A physiological approach for assessing human survivability and liveability to heat in a changing climate

Domain: earth_science
Published: 2023-11-29
Editorial outcome: major_revision

Abstract
Most studies projecting human survivability limits to extreme heat with climate change use a 35°C wet-bulb temperature (Tw) threshold without integrating variations in human physiology. This study applies physiological and biophysical principles for young and older adults, in sun or shade, to improve current estimates of survivability and introduce liveability (maximum safe, sustained activity) under current and future climates. Our physiology-based survival limits show a vast underestimation of risks by the 35°C Tw model in hot-dry conditions. Updated survivability limits correspond to Tw ~25.8–34.1°C (young) and ~21.9–33.7°C (old)—0.9–13.1°C lower than Tw = 35°C. For older female adults, estimates are ~7.2–13.1°C lower than 35°C in dry conditions. Liveability declines with sun exposure and humidity, yet most dramatically with age (2.5–3.0 METs lower for older adults). Reductions in safe activity for younger and older adults between the present and future indicate a stronger impact from aging than warming.

Introduction
Adverse health impacts of extreme heat exposure are expected to rise globally due to a warming climate, urban-induced warming, and a growing and aging population1,2. The concerns for human health, productivity, and well-being are greater in humid climates and for vulnerable populations3–5, such as older adults, unhoused, and/or those with chronic diseases. Therefore, robust models to assess current heat-health impacts and project future risks must incorporate specific vulnerabilities and diverse environmental contexts6.

Methods to project future heat stress risk can be broadly categorized into epidemiology/econometric and physiology-based approaches, which have contrasting benefits and limitations. Epidemiology/econometric approaches are empirical in nature, analyzing time series of historical temperature paired with particular health consequences (e.g., morbidity or mortality) across populations to determine heat-health relationships. These studies often find higher rates of cardiovascular and respiratory deaths associated with high ambient temperatures. Future health burdens from heat can be estimated by applying these relationships to climate model outputs (i.e., daily temperature) under different warming scenarios7,8. Empirical approaches are based on real-life outcomes and the range of realistic living conditions, and they can explore the cumulative effects of exposures over multiple days. However, two limitations for climate change projections include 1) assumptions needed to extrapolate results to warmer temperatures than observed in the historical sample9 and 2) ambiguity regarding the role of humidity in heat-health outcomes10. While some epidemiological studies find a relationship between mortality in the heat and humidity11, most find minimal associations between humidity and heat-health outcomes12. Given that specific humidity is robustly expected to increase with global warming, this uncertainty is a key research gap for epidemiology-based projections of future heat stress.

Physiology-based studies of future heat stress risk employ relationships between the thermal environment and health outcomes based on human energy balance considerations, with parameters constrained by studies of physiologic processes. In contrast to epidemiology/econometric approaches, physiology-based studies of heat-health outcomes consistently find a robust role of atmospheric humidity in heat stress via its modulation of evaporative cooling from sweat10. However, physiology studies are limited in not directly observing health outcomes, such as hospitalization or death, and employ idealized conditions from thermal chamber studies.

A range of physiology-based metrics has been applied to project future heat stress. Sherwood & Huber12 introduced a 35°C wet bulb temperature (Tw) threshold that would result in death after 6 h of exposure and applied this threshold to project future adaptability limits under varying levels of warming. Since then, numerous studies have used this approach, wherein a psychometric Tw of 35°C assumes death13–17. The Tw of 35°C represents a thermodynamic limit to heat exchange, whereby the human body becomes an adiabatic system, assuming the person is indoors or shaded, unclothed, completely sedentary, fully heat acclimatized, and of average size without thermoregulatory impairments12. As an example of a different metric, Dunne et al.18 estimated future reductions in labor capacity under different warming scenarios using established guidelines for physical labor under different wet bulb globe temperature levels. While these studies incorporate valuable information about humidity and physiology more realistically than epidemiological studies, their thermal physiology theory remains relatively unsophisticated. These approaches cannot capture complexities and personal characteristics affecting human thermoregulation (e.g., body size, activity levels, clothing, or physiological restrictions—such as sweating—to thermoregulation6,19), which may cause substantial errors.

To be useful, heat-health projections should realistically account for factors that increase health risks, such as individual physical characteristics and physiological impairments, as well as interventions that modify or decrease impacts (e.g., lowering metabolic rate; behaviors to reduce exposures). Moreover, models should incorporate ranges in environmental parameters that, together with temperature, result in specific thermoregulatory effects (e.g., dry, humid, sun/shade, wind speed)19. Physiological and biophysical models offer new opportunities to assess how humans might live and work in a warmer future rather than merely determining the prospects for life and death. Here, we demonstrate a unique approach using physiological principles that align with human thermal responses to heat (e.g., heat strain) to overcome simplified approaches that miss essential physiologic and behavioral factors in the heat.

