92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Sunday, 22 January 2012
Correlating Errors in Hurricane Forecasts to Improve Probabilistic Storm Surge
Hall E (New Orleans Convention Center )
Alexandra N. Ramos, University of Puerto Rico, Aguada, PR; and A. A. Taylor and A. Kramer

Storm surge is the greatest threat to life during a hurricane; its study is of great relevance in the effort to minimize the impact of hurricanes on coastal populations. The research in this study determines if errors in hurricane forecasts are correlated, and if such correlations can be used to improve the probabilistic storm surge (p-surge) model developed and maintained by the Meteorological Development Lab (MDL) at the National Weather Service. The National Hurricane Center (NHC) uses p-surge guidance to help with their storm surge forecasts, so improving p-surge will reduce the social and economic impact of storm surge along coastlines. P-surge utilizes NHC forecasts of hurricane position and maximum wind velocity, as well as statistics of historic errors in NHC's forecast in its probability calculations. For this investigation, statistical methods were implemented to explore possible correlations between errors in the position and the maximum wind velocity, as well as to look for improvements in the historic errors of the forecast in the last 3 years. These methods include calculating the standard deviation and correlation between the maximum velocity, cross track, and along track differences between NHC's forecasts and their hindcast results. The storm advisories analyzed for this study ranged from the year 2000 through 2010. If correlations are discovered, p-surge could be improved by implementing these correlations into its calculations of possible storm surges.

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