Going Old School—Using raw surface observations and objective analysis to accurately forecast a tornado environment

It is well known that convectively-induced outflows can modify existing air masses to add support to a tornadic environment. On the morning of June 19, 2013, a mesoscale convective system (MCS) moved southeast through the Texas Panhandle and into the Rolling Plains region of West Texas causing flash floods in Caprock Canyon State Park. This MCS generated a southwestward moving outflow boundary that propagated through the South Plains region of West Texas and into the eastern plains of New Mexico creating an environment suitable for supercell thunderstorm development and tornadoes. Deterministic runs of the Texas Tech University Weather Research and Forecast (TTU-WRF) model and the High Resolution Rapid Refresh (HRRR) model struggled to identify this environment. However, careful subjective examination of raw surface observations along with objective analysis data proved instrumental in accurately forecasting the tornado environment.

A comparison of raw surface observations, objective analysis, and model data will be shown as it relates to the short-term forecast problem. We will show that hourly analysis of raw surface observations plus objectively analyzed data out-performed the deterministic run of the TTU-WRF and HRRR models. In this poster, we hope to convey that using raw surface observations, objective analysis products and other real-time data is imperative to a successful tornado environment forecast.