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For the analysis and prediction of coastal upwelling in a study region off the northwest African coast, artificial neural networks are applied to wind data and remotely sensed sea surface temperature data. The coastal upwelling phenomenon is seen as an input output system, built up by the dependence between local wind events as input and upwelling, quantified by the sea surface temperature index, as output. To gain a priori knowledge about the input output system it is studied from a theoretical point of view with coastal upwelling simulations, performed with a three dimensional ocean circulation model on artificial wind data. A mixture of neural networks is applied for system analysis and prediction.

Additional information

Authors: KRIEBEL S K T, Institut für Informatik, Technische Universität München (DE);BRAUER W, Institut für Informatik, Technische Universität München (DE);EIFLER W, JRC Ispra (IT)
Bibliographic Reference: Article: IEEE Transactions on Geoscience and Remote Sensing, IEEE Geoscience and Remote Sensing (1998)
Record Number: 199810801 / Last updated on: 1998-07-02
Original language: en
Available languages: en
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