Abstract
AbstractA comprehensive approach is presented to analyse season's coastal upwelling represented by weekly sea surface temperature (SST) image grids. Our three‐stage data recovery clustering method assumes that the season's upwelling can be divided into shorter periods of stability, ranges, each to be represented by a constant core and variable shell parts. Corresponding clustering algorithms parameters are automatically derived by using the least‐squares clustering criterion. The approach has been successfully applied to real‐world SST data covering two distinct regions: Portuguese coast and Morocco coast, for 16 years each.
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