Multi-year prediction model of North Atlantic hurricane activity |
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| Authors: | J B Elsner X Niu A A Tsonis |
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| Institution: | (1) Present address: Department of Meteorology, Florida State University, 32306-3034 Tallahassee, FL, USA;(2) Present address: Department of Statistics, Florida State University, 32306-3033 Tallahassee, FL, USA;(3) Present address: Department of Geosciences, University of Wisconsin-Milwaukee, 53201-413 Milwaukee, WI, USA |
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| Abstract: | Summary An empirical prediction algorithm is developed to assess the potential of useful multi-season forecasts of North Atlantic hurricane activity. The algorithm is based on combining separate univariate autoregressive moving average (ARMA) models for each of three dominant components of hurricane activity. A Bayesian criterion is used to select the order of each model. In a single retroactive hindcast experiment, the algorithm is found to make better hindcasts than an ARMA model of the detrended series. A real-time forecast of hurricane activity for the 1997 North Atlantic hurricane season proves to be more accurate than two competitive single-season forecast models. It is expected that the routine use of the forecast algorithm in an operational setting will result in only marginal skill against climatology; it could however offer considerable forecast value as realized by benefits to decision makers in the reinsurance industry.With 4 Figures |
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