Abstract
A new high-resolution climatic gridded dataset was built for Aragón (northeast Spain) using a large collection of daily precipitation and temperature observations from more than 3000 weather stations. The grid covers, at the unprecedented spatial resolution of 0.25 km(2), daily maximum and minimum temperatures and precipitation in the 1950-2020 period. The complex orography (from 70 to 3,400 m.a.s.l.) of the medium-sized region (∼48,000 km(2)) required a climate modelling method based on a spatially-dense weather monitoring network and local predictors. The 3-step workflow for grid creation consisted of: 1) a comprehensive quality control of raw observations, based on a spatial comparison with nearest data; 2) a climate reconstruction based on the creation of reference values, through multivariate linear regressions, for every day and location, based on the observed climate and terrain-based environmental variables; and 3) the prediction of precipitation and temperature values in a regular 500 × 500 m grid, based on the reconstructed data series. The resulting dataset improves the spatial representativity of climate and allows for a detailed analyses at landscape scale not only in climate studies but also in related disciplines such as hydrology or biogeography, amongst others.