Rainfall variability over Alagoas under the influences of SST anomalies

The rainfall variability for the state of Alagoas, Northeast of Brazil, was evaluated based on the Standardized Precipitation Index (SPI). Harmonic decomposition was applied to 31 years-long (1960–1990) series of SPI, from 33 stations, to relate their modes of variability to El Niño-Southern Oscilla...

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Bibliographic Details
Published in:Meteorology and atmospheric physics 2017-04, Vol.129 (2), p.157-171
Main Authors: Lyra, G. B., Oliveira-Júnior, J. F., Gois, G., Cunha-Zeri, G., Zeri, M.
Format: Article
Language:English
Subjects:
Aquatic Pollution
Atmospheric physics
Atmospheric Sciences
Drought
Droughts
Drying
Earth and Environmental Science
Earth Sciences
El Nino
Harmonic analysis
Harmonics
Intertropical convergence zone
Marine
Math. Appl. in Environmental Science
Meteorology
Ocean currents
Original Paper
Rain
Rainfall
Sea surface temperature
Southern Oscillation
Spectral analysis
Standardized precipitation index
Temperature
Terrestrial Pollution
Waste Water Technology
Water Management
Water Pollution Control
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Summary:The rainfall variability for the state of Alagoas, Northeast of Brazil, was evaluated based on the Standardized Precipitation Index (SPI). Harmonic decomposition was applied to 31 years-long (1960–1990) series of SPI, from 33 stations, to relate their modes of variability to El Niño-Southern Oscillation (ENSO) and the Atlantic Ocean sea surface temperature (SST). The most important harmonics identified by the spectral analysis had periods of 10–15 and 2–3 years, followed by other oscillations with smaller periods. The 10–15 years harmonic was associated with the Atlantic interhemispheric SST gradient (AITG), a cross-equatorial dipole which impacts the northeast region of Brazil by influencing the position of the intertropical convergence zone (ITCZ), leading to dry or wet conditions. The 2–3 years harmonic was consistent with the variability of ENSO events. The harmonic analysis is a powerful tool to identify the principal modes of variability of SPI. Although the magnitude of SPI is underestimated in some cases, this tool significantly increases the knowledge of the main drivers of rainfall and droughts in the region.
ISSN:0177-7971
1436-5065
DOI:10.1007/s00703-016-0461-1