The diverging predictions of extreme heat risk indicators

About two hundred thermal indicators exist and yield divergent assessments of heat stress impacts and mitigation. Thus, examining how these indicators respond to various meteorological variables and exploring the implications for their practical use is imperative. Using a correlation analysis, we cluster common indicators into three types: 1) human energy budget models, 2) integrated weather indices, and 3) thermal perception indicators. Distinct extreme hot conditions are identified differently by the various clusters of indicators: human energy budget models are more responsive to micro-scale variation in wind and radiation; while integrated weather indices mainly capture synoptic moist heat extremes. These biophysical indicators also do not concur with a metamodel of thermal perception, developed here using a meta-analysis of coefficients in existing thermal sensation vote equations. The developed thermal perception metamodel is more sensitive to radiation fluxes than other thermal stress indicators. It implies that humans’ thermal sensation may underestimate humid heat stress at nighttime, which can pose a significant risk to human health in hot, humid cities such as Chennai (India) and Dakar (Senegal) and across the Global South. These findings deepen our understanding of heat stress variability on humans and provide a framework for selecting suitable indicators in future applications.