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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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High-Resolution WRF Model Simulations for Offshore Wind Resource Assessment in Spanish Territorial Waters (1990-2014)

Authors: Thomas, Brieuc; Costoya, Xurxo;

High-Resolution WRF Model Simulations for Offshore Wind Resource Assessment in Spanish Territorial Waters (1990-2014)

Abstract

This dataset consists of annual output files from simulations performed using the Weather Research and Forecasting (WRF) Model version 4.3.3, with a spatial resolution of 0.1° in latitude and longitude. The simulations cover the period 1990–2014 and were generated to analyze the historical offshore wind energy resource in Spanish territorial waters. Each annual file, named “wrfpost_d02_XXXX.nc” (where XXXX represents the year), is stored in netCDF4 format and follows CF-1.6 conventions. The simulation domain (d02) is configured with a Lambert Conformal projection. Geographical Coverage Minimum Latitude: 33.239681°N Maximum Latitude: 49.625706°N Minimum Longitude: -17.924255°E Maximum Longitude: 7.781036°E Variables Included Each file contains the following atmospheric variables at different heights and time steps: Sea Level Pressure (slp) [hPa] 2m Air Temperature (t2m) [K] 10m Wind Components (u10m, v10m) [m/s] 10m Wind Speed and Direction (ws10m, wd10m) [m/s, degrees] 100m Wind Components (u100m, v100m) [m/s] 100m Wind Speed and Direction (ws100m, wd100m) [m/s, degrees] Methodology and Data Sources These high-resolution simulations were conducted as part of the study: 📖 Thomas, B., Costoya, X., Decastro, M., Insua-Costa, D., Senande-Rivera, M., & Gómez-Gesteira, M. (2023). Downscaling CMIP6 climate projections to classify the future offshore wind energy resource in the Spanish territorial waters. Journal of Cleaner Production, 433, 139860. DOI: 10.1016/j.jclepro.2023.139860 The WRF model was forced with climate projections from the CMIP6 multimodel ensemble published in: 📖 Xu, Z., Han, Y., Tam, C.-Y., Yang, Z.-L., & Fu, C. (2021). Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100). Scientific Data, 8, 293. DOI: 10.1038/s41597-021-01079-3 Acknowledgement:Computation took place at Finisterrae III supercomputer that belongs to CESGA (Centro de Supercomputación de Galicia) located at Santiago de Compostela, Galicia, Spain.

Related Organizations
Keywords

WRF, Downscaling, CMIP6, Offshore wind energy, Iberian Peninsula

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average