Cascading Simplifying Assumptions Overestimates Damages From Heat Stress

Heat stress is the convolution of two principle components: environmental conditions and human health/activity. Focusing on global scale environmental conditions, researchers simplify heat stress approximations by omitting solar-thermal radiation and even humidity, by modifying carefully calibrated metrics. For example, some approximations for heat stress assume workers shift to nighttime labor conditions, thus remove solar radiation. Have these cascading assumptions oversimplified extreme covariance to the point of meaninglessness?

To analyze outcomes from extreme covariance of temperature, humidity, and solar radiation, we use a commonly applied global circulation model. We account for daytime and nighttime conditions by using the diurnal cycle for a 1986-2005 baseline. We calculate labor capacity using a commonly used industry standardized metric for heat stress that includes temperature, humidity, and solar radiation. Also, we use a proxy for the same metric with one commonly used by researchers that is simplified by omitting radiation. Our results show that there are substantial differences in labor capacity between metrics for the baseline period. For example, while using the simplified metric, South East Asia experiences 50% labor capacity. In contrast, the metric that includes radiation (theoretically hotter conditions) has 90% labor capacity for the same baseline! To determine when all work stops due to heat stress, we scale the baseline conditions by global mean surface temperature changes. For South East Asia, the simplified metric labor capacity drops to 0% at 4°C of warming. However, the standardized heat stress metric including radiation shows labor capacity dropping to 0% at >7°C of warming. Utilizing simplified heat stress metrics reduces the accuracy of projected climate change impacts.