Heat strain, characterized by thermal, cardiovascular, and renal strain, can lead to adverse health outcomes such as heat exhaustion, heat stroke, or cardiovascular collapse. Risk is higher in people with pre-existing illnesses (e.g., cardiovascular disease20, or are immunocompromised21). Aging1,21, certain medications22, and differences in body composition23 may exacerbate heat strain due to impairments to sweating and/or blood flow or the internal management of body heat storage. Conversely, fitness24, heat acclimatization25, and behavioral adaptations26–28 protect against excessive heat strain. This study and others assessing survivability limits (e.g., refs. 12,14,16) estimate deaths from critical high core temperatures causing heat stroke, where a complex cascade of events29 ultimately leads to multi-organ failure30,31 and often death29. Hence, we model heat stroke deaths (hyperthermia) and do not model the two other common types of heat-related deaths: cardiovascular collapse and renal failure, acknowledging that heat stroke deaths are a fraction of total excess heat-related deaths. A human would experience heat stroke death from hyperthermia on 99.9% of occasions when an individual’s core temperature (Tcore) exceeds 43°C29,32 (see Table 1). Thus, we define the limit of survivability as reaching a Tcore of 43°C in 3- or 6-hour exposure windows to allow for comparison with the Tw of 35°C assumption (heat stroke death after 6 hours). Liveability is the maximum internal heat production, or level of physical activity, that a person can generate without a sustained positive rate of heat storage in the prevailing environment, thus allowing safe, sustained work and play for an extended period. The realistic final Tw value for the limits of survivability or liveability will differ by person (age, body size) and climate (dry versus humid; sun versus shade), and thus is flexible (i.e., the limits will differ). Hence, while we state a final Tw at which heat stroke death will almost inevitably occur, our approach does not assume a unique Tw threshold; rather, hundreds of Tw thresholds are possible depending on differences in people and conditions modeled, with wide-ranging opportunities of the model in future research.

The overarching goal of this study is to improve heat survivability modeling frameworks and approaches used in climate change research and introduce an approach to assess liveability. As an initial step towards these advances, we apply a whole-body human heat exchange model to estimate heat stroke deaths and maximum/safe activity intensity. We focus on two subpopulation types (younger (~18–30 y) and older (>65 y) female adults), considering sweat rate impairments (due to older age) and heat exposures in the sun or shade across an array of air temperature (Tair) and humidity levels. We estimate 1) a range of survivability conditions for humans, particularly where deviations from the 35°C Tw model exist, and 2) the liveability of humans based on levels of physical activity that can be safely carried out without sustained positive heat storage. Finally, we apply the new liveability approach using global climate model (GCM) data to estimate liveability at a global scale, under current and projected climates. An overview of environmental conditions, populations modeled, and assessment types included herein is provided in Fig. 1. We do not demonstrate the sensitivity to illness or health status (including acclimatization) in the population, activity velocity, personal cooling strategies, or an ensemble of climate projections—investigations that are worthy future extensions of the methods described in this paper, but out of scope for the present work (see below).

Results
Survivability
All survivability results are presented by age (younger versus older female adults) for discrete 3- and 6-hour heat exposure durations. These durations are consistent, and thus comparable, with past studies assessing future survivability12 and the highest time resolution data commonly saved from GCM simulations. Results are shown for moderate to extreme combinations of temperature and humidity that may occasionally be reached today, both indoors and outdoors, but more frequently in the future32. Further, we acknowledge that in most circumstances, human agency allows people to seek shade to reduce their heat load33; hence, we primarily focus on shaded survivability results, allowing a more direct comparison with the Tw of 35°C adaptability hypothesis.

The updated physiologic survivability curves—or the environmental limits indicating heat stroke—by exposure duration and age group are shown in Fig. 2 (thick black lines). These environmental ranges, or zones, indicate that survivability are larger for young adults (Fig. 2a). As conditions become drier, the survivability area declines and the curves bend down due to sweating restrictions, a feature not captured by the traditional Tw of 35°C approach. These shifts are observed at the intersection between zones 3 (pink), 4 (purple), and 5 (gray) in Fig. 2, each indicating a different reason for the increase in Tcore towards death—i.e., due to environmental restrictions (Emaxenv) (pink), sweating restrictions (Emaxsweat) (purple), or both (Emaxsweat and Emaxenv) (gray) (see Methods and SM).

