The effect of the synoptic scale atmospheric circulation on the urban heat island phenomenon over Athens, Greece, was investigated and quantified for a period of two years, using a neural network approach. A neural network model was appropriately designed and tested for the estimation of the heat island intensity at twenty-three stations during the examined period. The day-by-day synoptic scale atmospheric circulation in the lower atmosphere for the same period was classified into eight statistically distinct categories.
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