Buscar

 Detalle_Publicacion

A multivariate, stochastic, climate-based wave emulator for shoreline change modelling

Abstract: Coastal hazards often result from the combination of different simultaneous oceanographic processes that occur at multiple spatial and temporal scales. To predict coastal flooding and erosion, it is necessary to accurately represent hydrodynamic conditions. For this reason, here we present a stochastic, climate based wave emulator that provides the hydrodynamic conditions needed for these predictions. The emulator can generate an infinitely long data series maintaining its statistical properties at different time scales, from intra-storm to inter-annual variability, and its link to large scale climate patterns. The proposed methodology relies on the use of weather types and an autoregressive logistic regression model forced with different variables to simulate daily scale chronology. Considering the dependencies of wave conditions on the different weather types, the intra-storm chronology is solved by means of shuffling and stretching historical wave sequences. To demonstrate the replicability of this emulator worldwide, we have applied the model to 3 different locations and found good agreement when compared to the historical data. Furthermore, to illustrate and explain the strengths and limitations of the emulator, we present a different application for each of the different locations.

 Fuente: Ocean Modelling Volume 154, October 2020, 101695

Editorial: Elsevier Ltd

 Fecha de publicación: 01/10/2020

Nº de páginas: 14

Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.ocemod.2020.101695

ISSN: 1463-5003,1463-5011

Url de la publicación: https://doi.org/10.1016/j.ocemod.2020.101695

Autores/as

LAURA CAGIGAL GIL

ANA CRISTINA RUEDA ZAMORA

ANDERSON, DYLAN

RUGGIERO, PETER

MERRIFIELD, MARK A.

MONTAÑO, JENNIFER