The 6-hour survival limit for Tw differs depending on the magnitudes of Tair and relative humidity (RH). For example, at an RH of 50%, a healthy young adult can withstand conditions up to 43.3°C Tair (representing a Tw of 33.6°C). However, under drier conditions (RH of 25%), the same young, healthy adult may withstand a Tair up to 49.9°C (or a Tw of only 31.3°C). The survivability in these dry conditions is impacted by the body’s ability to produce sweat, as visualized by the growth of zone 4 (curve shifting down) in Fig. 2 as conditions become drier. For older adults, this downward shift is prominent at a lower Tair and higher RH, where these older individuals can survive only a 6-hour exposure at a Tair of 45.4°C at 25% RH (Tw of 27.8°C), which is 3.5°C Tw lower than for young adults, and 7.2°C lower than the 35°C Tw.

When expressing the survivability limits of the physiological model in terms of the critical Tw within very humid (RH > 90%) and shaded conditions, values are broadly in agreement with the traditional Tw = 35°C assumption (~0.7–1.3°C lower Tw for a 6-hour duration) (see Table 2, Fig. 3). However, in drier conditions, the physiological survival Tw limits are much lower (distance between survivability line and Tw = 35°C line, Fig. 3). As such, the most critical differences from the Tw = 35°C assumption occur as conditions become very hot and dry (Tair > 40°C and RH < 25%). For young adults, the physiological Tw survival limit ranges from 25.8–31.3°C (or 3.8–9.2°C lower than 35°C). These dry-condition limits are reduced further for older adults to a Tw of 21.9–27.8°C (or 7.2–13.1°C lower than 35°C). Further, shaded older adults would not survive a 6-hour exposure beyond Tw = 21.9°C at 10% RH (thus Tair = 46.4°C); yet the Tw = 35°C assumption presumes they could endure a 6-hour exposure at a Tair of 60°C+ at the same RH.

Liveability
The limit to safe physical activities differs by Tair, RH, age, and sun exposure (Fig. 4). Mmax, represented by metabolic equivalents (METs), is higher under cooler, drier conditions. In shade at Tair = 25°C, young adults can safely reach Mmax values around 5.0 METs (e.g., dancing) for humid conditions while maintaining thermal equilibrium, with even higher possible Mmax (8.4 METs, or running) in drier environments. When sun-exposed at the same Tair, the Mmax limit decreases to ~3.9–7.4 METs (e.g., housework, climbing stairs). As Tair rises in Fig. 4, the Mmax declines sharply for RH above 75%. In such humid conditions, young adults reach a limit in their ability to perform any activity safely at a Tair of ~35.5°C (or 34.0°C Tw for older adults). Accordingly, the hatched zone in Fig. 4 highlights the range of conditions in which no additional work > 1.5 METs can be safely performed. The lower limit corresponds to the transition from compensable, or safe heat stress, to uncompensable heat stress when the internal body temperature starts to rise.

Mmax decreases with age (Fig. 5), a factor that is considerably higher under dry conditions. For example, at high Tair and low RH, young and healthy adults can do ~2.5–3.0 METs more activity (e.g., sitting/resting versus walking) than older adults, who are more limited by their sweat rate. The differences between the two groups decrease (down to ~0.6–0.8 METs less) as humidity rises and temperatures drop. Accordingly, there is a wider range of conditions where older people can only rest safely (i.e., survivable but not livable). Direct solar radiation exposure also decreases Mmax to a certain extent in both groups (Figs. 4c, d and 5b). This effect is increasingly worse in more humid environments for any Tair. As a reference, under the same Tair and RH, sunlit exposures reduce activity levels by 1.0 MET in young adults and 0.86 METs in older adults compared to shaded.

Global climate projections using liveability analysis
Results are presented here for GFDLESM4; all MPIESM1.2 results can be found in the SM. Significant declines in Mmax between present-day (2016–2025) and end-of-century (2091–2100) are projected (Fig. 6), with exceptions in some locations above 50°N, the Himalayas, south New Zealand, and the Andean Cordillera. These global estimates suggest a likely average (median) decrease in Mmax (from present-day to end-of-century) of –0.25 METs following SSP2-4.5 for young, healthy adults (Fig. 6a) during days when Tair > 25°C (–0.64 METs for SSP5-8.5).

The median Mmax for the current decade when Tair is > 25°C (Fig. S.9) is higher (up to 5.9 METs) across extratropical and mountainous regions (e.g., Ethiopia and the Andean Cordillera in northern South America). In contrast, the lowest Mmax estimates, reaching an average minimum of 4 METs, are found across coastal areas and the most humid regions in the tropics (i.e., northern India and Bangladesh, the Amazon and Congo Rainforests, southeastern Asia, Eastern China, Gulf of Mexico). In such areas (and other regions covering the lower quartile with major Mmax changes), Mmax average declines of > 0.3 METs following SSP2-4.5 are expected by 2100 (see Fig. 6a, b) for young adults, which would more than double under SSP5-8.5 (–0.73 METs).

