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Abstract: Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model.
Fuente: Journal of Geophysical Research: Oceans 121, 775–791
Publisher: John Wiley & Sons
Publication date: 01/01/2016
No. of pages: 17
Publication type: Article
DOI: 10.1002/2015JC011107
ISSN: 2169-9275,2169-9291,0148-0227
Publication Url: http://onlinelibrary.wiley.com/doi/10.1002/2015JC011107/abstract#publication-history
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JOSE ANTONIO ALVAREZ ANTOLINEZ
FERNANDO JAVIER MENDEZ INCERA
PAULA CAMUS BRAÑA
VITOUSEK, SEAN
ERNESTO MAURICIO GONZALEZ RODRIGUEZ
RUGGIERO, PETER
BARNARD, PATRICK
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