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Performance evaluation of a global CMIP6 single forcing, multi wave model ensemble of wave climate simulations

Abstract: A performance evaluation is conducted for a state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6)-derived ensemble of global wave climate simulations. A single-model (forcing), single-scenario approach is considered to build the ensemble, where the differentiating factor between each member is the wave model or physics parameterization used to simulate waves. The 7-member ensemble is evaluated for the 1995-2014 historical period, highlighting the impact of the multiple source terms on its robustness. The ensemble?s ability to accurately represent the present wave climate is assessed through an extensive comparison with long-term ERA5 reanalysis and in-situ observational data. Relevant aspects such as the depiction of extremes and natural wave climate variability are analyzed, and inter-member uncertainties are quantified. Overall, the results indicate that the ensemble is able to accurately simulate the global wave climate, regarding the significant wave height (???? ), mean and peak wave periods (???? and ????, respectively) and mean wave direction (???? ??). However, we show that using multiple wave models and parameterizations should be cautiously considered when building ensembles, even under the same forcing conditions. Model- parameterization-induced ensemble spreads during the historical period are found to be high, compromising the robustness of projecte anges in wave parameters towards the end of the 21st century across several areas of the global ocean.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Ocean Modelling, 2023, 184, 102237

Editorial: Elsevier Ltd

 Fecha de publicación: 01/08/2023

Nº de páginas: 21

Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.ocemod.2023.102237

ISSN: 1463-5003,1463-5011

Url de la publicación: https://doi.org/10.1016/j.ocemod.2023.102237

Autoría

LEMOS, GIL

SEMEDO, ALVARO

KUMAR, RAJESH

DOBRYNIN, MIKHAIL

AKPINAR, ADEM

KAMRANZAD, BAHAREH

BIDLOT, JEAN