Following SSP2-4.5, large areas will experience > 5% reduction in median Mmax towards the end-of-century (Supplementary Fig. S.11) during warm conditions, including warm coastal areas and savannahs in North, South, and Central America, the Caribbean, the Sahel, much of Eastern Africa, the Arabian Peninsula, Southeast Asia, northern Australia, the Amazon, southeastern U.S., and scattered areas in Central and Eastern Europe, and Central and Eastern Asia. Many of these areas already experience frequent Tair > 25°C (> 60% of the time) and already-low Mmax (Fig. 6c, Supplementary Fig. S.12); the further reduction in Mmax will add major liveability challenges as climate change progresses. Finally, by end-of-century, select areas (Arabian Peninsula, Northern India, Bangladesh) are projected to see a significant increase in conditions that are survivable but not livable for young adults, reaching a frequency of 5–7% (6 months/decade) for SSP5-8.5 (see hatched zones in Fig. 4, Supplementary Information (SI) S.13).

The Mmax distribution for select locations in Fig. 7 shows a more pronounced decrease in safe activity in older versus younger adults compared to the decline expected from projected warming (i.e., individual age and age of the overall population can be a stronger heat risk predictor than warming due to climate change). For regions around Riyadh, Cartagena, New Delhi, and Dhaka, there is already a high frequency of time where an older adult cannot presently perform more than 2.5 METs of activity (slow walking). Thus, moving forward, these locations will increasingly become unliveable despite being survivable (increases of frequencies at 1.5 METs or less for old adults, especially following SSP5-8.5). See also Supplementary Figs. S9–S15 for further context.

Methods
Overview
Our approach leverages methods of partitional calorimetry to model human heat balance71 describing heat transfer between the human body and surrounding environment for warm conditions. Models are run across all plausible combinations of air temperature and moisture levels (e.g., RH) for warm conditions. The baseline approach builds on the general core principles of assumptions within Sherwood & Huber12, with additional complex rational equations and population-specific inputs. The complete model, including all equations and the fundamental physiology and biophysical details, are outlined in the SM and available code. Below, we briefly explain how the full model is applied to comprehensively predict heat stroke death (survivability) and maximum safe sustained levels of physical activity (liveability) (Fig. 1).

We evaluate environments across all plausible moisture levels for warm Tair between 25–60°C, holding wind speed constant at 1 m.s−1. Assessments are completed for indoors (or shade), where mean radiant temperature (Tr) = Tair and outdoors (sun-exposed), where Tr = Tair + 15°C, assuming partly sunny conditions averaged over eight midday hours19. Finally, we assess healthy young (18–40 years) and older female adults (> 65 years). Specifics and assumptions are listed in Fig. 1 and the SM.

Survivability estimates
Survivability estimates are provided for 3 and 6-hour of constant thermal exposure to align with current climate model outputs and past studies. The model detects increases in Tcore from an initial value of 37.0°C to ≥ 43.0°C. The ΔTcore = 6.0°C represents the upper limits of heat stroke29 (however, we acknowledge that the severity of hyperthermia is variable, ranging from 41 to 47°C72). Thus, this model assumes that a person cannot store more than 17.88 kJ kg−1, taking a typical human’s heat capacity (Cp) as 2.98 kJ Kg−1 °C−173. Therefore, the critical rate of heat storage (S) before inevitable heat stroke death during rest is 0.82 W Kg−1 for a 6-hour constant exposure (Ssurv6), and 1.65 W kg−1 for a 3-hour constant exposure (Ssurv3). Assuming a resting metabolic rate of 1.5 METs (1.8 W kg−1), the maximum permissible net Hloss is 0.98 W kg−1 for 6-hour and 0.15 W kg−1 for 3-hour exposures:

Hloss6 = Hprod − Ssurv6 = (1.8 − 0.82) = 0.98 (W kg−1) (1)

Hloss3 = Hprod − Ssurv3 = (1.8 − 1.65) = 0.15 (W kg−1) (2)

where Hloss is the net heat loss from the skin surface to the surrounding environment and Hprod is internal metabolic heat production. Note that Hloss is a function of weight and thus would vary across populations. Hprod is equivalent to metabolic rate (M) because Wk = 0. A person is also assumed nude for the survivability assessment (thus, dry and evaporative heat transfer clothing resistances are 0 m2 °C W−1), in line with assumptions made by other survivability models12.

