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Piece‐wise constant cluster modelling of dynamics of upwelling patterns

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A 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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Coastal upwelling Data recovery clusterings Spatiotemporal clustering SST Images Time series segmentation

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