PL1GD-T – gridded dataset of the mean, minimum and maximum daily air temperature at the level of 2 m for the area of Poland at a resolution of 1 km × 1 km

Abstract. This paper presents a high-resolution gridded dataset of daily minimum (TN), mean (TG) and maximum (TX) near-surface air temperatures over Poland, covering the period from 1951 to 2020, with a spatial resolution of 1 km². PL1GD-T dataset was developed using radial basis functions (RBFs) applied to quality-controlled observations from ground weather stations from the Institute of Meteorology and Water Management – National Research Institute. Cross-validation methods evaluated the gridding procedure on a monthly basis. The linear RBF was employed by hold-out cross-validation (HO-CV) as the most suitable for the gridding procedure among other RBFs. The leave-one-out cross-validation (LOO-CV) was performed to ensure the ability to reproduce the original characteristics variability. The values of the scores averaged over all stations for individual months are in range 0.3–0.2, 0.3–0.2, 0.1–0.2 for the bias, in range 1,23–1,46, 0.69–0.92, 0.84–0.99 the root-mean-squared difference (RMSD) and in range 0.91–0.97, 0.98–0.99, 0.98–0.99 for the correlation for TN, TG and TX, respectively. The RSMD is clearly altitude dependent, increasing from low-land to mountainous regions. The dataset's scope and resolution allowed robust estimation of local climate variability characteristics and observed trends. The availability of high-resolution datasets in both spatial and temporal contexts is essential for climate change impact analysis on a smaller scale. This new dataset provides a quality-validated, high-resolution, and open-access dataset that could be utilised by society, administrative bodies, or research institutions for further analysis. The dataset is publicly available from the repository of the Institute of Meteorology and Water Management – National Research Institute under https://doi.org/10.26491/imgw_repo/PL1GD-T (Jaczewski et al., 2024).