Improving the Understanding and Prediction of Nocturnal Convection through Advance Data Assimilation and Ensemble Simulations for Plains Elevated Convection At Night (PECAN)

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Researchers have long established that summer thunderstorms and convective precipitation are most frequent not in the afternoon, but after sunset over a large swath of the Great Plains of North America. Nocturnal rainfall is critical to the hydrology and agriculture of this region, and nocturnal mesoscale organized convection is often accompanied by severe weather. However, a conceptual framework describing how nocturnal convection initiates and evolves at night is still lacking, and the prediction of nocturnal convection still remains a scientific and technical challenge. To improve both our understanding of and our ability to forecast nocturnal convection, the Plains Elevated Convection At Night (PECAN) field experiment is planned to occur across portions of Oklahoma, Kansas and Nebraska from June 1 to 15 July 2015. PECAN promises to collect unprecedented observations that capture the multi-scale aspects of nocturnal convection. Such data will not only advance the understanding of key processes associated with nocturnal convection through observational analysis , but also will enable investigators to use advanced data assimilation (DA) and ensemble modeling systems to significantly advance both the understanding and prediction of nocturnal convective systems. This research focuses on the prediction component of PECAN, but also makes major contributions to the other three components of PECAN. Specifically, this research seeks funding to : 1) Support the dry run and field-phase of PECAN through generation of real-time convection-permitting ensemble forecasts initialized using an advanced ensemble based DA and ensemble forecast system; 2) Assimilate special PECAN observations including ground-based remote sensing and compare these simulations against the real-time simulations and the observations to assess the role that the unique PECAN observations play in improving predictive skill; 3) Comprehensively diagnose the ensemble analyses and simulations to determine the dynamical and physical processes that initiate and maintain nocturnal convection and control their structure and evolution; 4) Comprehensively evaluate ensemble analyses and forecasts against special PECAN observations to determine the appropriate modeling strategies (e.g., grid spacing; physical parameterization) for improved prediction.Intellectual Merit :This effort will advance our knowledge of the processes that control the initiation, maintenance, evolution and structure of elevated nocturnal convective systems. These goals will be accomplished through a focus on the next generation of convection-permitting models and advanced DA techniques. The simulations under this project will play an important role in bridging between efforts of other PECAN investigators focused on observational analysis of PECAN data and on idealized modeling. This effort will also address the inherent role that bores and stable layer disturbances play in the maintenance of elevated nocturnal systems through analysis of simulations and comparison against observations. Ensemble diagnostics will allow for a novel assessment of the capability of a convection-permitting model simulation to reproduce these key processes. The research findings will provide new insights into advancing DA strategies, model physics and observing strategies of high impact convective weather events.Broader Impacts :This research will address one of the most important goals of weather research - to improve our ability to accurately predict intense hazardous weather that causes large monetary loss, injuries and fatalities. It will directly address three established national priorities in weather: Warn on Forecast for High Impact Weather, the Next-Generation Forecast System, as key component of the Next-Generation Air Transportation System, and Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. It will provide much needed education and training in the areas of advanced DA and high-resolution ensemble modeling and numerical prediction and expose the next generation of modeling and DA experts to a major scientific field experiment. The research findings have a direct path to operations because the ensemble DA system to be used is developed based on the new US operational DA system, and because of the significant roles of the PIs in and/or linkage of the PIs have made with NOAA National Severe Storm Lab (NSSL), National Centers for Environmental Prediction (NCEP) Storm Prediction Center (SPC) and Environmental Modeling Center (EMC).