Rainy Season Migration across the Northeast Coast of Brazil Related to Sea Surface Temperature Patterns

Author:

Pereira Marcos Paulo Santos1ORCID,Couto Fabiana2ORCID,Schumacher Vanúcia3ORCID,Silva Fabrício Daniel dos Santos1ORCID,Barros Gomes Helber1ORCID,da Silva Djane Fonseca1,Gomes Heliofábio Barros1ORCID,Costa Rafaela Lisboa1ORCID,Justino Flávio B.4ORCID,Herdies Dirceu Luís3ORCID

Affiliation:

1. Institute of Atmospheric Sciences, Federal University of Alagoas, Maceió 57072-900, Alagoas, Brazil

2. Climainfo Institute, São Paulo 05454-030, São Paulo, Brazil

3. National Institute for Space Research, Cachoeira Paulista 12630-000, São Paulo, Brazil

4. Department of Agricultural and Environmental Engineering, Federal University of Viçosa, Viçosa 36570-000, Minas Gerais, Brazil

Abstract

Accurate regional seasonal forecasts of the rainy season are essential for the implementation of effective socioeconomic activities and policy. However, current characteristics of the period of occurrence of the rainy season in the Eastern Northeast Brazil (ENEB) region demonstrated that maximum precipitation varies substantially depending on the period analyzed. From 1972 to 2002, the rainy season occurred during the June–July–August (JJA) quarter, while from 1981 to 2011, it occurred in the April–May–June (AMJ) quarter. To access how these differences may be due to different patterns of sea surface temperature (SST), using observed precipitation and SST data from NOAA for the period from 1982 to 2018, this study identified the spatial patterns of inter-annual changes in Pacific and Atlantic SST related to the occurrence of the ENEB rainy seasons. We focus on the statistical method of symmetric mean absolute percentage error (sMAPE) for forecasting these periods based on SST information. Our results revealed five different quarterly periods (FMA, MAM, AMJ, MJJ, JJA) to the rainy season, in which MJJ is more prevalent. The sMAPE values of the SST patterns are inversely proportional to precipitation in the ENEB. Hence, it may be concluded that our climate analysis demonstrates that seasonal SST patterns can be used for forecasting the period of the rainy season.

Publisher

MDPI AG

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