Predictors of Tropical Cyclone Numbers and Extreme Hurricane Intensities over the North Atlantic Using Generalized Additive and Linear Models

• Published in: Journal of Climate
• Main Authors: Mestre, Olivier, Hallegatte, Stéphane
• Other Authors: Ecole Natl Meteorol, F-31057 Toulouse, France, affiliation inconnue, Inst Math, Lab Stat and Probabil, Toulouse, France, centre international de recherche sur l'environnement et le développement (CIRED), Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École des hautes études en sciences sociales (EHESS)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Météo-France Paris, Météo France
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2009
• Subjects: [SDE]Environmental Sciences; [SDE.MCG]Environmental Sciences/Global Changes; Soi; North Atlantic; North Atlantic oscillation
• Online Access: https://hal-enpc.archives-ouvertes.fr/hal-00716543; https://doi.org/10.1175/2008JCLI2318.1

International audience Fluctuations of the annual number of tropical cyclones over the North Atlantic and of the energy dissipated by the most intense hurricane of a season are related to a variety of predictors [global temperature, SST and detrended SST, North Atlantic Oscillation (NAO), Southern Oscillation index (SOI)] using generalized additive and linearmodels. This study demonstrates that SST and SOI are predictors of interest. The SST is found to influence positively the annual number of tropical cyclones and the intensity of the most intense hurricanes. The use of specific additive models reveals nonlinearity in the responses to SOI that has to be taken into account using changepoint models. The long-term trend in SST is found to influence the annual number of tropical cyclones but does not add information for the prediction of the most intense hurricane intensity.