Analysis of Economic Losses and Comprehensive Impact Factors of Heatwave, Drought, and Heavy Rain Disasters in Hainan Island

The increasing frequency of extreme weather events presents serious challenges to both regional and global economies. This study focuses on quantifying the economic losses caused by three major types of extreme climate events (heatwaves, droughts, and heavy rain) in Hainan Island from 2001 to 2020. Moreover, a comprehensive dataset of related economic losses was developed. To support the analysis, we constructed an Extreme Climate Economic Loss Model (ECELM). Drought and heavy rain losses were estimated using a loss intensity index based on precipitation and typhoon landfall wind speeds. Heatwave-related losses were assessed through a threshold-based optimization approach. The results show that both heatwaves and heavy rain have exhibited increasing impacts from 2001 to 2020. Although heatwaves were the most frequent extreme event in more than half of the years, heavy rain caused the highest cumulative losses, reaching CNY 75 billion. Spatial analysis indicates that the southeastern coastal areas were the most severely affected. These findings provide valuable quantitative evidence for designing targeted regional climate adaptation strategies.

Authors

Institutions

Publication Details

Journal
Atmosphere
Published
2025-08-28
DOI
https://doi.org/10.3390/atmos16091017
Citations
1
Primary Topic
Climate Change and Health Impacts
Type
article
Field-Weighted Citation Impact
1.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Economic Losses and Comprehensive Impact Factors of Heatwave, Drought, and Heavy Rain Disasters in Hainan Island

Jiquan Lin, Chenyang Yuan, Wenli Lai, Yuxin Zhou et al.
1 citations
Atmosphere
Climate Change and Health Impacts
1.20
article

Analysis of Economic Losses and Comprehensive Impact Factors of Heatwave, Drought, and Heavy Rain Disasters in Hainan Island

Jiquan Lin, Chenyang Yuan, Wenli Lai, Yuxin Zhou, Yichen Zhang, Jie Zhang
article en
1 citations

Abstract

The increasing frequency of extreme weather events presents serious challenges to both regional and global economies. This study focuses on quantifying the economic losses caused by three major types of extreme climate events (heatwaves, droughts, and heavy rain) in Hainan Island from 2001 to 2020. Moreover, a comprehensive dataset of related economic losses was developed. To support the analysis, we constructed an Extreme Climate Economic Loss Model (ECELM). Drought and heavy rain losses were estimated using a loss intensity index based on precipitation and typhoon landfall wind speeds. Heatwave-related losses were assessed through a threshold-based optimization approach. The results show that both heatwaves and heavy rain have exhibited increasing impacts from 2001 to 2020. Although heatwaves were the most frequent extreme event in more than half of the years, heavy rain caused the highest cumulative losses, reaching CNY 75 billion. Spatial analysis indicates that the southeastern coastal areas were the most severely affected. These findings provide valuable quantitative evidence for designing targeted regional climate adaptation strategies.

AtmosphereVol. 16(9)
Hainan Normal University (CN), Hainan University (CN), Department of Ecology and Environment of Hainan Province (CN), Beijing Municipal Ecological and Environmental Monitoring Center (CN), Hainan Marine Monitoring and Forecasting Center (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 19%
Climate Change and Health Impacts
1.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.