Liang et al. (2025) Is There Sufficient Information to Reliably Estimate Return Periods for Very Rare Heat Extremes in Event Attribution?

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

Identification

• Journal: Earth s Future
• Year: 2025
• Date: 2025-11-01
• Authors: Yongxiao Liang, Megan C. Kirchmeier‐Young, Xuebin Zhang
• DOI: 10.1029/2025ef006073

Research Groups

Not available from the abstract.

Short Summary

This study evaluates methods for estimating return periods of hot extremes in event attribution, finding that multi-year block maxima improve accuracy for very rare events compared to annual maxima, which tend to overestimate return periods in the far right tail.

Objective

• To evaluate the effectiveness and accuracy of approaches used in event attribution studies for estimating the return periods of hot extremes, particularly for events with long return periods.

Study Configuration

• Spatial Scale: Not explicitly defined, but implied to be regional to global, focusing on hot extremes.
• Temporal Scale: Decadal to centennial (or longer) for return periods of extreme hot events; analysis based on annual and multi-year block maxima.

Methodology and Data

• Models used: Large ensembles of climate model simulations.
• Data sources: Large samples generated from large ensembles of climate model simulations.

Main Results

• Annual maxima of temperature extremes do not fit well to a Generalized Extreme Value (GEV) distribution in the far right tail, leading to an overestimation of return period for very rare events.
• Maxima of multi-year blocks generally fit well to a GEV distribution, improving the accuracy of exceedance probability estimates for very rare events.
• For events with shorter return periods (tens of years or less), fitting annual maxima to a GEV distribution can generally still provide robust estimates.
• Estimates based on data samples of similar lengths to observational records are less reliable due to limited sample sizes.

Contributions

• Highlights the need for caution and potential inaccuracies when interpreting event attribution results for events with long return periods.
• Demonstrates that using multi-year block maxima improves the accuracy of GEV fitting and return period estimation for very rare hot extremes.
• Provides insights into the reliability of different extreme value analysis approaches based on sample size and event rarity.

Funding

Not available from the abstract.

Citation

@article{Liang2025Is,
  author = {Liang, Yongxiao and Kirchmeier‐Young, Megan C. and Zhang, Xuebin},
  title = {Is There Sufficient Information to Reliably Estimate Return Periods for Very Rare Heat Extremes in Event Attribution?},
  journal = {Earth s Future},
  year = {2025},
  doi = {10.1029/2025ef006073},
  url = {https://doi.org/10.1029/2025ef006073}
}