资源环境科技发展态势分析平台

This paper presents a simple methodology to identify sea breeze frontal passage in the city of Sao Paulo, Brazil, based in hourly wind direction data. Fifty-year time series of annual frequency of sea breeze frontal passage and of its time of arrival in Sao Paulo are generated and related to global climate indicators and local variables. The frequency of occurrence and time of arrival of sea breeze shows long-term oscillations in the interannual and decadal time scales. Multiple regression is used to identify the variables that explain the observed variance of both frequency of occurrence and timing of the sea breeze in Sao Paulo. Local variables such as air temperature in Sao Paulo and sea surface temperature (SST) in the vicinity of the coast explain more than 95% of the total R-2 (R-2 = 51%) in a multiple regression model of the frequency of sea breeze frontal passage. Global climate indices such as the Atlantic Multidecadal Oscillation, the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation explain about 85% of the total R-2 (R-2 = 52%) in a multiple regression model of the time of arrival of the sea breeze in Sao Paulo. The sea breeze circulation is shown to impact the rainfall in Sao Paulo and vicinity and to be associated with extreme rainfall events.