Ghosh et al. (2025) Optimal Configuration of a Convection-Permitting Regional Climate Model in Simulating Precipitation Extremes: The Saguenay Flood

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

Identification

• Journal: Journal of Hydrometeorology
• Year: 2025
• Date: 2025-10-10
• Authors: Soumik Ghosh, Philippe Lucas‐Picher, Philippe Roy, Philippe Gachon, Alejandro Di Luca
• DOI: 10.1175/jhm-d-25-0011.1

Research Groups

The abstract refers to "our RCM" and the CRCM6/Global Environmental Multiscale (GEM) model, version 5 (GEM5). This suggests involvement from institutions responsible for the development and application of these models, likely Environment and Climate Change Canada (ECCC) and Ouranos, given the model names and geographical context (Québec, Canada).

Short Summary

This study evaluates the added value of convection-permitting (2.5 km) simulations and the impact of spectral nudging and initial soil moisture conditions on extreme precipitation characteristics using the CRCM6/GEM5 regional climate model for the July 1996 Saguenay flood. It finds significant improvements in reproducing precipitation extremes with the 2.5 km model, with spectral nudging enhancing spatial and temporal patterns, and initial soil moisture conditions improving rainfall intensity capture.

Objective

• To evaluate the added value of convection-permitting (CP) simulations (2.5 km resolution) compared to 12 km resolution on simulated extreme precipitation characteristics.
• To test the effects of spectral nudging (SN) and initial soil moisture conditions (ISMCs) on simulated rainfall.
• To contribute to the understanding of extreme precipitation events and their reliability as simulated by various configurations of the CRCM6/GEM5 regional climate model.

Study Configuration

• Spatial Scale: Saguenay region (Québec, Canada). Model resolutions used were 12 km (0.11° × 0.11°) and 2.5 km (0.0225° × 0.0225°).
• Temporal Scale: A major flood event in July 1996. Initial soil moisture conditions were derived from long-term simulations.

Methodology and Data

• Models used: CRCM6/Global Environmental Multiscale (GEM) model, version 5 (GEM5), a regional climate model (RCM). Various configurations were tested, including different resolutions (12 km and 2.5 km), with and without spectral nudging, and with different initial soil moisture conditions.
• Data sources: Rainfall observed stations were used as a reference dataset for evaluating simulations.

Main Results

• The convection-permitting model (CPM) at 2.5 km resolution showed a significant improvement in reproducing precipitation extremes.
• Both spectral nudging (SN) and initial soil moisture conditions (ISMCs) had substantial influences on the simulated rainfall.
• SN in the CP simulation improved the spatial and temporal patterns of precipitation extremes.
• Forced ISMC from long-term simulations at 12 km resolution significantly enhanced the model’s ability to capture rainfall intensity.

Contributions

• Demonstrates the significant added value of convection-permitting resolution (2.5 km) in the CRCM6/GEM5 model for simulating extreme precipitation events.
• Quantifies the positive impact of spectral nudging on improving the spatial and temporal patterns of extreme precipitation.
• Highlights the critical role of accurate initial soil moisture conditions in enhancing the model's ability to capture rainfall intensity.
• Emphasizes the necessity of applying higher resolution and accurate surface conditions in CRCM6/GEM5 for future projections, infrastructure design, and flood risk management strategies.

Funding

Not specified in the abstract.

Citation

@article{Ghosh2025Optimal,
  author = {Ghosh, Soumik and Lucas‐Picher, Philippe and Roy, Philippe and Gachon, Philippe and Luca, Alejandro Di},
  title = {Optimal Configuration of a Convection-Permitting Regional Climate Model in Simulating Precipitation Extremes: The Saguenay Flood},
  journal = {Journal of Hydrometeorology},
  year = {2025},
  doi = {10.1175/jhm-d-25-0011.1},
  url = {https://doi.org/10.1175/jhm-d-25-0011.1}
}