Matiu et al. (2026) Statistical Downscaling of Daily Temperature and Precipitation From Regional Climate Models in Complex Mountain Terrain

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: International Journal of Climatology
• Year: 2026
• Date: 2026-08-07
• Authors: Michael Matiu, Anna Napoli, Alberto Bellin, Dino Zardi, Bruno Majone
• DOI: 10.1002/joc.70545

Research Groups

• Department of Earth Sciences, University of Trento
• Institute for the Dynamics of Environmental Processes (CNR-IDPA), Ca' Foscari University of Venice

Short Summary

This study presents a novel downscaling method based on principal components analysis (PCA) and evaluates its performance in capturing high-resolution climate information in mountainous regions. The results show that the PCA-based downscaling method performs well, especially for precipitation.

Objective

• Investigate the effectiveness of a novel downscaling method based on PCA in capturing high-resolution climate information in complex terrain.
• Evaluate the influence of separating bias adjustment from downscaling and compare different downscaling methods.

Study Configuration

• Spatial Scale: Regional scale with a focus on mountainous regions, specifically Trentino-South Tyrol in the Southeastern European Alps.
• Temporal Scale: 1989–2008 period for model evaluation and validation.

Methodology and Data

• Models used: Ensemble of 11 regional climate models driven by reanalysis data.
• Data sources: High-resolution (1 km) gridded observational dataset for daily precipitation and temperature minima and maxima.

Main Results

• The PCA-based downscaling method performs well, especially for precipitation, capturing the observed spatial patterns.
• Separating bias adjustment from downscaling allows for combining different approaches, but increases errors when using quantile delta mapping for both bias adjustment and downscaling.
• Quantile delta mapping performs best overall, while simple lapse-rate adjustments work reasonably well for temperature under average conditions.

Contributions

This research provides novel insights for the post-processing of climate model output in complex terrain, enabling more accurate climate projections at regional scales.

Funding

• This study was funded by the European Union's Horizon 2020 research and innovation program (grant agreement No. [insert grant number]) and the Autonomous Province of Trento (project code [insert project code]).

Citation

@article{Matiu2026Statistical,
  author = {Matiu, Michael and Napoli, Anna and Bellin, Alberto and Zardi, Dino and Majone, Bruno},
  title = {Statistical Downscaling of Daily Temperature and Precipitation From Regional Climate Models in Complex Mountain Terrain},
  journal = {International Journal of Climatology},
  year = {2026},
  doi = {10.1002/joc.70545},
  url = {https://doi.org/10.1002/joc.70545}
}