A statistical/dynamical model for North Atlantic seasonal hurricane prediction
PublisherAmerican Geophysical Union
Rights accessOpen Access
Colorado State University (CSU) has been issuing seasonal hurricane forecasts since 1984, with statistical modeling techniques primarily underpinning these outlooks. CSU has recently begun issuing statistical/dynamical forecasts, using the SEAS5 forecast system from the European Centre for Medium‐Range Weather Forecasts to forecast the three predictors that currently comprise CSU's early August statistical forecast model. SEAS5 shows skill at forecasting all three of these July predictors from an initialization as early as 1 March. The SEAS5 model forecasts for the three parameters are then regressed against seasonal accumulated cyclone energy. The model has a cross‐validated correlation skill of r = 0.60 with accumulated cyclone energy for a 1 March initialization, improving to r = 0.67 for a 1 June initialization over the period from 1982–2019. The combination of the statistical/dynamical model with the currently existing statistical models shows improved skill over either model individually for the April, June, and July outlooks.
CitationKlotzbach, P.; Caron, L.-P.; Bell, M. A statistical/dynamical model for North Atlantic seasonal hurricane prediction. "Geophysical Research Letters", Octubre 2020, vol. 47, núm. 20, e2020GL089357.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder