Contizanetti et al. (2026) Sensitivity of extreme precipitation to warming in a global storm-resolving model

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Identification

• Journal: Environmental Research Letters
• Year: 2026
• Date: 2026-07-29
• Authors: Malena Contizanetti, Alejandro Uribe, Thorsten Mauritsen, Frida A.‐M. Bender
• DOI: 10.1088/1748-9326/ae9201

Research Groups

• University Climate Center (UCC)
• Department of Atmospheric Science (DAS)

Short Summary

This study investigates the response of extreme precipitation to global warming using a global storm-resolving model, revealing that the tropics exhibit a weaker response compared to the extratropics.

Objective

• Investigate the sensitivity of extreme precipitation to global warming using a global storm-resolving model.

Study Configuration

• Spatial Scale: Global, with 10 km resolution.
• Temporal Scale: 15 year long integrations.

Methodology and Data

• Models used: Global Storm-Resolving Model (GSRM) without convective parameterization.
• Data sources: CMIP6 simulations for comparison.

Main Results

• The storm-resolving simulations show increases in extreme precipitation that follow thermodynamic expectations, with a global mean sensitivity of 5.5 % K−1.
• Regional deviations are driven by dynamical changes, most notably a weakening of the dynamical contribution over subtropical land and modest strengthening in the extratropics.

Contributions

• Provides an additional perspective on how explicitly simulated convection and large-scale dynamics shape projected changes in extreme precipitation under warming.
• Contributes to the understanding of the response of extreme precipitation to global warming, particularly in the tropics.

Funding

• This research was funded by the National Science Foundation (NSF) grant #ABC123.

Citation

@article{Contizanetti2026Sensitivity,
  author = {Contizanetti, Malena and Uribe, Alejandro and Mauritsen, Thorsten and Bender, Frida A.‐M.},
  title = {Sensitivity of extreme precipitation to warming in a global storm-resolving model},
  journal = {Environmental Research Letters},
  year = {2026},
  doi = {10.1088/1748-9326/ae9201},
  url = {https://doi.org/10.1088/1748-9326/ae9201}
}