Abstract
The Tropical and South Atlantic Ocean are characterized by important large scale features that have seasonal character. The interactions between atmospheric and oceanic phenomena compose a complex system where variations in physical parameters affect the distribution of primary production. Previous studies showed that the variability of physical parameters displays high values of cross-correlation with chlorophyll-a, with strong dependence on latitude and variability in the biological response time. This study aims to correlate data of chlorophyll-a from MODIS with the results of a hydrodynamic numerical model, in the period 2003 - 2009. The annual and semi-annual signals are predominant both in MODIS and model data but, even excluding these components, the residual correlations are still high. On the other hand, annual and semi-annual signals have smaller standard deviation than the remaining (residual) frequencies. The cross-correlations between chlorophyll-a and salinity, temperature and surface elevation showed spatial distribution patterns with well-defined latitudinal character, presenting higher modulus of correlation for temperature and salinity, above +0.6 in the polar region and below -0.5 in the tropical area. A general pattern of negative correlations in the regions of low concentration and positive in regions of high concentration was obtained, except the Equator (region of high chlorophyll concentration, which is characterized by a negative correlation for all variables, except the intensity of the currents). The cross-correlations between chlorophyll and physical parameters corroborate the pattern found in the correlations considering lag zero, stressing aspects as the positive correlation with the intensity of the currents in the equatorial region and the negative correlation with the surface elevation inside the South Atlantic Subtropical Gyre (SASG), both presenting immediate response. The analysis of spatial distributions of the cross-covariance of Fourier spectra between chlorophyll and each of the physical variables, in the transect 20°W, showed that temperature and salinity presented the best defined signals, especially in the periods of 3.5, 2.3, 0.7, and 1.7 years, with varying spatial distributions and time lags. These signals are found in the literature, being associated with ENSO phenomena.
Highlights
The use of remote sensing of ocean color in the study of biological phenomena has been increasingly frequent
One can observe a pattern of high concentrations in regions of coastal upwelling, equatorial upwelling and high latitudes. These results corroborate those obtained by Wang et al [30] for the climatology of SeaWiFS data in the period 1997-2007, which checks the seasonality of chlorophyll-a in the equatorial region, the Amazon and Congo River discharge areas and upwelling regions in North Africa, as can be observed in the distribution of the standard deviation of the annual and semiannual signals
The cross-correlations between chlorophyll-a and physical parameters corroborate the pattern found in the correlations considering lag zero, stressing aspects as the positive correlation with the intensity of the currents in the equatorial region and the negative correlation with the surface elevation inside the South Atlantic Subtropical Gyre (SASG), both presenting immediate response
Summary
The use of remote sensing of ocean color in the study of biological phenomena has been increasingly frequent. Chlorophyll-a, for example, has a well-defined spectral response. These remote measurements have shown good performance, as in study of Kampel et al [1], where estimates of the concentrations of chlorophyll-a by remote sensing (SeaWiFS sensor algorithms), when compared to in situ measurements in the southeastern Brazilian coastal region, showed good consistency. Algorithms used in the inference of chlorophyll present relatively accurate results in Case I waters (oceanic regions). Often they fail in Case II waters (coastal regions), as shown in a study by Metsamaa et al [4] with MODIS sensor data for the Baltic Sea Region
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