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<p>Droughts and heatwaves are linked through different land-atmosphere coupling pathways. While high temperatures and depleted soil moisture (SM) characterize all drought-heatwave events, latent heat flux (LHF) reveals the dominant forcing mechanism driving these events. Our grid-based analysis of six drought-heatwave events since 2000 shows spatially inhomogeneous land-atmosphere coupling associated with surface flux partitioning. Atmospherically driven regimes, characterized by increased LHF following hot&#xa0;temperature anomalies, accounted for the majority of the 2022 East Asia event (64.8%). Land surface-driven regimes, exhibiting LHF deficits following&#xa0;dry SM anomalies, were most prevalent in the 2023 Central America event (45.4%). Using a medium-range forecast model, we reproduced both events and showed that the water-limited (2023 Central America) case exhibits a lead-time predictability improvement of about 2-3 days relative to the energy-limited (2022 East Asia) case. These results highlight the limits of domain-averaged coupling in the model and the potential to improve the model forecasted drought-heatwaves when incorporate regime-based characteristics.</p>

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Variations in land-atmosphere coupling during drought-heatwave events

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月5日

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  • Donghyuck Yoon,
  • Jan-Huey Chen,
  • Hsin Hsu,
  • Kirsten L. Findell

摘要

Droughts and heatwaves are linked through different land-atmosphere coupling pathways. While high temperatures and depleted soil moisture (SM) characterize all drought-heatwave events, latent heat flux (LHF) reveals the dominant forcing mechanism driving these events. Our grid-based analysis of six drought-heatwave events since 2000 shows spatially inhomogeneous land-atmosphere coupling associated with surface flux partitioning. Atmospherically driven regimes, characterized by increased LHF following hot temperature anomalies, accounted for the majority of the 2022 East Asia event (64.8%). Land surface-driven regimes, exhibiting LHF deficits following dry SM anomalies, were most prevalent in the 2023 Central America event (45.4%). Using a medium-range forecast model, we reproduced both events and showed that the water-limited (2023 Central America) case exhibits a lead-time predictability improvement of about 2-3 days relative to the energy-limited (2022 East Asia) case. These results highlight the limits of domain-averaged coupling in the model and the potential to improve the model forecasted drought-heatwaves when incorporate regime-based characteristics.