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Probabilistic hurricane surge forecasting using parameterized surge response functions
Author(s) -
Irish Jennifer L.,
Song Youn Kyung,
Chang KuangAn
Publication year - 2011
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2010gl046347
Subject(s) - storm surge , surge , probabilistic logic , flooding (psychology) , parameterized complexity , meteorology , computer science , environmental science , algorithm , geography , storm , psychology , artificial intelligence , psychotherapist
A method is proposed for rapidly determining probabilistic maximum hurricane surge forecasts based on surge response functions, available meteorological information, and joint probability statistics. In using this method for Hurricane Ike, surge forecasts prior to landfall were computed in a matter of seconds. From a theoretical standpoint, surge response functions are scaling laws derived from high‐resolution numerical simulations. Surge response functions allow rapid algebraic surge calculation while guaranteeing accuracy and detail by incorporating high‐resolution computational results into their formulation. The Hurricane Ike example presented here shows that this method has the potential to improve evacuation planning and public early warning of hurricane flooding by providing rapid and accurate probabilistic projections of maximum surge.