Self-Organizing Maps-based ocean currents forecasting system

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROM...

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Bibliographic Details
Published in:Scientific reports 2016-03, Vol.6 (1), p.22924-22924, Article 22924
Main Authors: Vilibić, Ivica, Šepić, Jadranka, Mihanović, Hrvoje, Kalinić, Hrvoje, Cosoli, Simone, Janeković, Ivica, Žagar, Nedjeljka, Jesenko, Blaž, Tudor, Martina, Dadić, Vlado, Ivanković, Damir
Format: Article
Language:English
Subjects:
704/4111
704/829/2737
Algorithms
Coastal zone
Humanities and Social Sciences
multidisciplinary
Neural networks
Ocean currents
Science
Weather forecasting
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Summary:An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.
ISSN:2045-2322
2045-2322
DOI:10.1038/srep22924