Our approach models evaporative restrictions to heat loss, which can exist due to three factors (see Supplementary Fig. S1): (1) high environmental humidity (or biophysical evaporative heat loss limit (Emaxenv)); (2) the physiological capacity to saturate the skin surface in high humidity environments due to a limited maximum skin wettedness (ωmax); and (3) by the maximum rate at which sweat can be produced (Smax). These are factored into both survivability and liveability analyses.

For survivability, we follow the framework in Supplementary Fig. S1 to determine whether a person can survive heat stroke based on three questions, with a potential for four outcomes given individual characteristics (e.g., differing age and size). Thus, the algorithm determines survivability (as a dichotomous variable: yes/no) and assigns outcomes based on combined environmental and physiological restrictions. Based on this framework, a person will (see zones in Fig. 2):

1. Survive while remaining within sweating limits.
2. Survive despite exceeding sweating limits.
3. Not survive because the environment restricts heat loss too much (in high humidity).
4. Not survive because the required sweat rate is not possible (in low humidity).
5. Not survive due to both critical environmental heat loss restrictions (3rd argument) and a required sweat rate that is not possible (4th argument).

Liveability estimates
Liveability is the maximum metabolic rate (Mmax) that can be generated before S≥0, or sustained compensable heat stress, where M = Hprod. The Mmax value indicates the sustained activity levels (intensity but not duration) possible without unchecked rises in Tcore (i.e., uncompensable heat stress74) within a given steady-state thermal environment. This definition assumes that people will self-pace their maximum level of physical activity over a prolonged period to attain S=0, as well as constant sweating and skin temperature. Mmax is a continuous variable (in Watts), which we convert to energy expenditure in METs for a simpler interpretation. A clothing insulation value of 0.36 clo is used (light shorts and cotton T-shirt) for liveability. Full details are in the SM.

Application of liveability model using climate models
To illustrate advanced model capabilities, we explore the distribution of liveability in present and projected future conditions in regions globally (as outlined above and in SM). The Coupled Model Intercomparison Project phase 6 (CMIP6) provides state-of-the-art GCMs projections under various warming scenarios75. We utilize CMIP6 data from GFDLESM4 and MPI ESM1.2 (~1° × 1.25° atmosphere/land grid) following SSP2-4.5 and SSP5-8.5 (Shared Socioeconomic Pathway). SSP2-4.5 represents a middle-of-the-road emissions scenario, which may be likely considering existing net-zero commitments76, and SSP5-8.5 represents a high emissions scenario. As inputs, we use 3-hourly near-surface air temperature, specific humidity, and surface atmospheric pressure for two 10-year global snapshots—present (2016–2025) and future (2091–2100)—to construct global maps of projected changes over land and detail Mmax in select cities. A grid cell was considered land if it contained > 45% land cover; otherwise, analyses were not performed.

We used two-sided Mann-Whitney U tests to detect significant projected changes in Mmax between present (2016–2025) and future (2091–2100) decades. Here, we test differences in median Mmax (50th percentile of distribution) using a significance level of p < 0.05 (Fig. 6). Six cities within the global top 5% of expected declines of Mmax were selected to display deceased Mmax in statistical distributions (Fig. 7): Roma, Italy (a); Riyadh, Saudi Arabia (b); Cartagena, Colombia (c); Kumasi, Ghana (d); New Delhi, India (e); and Dakha, Bangladesh (f). The Mann-Whitney U tests were used because Mmax is a continuous variable, not always normally distributed. We evaluated liveability changes solely for shaded warm/hot weather conditions (Tair > 25°C).

