Ahn Yoonjung, Tuholske Cascade, Parks Robbie M
Geography & Atmospheric Science Department University of Kansas Lawrence KS USA.
Institute of Behavioral Science University of Colorado Boulder Boulder CO USA.
Geohealth. 2024 Jan 23;8(1):e2023GH000923. doi: 10.1029/2023GH000923. eCollection 2024 Jan.
Climate change is escalating the threat of heat stress to global public health, with the majority of humans today facing increasingly severe and prolonged heat waves. Accurate weather data reflecting the complexity of measuring heat stress is crucial for reducing the impact of extreme heat on health worldwide. Previous studies have employed Heat Index (HI) and Wet Bulb Globe Temperature (WBGT) metrics to understand extreme heat exposure, forming the basis for heat stress guidelines. However, systematic comparisons of meteorological and climate data sets used for these metrics and the related parameters, like air temperature, humidity, wind speed, and solar radiation crucial for human thermoregulation, are lacking. We compared three heat measures (HI, WBGT, and WBGT) approximated from gridded weather data sets (ERA5-Land, PRISM, Daymet) with ground-based data, revealing strong agreement from HI and WBGT ( 0.76-0.95, RMSE 1.69-6.64°C). Discrepancies varied by Köppen-Geiger climates (e.g., Adjusted HI 0.88-0.95, WBGT 0.79-0.97, and WBGT 0.80-0.96), and metrological input variables (Adjusted 0.86-0.94, 0.91-0.94, Wind 0.33, Solar 0.38, Solar 0.38, relative humidity 0.51-0.74). Gridded data sets can offer reliable heat exposure assessment, but further research and local networks are vital to reduce measurement errors to fully enhance our understanding of how heat stress measures link to health outcomes.
气候变化正在加剧热应激对全球公共卫生的威胁,如今大多数人面临着日益严重和持久的热浪。反映测量热应激复杂性的准确气象数据对于减少极端高温对全球健康的影响至关重要。以往的研究采用热指数(HI)和湿球黑球温度(WBGT)指标来了解极端高温暴露情况,为热应激指南奠定了基础。然而,缺乏对用于这些指标的气象和气候数据集以及对人体体温调节至关重要的相关参数(如气温、湿度、风速和太阳辐射)的系统比较。我们将从网格化气象数据集(ERA5-Land、PRISM、Daymet)近似得出的三种热测量方法(HI、WBGT和WBGT)与地面数据进行了比较,结果显示HI和WBGT具有很强的一致性( 0.76 - 0.95,均方根误差1.69 - 6.64°C)。差异因柯本-盖格气候类型(例如,调整后的HI为0.88 - 0.95,WBGT为0.79 - 0.97,WBGT为0.80 - 0.96)以及气象输入变量(调整后的 为0.86 - 0.94, 为0.91 - 0.94,风速为0.33,太阳辐射为0.38,太阳辐射为0.38,相对湿度为0.51 - 0.74)而异。网格化数据集可以提供可靠的热暴露评估,但进一步的研究和本地网络对于减少测量误差以全面增强我们对热应激测量与健康结果之间联系的理解至关重要。