A 1-km Daily Gridded Climate Dataset for the Po River District (1991–2020): Regionalized Kriging within the GEOframe-NewAGE Framework

High-resolution, temporally consistent climate datasets are essential for hydrological modeling, water resource management, and climate impact assessments. The Po River District is the largest in Italy, spanning from the Alps to the plains, and exhibits substantial spatial heterogeneity in precipitation and temperature. However, existing datasets lack the spatial resolution necessary to capture the basin's diverse microclimates and complex orographic patterns, limiting their utility for process-based hydrological modeling and local-scale climate impact studies.

In this study, we generated a high-resolution (1 km x 1 km) daily gridded precipitation and temperature dataset over the Po River District. Following WMO standards, this 30-year (1991–2020) dataset provides a robust baseline for a region identified as one of Europe's most vulnerable climate change hotspots. The datasets were generated using the Kriging module available within the GEOframe-NewAGE modeling system, applied to quality-controlled ground station data. To address the vast area and topographic complexity, we implemented a spatial regionalization framework using Gaussian Mixture Models (GMM) to identify homogeneous climate zones. Zone-specific variogram models were derived and applied within the optimized Kriging framework. 

The model performance was rigorously evaluated using Leave-One-Out Cross-Validation (LOOCV) method. The validation results show exceptional accuracy for both variables. For temperature, the Kling-Gupta Efficiency (KGE) exceeded 0.75 at 99.7% of the stations, with strong correlations (>0.95). Notably for precipitation, over 80% of stations achieved KGE and correlation values above 0.75. The KGE decomposition revealed that errors primarily stemmed from variability estimation rather than bias, with 93% of stations showing optimal variance ratios (α = 0.75–1.25) and 99% maintaining near-unity bias (β ≈ 1).

This high-resolution dataset represents a significant advancement in regional climate data for the Po River District. The GMM-based regionalization successfully captured the basin's complex climatic regimes, enabling accurate spatial interpolation across diverse topographies. Beyond providing a WMO-compliant climatological baseline, these datasets are specifically designed to serve as high-resolution meteorological forcing input for distributed hydrological models, enabling process-based watershed simulations at unprecedented spatial detail. Future work will focus on coupling these datasets with the GEOframe-NewAGE hydrological modeling framework to assess the added value of 1-km climate forcing in capturing sub-basin scale hydrological responses, extreme event dynamics, and water balance components across the heterogeneous Po River landscape.

Acknowledgement

HS, JMW and RR would like to thank and acknowledge the funding support from Project “SPACE IT UP! ASI Contract n.2024-5-E.0 CUP Master n. I53D24000060005” SAP fund n: 000040104905.