Pall et al. (2025) Characterising the range and outliers in CMIP6 multi-model climate projections of extremes

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

Identification

• Journal: Environmental Research Letters
• Year: 2025
• Date: 2025-12-01
• Authors: Pardeep Pall, Andrew D. King
• DOI: 10.1088/1748-9326/ae293a

Research Groups

Not available in the abstract.

Short Summary

This study explores the projected ensemble ranges of mean and extreme temperature and precipitation changes from CMIP6 models, revealing that ensemble minimums and maximums are often dominated by one or two specific models, and this domination can vary significantly depending on whether the future is framed as a fixed time slice or a specific global warming level.

Objective

• To explore projected ensemble ranges in mean and extreme temperature and precipitation metrics and their relationships using simulations from the sixth Coupled Model Intercomparison Project (CMIP6).
• To examine if the framing of future changes, both in terms of a future time slice (2070–2099) and a future global warming level (GWL) of 3 K, relative to a historical period (1850–1900), affects the interpretation of results regarding ensemble spread.

Study Configuration

• Spatial Scale: Global patterns of change.
• Temporal Scale: Historical period (1850–1900), future time slice (2070–2099), and a future global warming level of 3 K.

Methodology and Data

• Models used: Simulations from the sixth Coupled Model Intercomparison Project (CMIP6). Specific models highlighted include CanESM5 and NorESM2-LM.
• Data sources: Multi-model climate simulations.

Main Results

• The 2070–2099 time slice exhibits known patterns of change, such as Arctic warming and regional drying/wetting, which are exacerbated depending on the ensemble percentile considered.
• For extreme temperature metrics, changes at the 25th, median, and 75th percentiles are relatively evenly contributed to by all models.
• However, ensemble-minimum and -maximum changes for extreme temperature metrics are often dominated by only one or two models.
• CanESM5 dominates ensemble-maximum changes by over 40%.
• NorESM2-LM dominates ensemble-minimum changes for the coldest night of the year (64%) and contributes significantly (23%) to ensemble-maximum changes for the warmest day of the year.
• When changes are framed by a 3 K global warming level, the domination by CanESM5 ceases, but the domination by NorESM2-LM persists.

Contributions

• Highlights the critical importance of quantifying and understanding ensemble spread in multi-model climate projections beyond just ensemble-average changes.
• Demonstrates that individual models can disproportionately influence the extreme ends (minimums and maximums) of ensemble projections, especially for extreme temperature metrics.
• Reveals that the framing of future periods (as a time slice versus a global warming level) significantly impacts the identification of dominant models and the interpretation of what constitutes an outlier model.
• Encourages multi-model studies to explicitly analyze and communicate ensemble spread to better inform decision-makers.

Funding

Not available in the abstract.

Citation

@article{Pall2025Characterising,
  author = {Pall, Pardeep and King, Andrew D.},
  title = {Characterising the range and outliers in CMIP6 multi-model climate projections of extremes},
  journal = {Environmental Research Letters},
  year = {2025},
  doi = {10.1088/1748-9326/ae293a},
  url = {https://doi.org/10.1088/1748-9326/ae293a}
}