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

Dong, Jianquan; Brönnimann, Stefan; Hu, Tao; Liu, Yanxu; Peng, Jian

The wet-bulb temperature (WBT; inline-formulaTW) 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 inline-formulaTW can be effectively used in monitoring humid heat waves and their effects on 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 HadISD (Met Office Hadley Centre Integrated Surface Database) dataset and integrating the NCEP-DOE reanalysis dataset, the daily maximum inline-formulaTW series of 1834 stations that have passed quality control were homogenized and reconstructed using the method of Climatol. These stations form a new dataset of global station-based daily maximum inline-formulaTW (GSDM-WBT) from 1981 to 2020. Compared with other station-based and reanalysis-based datasets of inline-formulaTW, the average bias was inline-formula−0.48 and 0.34 inline-formulaC, respectively. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, and also avoids the underestimation of the inline-formulaTW calculated from reanalysis data. The GSDM-WBT dataset can effectively support the research on global or regional extreme heat events and humid heat waves. The dataset is available at https://doi.org/10.5281/zenodo.7014332https://doi.org/10.5281/zenodo.7014332 (Dong et al., 2022).

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Dong, Jianquan / Brönnimann, Stefan / Hu, Tao / et al: GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020. 2022. Copernicus Publications.

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