@misc{10481/108068,
year = {2025},
month = {6},
url = {https://hdl.handle.net/10481/108068},
abstract = {Climate datasets with very high spatiotemporal resolution are essential to assess the impacts of climate change in mountain areas, which are complex systems in which climate is very changeable. However, these regions are characterized by a lack of climatic information, and if there is any, it is usually short, sparse, or incomplete. This work presents a new series of very high resolution (1 km) gridded climate datasets for Sierra Nevada (SN), a mountain range classified as a double climate change hotspot as it is a semi-arid mountain range in the Mediterranean area that is particularly vulnerable to climate change. The database, called HighResClimNevada, consists of a set of climate data derived from a climate simulation using the Weather Research and Forecasting (WRF) model for the period from 1991–2022 and forced with the European ReAnalysis (ERA5). HighResClimNevada provides not only hourly and daily primary climate variables (i.e., near-surface temperature, precipitation, near-surface relative humidity, surface pressure, surface net radiation, and wind speed), but also bioclimatic variables, extremes indices from the Expert Team of Climate Change Detection and Indices (ETCCDI), and precipitation-hour indicators, which were postprocessed using aggregated temperature and precipitation values from primary climate variables. To evaluate the database performance, HighResClimNevada temperature and precipitation values were compared with reference datasets from different sources. In general, HighResClimNevada captures reasonably well not only the spatiotemporal variability of raw temperature, but also bioclimatic variables and extreme indices in SN. It displays comparable behavior to other climatic products but with a greater level of detail due to its higher spatial resolution. For precipitation, which is variable, more uncertain, and difficult to characterize, HighResClimNevada exhibits a higher amount of precipitation when compared to station-based, coarse satellite-based, and reanalysis-based products. However, the latter two present problems in characterizing precipitation in high mountain regions probably due to the scarcity of data in areas with high spatiotemporal variability, such as SN. The precipitation from HighResClimNevada is comparable to other climatic products like CHIRPS or CERRA-Land, which captures better the spatiotemporal variability in this region. These findings, therefore, suggest HighResClimNevada as a valuable long-term climate tool for a variety of applications, including land management, hydrometeorological research, flora and fauna phenology, and risk assessment. The reported datasets are freely available for download via the Zenodo platform (Garcia-Valdecasas Ojeda et al., 2025, https://doi.org/10.5281/zenodo.14883471).},
organization = {Gobierno de España},
organization = {NextGenerationEU BIOD22_002},
organization = {MICIU/AEI/10.13039/501100011033 TED2021-130888B-I00, PID2021-126401OB-I00},
organization = {FEDER, UE},
publisher = {Copernicus Publications},
title = {HighResClimNevada: a high-resolution climatological dataset for a high-altitude region in southern Spain (Sierra Nevada)},
doi = {10.5194/essd-17-2809-2025},
author = {García Valdecasas Ojeda, Matilde María del Valle and Solano-Farias, Feliciano and Donaire-Montaño, David and Romero-Jiménez, Emilio and Rosa-Cánovas, Juan José and Castro Díez, Yolanda and Gámiz Fortís, Sonia Raquel and Esteban Parra, María Jesús},
}