UC Berkeley

Abstract The existing heat index is complicated and slow. Furthermore, its complexity has obfuscated both mathematical inconsistencies (double values) and physical inconsistencies (supersaturation). This paper presents a simplified heat index that resolves these issues. The new approach results in small changes to the heat index for air temperatures below 300 K but leaves the heat index unchanged for air temperatures above 300 K, where it is most commonly used. This simplification enhances interpretability, and a refactored algorithm accelerates the computation of the heat index by orders of magnitude. The optimized implementation is freely available in C++, R, and Python. In this article, we also clarify a long-standing ambiguity regarding “compensable” and “uncompensable” heat stress. Historically, uncompensable denoted conditions leading to fatal core temperatures. Recent studies, however, have applied the term to any inflection followed by a rise in core temperature. Using the heat index model, we show that such an observation does not necessarily imply lethality because heat loss increases with core temperature and can yield a stable, nonfatal equilibrium. To avoid ambiguity, we therefore replace compensable/uncompensable with normothermic, hyperthermic, and lethal categories based on the predicted steady-state core temperature. Significance Statement Despite the wide use of the heat index in meteorology and climate science, the thermoregulatory model underlying the heat index is not widely known or understood, likely due to its complexity. In this article, we simplify the model at low temperatures (<300 K) and present a graphical method for calculating the heat index, making its structure more intuitive. Additionally, we provide an implementation of the heat index in a low-level programming language, enabling efficient computation of the heat index for various applications.