Uncovering spatial and temporal patterns of Adriatic Sea colour with self-organizing maps

Fifteen years (1998–2012) of monthly chlorophyll-like pigment concentrations from satellite images (JRC database) were analysed using self-organizing maps (SOMs). The aim was to classify the pigment structures of the Adriatic Sea into a number of patterns present in the data by this novel neural network method. The images are represented by a vector in the multidimensional data-space limited to the Adriatic area. We tried using several predefined patterns, finally selecting an optimal number of 16 spatial structures. Distinct neurons are primarily associated with patterns of different pigment concentration over the whole Adriatic area and with a different extension of the colour front along the west coast. Rare phenomena and variability limited to smaller areas were less represented in the SOM patterns. Although temporal pigment dynamics are synchronous in many areas of the Adriatic Sea, the analysis of their annual course resulted in ten temporal patterns. This representation also demonstrates the ability of the SOM method to connect areas with a particular seasonal variation in chlorophyll.