A new empirical method to estimate mesoscale three-dimensional oceanic thermal structures from nearreal-time satellite altimetry data is presented. The method uses a two-layer model with a novel set of empirical parameters for stratification. Empirical parameters, which are calculated from altimetry data and in situ temperature and salinity profiles obtained from globally distributed Argo floats, allowed for significant increases in the spatiotemporal mapping of mesoscale temperature distributions. The accuracy of the method was validated by comparing the estimated isothermal depths with in situ temperature data. Three case studies in different regions and seasons showed excellent agreement, with a strong linear correlation between the estimated and observed isothermal depths. The authors present the details of the method, discuss its limitations, and demonstrate the ecological relevance of the method for fisheries management by successfully predicting pelagic fish distributions.
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