R2O Plans from the Rapid-Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) to the Unified Rapid Refresh Forecast System

The 3-km convection-allowing High-Resolution Rapid Refresh (HRRR) is an hourly updating weather forecast model that uses a specially configured version of the Advanced Research WRF (ARW) model and assimilates many novel and most conventional observation types on an hourly basis using Gridpoint Statistical Interpolation (GSI). The HRRR is run hourly out to eighteen forecast hours over a domain covering the entire coterminous United States and every three hours over Alaska with extensions to 36 hrs every six hours. With community-supported model components such as GSI, WRF-ARW and unified post-processing (UPP) along with computer resource growth, frequent contributions to the HRRR (and parent Rapid Refresh - RAP model) development have been possible, and as such, an agile model development paradigm with rapid prototyping for evolutionary upgrades to the RAP and HRRR including use of real-time experimental forecasts that permit operational forecaster feedback. This paradigm and close coordination with the National Center for Environmental Prediction (NCEP) Environmental Modeling Center (EMC) has facilitated a two-year research-to-operations (R2O) transition cycle for the RAP/HRRR between their operational inceptions in 2012/14 and present. We have now concluded the third and fourth R2O cycles of the HRRR and RAP respectively with an operational implementation on 12 July 2018. A final transition cycle is underway with a planned completion by mid-2020. This presentation will briefly (1) review the RAP/HRRR changes implemented in 2018 including a reduction in forecasted precipitation biases and forecast length/domain expansions, (2) preview candidate changes planned for the 2020 implementation including storm-scale ensemble data assimilation with use of new satellite and radar observations, wildfire-driven smoke forecasts and more advanced physics, and (3) describe the eventual incorporation into a Unified Rapid Refresh Forecast System (RRFS) by 2022.