Preprints
https://doi.org/10.5194/essd-2022-309
https://doi.org/10.5194/essd-2022-309
 
09 Sep 2022
09 Sep 2022
Status: this preprint is currently under review for the journal ESSD.

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

Jianquan Dong1,2, Stefan Brönnimann2, Tao Hu1, Yanxu Liu3, and Jian Peng1 Jianquan Dong et al.
  • 1Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
  • 2Institute of Geography and Oeschger Centre for Climate Change Research, University of Bern, Bern, 3012, Switzerland
  • 3State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

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).

Jianquan Dong et al.

Status: open (until 04 Nov 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2022-309', Jonathan Buzan, 13 Sep 2022 reply
    • AC1: 'Reply on CC1', Jian Peng, 14 Sep 2022 reply
  • RC1: 'Comment on essd-2022-309', Anonymous Referee #1, 22 Sep 2022 reply

Jianquan Dong et al.

Data sets

GSDM-WBT: Global station-based daily maximum wet-bulb temperature data for 1981-2020 Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, Jian Peng https://doi.org/10.5281/zenodo.7014332

Jianquan Dong et al.

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Short summary
We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.