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<p>The scarcity of long-term, high-resolution typhoon disaster data, particularly for agricultural metrics, poses significant challenges for stable typhoon agricultural disaster risk modeling, limiting predictive accuracy. To address this critical issue, we reconstructed a county-level dataset of typhoon-affected crop areas across China’s coastal regions (Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi and Hainan) from 1980 to 2022. Data used in this study included meteorological data from 530 county-level weather stations and 1,845 original disaster records (2004–2013; 75 typhoons were included) that could be matched to local weather stations (398 stations are covered). After error revisions, we obtained a dataset covering 530 stations and 514 typhoons from 1980 to 2022. To increase the applicability of the dataset, we categorized the disasters into four classes, light, moderate, severe, and extremely severe, regarding to single station and typhoon cases, respectively. Validation through comparative analyses confirmed the strong reliability of the reconstructed dataset. The reconstructed dataset can be used to advance typhoon disaster risk research, improve forecasting and early warning systems, and support related decision-making efforts.</p>

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Reconstructed county-level dataset of crop areas affected by typhoons in China’s coastal regions (1980–2022)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月29日

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  • Wenjing Wang,
  • Caiming Wu,
  • Fumin Ren

摘要

The scarcity of long-term, high-resolution typhoon disaster data, particularly for agricultural metrics, poses significant challenges for stable typhoon agricultural disaster risk modeling, limiting predictive accuracy. To address this critical issue, we reconstructed a county-level dataset of typhoon-affected crop areas across China’s coastal regions (Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi and Hainan) from 1980 to 2022. Data used in this study included meteorological data from 530 county-level weather stations and 1,845 original disaster records (2004–2013; 75 typhoons were included) that could be matched to local weather stations (398 stations are covered). After error revisions, we obtained a dataset covering 530 stations and 514 typhoons from 1980 to 2022. To increase the applicability of the dataset, we categorized the disasters into four classes, light, moderate, severe, and extremely severe, regarding to single station and typhoon cases, respectively. Validation through comparative analyses confirmed the strong reliability of the reconstructed dataset. The reconstructed dataset can be used to advance typhoon disaster risk research, improve forecasting and early warning systems, and support related decision-making efforts.