A Multiscale Approach to Shoreline Prediction
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Identificadores
URI: http://hdl.handle.net/10902/20764DOI: 10.1029/2020GL090587
ISSN: 0094-8276
ISSN: 1944-8007
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Montaño, Jennifer; Coco, Giovanni; Cagigal Gil, Laura


Fecha
2021-01-16Derechos
© American Geophysical Union
Publicado en
Geophysical Research Letters Volume 48, Issue 1 16 January 2021 e2020GL089263
Editorial
American Geophysical Union
Resumen/Abstract
ABSTRACT: Shorelines respond to a number of "drivers" operating on a variety of time-scales. For some time-scales (e.g., seasonal), the driver-shoreline relationship is often evident; however, at longer timescales (e.g., multiannual), the shoreline changes may be superimposed on changes at shorter time-scales and thus are diffcult to identify. Here, we predict shoreline evolution from storm events to decadal timescales, using a novel approach based on the Complete Ensemble Empirical Mode Decomposition. This approach identifies and links the primary time-scales in the model drivers (large-scale sea level pressure [SLP] and/or waves) with the same time-scales in the shoreline position. The multiscale approach reproduced shoreline changes at two beaches more skillfully than a common shoreline model when SLP and wave information were used in combination. In addition, the analysis can be applied to climate indices, providing the opportunity to link longer time-scales with climate patterns (e.g., El Niño Southern Oscillation).
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