Our analyses focus on exploring uncertainties associated with the physiological model; future work will complete a more comprehensive climate change impact analysis using many GCM simulations to consider uncertainties due to model structure, internal variability of the climate system, and emissions scenario. GFDLESM4 and MPI ESM1.2, like any climate models, possess biases in their simulation of mean climate and the diurnal cycle, and do not capture details of urban landscapes77. Future impact assessments might consider bias correcting and downscaling the GCM output prior to inputting in the physiological model.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Review of “ A physiological approach for assessing human survivability and liability to heat in a 2\nchanging climate” by Vanos, et al.\nThe authors integrate a physiological model of heat stress with climate projections, to enumerate how,\nsurvivability and livability at various activity levels relate to temperature humidity contributions. They\nalso consider people over 65, and shaded vs. sunlight conditions. The paper is generally very well-\nwritten, and with minor-to-major revisions I believe it will ultimately be an important contribution to the\nliterature and worthy of Nature Communications. There are however, some general and specific (line by\nline) concerns/comments, I have, which I outline below respectively.\nGeneral/Major Comments\n1. The single biggest question, which I don’t feel particularly well-suited as a climate scientist to answer,\nis how much trust to put in their this study, based on a single physiological model and the Wolf\nreference. Everyone at this point knows at this point that a lot of people will be dying long before 35C\nwet bulb (see Horton et al. 2021 for example on humid heat and habitability) but the extent of your\ndownward revisions under high dry bulb low RH, and the absence of downward revision for high RH and\n‘low’ dry bulb T are…striking, and major departures from most prior work in a field that has built up a\nfair number of papers in a hurry. Here I should note that I myself have been burned by reviewers with\nblinders on, who told my co-authors our results, ~ ‘weren’t plausible’ without pointing to anything more\nthan their intuition. But I find myself feeling similarly about some aspects of these findings. I would feel\nbetter if these results were compared to other physiological models, results from (even critiqued)\nepidemiological studies, etc. Most fundamentally, the authors don’t really 1) discuss that their findings\nat least to my mind, don’t align with experience and 2) offer explanations, based on what their model\nmay be missing.\nAs examples of the former, the model seems insufficiently sensitive at low RH and high dry bulb\ntemperature extremes. What for example should we make of all the outdoor, sun exposed elderly\npeople around the world who are surviving and performing basic activities at dry bulb T and RH\ncombinations your findings suggest should not be possible? Or in fig 3, all the 18-40 year olds who are\nable to do strenuous (running) activities outdoors at 86F and near-zero humidity in the absence of sun?\nDoesn’t one find 18-40 year olds able to actively play/dance in the sun at 86 and zero humidity?\nThese points seem even more problematic when one notes that the model used by the authors neglects\nother health issues that can limit sweating, and assumes nudity. How can this be explained?\nThe models also seems too sanguine about high RH and lower dry bulb temperatures. Does evidence\nreally suggest that 93F and 100 percent RH would be survivable for a 65+ in the sun?? Or that they could\ndo light walking in the sun at 79F and 100 percent humidity? These findings seem questionable too,\nalthough here it is easier to invoke things missing from the model perhaps, like pre-existing health\nconditions.\n2. (And related to ‘1’ above): Word count restrictions notwithstanding, in general more caveating and\ndiscussion are needed. For example, mention your assumption of very weak wind. While I am not asking\nyou to model other wind speeds, it seems insufficient to not mention your assumption in the main, and\nhow it could impact your assumptions about max cooling through sweating.\nIn general, the paper needs to talk more about smooth gradients, for example the idea that the 65 age\ncutoff you use is not a perfect binary. What about people with health conditions? What about people\nwith different constraints/goals in their activities (Horton et al. 2021)? Adaptation options like putting\ncold water on yourself? Note that I am not suggesting new analyses here. Rather that there is a chasm\nbetween the needs you articulate in the introduction, and the nice additions you address through this\nnice study. In the discussion, circle back to remind us how your study helps fill in some of the missing\npieces, but a chasm remains before anyone is able to fully model/understand all the factors that\ninfluence the relationship between humid heat and mortality/liveability.\nMost fundamentally, you need to be much clearer about which aspects of the gaps in our\nunderstanding/prior work your analysis addresses, and which ones it doesn’t. For example, lines 49-52\nread almost as legerdemain, that needs to be cleaned up. I think you can still make your overall point,\neven if it means adding a sentence or two, in a way that acknowledges that some\nepidemiological/econometric approaches (even with projections) have included humidity. See my\ncomments above about how you need to engage epidemiology/econometrics/empirical approaches a\nbit more. This is one of the major branches of analysis in assessing heat impacts on health, so it needs\nsignificantly more attention here. This can help strengthen the case that a reader should instead trust\nyour single physiological model result!