High-Resolution Climate Database for Hydrological Applications over the Miño–Limia River Basins Based on Dynamically Downscaled CMIP6 Simulations

This dataset provides a high-resolution climate database developed to support the assessment of climate change impacts on the hydrological regime of the international Miño–Limia river basins. The database contains two key atmospheric variables governing the hydrological cycle: precipitation and 2 m air temperature. The dataset includes historical climate conditions for the period 1985–2014 and future climate projections for 2020–2100 under the SSP2-4.5 and SSP5-8.5 scenarios. The atmospheric fields were obtained from dynamically downscaled CMIP6 climate simulations using the Weather Research and Forecasting (WRF) model. The WRF configuration, including model domains and physical parameterizations, follows the methodology described in the associated studies: Forecasting offshore wind energy in Atlantic Europe using CMIP6 dynamically downscaled data and Neural network approach for modeling future natural river flows: Assessing climate change impacts on the Tagus River. For the development of this database, precipitation and temperature fields were extracted at the grid points covering the Miño–Limia river basins, providing a spatially consistent climate dataset specifically tailored for hydrological and climate change impact assessments in the study area. The dataset is provided in NetCDF format, with a spatial resolution of 0.1° × 0.1° and a daily temporal resolution. This database was developed within the framework of the RISC_PLUS project (0031_RISC_PLUS_6_E), co-funded by the European Regional Development Fund (ERDF) through the Interreg VI-A Spain–Portugal Cross-Border Cooperation Programme (POCTEP) 2021–2027. The dataset supports the assessment of future climate and hydrological conditions in the international Miño–Limia river basins, contributing to the analysis of climate change impacts on water availability, droughts, floods, and other hydrological extremes. The computational resources required for generating and processing the climate simulations were provided by the Galician Supercomputing Centre (CESGA). Users of this dataset are encouraged to cite both this Zenodo repository and the associated publications describing the atmospheric downscaling methodology and its application to climate change impact assessment.