Incorporating Global Model Uncertainty Information into the Monte Carlo Wind Speed Probability Model

Thursday, 21 April 2016: 9:00 AM
Ponce de Leon C (The Condado Hilton Plaza)
Andrea B. Schumacher, CIRA/Colorado State Univ., Fort Collins, CO; and M. DeMaria

Tropical cyclone forecasts are inherently uncertain. As such, the incorporation of uncertainty into forecast products continues to be an active and important topic of study. Currently, forecast-specific uncertainty information is incorporated into the National Hurricane Center (NHC) Wind Speed Probabilities through the incorporation of Goerss Predicted Consensus Error, a proxy for track forecast uncertainty.

In this study we explore alternative methods for incorporating track uncertainty into the Monte Carlo wind speed probability model (MC Model), the model upon which the NHC wind speed probabilities are based, through the use of global model TC track forecasts. Global model tracks are incorporated in a variety of ways, from the development of model-based wind speed probabilities based on past model error statistics to the explicit use of global model ensemble tracks to generate hybrid statistical-dynamical wind speed probabilities. We will demonstrate the strengths and weaknesses of each of these methods through case studies and show the results of basin-wide seasonal verification for each method compared to those of the current operational MC Model.

Disclaimer: The views, opinions, and findings contained in this article are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration (NOAA) or U.S. Government position, policy, or decision.

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