Empirical Forecasting of HF-Radar Velocity Using Genetic Algorithms

We present a coastal ocean current forecasting system using exclusively past observations of a high-frequency radar (HF-Radar). The forecast is made by developing a new approach based on physical and mathematical results of the nonlinear dynamical systems theory that allows to obtain a predictive eq...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2015-05, Vol.53 (5), p.2875-2886
Main Authors: Orfila, Alejandro, Molcard, Anne, Sayol, Juan M., Marmain, Julien, Bellomo, Lucio, Quentin, Celine, Barbin, Yves
Format: Article
Language:English
Subjects:
Atmospheric and Oceanic Physics
Coastal
Dynamical systems
Empirical analysis
Empirical modeling
Equations
Forecasting
Genetic algorithms
Hafnium
high-frequency radar (HF-Radar)
Mathematical analysis
Mathematical models
Meteorology
Nonlinear dynamics
operational oceanography
Physics
Radar
Sea measurements
Sea surface
System theory
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Summary:We present a coastal ocean current forecasting system using exclusively past observations of a high-frequency radar (HF-Radar). The forecast is made by developing a new approach based on physical and mathematical results of the nonlinear dynamical systems theory that allows to obtain a predictive equation for the currents. Using radial velocities from two HF-Radar stations, the spatiotemporal variability of the fields is first decomposed using the empirical orthogonal functions. The amplitudes of the most relevant modes representing their temporal evolution are then approximated with functions obtained through a genetic algorithm. These functions will be then combined to obtain the hourly currents at the area for the next 36 h. The results indicate that after 4 h and for a horizon of 24 h, the computed predictions provide more accurate current fields than the latest available field (i.e., persistent field).
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2014.2366294