Distinct intraseasonal pathways driving rapidly escalating heat extremes in North China and their subseasonal predictability

Rapidly escalating heat extremes, characterized by abrupt onset and limited preparation time, pose disproportionate risks to public health, agriculture, and regional economies, yet their governing mechanisms and subseasonal predictability remain poorly understood. Here we identify 107 such events over North China during the summers of 1940–2024 and classify them into four spatial types. Thermodynamic and circulation analyses show that rapid warming arises from different combinations of horizontal warm advection and subsidence-induced adiabatic heating. The four types are linked to distinct intraseasonal circulation patterns involving tropical convection, mid–high-latitude wave trains, or their interference. Forecasts from subseasonal-to-seasonal dynamical prediction systems show a consistent hierarchy: events driven mainly by tropical intraseasonal variability are the most predictable, whereas events associated with two extratropical wave trains have the lowest skill. These results establish a process-based framework linking intraseasonal dynamics to rapid heat escalation and provide a physical basis for improving subseasonal prediction of high-impact heat extremes. Rapidly escalating heat extremes in North China are classified into four types with distinct intraseasonal physical pathways, with tropical-driven events showing the highest predictability and dual-extratropical-wave-train events the lowest, as revealed by observations and climate model experiments.

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Publication Details

Journal
Communications Earth & Environment
Published
2026-11-01
DOI
https://doi.org/10.1038/s43247-026-04031-8
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00

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article

Distinct intraseasonal pathways driving rapidly escalating heat extremes in North China and their subseasonal predictability

Huayu Chen, Jing Yang, Qinmei Han, Chen Xiaochen et al.
4 links
Communications Earth & Environment
Climate variability and models
article

Distinct intraseasonal pathways driving rapidly escalating heat extremes in North China and their subseasonal predictability

Huayu Chen, Jing Yang, Qinmei Han, Chen Xiaochen, Shuai Hu, Wenqi Zhang, Qing Bao, Yixuan He, delete
article en

Abstract

Rapidly escalating heat extremes, characterized by abrupt onset and limited preparation time, pose disproportionate risks to public health, agriculture, and regional economies, yet their governing mechanisms and subseasonal predictability remain poorly understood. Here we identify 107 such events over North China during the summers of 1940–2024 and classify them into four spatial types. Thermodynamic and circulation analyses show that rapid warming arises from different combinations of horizontal warm advection and subsidence-induced adiabatic heating. The four types are linked to distinct intraseasonal circulation patterns involving tropical convection, mid–high-latitude wave trains, or their interference. Forecasts from subseasonal-to-seasonal dynamical prediction systems show a consistent hierarchy: events driven mainly by tropical intraseasonal variability are the most predictable, whereas events associated with two extratropical wave trains have the lowest skill. These results establish a process-based framework linking intraseasonal dynamics to rapid heat escalation and provide a physical basis for improving subseasonal prediction of high-impact heat extremes. Rapidly escalating heat extremes in North China are classified into four types with distinct intraseasonal physical pathways, with tropical-driven events showing the highest predictability and dual-extratropical-wave-train events the lowest, as revealed by observations and climate model experiments.

Communications Earth & Environment
China Meteorological Administration (CN), Chinese Academy of Sciences (CN), Nanjing University of Information Science and Technology (CN), Beijing Normal University (CN), Institute of Atmospheric Physics (CN), Max Planck Institute for Meteorology (DE), International Max Planck Research School on Earth System Modelling (DE)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 47%
Climate variability and models
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