Zhao et al. (2026) Event‐Based Detection and Attribution‐Oriented Diagnosis of Compound Hot–Drought Extremes in a Typical Region of Central North China

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

Identification

• Journal: International Journal of Climatology
• Year: 2026
• Date: 2026-08-14
• Authors: Haiyan Zhao, Siyan Dong, Xinlei Zhang, Hao Wu, Zhenyu Han
• DOI: 10.1002/joc.70515

Research Groups

• Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS)
• University of Science and Technology of China (USTC)

Short Summary

This study develops an event-based framework to detect and attribute warm-season compound hot-drought events in Central North China, revealing intensified risk in recent decades.

Objective

• Investigate the occurrence and characteristics of compound hot-drought events in inland transitional regions, particularly Shanxi Province.

Study Configuration

• Spatial Scale: Regional (Shanxi Province) to continental scale.
• Temporal Scale: Daily to decadal scale.

Methodology and Data

• Models used: None mentioned; observational data analysis.
• Data sources: Meteorological Drought Composite Index, satellite and ground-based temperature records, disaster-impact records.

Main Results

• The annual number of compound hot-drought event days and the annual compound-event percentage increased significantly during 1961–2023.
• An abrupt shift around 1996–1997 was detected, with most top-ranked event years occurring after this transition.
• Event-scale analyses identified representative major events in 1997, 2001, and 2019.

Contributions

• This study provides an observational-impact-circulation evidence chain for attribution-oriented diagnosis of compound hot-drought extremes.
• The findings highlight the importance of considering heat-dominated intensification pathways in regional climate risk assessments.

Funding

• National Natural Science Foundation of China (NSFC) projects: [project codes and titles not provided]
• CAS Key Research Program of Frontier Sciences: [project code and title not provided]

Citation

@article{Zhao2026EventBased,
  author = {Zhao, Haiyan and Dong, Siyan and Zhang, Xinlei and Wu, Hao and Han, Zhenyu},
  title = {Event‐Based Detection and Attribution‐Oriented Diagnosis of Compound Hot–Drought Extremes in a Typical Region of Central North China},
  journal = {International Journal of Climatology},
  year = {2026},
  doi = {10.1002/joc.70515},
  url = {https://doi.org/10.1002/joc.70515}
}