WRF Hourly 2 m Temperature and Relative Humidity Simulations over Galicia from CMIP6 Downscaling (1985–2014, 2030–2059, SSP2-4.5)

This repository contains a database of regional climate simulations performed with the WRF v4.3.3 atmospheric model for the region of Galicia (NW Iberian Peninsula), covering latitudes 41.5°N – 44°N and longitudes –9.5°E – –6.5°E. The database includes two 30-year periods: Historical: 1985–2014 Future projection (SSP2-4.5): 2030–2059. Data structure Format: netCDF4 Temporal resolution: hourly (24 records per day) Spatial resolution: ~0.1° × 0.1° (~10 km) Domain: Lambert Conformal (true latitudes: 38.0, standard longitude: –10.0) Files: Data are organized in daily files with the format:wrfpost_d02_YYYY-MM-DD_rec.nc Each file contains 24 hourly records. Daily files are grouped into annual .zip archives (30 for the historical period and 30 for the future). Each annual archive contains 365 or 366 files, depending on whether the year is a leap year. Available variables Each netCDF file includes: t2m: 2 m air temperature (K) rh2m: 2 m relative humidity (%) lat: latitude (degrees north) lon: longitude (degrees east) time: time (hours since the beginning of the simulated day, proleptic_gregorian calendar) Methodology Simulations were carried out with the WRF v4.3.3 model using physical options and parameterizations described in: 📖 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. https://doi.org/10.1016/j.jclepro.2023.139860 The model was forced with climate projections from the CMIP6 multimodel ensemble, bias-corrected and 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. https://doi.org/10.1038/s41597-021-01079-3 Notes The high temporal resolution (hourly) and spatial resolution (~10 km) imply a considerable computational effort. The dataset is suitable for applications in climate research, environmental studies, and energy resource assessment in Galicia.