Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/50070
Title: Sea surface temperature variability off north-west Africa: 1981-1989
Authors: Hernandez-Guerra, A. 
Nykjaer, L.
UNESCO Clasification: 2510 Oceanografía
250616 Teledetección (Geología)
Keywords: Orthogonal Function-Analysis
Santa-Barbara Channel
Atlantic
Ocean
California, et al
Issue Date: 1997
Publisher: 0143-1161
Journal: International Journal of Remote Sensing 
Abstract: A temporal and spatial Empirical Orthogonal Function (EOF) analysis has been performed on monthly maximum sea surface temperature (SST) satellite data over eight years (July 1981-August 1989) to examine the SST patterns of variability off north-west Africa. The first temporal EOF mode (75 per cent) represents the cooling and warming cycle over the region. The temporal amplitudes show an interannual variability with 1982 summer temperatures abnormally much colder, immediately preceding the largest El Nino phenomenon of the century. The second temporal mode (9 per cent) distinguishes a large-scale behaviour of the northern and southern areas of the region, the two areas being out of phase presumably related to the variability of the wind field. The first spatial EOF mode (66 per cent), which resembles the mean of all images, is stronger in fall, with a smaller second maximum at the beginning of spring. The second spatial mode (10 per cent) shows the coastal upwelling region where a seaward extension of upwelled water around 300km offshore is observed off Cape Blanc. All the modes show complex eastern boundary dynamics with different regimes north and south of Cape Blanc. The Cape Blanc vicinity must have some interesting dynamics with a sharp boundary evident in all the modes. Only these two first temporal and spatial EOF modes are significantly above the noise level. The EOF method is efficient in compressing monthly SST satellite imagery off north-west Africa, with a great percentage of the total variance being accounted by only two modes.
URI: http://hdl.handle.net/10553/50070
ISSN: 0143-1161
DOI: 10.1080/014311697217468
Source: International Journal of Remote Sensing [ISSN 0143-1161], v. 18, p. 2539-2558
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