First Demonstration of the NSSL Experimental Warn-on-Forecast System as Part of the 2017 Spring Experiment

The Warn-on-Forecast project at the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory in Norman, OK, USA, aims to improve severe weather forecasts, warnings, and decision support for high-impact events (e.g., tornadoes, hail, wind, and extreme rainfall) by leading convective-scale research and development activities that enable a new paradigm where convection-resolving, ensemble model forecasts become a key resource for NOAA National Weather Service (NWS) watch and warning operations. The result of these efforts is the development of an experimental Warn-on-Forecast system called the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e).

NEWS-e is a frequently updated, regional-scale, on-demand convection-resolving ensemble analysis and prediction system, nested with an hourly convection-allowing ensemble forecast system. The 2017 version of this system assimilates radar and satellite data every 15 minutes, surface data every 30 minutes, and generates new probabilistic 3-hour and 1.5-hour forecasts at the top and bottom of each hour, respectively, at grid spacing of 3 km. This multiscale data assimilation system uses the advanced research version of WRF, version 3.8+ (ARW) to produce storm-scale ensemble analyses and forecasts. The NEWS-e background is the experimental HRRR-ensemble (HRRRE) provided by the NOAA ESRL/Global Systems Division. A 15-hour ensemble forecast is launched from the 1500 UTC HRRRE analysis to provide boundary conditions for the NEWS-e system for the period 1800 UTC Day 1 – 0600 UTC Day 2 and a 1-hour ensemble forecast is launched from the 1700 UTC HRRRE analysis to provide initial conditions for the NEWS-e system at 1800 UTC.

With the aim of providing useful forecast guidance between the issuance of watches and warnings, NEWS-e’s use in this capacity was explored within the NOAA Hazardous Weather Testbed (HWT) for the first time during the 2017 Spring Experiment. The primary goals of this part of the experiment were to 1) survey participants’ interpretations of different probabilistic forecast variables and visualizations, 2) explore how short-term ensemble forecast guidance from NEWS-e could be used by an expert forecaster to produce a series of 1-hour severe weather outlooks, and 3) observe how the forecaster’s understanding, use, and attitudes about NEWS-e guidance evolved through the experiment. Each morning, verification was performed by comparing to the “practically perfect” outlooks created after the outlook period. This presentation will share preliminary results from analysis of the outlooks and the evolution of the expert forecaster’s use of NEWS-e during the experiment. The results from the survey will be shared in a separate presentation.