Dustan Wheatley, CIMMS, Univ. of Oklahoma, NOAA/NSSL

Real-time storm-scale data assimilation and forecasting experiments for NOAA’s Warn-on-Forecast Project

Kent Knopfmeier, Thomas Jones, David Dowell, Therese Thompson, Louis Wicker


The NOAA Warn-on-Forecast (WoF) Project is tasked with developing a regional 1-km storm-scale prediction system for the United States that assimilates radar, satellite, and conventional (e.g., surface) data. The proposed WoF system will generate new 0-3 h probabilistic forecasts 3-4 times an hour, for the purpose of predicting hazardous weather phenomena, such as thunderstorm rotation, hail, high winds, and flash flooding. A prototype system, known as the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e), is based on the Weather Research and Forecasting (WRF) model with 3-km (1-km) horizontal grid spacing for real-time (retrospective) experiments, and was tested during May 2015 with promising results.

This year, the NEWS-e will be run in realtime each day from 2 May – 3 June, which coincides with the NOAA Hazardous Weather Testbed 2016 Spring Forecast Experiment. The starting point for each day’s experiment will be a 3-km, hourly cycled WRF ensemble under development at the Global Systems Division (GSD). The 1500 UTC forecast cycle from the GSD ensemble will provide initial and boundary conditions for the NEWS-e, a 36-member ensemble covering a 1000-km wide region with very frequent (sub-hourly) updates. The daily NEWS-e domain location will target the primary 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 an ensemble Kalman filter approach. A 90-min ensemble forecast will be initialized from the resultant storm-scale analyses every 30 minutes during each hour of the real-time experiment. Preliminary work will evaluate the ability of model-derived measures of low-level (e.g., vorticity) and mid-level (e.g., updraft helicity) storm rotation to anticipate tornadic supercell thunderstorms and mesoscale convective systems. Probabilistic forecasts of thunderstorm winds and flash flooding will also be evaluated.

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