The optimization of southeast Texas extreme rainfall prediction utilizing the Weather Research and Forecast - Environmental Modeling System

The research focuses on varying multiple initialization datasets, along with planetary boundary layer and microphysical schemes, for a Houston, Texas-centered, local high - resolution Weather Research and Forecast - Environmental Modeling System (WRF - EMS) numerical weather prediction model. Statistical and graphical analyses of WRF - EMS model output and verification will be explored in an attempt to accurately simulate the April 18th, 2009 high rainfall event that adversely-affected the greater Houston metro area. Previous work has shown that high-resolution modeling has historically performed poorly on weakly-forced events (e.g., sea breeze boundary, summer convection) while performing more favorably with stronger-forced convective events (e.g., cold frontal passages, shortwave disturbances). Thus, numerous WRF - EMS model runs have been performed upon this cool season (i.e., stronger synoptically-forced) episode. Numerous WRF - EMS model simulations were run employing differing initial conditions while varying planetary boundary layer and microphysical scheme combinations. The validation of the numerical weather prediction model output will be against quality-controlled Weather Service Doppler radar (WSR-88D) data (i.e., Stage IV radar data). The inclusion of high-resolution land-surface modeling data into the WRF - EMS system will be analyzed to discern this data’s overall significance, or consequence, to final WRF - EMS model output. The research goal is to determine if, through iterative computer model simulation, a specific initialization-planetary boundary layer-microphysical scheme combination could more accurately re-create the convective characteristics of a southeastern Texas heavy, or extreme, rainfall event.