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<p>As global warming intensifies, extreme heat events, especially those occurring simultaneously or sequentially in multiple regions, are becoming more frequent. This highlights the growing need to analyze heat stress from the perspectives of human health and spatiotemporal correlations. Wet-Bulb Globe Temperature (WBGT) is a well-established heat stress indicator closely linked to human health. However, its reliance on specialized measurements and resource-intensive computations limits its widespread use, particularly for researchers without an earth sciences background. To address this, we adopted a simplified WBGT (sWBGT), which effectively simulates human cooling through sweating, to generate a global 2° resolution dataset of daily maximum sWBGT from 1940 to 2022. This dataset fills a critical gap in long-term, global-scale heat stress data. Additionally, we employed climate network methods to innovatively explore teleconnections of extreme heat events, providing a tool to reveal their spatiotemporal relationships and supporting the development of effective health protection strategies.</p>

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Daily Max Simplified Wet-Bulb Globe Temperature and its Climate Networks for Teleconnection Study, 1940–2022

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月7日

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  • Yan Liu,
  • Changqing Song,
  • Sijing Ye,
  • Jiaying Lv,
  • Peichao Gao

摘要

As global warming intensifies, extreme heat events, especially those occurring simultaneously or sequentially in multiple regions, are becoming more frequent. This highlights the growing need to analyze heat stress from the perspectives of human health and spatiotemporal correlations. Wet-Bulb Globe Temperature (WBGT) is a well-established heat stress indicator closely linked to human health. However, its reliance on specialized measurements and resource-intensive computations limits its widespread use, particularly for researchers without an earth sciences background. To address this, we adopted a simplified WBGT (sWBGT), which effectively simulates human cooling through sweating, to generate a global 2° resolution dataset of daily maximum sWBGT from 1940 to 2022. This dataset fills a critical gap in long-term, global-scale heat stress data. Additionally, we employed climate network methods to innovatively explore teleconnections of extreme heat events, providing a tool to reveal their spatiotemporal relationships and supporting the development of effective health protection strategies.