PREEVENTS: Workshop on Integrated Framework for Modeling and Prediction of Extreme Events; College Park, Maryland; Summer 2016

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PREEVENTS: Workshop on Uncertainty Quantification in Forecasting Extreme Space WeatherThe project is to organize and provide travel support for a three-day workshop that targets the understanding of extreme events in space weather. The extreme nature of events arises when many conditions reinforce disturbances, such as geospace storms and substorms. The identification and characterization of these conditions are essential to uncertainty quantification and to improvements in modeling and prediction. The workshop will bring together experts in geospace modeling and simulation to explore common issues in the modeling and prediction of space weather using data-driven and first-principles approaches. A primary objective will be the identification of what is needed for the development of an integrated framework for uncertainty quantification that leverages advances in the two approaches to accelerate research to improve space weather forecasting. This is an important next step that will most likely lead to innovative and synergistic approaches to developing future capabilities. An important output of the workshop will be a comprehensive report on the current state of, and future outlook for, modeling and prediction of extreme space weather events and the associated natural hazards. The workshop provides a rare and valuable opportunity to broaden the education of postdocs, graduate and undergraduate students and enable networking. The workshop will contribute to the development of a multi-disciplinary community for disaster science, which is critical to accelerate the development of a framework for extreme event prediction and mitigation.The understanding of the statistics of rare events and their variability is critical to uncertainty quantification in space weather forecasting, and the paucity of data of extreme events requires development of new techniques. The nonlinear coupling among the different multiphysical processes underlying extreme events, and the incomplete knowledge of the underlying processes themselves, are among the main sources of uncertainty in first principles models. An essential step to improving forecasts of extreme space weather is uncertainty quantification, which is inherently interdisciplinary, requiring a comprehensive effort that brings together disciplinary researchers, computational scientists, modelers, and statisticians. The workshop provides a forum for identifying and exploring important synergisms in forecasting extreme events in space weather and its outcomes can impact extreme events forecasting in general.