Commonly used indices disagree about the effect of moisture on heat stress

High atmospheric humidity can limit sweat evaporation, increasing heat stress. Heat stress indices (HSIs) combine temperature and humidity (some incorporate radiation and wind speed) to assess atmospheric conditions. The choice of index is crucial as it determines the relative importance of temperature and humidity in determining heat stress and health outcomes. Different HSIs lack a common scale, making direct comparisons difficult. Studies show that drier conditions lead to higher air temperatures, exacerbating heatwaves, while irrigated land tends to reduce air temperature. However, some studies suggest droughts decrease heat stress due to reduced humidity, while irrigation increases it due to increased humidity. This discrepancy has significant implications for climate adaptation actions like urban greening. This study focuses on commonly used HSIs in heat-health studies: WBT, "indoor" wet-bulb globe temperature (WBGT), simplified WBGT (sWBGT), apparent temperature, NOAA's HI, humidex, and UTCI. Neglecting radiation effects, the study uses calculus of variations to estimate the relative marginal sensitivity of different HSIs to air temperature and humidity, providing a quantitative comparison and identifying conditions where HSIs disagree. This addresses a knowledge gap in climate-health studies.

Many studies have explored the relationship between soil moisture, temperature, humidity, and heat stress. Some studies have shown a negative correlation between soil moisture and heat stress, attributing it to the mitigating effect of evapotranspiration on air temperature. Conversely, other studies have found a positive correlation, arguing that increased humidity from irrigation or higher soil moisture levels can exacerbate heat stress. This conflicting evidence highlights the need for a systematic comparison of the sensitivity of different HSIs to temperature and humidity, which is the focus of the present study.

The study employs calculus of variations to compare the sensitivity of different HSIs to temperature and humidity. The method focuses on the marginal temperature-equivalent change (M), which represents how much change in humidity is equivalent to a unit change in temperature in terms of its effect on the HSI. M is calculated using a forward difference approximation of the partial derivatives of the HSI with respect to temperature and humidity. The analysis includes several commonly used HSIs: WBT, WBGT (indoor), sWBGT, Apparent Temperature, NOAA's Heat Index, Humidex, and UTCI. The calculations are performed for a range of temperatures and relative humidity values, and the results are presented as isopleths and contour plots showing the value of M for different HSIs under various atmospheric conditions. The study also examines two case studies from the literature where different HSIs resulted in contrasting conclusions about the effect of soil moisture on heat stress. One study used a specific heat stress metric (Ts) and showed that soil drought reduces heatwave lethality. However, the current study recalculates this using various HSIs and finds opposite correlations with specific humidity. Another study modeled the impact of irrigation and concluded that it increases WBT, which leads to increased heat stress, contradicting other studies. The study uses ERA5 reanalysis data (1992-2022) to define the range of observed temperature and humidity conditions.

The analysis of M reveals significant differences in the sensitivity of various HSIs to temperature and humidity across different atmospheric conditions. In the low-temperature regime, AT, HI, and UTCI are primarily sensitive to temperature, while WBT shows higher sensitivity to humidity. In the hot-dry regime, AT, WBT, humidex, WBGT-indoor, and sWBGT exhibit low M values, indicating a lower sensitivity to humidity, whereas HI and UTCI have higher M values. In the hot-humid regime, most HSIs show low M values, indicating a general agreement on the importance of humidity. The comparison of M values allows for direct comparisons between HSIs, even when they operate on different scales. The study highlights instances where different HSIs yield opposing conclusions about the effects of changes in temperature and humidity. For example, the use of different HSIs can reverse the conclusion on the effects of soil moisture on heat stress (increased soil moisture decreases temperature but increases humidity, the impact of which on heat stress depends on the selected HSI). In one case study, the selected HSI showed a negative correlation between soil moisture and a heat stress metric, while other HSIs showed a positive correlation. In another case study, the use of WBT indicated increased heat stress with irrigation due to higher humidity, despite temperature decreases; however, using the heat index shows decreased heat stress. This emphasizes the importance of carefully selecting an appropriate HSI, considering its sensitivity to temperature and humidity under the specific conditions of the study.

The study's findings underscore the critical importance of HSI selection in studies involving changes in temperature and humidity, particularly those investigating the effects of climate adaptation measures such as irrigation or urban greening. The choice of HSI can significantly influence conclusions on the impact of these measures on heat stress. The substantial discrepancies highlighted demonstrate the need for researchers to justify their HSI selection based on the specific context and to report multiple HSIs when significant differences in sensitivity are expected. This improves the transparency and reliability of research findings. The conflicting results obtained from using different HSIs in existing studies underscore the need for a more consistent and carefully considered approach to HSI selection in future research. This also indicates that results from previous studies might be revisited to explore how the choice of HSI influences the interpretations and conclusions.

This study introduces a quantitative method (M) for comparing the sensitivity of different HSIs to temperature and humidity. The analysis reveals significant discrepancies between commonly used HSIs under various atmospheric conditions, highlighting the need for careful HSI selection. The authors emphasize the importance of reporting multiple HSIs when evaluating the effects of interventions affecting temperature and humidity, such as irrigation or urban greening. Future research should focus on developing and validating HSIs that better capture human physiological responses under a wider range of environmental conditions. The authors also encourage researchers to report component temperature and humidity measurements alongside composite indices, facilitating comparisons across studies and HSIs.

The study primarily focuses on the relative effects of temperature and humidity, neglecting other factors such as radiation and wind speed, which can influence heat stress. While the study uses ERA5 reanalysis data to establish a baseline climate range, the analysis doesn't account for spatial variability in atmospheric conditions or microclimatic effects. The study's quantitative comparison method is limited to the specific HSIs included and may not be generalizable to all available HSIs. Finally, the study relies on existing literature case studies for illustrating the impact of HSI selection on research conclusions, which may not capture the full spectrum of studies in this field.