\nI think the Introduction is generally strong—well written, especially when describing gaps and\nlimitations in prior work. That said, I needed a little more info before the paragraph on lines 88-92.\nDespite excellent text before this paragraph, the 43C threshold still comes seemingly out of nowhere in\nthe first sentence. And then in the second sentence we hear about maintaining core temperature, which\nleads one to wonder about the gray area between these two extremes. I don’t question the use of these\ntwo measures—we just need some added context before you introduce these two specific ‘lines in the\nsand’ after talking too us earlier about all the nuances that can render lines in the sand blurry (pre-\nexisting health conditions, adaptations, etc.).\nAgain, your summary of what is needed, and the importance of more nuance in these studies is strong.\nIt is just odd that you aren’t more precise about which of these many pieces you all chew off in your\nanalysis. Without a close read, once could easily assume your study addresses ALL the shortcomings of\nprior studies you have just (nicely) elucidated, rather than just a couple (important ones).\nAlong similar lines, the critiques of prior work on lines 66-67 seem fair, but seem to promise more than\nyou deliver. For example, in contrast to prior authors, do you consider body size, or more than a single\n(age 65+)’ restriction to thermoregulation’? Why not say that you don’t?\n3. I am trying to figure out how in the extremes of high T and low RH the downward revisions of the\ndanger thresholds relate/don’t relate to actual weather conditions (as opposed to theoretical or lab\nexperiment-driven conditions). Once temps get really high (e.g. 115+ F) on your figures, there currently\naren’t any RHs of 40 percent, for example. Along similar lines, does any literature suggest that anything\nlike 35C wet bulbs occur or will occur at low RH? In a sense my point is that not only does this paper\nfocus on a single physiological/human model, not only does it largely punt on describing humid heat\nepidemiology, but it also largely punts on describing the climatology of observed heat and humidity. It is\ncritical to know which combinations of T and RH are experienced and likely to be experienced. As a bare\nminimum revision, can we see reported combinations of T and RH somewhere, perhaps added to some\nof the existing figures 1-4?\n4. One GCM, one RCP is a problematic. For Nature Communications, I think you need to include more\nmodels in the main, and probably another RCP in the Supplement. Note that these additions would not\nstarve the follow up study you refer to about sources of uncertainty, in a field with so many possible\npermutations (Petkova et al. 2014, for example.)\nLine by line comments\nLiability’ in title to ‘Liveability’\nAbstract, second sentence: move the last 9 words (perhaps further shortened) up to earlier in the\nsentence. As written, it seems like they only apply to livability not survivability.\nIntroduction\nIs the term ‘heatstroke death’ sufficient here? (I am wondering if there are other kinds of heat related\ndeaths you mean to include that are not captured by the term ‘heatstroke death’)?\nPenultimate paragraph—clarify that you mean an individuals aging, rather than the average age of\nhumans (or more to the point the number and age of older people) going up in the future\n‘3.2’ at first use in heading to 2.2’\n‘3.3 at first use in a heading to 2.3’\nI feel Figures 1 through 4, while all excellent, are so similar stylistically and content-wise similar as to\nargue for making a hard decision to move at least one of them (possibly two of them) to the\nsupplement.\nLine 273:’Plan’ to ‘Plain’\nFigure 3: Give us a better sense, through examples in the text of what levels of activity different values\nof ‘Met’ correspond to. Figure 3 is nice in this regard, but say more in the main text.\nAlso do the icons, like running, assume no rest during 3 hours?\nFigure 5a: why are some areas showing reduced MET?\nFigure 5b: worth exploring why Bangladesh has the lowest values. I think of this area as closer to high RH\nlow dry bulb than many of the other humid heat hotspots around the world like the Indus Valley for\nexample. Given your findings (high dry bulb at low RH is more dangerous than most researchers have\nrealized) this is somewhat counterintuitive. Can you look into some explanations? (Maybe GCM\nresolution, maybe the sheer number of days per year is a more dominant term in your model [maybe\nBangladesh has a lot of pretty oppressive days, rather than having the individual days that are the most\nextreme], etc.).\nFigure 6 caption: ‘Dix’ to ‘Six’\nFigure 7: I think this should be much earlier in the paper.\nFigure 8 caption: Is ‘wittedness’ intended? Especially if you are constrained in your number of Figures,\nthis is a very logical figure to move to the Supplement.\nMethods 4.4. did you bias correct for cities? If not, it is OK, but you should say so.\nReferences\nHorton, R. M., de Sherbinin, A., Wrathall, D., & Oppenheimer, M. (2021). Assessing human habitability\nand migration. Science, 372(6548), 1279-1283.\nPetkova, E. P., Vink, J. K., Horton, R. M., Gasparrini, A., Bader, D. A., Francis, J. D., & Kinney, P. L. (2016).\nTowards more comprehensive projections of urban heat-related mortality: estimates for New York City\nunder multiple population, adaptation, and climate scenarios. Environmental health perspectives.", "reviewer_2": "The manuscript focuses on assessing survivability and livability by applying physiological and biophysical\nprinciples. The authors suggest that the 35oC Tw threshold underestimates the risks for older adults.\nThey also suggest that the risk continues to increase in a changing climate.