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A Statistical Prediction Model for East Pacific and Atlantic Tropical Cyclone Genesis

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February 22, 2012
Stephanie Slade
Hosted by Eric Maloney (advisor), Dave Thompson, Edwin Chong (Electrical and Computer Engineering)


A statistical model is developed via multiple logistic regression for the prediction of weekly tropical cyclone activity over the East Pacific and Atlantic Ocean regions using data from 1975 to 2009. The predictors used in the model include a climatology of tropical cyclone genesis for each ocean basin, an El Niño-Southern Oscillation (ENSO) index derived from the first principal component of sea surface temperature over the Equatorial East Pacific region, and two indices representing the propagating Madden-Julian Oscillation (MJO). These predictors are suggested as useful for the prediction of East Pacific and Atlantic cyclogenesis based on previous work in the literature and are further confirmed in this study using basic statistics. Univariate logistic regression models are generated for each predictor in each region to ensure the choice of prediction scheme. Using all predictors, cross-validated hindcasts are developed out to a seven week forecast lead. A formal stepwise predictor selection procedure is implemented to select the predictors used in each region at each forecast lead.

Brier skill scores and reliability diagrams are used to assess the skill and dependability of the models. Results show a significant increase in model skill at predicting tropical cyclogenesis by the inclusion of the MJO out to a three week forecast lead for the East Pacific and a two week forecast lead for the Atlantic. The importance of ENSO for Atlantic genesis prediction is highlighted, and the uncertain effects of ENSO on East Pacific tropical cyclogenesis are re-visited using the prediction scheme. Future work to extend the prediction model with other predictors is discussed.