Next Article in Journal
Ice Accretion Forecast for Power Grids Based on Pangu Model and Machine Learning Correction: A Case Study on Late December 2021 in Xinjiang, China
Previous Article in Journal
NO2 Forecasting by China Meteorological Administration Evaluated According to TROPOMI Sentinel-5P Satellite Measurements and Surface Network
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province

School of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou 121000, China
*
Author to whom correspondence should be addressed.
Atmosphere 2026, 17(1), 22; https://doi.org/10.3390/atmos17010022
Submission received: 13 November 2025 / Revised: 19 December 2025 / Accepted: 19 December 2025 / Published: 24 December 2025
(This article belongs to the Special Issue Compound Events and Climate Change Impacts in Agriculture)

Abstract

In the context of global warming, the continued increase in the frequency of compound events—where drought and high-temperature extremes coincide—has led to severe natural disasters and substantial socio-economic losses. To systematically reveal the evolution of summer dry-heat compound events in Liaoning Province, this study constructs a whole-chain analysis framework of “identification–feature extraction–multivariate probability assessment”. Based on the Standardised Precipitation Index (SPI) and the Standardised Temperature Index (STI), we develop the Standardised Dry-Heat Index (SDHI) to identify dry-heat compound events. Run theory is applied simultaneously to extract key attributes for three types of events—drought, high temperature, and dry-heat compound events—and the Mann–Kendall test is used to detect their temporal mutation characteristics. By combining Copula functions with spatial analysis techniques, we further establish a whole-chain analysis method from “identification–feature extraction–hazard quantification”. The results show that during 1961–2020, summer drought, high-temperature, and dry-heat compound events occurred 4, 14, and 10 times, respectively, in Liaoning Province, with all three types showing a significant increase in frequency after the late 1990s. Spatially, zones of high drought intensity are mainly located in western Liaoning; the duration and severity of high temperatures are most pronounced in inland basin areas; and regions with high compound hazard intensity of dry-heat events largely coincide with urbanised areas. Climate propensity analyses further reveal that the province is experiencing an increasingly dry-heat-prone climate, with high temperatures being the dominant factor driving the enhanced hazard associated with dry-heat compound events. This study overcomes the limitations of traditional single-event analyses and provides a more accurate scientific basis for hazard assessment and zonal prevention and control of dry-heat disasters in Liaoning Province.
Keywords: dry-heat composite index; run theory; Copula function; SDHI dry-heat composite index; run theory; Copula function; SDHI

Share and Cite

MDPI and ACS Style

Bai, X.; Wang, R.; Shan, F.; Cong, L. Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province. Atmosphere 2026, 17, 22. https://doi.org/10.3390/atmos17010022

AMA Style

Bai X, Wang R, Shan F, Cong L. Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province. Atmosphere. 2026; 17(1):22. https://doi.org/10.3390/atmos17010022

Chicago/Turabian Style

Bai, Xiaotian, Rui Wang, Fengjun Shan, and Longpeng Cong. 2026. "Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province" Atmosphere 17, no. 1: 22. https://doi.org/10.3390/atmos17010022

APA Style

Bai, X., Wang, R., Shan, F., & Cong, L. (2026). Spatiotemporal Evolution Characteristics of Summer Dry-Heat Compound Events in Liaoning Province. Atmosphere, 17(1), 22. https://doi.org/10.3390/atmos17010022

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop