Evidence map›Paper›PMID 41932945›Full record

ArticleScientific data2026

High-Resolution Wave Climate Data under Future Climate Scenarios along the European Atlantic Coast.

B Arguilé-Pérez, X Costoya, A S Ribeiro, M deCastro, P Carracedo, M Gómez-Gesteira

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Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

B Arguilé-PérezCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus Auga, 32004, Ourense, Spain. beatriz.arguile.perez@uvigo.es.
X CostoyaCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus Auga, 32004, Ourense, Spain.ORCID http://orcid.org/0000-0001-8050-760X
A S RibeiroCESAM, Physics Department, University of Aveiro, 3810-193, Aveiro, Portugal.
M deCastroCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus Auga, 32004, Ourense, Spain.
P CarracedoConsellería de Medio Ambiente e Cambio Climático, Edificio Administrativo San Lázaro, s/n 15781, Santiago de Compostela, Spain.
M Gómez-GesteiraCentro de Investigación Mariña, Universidade de Vigo, Environmental Physics Laboratory (EPhysLab), Campus Auga, 32004, Ourense, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding future wave climate is critical for coastal adaptation, infrastructure planning, and marine renewable energy development. This study presents a high-resolution spectral wave dataset for the European Atlantic coast, derived through regional downscaling of CMIP6 climate projections. The dataset was generated using the WRF atmospheric model and two wave models-WAVEWATCH III and Simulating WAves Nearshore (SWAN)-to simulate 3-hourly directional wave spectra at 1,031 offshore locations spaced 10 km apart and approximately 50 km from shore. Simulations cover three 30-year periods: historical (1985-2014) and two future projections (2030-2059) under SSP2-4.5 and SSP5-8.5 scenarios. Two datasets are provided: spectral energy densities and integrated wave parameters, both validated and formatted in CF-1.8-compliant NetCDF-4 files. The spectral data can be used to initialize new SWAN simulations, enabling efficient, site-specific wave modeling. The integral wave parameters support regional-scale assessments of climate change impacts on wave conditions. The dataset is openly available through the Centre for Environmental Data Analysis (CEDA) repository, offering a valuable resource for research, engineering, and policy-making in coastal and marine domains.

Identifiers

PMID41932945
PMCPMC13223198

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.