at NCEP/EMC and the Developmental Testbed Center (DTC), to create a basin scale configuration of HWRF that operates with multiple moving nests. This configuration, which is now an option in the centralized HWRF code, was run for the 2015 hurricane season and also in retrospective mode for the 2011-2014 seasons. Results from the basin scale HWRF will be presented to show that an extension of the multi nested basin scale paradigm to global models could be considered for the NOAA's Next Generation Global Prediction System (NGGPS).
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