Developing the National Blend of Models for National Weather Service Operations

The National Weather Service (NWS) is developing the National Blend of Models (NBM) to provide a nationally consistent and skillful suite of calibrated forecast guidance based on a blend of NWS and non-NWS deterministic, ensemble, and statistically post-processed model output. The first version of the NBM was implemented on the NOAA supercomputer in January 2016 and contains blended guidance for 10 National Digital Forecast Database (NDFD) elements over the conterminous United States (CONUS) based on output from the GFS deterministic, GFS ensemble, Canadian ensemble, Gridded MOS (GMOS) and Ensemble Kernel Density MOS (EKDMOS).  The second version of the NBM, to be implemented Fall 2016, expands the blend to Alaska, Hawaii and Puerto Rico, and adds precipitation (PoP12 and QPF) guidance over the CONUS.

The third version of NBM planned for implementation later this year introduces mesoscale models over the CONUS, hourly resolution for the first 36 hours of the forecast, and adds ceiling and visibility to support digital aviation services.  It will update every hour using latest available model guidance.  Further, the existing global blend will be augmented to include PoP12 and QPF over Alaska, Hawaii, and Puerto Rico, and provide inputs to support local production of snow amount and predominant weather grids.   

This presentation will provide details on the datasets and techniques used in the development of the blended guidance and a sample of verification results.  Future development plans for a more probabilistic NBM will also be discussed.