WRF-ARW Physics Parameterizations Influence on Mesoscale Convective System (MCS) Forecasts and Development of Process-Oriented Verification for WRF-ARW Output

Friday, 19 December 2014
Taleena Rae Sines, Iowa State University, Ames, IA, United States and Raymond W Arritt, Iowa State Univ, Ames, IA, United States
Several methods of verification such as statistical analysis of precipitation estimate performance, but don't reveal if the model is reproducing physical storms occurring in nature. The goal of this procedure is to assess whether accurate precipitation forecasts reflect sound physics. We have developed an algorithm for mesoscale convective system (MCS) detection and tracking as a step toward process-oriented verification of regional climate models. The algorithm detects MCSs as contiguous regions of precipitation exceeding 1.5mm/hr co-located with 925-700hPa thickness change of <5 m/h. The latter criterion reflects mesoscale evaporative cooling. When tested with 3-hourly North American Regional Reanalysis (NARR) data from Apr.-Sept. 1993, the algorithm detected 98 MCSs. Of these, 10 were determined as false alarms after comparing precipitation and infrared satellite imagery. The end result of this research will be a regional climate model configured with parameterization schemes that most accurately reproduce MCSs over the central United States and a tool which is applicable to the detection and tracking of MCSs in model output.