Use of Radar Data in the NSSL Experimental Warn-on-Forecast System for Ensembles

The NOAA Warn-on-Forecast (WoF) Project is tasked with developing a rapidly updating, storm-scale prediction system for the purpose of predicting hazardous weather phenomena, such as thunderstorm rotation, hail, high winds, and flash flooding. Ensemble-based assimilation of radar, satellite, and conventional (e.g., surface) data is an important component of the proposed WoF system, which will likely generate new 0-3 h probabilistic forecasts 3-4 times an hour. A prototype system—known as the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e)—has been developed in collaboration with the Global Systems Division (GSD), and is based on the Weather Research and Forecasting (WRF) model with 3-km horizontal grid spacing for real-time experiments.

This year, the NEWS-e will be run in real-time each day from 1 May – 2 June, which coincides with the NOAA Hazardous Weather Testbed 2017 Spring Forecast Experiment. The experimental High Resolution Rapid Refresh Ensemble (HRRRE)—under development at GSD—will provide daily initial and boundary conditions for the NEWS-e, a 36-member ensemble covering a 1000-km wide region where severe weather is anticipated. Radar reflectivity and radial velocity, satellite (cloud water path retrievals), and surface data will be assimilated every 15 min using the ensemble Kalman filter (EnKF) method, beginning at 1800 UTC each day.

This presentation will provide a more detailed description of the HRRRE to NEWS-e workflow, and then assess the impact of radar data assimilation on NEWS-e ensemble forecasts initiated from the very frequent updates. In particular, preliminary work will evaluate the ability of model-derived measures of storm rotation (e.g., 2-5 km updraft helicity) to anticipate tornadic supercell thunderstorms and mesoscale convective systems.