Prediction of Sea Surface Temperatures in the Western Mediterranean Sea by Neural Networks using Satellite Observations

We use artificial neural networks (ANNs) to predict sea surface temperatures (SSTs) in the Western Mediterranean Sea. The ANNs are trained with meteorological variables as input and concurrent satellite-derived SSTs as target. The trained ANNs predict well both the seasonal and the interannual variability of SST in that region. We also reproduce the impact of the heat wave occurred during the summer of 2003 on the SSTs of the Western Mediterranean Sea. The ANN technique allows us to predict SST maps in the Western Alboran Sea for time coordinates before SST satellite-availability. The presence and later partial collapse of the Western Alboran gyre throughout 1980 is detected with good agreement by both the ANN predictions and the concurrent results from a 3-D circulation model. The same methodology is used to reconstruct incomplete SST satellite images.

GARCIA GORRIZ Elisa;  GARCIA SANCHEZ Joan; 

2007-06-19

AMER GEOPHYSICAL UNION

JRC37096

https://publications.jrc.ec.europa.eu/repository/handle/JRC37096,