Teleconnections between sea-surface temperature anomalies and air temperature in northeast Brazil

Details Teleconnections between sea-surface temperature anomalies and air temperature in northeast Brazil Teleconnections between sea-surface temperature anomalies and air temperature in northeast Brazil

Apr 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006jastp..68..781s&link_type=abstract

Journal of Atmospheric and Solar-Terrestrial Physics, Volume 68, Issue 7, p. 781-792.

Physics

Scientific paper

The relationship between sea-surface temperature (SST) and air temperature in northeast Brazil was analyzed using sea-surface temperature anomalies (SSTA) and geographic coordinates. Mean monthly time series of air temperatures (daily mean, maximum and minimum) of 69 meteorological stations and SSTA from the Atlantic (North and South), the Global Tropics and the Pacific (Niño 3 area) Oceans were analyzed within the framework of principal component analysis (PCA) and linear regression approach. The PCA model was used to identify the dominant temporal and spatial variability patterns of air temperature estimated by the SSTA model and observed air temperature in northeast Brazil. The main objective of this research was to establish a predicting model from the geographic coordinates and SSTA, capable of reconstructing air temperature time series. Data analysis indicated statistically significant correlation (p<0.01) between SST and air temperature. This relationship was less using the SST from the Equatorial Pacific Ocean (Niño 3 area) and it also proved to be statistically significant (p<0.01). Results also showed that air temperature in northeast Brazil can be obtained with reasonable accuracy as a function of the geographic coordinates and SSTA. A substantial amount of data variance was accounted for by the first two components. The first and the second principal components (PC) of the mean daily air temperature time series, reconstructed on the basis of the SSTA, explained 90.2% (North Atlantic), 90.7% (South Atlantic), 91.5% (Global Tropics), 92.6% (Pacific Niño 3) and 64.4% (observed data) of the data variance. The first and the second PCs have been associated with the main atmospheric systems that act in northeast Brazil.

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