Incorporating Mesoscale Ensemble Model Data in the Forecasting of Severe Convective Events

The forecasting of severe convective events is an important function at National Weather Service Forecast Offices (NWSFO). There are a wide variety of deterministic mesoscale models that provide forecasts of fields related to severe convection. However, ensemble model data provides additional probabilistic information on the range of model solutions. The forecaster can use this information to assess the likelihood of a particular model solution. The Texas Tech University WRF ensemble model system (TTU-ENS) consists of 42 members utilizing an ensemble Kalman filter (EnKF) and GEFS lateral boundary conditions. Its inner domain has a 4-km horizontal resolution and is centered over the U.S. southern plains. The ensemble output includes several fields useful to severe weather forecasts including means and probabilities of simulated reflectivity, probabilities of updraft helicity and surface wind speed, and “spaghetti” or “paintball” plots of individual member updraft helicity and reflectivity forecasts. In the spring of 2016 ensemble sensitivity information was added to the operational TTU-ENS. The sensitivity information allows the convective parameters listed above to be related back to earlier model forecasts of synoptic-type variables such as 500 hPa height, 300 hPa wind speed, etc. Forecasters can use this information to determine if the convective parameter forecasts are consistent with the trends of the larger scale pattern. This study will look at the TTU-ENS data from two events from the Spring of 2016 which produced severe weather in the Lubbock, Texas NWSFO service area and evaluate the usefulness of its output in the operational environment.