Argañaraz et al. (2025) Building a High‐Resolution Climate Gridded Dataset in Complex Terrain: Validating Different Methods in the Abruzzo Region in Italy

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Identification

• Journal: International Journal of Climatology
• Year: 2025
• Date: 2025-10-27
• Authors: Carina I. Argañaraz, Andreu Salcedo‐Bosch, Simone Lolli, Gabriele Curci
• DOI: 10.1002/joc.70153

Research Groups

Not explicitly stated in the abstract.

Short Summary

This study compares different interpolation methods to create high-resolution daily gridded maps of precipitation and temperature for Abruzzo, central Italy, and validates the resulting local dataset (ADAMO) against global datasets. It finds that universal kriging performs best, and the locally derived ADAMO dataset significantly outperforms global datasets in regions with high topographic variability.

Objective

• To calculate gridded daily maps of precipitation and temperature at a regional scale in Abruzzo (central Italy) by comparing universal kriging, radial basis function, and gradient boosting forest interpolation methods, and to validate the results against independent observations and global datasets.

Study Configuration

• Spatial Scale: Regional scale in Abruzzo (central Italy), with a grid resolution of approximately 0.01° (roughly 1 km).
• Temporal Scale: Daily resolution, covering the period from 1994 to 2013.

Methodology and Data

• Models used: Universal kriging, radial basis function, and gradient boosting forest (interpolation methods).
• Data sources: In situ observations from a local station network (1994–2013), an independent set of stations for validation, and two widely used global datasets (CHELSA and WorldClim).

Main Results

• Universal kriging achieved the best performance among the tested interpolation methods.
• The daily root mean square error (RMSE) for universal kriging was approximately 0.45 mm/day for precipitation and 1.2 °C for temperature.
• Seasonality affects bias, with larger biases observed in winter for precipitation and in summer for temperature, particularly in isolated mountainous stations.
• The locally derived ADAMO dataset (0.01° daily resolution) showed decreased bias compared to global databases.
• For precipitation, ADAMO had an RMSE of 35 mm/month, significantly lower than CHELSA and WorldClim (RMSE ≥ 60 mm/month).
• Global datasets, especially WorldClim, exhibited a too strong altitude effect for temperature.
• Temperature RMSE increased in summer compared to winter, a trend more pronounced in global datasets.
• Precipitation RMSE increased in winter compared to summer, a trend more evident in the ADAMO dataset.

Contributions

• Demonstrates that high-resolution datasets implemented with diffuse local observations are significantly more accurate than global datasets in regions with large topographic variability.
• Provides a new, validated, high-resolution daily gridded dataset (ADAMO) for precipitation and temperature in Abruzzo, central Italy.
• Highlights the critical importance of local, high-accuracy climate information for fields such as climatology, ecology, and biology in complex terrains.

Funding

Not explicitly stated in the abstract.

Citation

@article{Argañaraz2025Building,
  author = {Argañaraz, Carina I. and Salcedo‐Bosch, Andreu and Lolli, Simone and Curci, Gabriele},
  title = {Building a High‐Resolution Climate Gridded Dataset in Complex Terrain: Validating Different Methods in the Abruzzo Region in Italy},
  journal = {International Journal of Climatology},
  year = {2025},
  doi = {10.1002/joc.70153},
  url = {https://doi.org/10.1002/joc.70153}
}