Ran et al. (2025) Intensification of Compound Extreme Drought and Hot Events in Tibet: Insights from a Novel Compound Framework

Identification

• Journal: Earth Systems and Environment
• Year: 2025
• Date: 2025-12-29
• Authors: Yaowen Ran, Zegen Wang, Mi Chen, Xingyu Chen, Jiayi Hu, Chaoyue Li, Zhilong Liang, Zhiwei Yong, Yanmei Yang
• DOI: 10.1007/s41748-025-00992-6

Research Groups

• School of Geoscience and Technology, Southwest Petroleum University, Chengdu, China
• School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, China

Short Summary

This study developed a novel spatiotemporal framework to identify and analyze compound extreme drought and hot events (CDHEs) in Tibet from 2000-2020, revealing their widespread occurrence, significant spatiotemporal clustering, and rapid intensification, particularly in duration and frequency, highlighting an urgent need for enhanced early-warning systems.

Objective

• To develop a novel spatiotemporal framework for identifying compound extreme drought and hot events (CDHEs) that integrates temporal dynamics and spatial heterogeneity.
• To systematically characterize multiple spatiotemporal compound patterns of CDHEs in Tibet, including simultaneous and sequential occurrences at site and area scales.
• To reveal the hotspot areas and spatiotemporal evolution of CDHEs in Tibet from 2000 to 2020.

Study Configuration

• Spatial Scale: Tibet (78°25′–99°06′E, 26°50′–36°53′N), covering approximately 1.23 million square kilometers, with an average elevation exceeding 4,000 meters.
• Temporal Scale: 2000–2020 (21 years), with a focus on the May–September period for monthly variations.

Methodology and Data

• Models used:
  • Extreme Hot Events (EH): Relative threshold method (90th percentile of daily maximum temperature over a 31-day moving window), requiring 3 or more consecutive days above the threshold.
  • Extreme Drought Events (ED): Soil Moisture Deficit Index (SMDI), with an event defined when SMDI < -2.
  • Compound Extreme Drought and Hot Events (CDHEs) Framework: A novel spatiotemporal identification framework defining four patterns:
    • Concurrent Site Extreme Drought and Hot Event (COSDH)
    • Concurrent Area Extreme Drought and Hot Event (COADH)
    • Sequential Site Extreme Drought and Hot Event (SESDH)
    • Sequential Area Extreme Drought and Hot Event (SEADH)
  • Trend Analysis: Theil-Sen median trend analysis and Mann–Kendall test.
• Data sources:
  • ERA5-Land Reanalysis Dataset (ECMWF): 2-meter air temperature and soil water (0–28 cm layer).
    • Spatial resolution: 0.1° × 0.1°.
    • Temporal resolution: Hourly (aggregated to daily maximum temperature).
  • Administrative Boundaries: National Geographic Information Service Platform.
  • Elevation Data: ASTER DEM v3 from the National Earth System Science Data Center (30 m spatial resolution, resampled to 0.1° × 0.1°).

Main Results

• CDHEs are widespread across Tibet (excluding parts of Nyingchi) and exhibit strong spatiotemporal clustering, with June–August being the most affected season.
• The monthly average duration of CDHEs is 6.63 days, with hotspots identified in western Ngari and the Lhasa region.
• Across the four CDHEs modes, the mean duration reaches 8.59 days, with Sequential Area Extreme Drought and Hot Events (SEA_DH) persisting the longest at an average annual duration of 13.95 days.
• All CDHEs indicators (average duration, total duration, number of occurrences, and frequency) show significant upward trends from 2000 to 2020.
• The mean duration of CDHEs increased by 0.24 days per year across Tibet, with growth rates exceeding 0.30 days per year in Nagqu, Shannan, and Lhasa.
• Annual growth rates for the average duration of COSDH, COADH, SESDH, and SEADH are 0.13, 0.12, 0.32, and 0.38 days per year, respectively, indicating that sequential events are intensifying faster.
• The most rapid strengthening of CDHEs occurs in June and August, with average growth rates exceeding 0.15 days per year, and annual total duration increases exceeding 4 days per year in parts of central–northern Tibet and the Chamdo region.
• Hotspot regions for CDHEs are primarily concentrated in southwestern Ngari, northwestern Shigatse, and southern Chamdo.
• Central valleys in Tibet, particularly densely populated and agricultural areas around Lhasa, face increasing CDHE risks, with average duration increases exceeding 0.25 days per year in August.

Contributions

• Developed a novel spatiotemporal framework for identifying compound extreme drought and hot events (CDHEs) that explicitly integrates temporal dynamics and spatial heterogeneity, addressing limitations of traditional statistical methods.
• Defined and systematically characterized four distinct spatiotemporal compound patterns of CDHEs (COSDH, COADH, SESDH, SEADH), offering a more nuanced understanding of their occurrence.
• Provided a comprehensive analysis of the spatiotemporal characteristics, hotspot regions, and evolutionary trends of CDHEs in Tibet, a highly climate-sensitive region.
• Offered a robust scientific basis for regional climate risk assessment and disaster management in the Qinghai–Tibet Plateau and a methodological framework transferable to the study of multi-hazard compound events in other regions.

Funding

• Sichuan Science and Technology Program (NO.24YFHZ0133)
• Open Fund of Technology Innovation Center for Remote Sensing Monitoring of Natural Resources in Southwest China Mountains, Ministry of Natural Resources (No. RSMNRSCM-2024–008)
• Sichuan Science and Technology Program (No. 2025ZNSFSC0004)
• National Key R&D Program of China (2023YFB3907600)

Citation

@article{Ran2025Intensification,
  author = {Ran, Yaowen and Wang, Zegen and Chen, Mi and Chen, Xingyu and Hu, Jiayi and Li, Chaoyue and Liang, Zhilong and Yong, Zhiwei and Yang, Yanmei},
  title = {Intensification of Compound Extreme Drought and Hot Events in Tibet: Insights from a Novel Compound Framework},
  journal = {Earth Systems and Environment},
  year = {2025},
  doi = {10.1007/s41748-025-00992-6},
  url = {https://doi.org/10.1007/s41748-025-00992-6}
}