Robust scaling with global mean temperature of future heat stress projections within CMIP5 and CESM LENS

Heat stress is of global concern because it threatens human and animal health and productivity. Here we use the HumanIndexMod to calculate 3 moist thermodynamic quantities and 9 commonly and operationally used heat stress metrics (Buzan et al., 2015). We drive the HumanIndexMod with output from CMIP5 and the Community Earth System Model Large Ensemble (LENS) using the greenhouse gasses forcing, representative concentration pathway 8.5 (RCP8.5). We limit our analysis to models that provide 4x daily output of surface pressure, reference height temperature and moisture, and use lowest model level winds where available, 18 CMIP5 and 40 LENS simulations. We show three novel results:

Comparing time slices (2081-2100 and 2026-2045 for CMIP5, and 2071-2080 and 2026-2035 for LENS), we note that each individual heat stress metric extreme, within the multi-model mean, has spatial patterns that are highly correlated (>0.99). Moist thermodynamics and heat stress extremes are intrinsically linked to the thermodynamics of the climate, and scales simply with global mean surface temperature (GMT) changes. For example, large swaths of land surface area from 30°N to 30°S, excluding the Sahel, the Arabian Peninsula, and Himalayan Plateau, show the response of wet bulb temperature to be 0.85°C/°C GMT (standard deviation <0.25) for CMIP5 and 0.85°C/°C GMT (standard deviation <0.2) for LENS in agreement with prior work by Sherwood and Huber (2010). Many heat stress metrics, after being normalized by global mean surface temperature changes, are highly spatially correlated with each other, and may reduce the necessity of numerous metrics to properly quantify total heat stress. The three results establish that different climate models, with various underlying assumptions (CMIP5) and ranges of internal variability (LENS), show similar responses in heat stress with respect to global mean temperature changes. Thus, we find the uncertainty of heat stress extremes, even changes at the fine scale, is largely subsumed within the main uncertainties encompassed in transient climate sensitivity. These results are consistent with the hypothesis that outdoor worker productivity will drop significantly with substantial climate change.