A Look at the NSSL-WRF Forecast Output for the Violent Tornado Events in Central Oklahoma on May 19th and 20th, 2013

On May 19th and 20th, 2013, two violent (EF4 and EF5) tornadoes struck central Oklahoma. The May 19th event also included an EF3 tornado, with both tornadoes occurring east of the Oklahoma City metropolitan in sparsely populated areas. However, on May 20th, an EF5 tornado, the second such tornado to strike Moore, OK in the past 14 years, resulted in over 2000 destroyed and damaged homes and 24 fatalities. In both cases, the combination of radar and spotter reports aided the NWS Norman Forecast office in issuing a tornado warning with 15 to 20 minutes of lead time. Within the next 10 years, a convective-scale probabilistic hazardous weather forecast system, called Warn-on-Forecast, may be implemented to significantly increase severe weather and tornado lead times. It is envisioned that these forecasts would predict the approximate time, location, and intensity of severe events several hours in advance. An experimental 4-km grid-spacing version of the WRF model run in real-time at NSSL, which is known as the NSSL-WRF, has been used to provide input into the Warn-on-Forecast process. The NSSL-WRF provides storm-scale guidance to SPC forecasters and serves as a testing ground for the development of storm-scale model diagnostics. The NSSL-WRF, along with other storm scale models, were examined during the five week 2013 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment. Various fields from these models were compared to observations during formal model evaluations to gauge their relative performance/utility, and forecast output was also used in the preparation of daily experimental severe weather forecasts. This manuscript takes a look at the 00z NSSL-WRF model output the evening before the May 19th and 20th tornadic events to examine the forecast output 20-22 hours before storms developed. While the NSSL-WRF output was better on May 19th than the 20th, the model on both days showed great promise in providing specific and accurate information on the timing, location, intensity and mode of storms many hours before storms develop.