The CCH project (Climate Change and Health in sub-Saharan Africa, https://cch-africa.de) focuses on the rising health impacts of climate change, particularly in sub-Saharan Africa where vulnerable populations are most at risk. Despite the urgency, there has been little collaboration across disciplines to assess these effects or develop effective adaptation strategies. Key health challenges - childhood undernutrition, malaria, and cardiovascular dysfunction—remain under-researched in the context of climate change. As part of this experiment, we generated a global dataset of Wet-Bulb Globe Temperature (WBGT) projections to serve as a bioclimatic indicator for quantifying the potential health impacts of climate change. An ensemble of daily average WBGT estimates based on the primary and secondary ISIMIP3b (https://www.isimip.org) model ensemble (10 models) is provided. The ensemble includes the historical (1850–2014), SSP1-2.6 (2015–2100), SSP3-7.0 (2015–2100), and SSP5-8.5 (2015–2100) experiments. WBGT was estimated on an hourly basis using the PyWBGT Python package (Kong and Huber, 2022, doi:10.1029/2021EF002334), based on the Liljegren method (Liljegren et al., 2008, doi:10.1080/15459620802310770). This method estimates WBGT from 2 m air temperature (tas), near-surface relative humidity (hurs), surface pressure (ps), 10 m wind speed (sfcWind), and surface downward solar radiation (rsds). Hourly values were derived from daily values using an average diurnal cycle calculated separately for each Julian day. WBGT was estimated for each hour and then averaged to obtain daily values. The dataset covers the entire globe, excluding Antarctica. The following 10 models from the ISIMIP3b projects are used: CanESM5 - r1i1p1f1 CNRM-CM6-1 - r1i1p1f2 CNRM-ESM2-1 - r1i1p1f2 EC-Earth3 - r1i1p1f1 GFDL-ESM4 - r1i1p1f1 IPSL-CM6A-LR - r1i1p1f1 MIROC6 - r1i1p1f1 MPI-ESM1-2-HR - r1i1p1f1 MRI-ESM2-0 - r1i1p1f1 UKESM1-0-LL - r1i1p1f2
Menz, Christoph; Lange, Stefan; Volkholz, Jan; Hattermann, Fred F. (2025). Global WBGT estimates based on ISIMIP3b. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/WBGT_ISIMIP
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2025-07-22
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
Description
1. Number of data sets is correct and > 0: passed; 2. Size of every data set is > 0: passed; 3. The data sets and corresponding metadata are accessible: passed; 4. The data sizes are controlled and correct: passed; 5. The spatial-temporal coverage description (metadata) is consistent to the data: passed; 6. The format is correct: passed; 7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
[1] DOIKong, Qinqin; Huber, Matthew. (2022). Explicit Calculations of Wet‐Bulb Globe Temperature Compared With Approximations and Why It Matters for Labor Productivity. doi:10.1029/2021ef002334
[2] DOILiljegren, James C.; Carhart, Richard A.; Lawday, Philip; Tschopp, Stephen; Sharp, Robert. (2008). Modeling the Wet Bulb Globe Temperature Using Standard Meteorological Measurements. doi:10.1080/15459620802310770