Bai et al. (2025) Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province

Identification

• Journal: Atmosphere
• Year: 2025
• Date: 2025-12-24
• Authors: Xiaotian Bai, Rui Wang, Fengjun Shan, Longpeng Cong
• DOI: 10.3390/atmos17010022

Research Groups

School of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou, China.

Short Summary

This study developed a comprehensive framework to analyze the spatiotemporal evolution of summer dry-heat compound events in Liaoning Province from 1961 to 2020, revealing a significant increase in their frequency and intensity, primarily driven by rising temperatures in urbanized and inland basin areas.

Objective

• To systematically reveal the spatiotemporal evolution characteristics of summer dry-heat compound events in Liaoning Province by constructing a whole-chain analysis framework of "identification–feature extraction–multivariate probability assessment".
• To extend the application of run theory to high-temperature and compound events, establishing a unified methodological framework for feature extraction across multiple types of extreme climate events.
• To construct a joint distribution model of duration and severity using Copula functions to probabilistically assess "long-duration–high-severity" extreme compound events.

Study Configuration

• Spatial Scale: Liaoning Province, China (118°53′ E–125°46′ E and 38°43′ N–43°26′ N), utilizing data from 25 national standard meteorological stations.
• Temporal Scale: 60 years (1961–2020), focusing on the summer season (June–August).

Methodology and Data

• Models used:
  • Standardised Precipitation Index (SPI-3)
  • Standardised Temperature Index (STI-3)
  • Standardised Dry-Heat Index (SDHI-3)
  • Run theory (for event identification and feature extraction: duration, severity)
  • Mann–Kendall mutation test (for temporal trend and abrupt change detection)
  • Copula functions (for multivariate joint probability assessment of duration and severity, with GEV, EV, EXP, POISS, NORM, GAM, RALY for marginal distributions and AIC criterion for selection)
  • Climate Propensity Rate (linear regression for trend magnitude)
• Data sources: Daily precipitation and air temperature data from 25 national standard meteorological stations in Liaoning Province, obtained from the China Meteorological Science Data Sharing Service (https://data.cma.cn/).

Main Results

• During 1961–2020, summer drought, high-temperature, and dry-heat compound events occurred 4, 14, and 10 times, respectively, in Liaoning Province. All three types showed a significant increase in frequency after the late 1990s, with dry-heat events increasing from 6% in the first 30 years to 26% in the latter 30 years.
• The year 2000 recorded the most severe dry-heat event, with a minimum SDHI of -1.19, a duration of 2.8 months, and a severity of 3.56.
• Temporally, a significant abrupt change in high-temperature events was detected in 2011, with the Standardised Temperature Index (STI) increasing markedly thereafter. The Standardised Dry-Heat Index (SDHI) showed a significant decline after 2015, indicating increasing frequency and intensification of dry-heat events.
• Spatially, high drought intensity was concentrated in western Liaoning (e.g., Chaoyang) and parts of Dandong. High-temperature duration and severity were most pronounced in inland basin areas (e.g., Benxi, Xinbin, Kuandian) due to topographic "heat-gathering" effects.
• Regions with high compound dry-heat hazard intensity largely coincided with urbanized areas (e.g., Shenyang, Dalian, Anshan), where the urban heat island effect amplifies warming.
• Climate propensity analyses revealed an overall warming trend across the province (positive STI propensity rate) and an increasing hazard of dry-heat events (negative SDHI propensity rate). High temperatures were identified as the dominant factor driving the enhanced hazard associated with dry-heat compound events.

Contributions

• Overcame limitations of traditional single-event analyses by constructing a unified "identification–feature extraction–hazard quantification" framework for dry-heat compound events.
• Extended the application of run theory from traditional drought studies to systematically characterize high-temperature and dry-heat compound events, providing a unified methodological approach.
• Utilized Copula functions to construct joint probability distributions of event duration and severity, enabling a probabilistic assessment of "long-duration–high-severity" extreme compound events.
• Provided a more accurate scientific basis for hazard assessment and zonal prevention and control of dry-heat disasters in Liaoning Province, highlighting the synergistic impacts of climate warming, topography, and urbanization.

Funding

• 2024 Fundamental Research Funding of the Educational Department of Liaoning Province, grant number (LJZZ232410154014)
• 2025 Fundamental Research Funding of the Educational Department of Liaoning Province, grant number (LJ212510154014)

Citation

@article{Bai2025Spatiotemporal,
  author = {Bai, Xiaotian and Wang, Rui and Shan, Fengjun and Cong, Longpeng},
  title = {Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province},
  journal = {Atmosphere},
  year = {2025},
  doi = {10.3390/atmos17010022},
  url = {https://doi.org/10.3390/atmos17010022}
}