The Annual Cycle of Satellite-derived Sea Surface Temperature in the Southwestern Atlantic Ocean

Guillermo P. Podestá Division of Meteorology and Physical Oceanography, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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Otis B. Brown Division of Meteorology and Physical Oceanography, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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Robert H. Evans Division of Meteorology and Physical Oceanography, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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Abstract

The annual cycle of sea surface temperature (SST) in the southwestern Atlantic Ocean was estimated using four years (July 1984-July 1988) of NOAA Advanced Very High Resolution Radiometer observations. High resolution satellite observations at 1-km space and daily time resolution were grided at 100-km space and 5- day time intervals to develop an analysis dataset for determination of low fluency SST variability. The integral time scale, a measure of serial correlation, was found to vary from 40 to 60 days in the domain of interest. The existence of superannual trends in the SST data was investigated, but conclusive results could not be obtained. The annual cycle (and, in particular, the annual harmonic) explains a large proportion of the SST variability. The estimated amplitude of the cycle ranges between 5° and 13°C throughout the study area, with minima in August-September and maxima in February. The resultant climatology is compared with an arbitrary 5-day satellite SST field, and with the COADS/ICE SST climatology. It was found that the higher resolution satellite- based SST climatology resolves boundary current structure and has significantly better structural agreement with the observed field.

Abstract

The annual cycle of sea surface temperature (SST) in the southwestern Atlantic Ocean was estimated using four years (July 1984-July 1988) of NOAA Advanced Very High Resolution Radiometer observations. High resolution satellite observations at 1-km space and daily time resolution were grided at 100-km space and 5- day time intervals to develop an analysis dataset for determination of low fluency SST variability. The integral time scale, a measure of serial correlation, was found to vary from 40 to 60 days in the domain of interest. The existence of superannual trends in the SST data was investigated, but conclusive results could not be obtained. The annual cycle (and, in particular, the annual harmonic) explains a large proportion of the SST variability. The estimated amplitude of the cycle ranges between 5° and 13°C throughout the study area, with minima in August-September and maxima in February. The resultant climatology is compared with an arbitrary 5-day satellite SST field, and with the COADS/ICE SST climatology. It was found that the higher resolution satellite- based SST climatology resolves boundary current structure and has significantly better structural agreement with the observed field.

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