Performance of Satellite-Based Ocean Forecasting (SOFT) Systems: A Study in the Adriatic Sea

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Abstract
Continuous monitoring by satellites of the ocean spatiotemporal variability allows empirical forecasting of satellite-observed data. The forecast of satellite data is achieved in three major phases: decomposition of the spatiotemporal variability of the satellite data, noise reduction of the encoded space, and time variability and the prediction, by a nonlinear forecasting technique, of the time variability. Different techniques can be employed in each processing phase. Specifically, decomposition can be carried out using spatial or temporal variance EOF decomposition. With spatial variance EOFs, performance of the empirical forecasting is associated with the predictability of the dynamics of spatial structures with strong spatial gradients (fronts, eddies, etc. . . .). Conversely, if temporal variance decomposition is employed, the success of the empirical prediction system will be related to features with strong temporal variability. Both approaches have been employed to empirically forecast sa... Abstract Continuous monitoring by satellites of the ocean spatiotemporal variability allows empirical forecasting of satellite-observed data. The forecast of satellite data is achieved in three major phases: decomposition of the spatiotemporal variability of the satellite data, noise reduction of the encoded space, and time variability and the prediction, by a nonlinear forecasting technique, of the time variability. Different techniques can be employed in each processing phase. Specifically, decomposition can be carried out using spatial or temporal variance EOF decomposition. With spatial variance EOFs, performance of the empirical forecasting is associated with the predictability of the dynamics of spatial structures with strong spatial gradients (fronts, eddies, etc. . . .). Conversely, if temporal variance decomposition is employed, the success of the empirical prediction system will be related to features with strong temporal variability. Both approaches have been employed to empirically forecast sa...

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