Journal article
Forecasting tropical cyclone formation in the Fiji region: A probit regression approach using bayesian fitting
SS Chand, KJE Walsh
Weather and Forecasting | AMER METEOROLOGICAL SOC | Published : 2011
Abstract
An objective methodology for forecasting the probability of tropical cyclone (TC) formation in the Fiji, Samoa, and Tonga regions (collectively the FST region) using antecedent large-scale environmental conditions is investigated. Three separate probabilistic forecast schemes are developed using a probit regression approach where model parameters are determined via Bayesian fitting. These schemes provide forecasts of TC formation from an existing system (i) within the next 24 h (W24h), (ii) within the next 48 h (W48h), and (iii) within the next 72 h (W72h). To assess the performance of the three forecast schemes in practice, verification methods such as the posterior expected error, Brier sk..
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Funding Acknowledgements
We would like to acknowledge Johnny Chan of the Guy Carpenter Asia-Pacific Climate Impact Centre for inspiring this work. We greatly appreciate constructive comments by Elizabeth Ebert of the Australian Centre for Weather and Climate Research (CAWCR) on forecast verification procedures. The authors are also thankful to the Fiji Meteorological Services for providing cyclone data for the Fiji region. We also thank the University of Melbourne for providing partial funding for this work. The first author also appreciates the Australian government sponsored Endeavour Postgraduate Award for funding his doctorate degree at the University of Melbourne. Finally, we appreciate the comments of three anonymous reviewers.