High-resolution daily climate data remain scarce for complex Alpine terrain, where coarse gridded products often fail to resolve orographic precipitation gradients and elevation-dependent temperature variability. Here we present a 1-km gridded daily precipitation and temperature dataset for the Po River District (Northern Italy) covering the 1991–2020 climatological period. The dataset is based on a harmonized multi-source observational network comprising 1,583 precipitation and 1,555 temperature stations after quality control. Spatial interpolation was performed using Ordinary Kriging for precipitation and Detrended Kriging for temperature, with elevation as the trend variable, and daily-adaptive semivariogram models selected from five candidate functions via Particle Swarm Optimisation. Leave-one-out cross-validation indicates strong overall performance. For precipitation, the mean Kling–Gupta Efficiency (KGE) across all station-wise leave-one-out cross-validations exceeds 0.84 under All-Days conditions and 0.82 under Wet-Days conditions, with mean absolute errors of 1.28 mm and 3.05 mm, respectively. Temperature interpolation achieves a mean KGE of 0.88 and a mean absolute error of 1.14 °C, with negligible bias. Spatial diagnostics reveal higher precipitation errors in high-relief Alpine sectors and along basin boundaries, while temperature performance remains comparatively uniform. Interpolation skill decreases with altitude, particularly for precipitation during wet events, due to decreasing station density. The resulting dataset provides spatially continuous daily climate fields suitable for hydrological modelling, climate variability assessment, and environmental analysis in one of Europe’s most topographically diverse river basins.