DOI: 10.26050/wdcc/highresclimnevada_eval_v2
title: High-resolution Climate Data for a High-altitude Region in Southern Spain (Sierra Nevada): Evaluation (Version 2)

description: Project: High-resolution Climate Data for a High-altitude Region in Southern Spain: Sierra Nevada - Climate data at very-high resolution (1 km spatial resolution) for Sierra Nevada, the highest mountain region in the Iberian Peninsula located in southeastern Andalusia (Spain) https://smartecomountains.lifewatch.dev/.
The use of very high resolution simulations allows a more adequate characterisation of the climate in regions with complex orography such as the Sierra Nevada, since at this resolution the convection is resolved by the model and is not parameterised.
Scientific Project: "Thematic Center on Mountain Ecosystem Remote sensing, Deep learning-AI e-Services University of Granada-Sierra Nevada” (LifeWatch-2019-10-UGR-01), which has been co-funded by the Ministry of Science and Innovation through the FEDER funds from the Spanish Pluriregional Operational Program 2014-2020 (POPE), LifeWatch-ERIC action line (https://smartecomountains.lifewatch.dev/)
Summary: This database offers highly valuable climate information for the Sierra Nevada (SN) mountain range, identified as a double climate-change hotspot since it constitutes a semi-arid mountain system within the Mediterranean, a region especially vulnerable to climate change. Moreover, SN is an area where high-quality climate data are particularly scarce, largely due to its difficult accessibility. 

Present climate data (1991–2022) at very high spatial resolution (1 km) for Sierra Nevada (SN), the highest mountain range in the Iberian Peninsula (IP), located in southeastern Andalusia (Spain). The data were generated using version 4.3.3 of the Weather Research and Forecasting (WRF) model (Skamarock et al., 2021), driven by ERA5 reanalysis data (Hersbach et al., 2018). The planetary boundary layer (PBL) scheme used was the Asymmetric Convective Model version 2 (ACM2; Pleim, 2007). Both longwave and shortwave radiation were parameterized using the Community Atmosphere Model version 3.0 (CAM3.0; Collins et al., 2004). The microphysics scheme applied was the WRF Single-Moment 7-class scheme (WSM7; Bae et al., 2019), and the land surface model used was NOAH-MP (Niu et al., 2011). Convection was explicitly resolved (i.e., no cumulus parameterization was used).

The dataset is organized into four categories:

Primary Climate Variables (72 files): Daily values of relative humidity, net radiation, accumulated precipitation, surface pressure, maximum temperature, minimum temperature, mean temperature, and wind speed; and hourly values of accumulated precipitation and mean temperature for the entire period.

Hourly Precipitation Extremes (3 files): Frequency and intensity (Fwet and Iwet respectively) of wet hours (precipitation 0.1 mm/hour) and the maximum hourly precipitation during the wettest month.

ETCCDI Extreme Indices (12 files): Annual values of selected indices from the Expert Team on Climate Change Detection and Indices (ETCCDI), including: Consecutive Dry Days (CDD), Daily Temperature Range (DTR), Growing Season Length (GSL), Icing Days (ID), Number of Wet Days (R1mm), Heavy Precipitation Days (R10mm), Very Heavy Precipitation Days (R20mm), Wettest Pentad (Rx5day), Simple Daily Intensity Index (SDII), Frost Days (TNltm2), Coldest Night (TNn), and Warmest Day (TXx).

Bioclimatic Variables (18 files): Annual and seasonal mean temperature (BIO1 and BIO1*), annual mean maximum temperature (BIOmax and BIO1max*), annual mean minimum temperature (BIOmin and BIO1min*), isothermality (BIO3), temperature seasonality (BIO4), maximum temperature of the warmest month (BIO5), minimum temperature of the coldest month (BIO6), annual temperature range (BIO7), mean temperature of the wettest quarter (BIO8), mean temperature of the driest quarter (BIO9), annual precipitation (BIO12), seasonal mean precipitation (BIO12*), precipitation of the wettest month (BIO13), precipitation seasonality (BIO15), and precipitation of the coldest quarter (BIO19).

For more detailed information on the variables, see García-Valdecasas Ojeda et al. (2025).

This version has data updated to 2022 in the evaluation period and, as a new feature, adds hourly resolution climate information on temperature and precipitation, as well as new derived variables such as various ETCCDI indices or climate variables that are essential for characterizing the mountain climate in this region.