Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles
By:Michael Siek
Published on 2011-12-16 by CRC Press
Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled processes and relationships between the observed descriptive variables. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory. First, some fundamentals of physical oceanography, nonlinear dynamics and chaos, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.
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Book ID of Predicting Storm Surges: Chaos, Computational Intelligence, Data Assimilation and Ensembles's Books is S37NBQAAQBAJ, Book which was written byMichael Siekhave ETAG "7FLh/ZUscx0"
Book which was published by CRC Press since 2011-12-16 have ISBNs, ISBN 13 Code is 9781466553484 and ISBN 10 Code is 1466553480
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