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Exploring the feasibility of empirical, dynamical and combined probabilistic rainy season onset forecasts for São Paulo, Brazil
Author(s) -
Coelho Caio A. S.,
Firpo Mári A. F.,
Maia Aline H. N.,
MacLachlan Craig
Publication year - 2017
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.5010
Subject(s) - climatology , probabilistic logic , wet season , environmental science , meteorology , geography , statistical model , regression , statistics , mathematics , cartography , geology
This study investigates the feasibility and presents an assessment of probabilistic rainy season onset forecasts for São Paulo, Brazil, located in a region with a well‐defined wet season from mid‐austral spring (October) to austral autumn (March/April). The probabilistic forecasts were produced with (1) a simple empirical Cox‐regression model using July Niño‐3 index as predictor, (2) the dynamical coupled atmosphere‐land‐surface‐ocean‐sea‐ice model used in the UK Met Office Global Seasonal Forecast System ( GloSea5 ) and (3) a procedure that combines the empirical and dynamical model onset probabilistic forecasts. The probabilistic forecast assessment was performed over the 1996–2009 retrospective forecast period for the event rainy season onset earlier (or later) than the historical (mean) onset date. The three investigated approaches resulted in similar discrimination ability of around 80%, which represents the probability of the probabilistic forecasts correctly distinguishing earlier from a later than mean onsets, suggesting good potential for rainy season onset forecasts for São Paulo. The robustness of this assessment for an extended period (longer than 1996–2009) and for a region (20°S, 25°S, 45°W, 55°W) that includes the city of São Paulo was checked, reinforcing the validity of the obtained results at both local and regional scales.