1981—2019年中国及典型区域热环境变化特征
陈笑(2000-), 男, 硕士生, 研究方向为城市热环境与气候暴露风险。E-mail: chen_x_yun@163.com |
收稿日期: 2023-10-25
修回日期: 2025-03-07
网络出版日期: 2025-05-23
基金资助
国家自然科学基金项目(41922007)
Evolution characteristic and typical regional analysis of national thermal environment in 1981-2019
Received date: 2023-10-25
Revised date: 2025-03-07
Online published: 2025-05-23
Supported by
National Natural Science Foundation of China(41922007)
陈笑 , 孙涛 , 孙然好 . 1981—2019年中国及典型区域热环境变化特征[J]. 地理学报, 2025 , 80(5) : 1339 -1352 . DOI: 10.11821/dlxb202505012
The outdoor thermal environment impacts human heat exchange, subsequently affecting public health, travel decisions, labor production, and landscape design. However, there are still lacking large-scale and long time-series studies. Based on the Universal Thermal Climate Index (UTCI), Sen's slope estimation, and Mann-Kendall (MK) significance test, we analyze the spatiotemporal characteristics of UTCI in China from 1981 to 2019 and reveal the heat risk of typical urban agglomerations. The results show that the widespread growth trend of UTCI exists across China, with the highest intensity occurring in spring and the second highest in summer, while the trend is not significant in most areas in autumn and winter. UTCI trend intensity was higher during daytime in spring while nighttime in summer, and overall growth tended to be more pronounced in the north than in the south. High-growth areas are predominantly located in the northwest region, plateau and basin, exceeding 0.6 °C/10a. Urban agglomerations exhibit the highest UTCI growth trend in spring, generally exceeding 0.3 °C/10a, proving the "warm spring" exists. The days of different cold stress levels generally decrease while heat stress days increase thereby subjecting residents to greater levels of heat stress. The frequency of heat stress was only 24.2% in China, and generally exceeded 60% in urban areas, which would increase residents' heat exposure risk as the thermal environment shifts from comfortable to uncomfortable. This study further helps to understand the spatiotemporal patterns of thermal environment variations and provides fundamental insights for regional management, prevention, and control in the context of climate change.
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