Siler et al. (2026) Examining the Robustness of Weakened Orographic Influence on Precipitation in Downscaled Climate Projections Over the Western US

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

Identification

• Journal: Geophysical Research Letters
• Year: 2026
• Date: 2026-01-02
• Authors: Nicholas Siler, Matthew Koszuta, Stefan Rahimi, Joshua Norris, Alex Hall, Paul Ullrich
• DOI: 10.1029/2025gl119251

Research Groups

Not specified in abstract.

Short Summary

This study demonstrates that the weakening of orographic influence on precipitation due to warming is a robust effect across seasons and multiple dynamical downscaling ensembles, becoming more pronounced at higher model resolutions. It further reveals that this critical emergent climate change signal is absent in projections from widely used statistical downscaling models, highlighting a significant limitation of such methods.

Objective

• To investigate the robustness of the weakening of orographic influence on precipitation due to warming across different seasons and multiple dynamically downscaled ensembles, and to compare these findings with projections from statistical downscaling models.

Study Configuration

• Spatial Scale: Western United States; comparison across varying model resolutions (finer resolution relative to GCMs).
• Temporal Scale: Across seasons; future climate projections.

Methodology and Data

• Models used: Dynamically downscaled ensembles (using regional climate models), statistical downscaling model (LOCA2), and a hybrid statistical model (LOCA2-Hybrid).
• Data sources: Coarse global climate model (GCM) output (as input for downscaling), high-resolution future simulations (for training LOCA2-Hybrid).

Main Results

• The weakening of orographic influence on precipitation dueading to warming is robust across seasons and multiple dynamically downscaled ensembles.
• This effect is more pronounced at higher model resolutions.
• This emergent effect is absent in projections from the statistical model LOCA2, even when LOCA2-Hybrid is trained on high-resolution future simulations.

Contributions

• Confirms the robustness of an emergent climate change signal (weakening orographic influence on precipitation) across different seasons and dynamical downscaling configurations.
• Identifies a critical limitation of many statistical downscaling methods, demonstrating their inability to capture emergent changes in orographic precipitation patterns, even when trained with high-resolution future data.

Funding

Not specified in abstract.

Citation

@article{Siler2026Examining,
  author = {Siler, Nicholas and Koszuta, Matthew and Rahimi, Stefan and Norris, Joshua and Hall, Alex and Ullrich, Paul},
  title = {Examining the Robustness of Weakened Orographic Influence on Precipitation in Downscaled Climate Projections Over the Western US},
  journal = {Geophysical Research Letters},
  year = {2026},
  doi = {10.1029/2025gl119251},
  url = {https://doi.org/10.1029/2025gl119251}
}