Tang et al. (2025) Baseline temperature variability shapes the geographical distribution of future hot extremes under anthropogenic warming

Identification

• Journal: Communications Earth & Environment
• Year: 2025
• Date: 2025-11-26
• Authors: Zhili Tang, Shenghui Zhou, Xiaohui Ma, Lixin Wu, Wenju Cai, Zhao Jing, Zhaohui Chen, Bolan Gan
• DOI: 10.1038/s43247-025-02929-3

Research Groups

• Frontiers Science Center for Deep Ocean Multispheres and Earth System and Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao, China
• Academy of Future Ocean, Ocean University of China, Qingdao, China
• Laoshan Laboratory, Qingdao, China
• State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, China
• State Key Laboratory of Marine Environmental Science & College of Ocean and Earth Sciences, Xiamen University, Xiamen, China

Short Summary

This study identifies baseline temperature variability as a key factor shaping the global distribution of future hot extremes under anthropogenic warming, demonstrating that over 80% of the global increase in hot extremes is anticorrelated with this variability, a relationship anchored by persistent land-atmosphere coupling over century timescales.

Objective

• To identify the factors driving the heterogeneous geographical distribution of intensifying hot extreme events under anthropogenic warming.
• To investigate the statistical factors and associated physical processes driving the spatial heterogeneity of future hot extremes in a warming climate.

Study Configuration

• Spatial Scale: Global (70°S–70°N), with regional analyses. Model resolutions: HR-CESM (~0.25° atmospheric, ~0.1° oceanic); CMIP6 models (0.1° to 1° oceanic, 0.25° to 1° atmospheric).
• Temporal Scale: Historical (1850–2005, specifically 1981–2000 for baseline) and Future (2006–2100, specifically 2081–2100 for HR-CESM, 2031–2050 for CMIP6). Century timescales for land-atmosphere coupling persistence.

Methodology and Data

• Models used:
  • Eddy-resolving high-resolution Community Earth System Model (HR-CESM)
  • 10 climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6), including High-Resolution Model Intercomparison Project (HighResMIP) simulations.
• Data sources:
  • HR-CESM simulations (preindustrial control, historical, RCP8.5 scenario).
  • CMIP6 model simulations (historical, RCP8.5 scenario).
  • ERA5 reanalysis data (European Centre for Medium-Range Weather Forecasts) for 1979–2019.

Main Results

• Global average total duration of hot extremes is projected to increase more than 25-fold by the end of the 21st century (2081–2100) compared to historical (1981–2000) under the RCP8.5 scenario, with cumulative heat rising over 70 times.
• The geographical distribution of future hot extreme increases is highly heterogeneous; over 80% of the global increase in hot extremes (and 93% in CMIP6) is negatively correlated with historical (baseline) temperature variability.
• This negative correlation is consistent with the signal-to-noise ratio framework, where regions with lower baseline variability (higher signal-to-noise ratio) experience greater increases in hot extremes.
• Baseline temperature variability is primarily driven by latent heat flux variance and soil moisture variance, highlighting the critical role of soil moisture in modulating temperature variability.
• Land-atmosphere coupling, defined as the correlation between detrended evaporation and surface temperature, exhibits remarkable spatial stability and persistence over century timescales (correlation of 0.86 in HR-CESM, 0.97 in CMIP6), anchoring the spatial heterogeneity of future hot extremes.
• Atmospheric dynamics (synoptic scales, intraseasonal fluctuations, stationary waves) contribute to temperature variability but play a more localized and limited global role compared to land-atmosphere coupling.

Contributions

• Identifies baseline temperature variability as a robust, key factor shaping the global distribution of future hot extremes, validated across multiple climate models, warming levels, and thresholds.
• Provides a physical interpretation of this relationship within the signal-to-noise ratio framework.
• Demonstrates that the spatial distribution of baseline temperature variability is anchored by persistent land-atmosphere coupling over century timescales.
• Proposes baseline temperature variability as a potential, simplified predictive indicator for the geographical distribution of future hot extremes, offering valuable insights for developing targeted adaptation strategies.

Funding

• Scientific Research Innovation Capability Support Project for Young Faculty (ZYGXQNJSKYCXNLZCXM-O6)
• National Natural Science Foundation of China (42376025)
• Science and Technology Innovation Program of Laoshan Laboratory (LSKJ202300302, LSKJ202202503)
• Shandong Provincial Natural Science Foundation (ZR2022YQ29)
• Taishan Scholar Funds (tsqn202103028)

Citation

@article{Tang2025Baseline,
  author = {Tang, Zhili and Zhou, Shenghui and Ma, Xiaohui and Wu, Lixin and Cai, Wenju and Jing, Zhao and Chen, Zhaohui and Gan, Bolan},
  title = {Baseline temperature variability shapes the geographical distribution of future hot extremes under anthropogenic warming},
  journal = {Communications Earth & Environment},
  year = {2025},
  doi = {10.1038/s43247-025-02929-3},
  url = {https://doi.org/10.1038/s43247-025-02929-3}
}