GSDM-WBT: Global station-based daily maximum wet-bulb temperature data for 1981–2020

作者：Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, Jian Peng · 年份：2022 · DOI：10.5194/essd-2022-309 · 被引用次数：1 · 研究领域：Climate Change and Health Impacts、Climate variability and models、Solar Radiation and Photovoltaics

Abstract. The wet-bulb temperature (WBT) comprehensively characterizes the temperature and humidity of the thermal environment and is a relevant variable to describe the energy regulation of the human body. The daily maximum WBT can be effectively used in monitoring humid heatwaves and the response on human health. Because meteorological stations differ in temporal resolution and are susceptible to non-climatic influences, it is difficult to provide complete and homogeneous long-term series. In this study, based on the sub-daily station-based dataset of HadISD and integrating the NCEP-DOE reanalysis dataset, the daily maximum WBT series of 1834 stations that have passed quality control were homogenized and reconstructed using the method of Climatol. These form a new data set of global station-based daily maximum WBT (GSDM-WBT) from 1981 to 2020. Compared with other station-based and reanalysis-based datasets of WBT, the average bias was -0.48 °C and 0.34 °C respectively. GSDM-WBT handles stations with many missing values and possible inhomogeneities, and also offsets the underestimation of the WBT calculated from reanalysis data. The GSDM-WBT dataset can effectively support the research on global or regional extreme heat events and humid heatwaves. The dataset is available at https://doi.org/10.5281/zenodo.7014332 (Dong et al. 2022).