Hu et al. (2025) Century-scale attribution and constrained projection of temperature extremes in eastern China

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

Identification

• Journal: Environmental Research Letters
• Year: 2025
• Date: 2025-12-11
• Authors: Ting Hu, Ying Sun
• DOI: 10.1088/1748-9326/ae2b87

Research Groups

Not explicitly mentioned in the abstract, but likely involves climate modeling centers contributing to CMIP6 and research groups focused on climate attribution and observational data homogenization.

Short Summary

This study performs a multi-scale attribution analysis of temperature extremes from 1901 to 2020, finding that greenhouse gas forcing is the dominant driver of observed warming, with century-scale attribution providing the most robust results for constraining future projections.

Objective

• To perform a multi-scale attribution analysis of temperature extremes over the period 1901–2020 and examine the robustness of attribution-based scaling factors across different time scales.

Study Configuration

• Spatial Scale: Global (implied by CMIP6 and general climate attribution, but not explicitly detailed in the abstract).
• Temporal Scale: 1901–2020 for historical analysis, with sub-periods like pre-1950 and post-1950s, and projections for 2081–2100.

Methodology and Data

• Models used: Coupled Model Intercomparison Project Phase 6 (CMIP6) models, large-ensemble model framework, optimal fingerprinting.
• Data sources: Newly developed homogenized observations.

Main Results

• Homogenized observations show pronounced warming in both cold and hot temperature extremes, along with a lengthening of the growing season during 1901–2020.
• These trends intensified markedly after the 1950s, with the magnitude of changes approximately doubling for some extreme indices.
• CMIP6 models successfully reproduce overall warming trends but underestimate the magnitude of changes, particularly in the pre-1950 period.
• More than 70% of the observed changes are attributed to greenhouse gas forcing.
• Aerosols offset less than 35% of the greenhouse gas-induced warming.
• The ranges of best estimates and confidence intervals (CIs) for scaling factors decrease as the attribution time period lengthens.
• Century-scale attribution (1901–2020) yields the narrowest CIs and most robust best estimates, indicating the most robust detection results.
• Scaling factors from 1951–2020 were selected to constrain projections due to more reliable observational constraints.
• Constrained end-of-century (2081–2100) projections show amplified increases of 20.3%–33.1% for most extremes compared to raw projections.

Contributions

• Provides a multi-scale attribution analysis of temperature extremes over a long historical period (1901–2020), including periods with sparse data.
• Examines the robustness of attribution-based scaling factors across different time scales, identifying the century-scale as most robust.
• Highlights the critical impact of attribution period selection on future climate projections.
• Offers a transferable framework for regional climate risk assessment by demonstrating how to constrain projections using attribution results.

Funding

Not mentioned in the abstract.

Citation

@article{Hu2025Centuryscale,
  author = {Hu, Ting and Sun, Ying},
  title = {Century-scale attribution and constrained projection of temperature extremes in eastern China},
  journal = {Environmental Research Letters},
  year = {2025},
  doi = {10.1088/1748-9326/ae2b87},
  url = {https://doi.org/10.1088/1748-9326/ae2b87}
}