Daily Max Simplified Wet-Bulb Globe Temperature and its Climate Networks for Teleconnection Study, 1940-2022

This dataset comprises global simplified Wet-Bulb Globe Temperature (sWBGT) values from 1940 to 2022, calculated at a daily maximum with a spatial resolution of 2°x2°. The sWBGT integrates air temperature, dew point temperature, and surface air pressure to provide a measure of heat stress. The dataset was derived from the ERA5 hourly data on single levels.
In addition to the sWBGT values, the dataset includes climate network data and network metrics calculated for selected years (every five years from 1940 through 2020). These data facilitate the analysis of teleconnections, or long-distance correlations in heat stress events, and provide insights into the spatial correlations and propagation of heat stress effects across different regions.
The sWBGT data are stored in NetCDF format, making them compatible with commonly used data analysis tools in climate research. The climate network data and network metrics are saved in the pickle format to ensure efficient serialization and deserialization of Python objects used in network analysis.
All the Python scripts required to calculate the dataset are also included. These scripts allow users to replicate the dataset or adapt the methodology for their own research needs.
This dataset supports researchers in climate science, public health, and environmental policy by enabling the examination of historical trends and the assessment of future risks associated with heat stress.

本数据集包含1940年至2022年的全球简化湿球黑球温度（sWBGT）值，以日最大值计算，空间分辨率为2°×2°。sWBGT整合了气温、露点温度和地面气压，以提供热应激的度量指标。该数据集源自ERA5单层次逐小时数据。
除sWBGT值外，数据集还包含气候网络数据及针对选定年份（1940年至2020年每五年一次）计算的网络指标。这些数据有助于分析遥相关（即热应激事件中的远距离相关性），并为不同区域热应激效应的空间相关性及传播规律提供见解。
sWBGT数据以NetCDF格式存储，可与气候研究中常用的数据分析工具兼容。气候网络数据及网络指标以pickle格式保存，以确保网络分析中所用Python对象的高效序列化与反序列化。
数据集还包含计算所需的所有Python脚本，用户可通过这些脚本复现数据集，或根据自身研究需求调整方法。
该数据集通过支持对历史趋势的考察及热应激相关未来风险的评估，为气候科学、公共卫生及环境政策领域的研究者提供助力。