Data from Environmental Research Letters manuscript 'Global labor loss due to humid heat exposure underestimated for outdoor workers', DOI: https://doi.org/10.1088/1748-9326/ac3dae. Associated Python (Jupyter Lab) scripts and working environment to load and plot data can be found at: https://github.com/LukeAParsons/erfs_comparison Abstract: 'Humid heat impacts a large portion of the world���s population that works outdoors. Previous studies have quantified humid heat impacts on labor productivity by relying on exposure response functions that are based on uncontrolled experiments under a limited range of heat and humidity. Here we use the latest empirical model, based on a wider range of temperatures and humidity, for studying the impact of humid heat and recent climate change on labor productivity. We show that globally, humid heat may currently be associated with over 650 billion hours of annual lost labor (148 million full time equivalent jobs lost), 400 billion hours more than previous estimates. These differences in labor loss estimates are comparable to losses caused by the COVID-19 pandemic. Globally, annual heat-induced labor productivity losses are estimated at 2.1 trillion in 2017 PPP$, and in several countries are equivalent to more than 10% of gross domestic product. Over the last four decades, global heat-related labor losses increased by at least 9% (>60 billion hours annually using the new empirical model) highlighting that relatively small changes in climate (<0.5 ���C) can have large impacts on global labor and the economy.'

sWBGT based on ERA5 data, ~31kmx31km horizontal resolution at equator. Per capita work hours lost on era5 grid, other data on 0.5x0.5 degree lat/lon grid structure. Other data from ILOSTAT and World Bank. Population data from 2017 GPWv4 dataset. Country mask and associated csv files with country names thanks to G. Faluvegi at NASA. K Seltzer regridded the GPWv4 grid to 0.5x0.5 degree. ILO data downloaded by Y. Zhang.