School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, 510006, China.
Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, China.
Sci Data. 2023 Sep 18;10(1):634. doi: 10.1038/s41597-023-02535-y.
Human-perceived temperature (HPT) describes the joint effects of multiple climatic factors such as temperature and humidity. Extreme HPT events may reduce labor capacity and cause thermal discomfort and even mortality. These events are becoming more frequent and more intense under global warming, posing severe threats to human and natural systems worldwide, particularly in populated areas with intensive human activities, e.g., the North China Plain (NCP). Therefore, a fine-scale HPT dataset in both spatial and temporal dimensions is urgently needed. Here we construct a daily high-resolution (~1 km) human thermal index collection over NCP from 2003 to 2020 (HiTIC-NCP). This dataset contains 12 HPT indices and has high accuracy with averaged determination coefficient, mean absolute error, and root mean squared error of 0.987, 0.970 °C, and 1.292 °C, respectively. Moreover, it exhibits high spatiotemporal consistency with ground-level observations. The dataset provides a reference for human thermal environment and could facilitate studies such as natural hazards, regional climate change, and urban planning.
人体感知温度（HPT）描述了温度和湿度等多种气候因素的综合影响。极端 HPT 事件可能会降低劳动能力，并导致热不适甚至死亡。在全球变暖的背景下，这些事件变得更加频繁和剧烈，对全球范围内的人类和自然系统构成了严重威胁，特别是在人口密集、人类活动强度大的地区，如华北平原（NCP）。因此，迫切需要在时空维度上具有精细尺度的 HPT 数据集。在这里，我们构建了一个华北平原 2003 年至 2020 年期间（HiTIC-NCP）的每日高分辨率（~1km）人类热指数数据集。该数据集包含 12 个人体感知温度指数，具有很高的精度，平均决定系数、平均绝对误差和均方根误差分别为 0.987、0.970°C 和 1.292°C。此外，它与地面观测具有高度的时空一致性。该数据集为人类热环境提供了参考，并有助于自然灾害、区域气候变化和城市规划等方面的研究。
