Evaluating Predictability of Mesoscale Circulations, Morphologies, and Rainfall Evolution for Warm Season Convective Systems

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Warm season mesoscale convective system (MCS) rainfall prediction remains a difficult challenge. Accurate simulation of MCSs is hampered by deficiencies in both initialization data and model parameterizations of processes important in these systems' development and evolution. The Principal Investigator's previous projects have examined several approaches toward improving numerical model Quantitative Precipitation Forecast (QPF) guidance for summer convection. The research under this award builds on prior research to examine differences in the predictability of mesoscale circulations and rainfall associated with MCSs in the Midwest/Plains possessing different morphologies.To allow for thorough evaluation of observed events and detailed verification of model simulations, MCS cases will be primarily chosen from two recently completed field projects. The research will pursue two primary goals. First, careful analysis of observed MCSs will further understanding about the circulations important to different morphologies and allow for determination of systematic biases in the near-cloud resolving simulations of the circulations, rainfall, and morphologies of these events. Second, sensitivity tests performed with various configurations of the Weather Research and Forecasting (WRF) numerical model will help establish optimal methods (e.g., dynamics-physics settings) for successful simulation of warm season MCS rainfall with this newly developed yet heavily used research and forecasting model. The Principal Investigator will evaluate the hypothesis that mixed physics ensembles may be the most direct way to improve warm season mesoscale QPF because differences in physics schemes enhance spread. The Principal Investigator will contrast diversity obtained through the use of different microphysical schemes or parameters within them at near-cloud resolving grid spacings with spread occurring from the use of different dynamic cores and initial conditions. Also, for some cases a range of grid spacings from 4 km to 10 km will be used to examine impacts in fully explicit cloud runs from changes in grid spacing. In addition, coarser runs will be performed to compare the usefulness of ensemble systems with many members that require the use of convective parameterizations (which are known to possess large errors) with individual fully explicit 4 km deterministic forecasts, or small ensembles (4-8 members) of these finer grid runs. The study will implement some relatively new methodologies, including: (i) strategies for verification of high resolution models that will improve understanding about verification/evaluation of rainfall on refined spatial and temporal scales, and (ii) a factor separation approach for adequate interpretation of sensitivity analyses. This effort has several broader impacts. It focuses on one of the most challenging short- range forecast problems -- warm season convective rainfall occurring typically in weakly forced environments, and addresses a present central QPF issue -- the use of fine enough grid spacing to neglect convective parameterizations. Completion of the research will improve understanding of the development and evolution of convective systems in the Midwest/Plains, and assist in improvements of forecasts issued to the public and various industry sectors. The WRF model was designed to become a primary vehicle for both research and short-range operational forecasting in the coming years in the United States, facilitating broader impacts of the research. In addition, the study will support graduate students. Publication of research results in atmospheric science journals and presentation at conferences and workshops will permit research findings to directly benefit operational forecasters and through them, the general public.