\nI have two major concerns with the manuscript. First, the authors use only a single GCM and a single\nscenario that fails to capture the range of future climate uncertainties. Secondly, the authors extract\ncity-level data from a pretty coarse resolution GCM. The majority of GCMs in CMIP6 are still pretty\ncoarse resolution including the GFDL-ESM4 model that the authors have used. Using GCM data to draw\nsuch conclusions can be misleading given that it fails to capture various city-specific features and will\nhave substantial biases. From the title of the manuscript, it looks like the authors are trying to evaluate\nthe survivability and livability in a changing climate, and therefore, using single coarse resolution GCM is\nnot justified. A minor comment- it should be “livability” and not “liability” in the title.", "reviewer_3": "OVERALL:\nThe goal of the paper by Vanos et al. was to improve upon the modeling of survivability and livability\nlimits of humans exposed to increasingly hot environments due to climate change. In many ways the\nauthors succeed in their goal of advancing upon earlier modeling efforts. The authors, in particular,\nextend survivability and livability limits to very hot and very dry environments and attempt to show\ndifferences between young and old. Other advantages are mentioned (contingencies for disease states,\nacclimatization status, body size, fitness, etc.) but not described. The work submitted is in many ways\nmasterful, but there are numerous potential problems with the many assumptions made and as a result\nthe interpretations also appear problematic – even incorrect. A model such as the UTCI, validated\nagainst empirical data (such as Brode and Kampmann, 2023), may be a better approach? Questions and\ncomments follow for consideration.\nMINOR:\nLine 1: Title - liability should read livability.\nLines 183, 191: A decrease in Mmax of 0.2-0.26 METS does not seem like an appreciable difference (10-\n20% can be the measurement noise for METS). Can the authors better contextualize how this matters to\nhuman health, economic burden, etc.?\nLine 372: Did you mean reference #30 for this statement? Reference #67 I understand.\nLimes 389-403: It would be helpful for those interested to introduce the average height and weight used\nto arrive at the 1.60 m2 (young) and 1.78 m2 (old) (supplementary information) values that appear to\nhave been used for the calculations represented in all the tables and graphs. Were these population\nmedian values for height and weight in young and old populations?\nLine 406: It does not seem reasonable to use a nude body for survivability (how many people would be\nnude?) but minimal clothing for livability. I understand wanting to compare your results to previous\nwork, but the buck should stop somewhere? Or consider using nude estimates for livability as well?\nReferences: There are a number of references with errors in them. Please review and edit.\nTable 2: The lower Tw limit at lower humidity seems strange without the context of the very high\naccompanying air temperatures.\nFigures 1-4: Where are environmental conditions projected to rise to 50 degrees C or more to make\nthese projections less theoretical and more meaningful?\nFigure 6: Can the authors explain the y-axis probability?\nSupplemental Material and Model Assumptions:\nEquation 20: How is Smax determined? Is it simply Ereq?\nMAJOR:\nLine 389: The premise for using 43 degrees C for survivability is justified by citing the range (41-47), but\n40.8 degrees C was the average exertional heat stroke temperature observed in more than 100 military\ncases (see Figure 5-3 in:\n(https://armypubs.army.mil/ProductMaps/PubForm/Details.aspx?PUB_ID=1024722). Is 43 degrees C\nmore applicable for passive heat stroke? Should a distinction be made between passive and exertional\nheat stroke? Which are you modeling, specifically? Both? A more justified value ~41 degrees C could\ndrastically change your results and interpretations.\nLines 432-436: I am not sure I understand S = 0 in this explanation. Heat storage could and would take\nplace to elevate body temperature (from 37 degrees C) to a new but stable baseline (e.g., 37.5, 38.0,\n38.5,…). Why must no heat storage be assumed (not realistic)?\nSupplemental Material and Model Assumptions:\n1. Is airflow 1 m/s used in both survivability and livability scenarios? In Figure 3, a MET value of 2.5\n(walking) arguably creates airflow around a person equal to ~1 m/s, but jogging at 7.5 METS would be\nmore like ~2.25 m/s. Riding a bicycle at 5 METS would produce an airflow of ~5 m/s, completely ablating\nthe insulative air boundary layer. The under-estimation of airflow will have important effects on your\ninterpretations that rely so heavily on evaporative cooling.\n2. Mean Tsk is set to 35 degrees C. Though it may align with other publications, mean Tsk can be easily\n36 or 37 degrees c in very hot air (40 to 50 degrees C), especially when globe temperature is higher still.\nSome military models use 36 degrees C or establish a scaling factor for the best gradient. This too will\npotentially impact your interpretations and calculus as dry heat gain is somewhat exaggerated.\n3. The skin wettedness values employed of 0.50 to 0.65 seem too low, especially 0.50 (e.g., Candas et al.,\n1979; Ravanelli et al., 2018). This makes a huge potential difference to Emaxlim. Can the authors provide\njustification for such small values? If 0.65 to 0.85 were used, how would this impact your results? I\nsuspect greatly.\n4. There is a major emphasis on how age impacts the results of the model, but little explanation is given\nfor why. Reference #15 is cited for age negatively impacting Emaxwet. However, while reductions in\nvasomotor and sudomotor function have been convincingly demonstrated to occur with aging,\ntranslation to heat balance on the whole body level is less clear. For example, men 45 years older than\nyounger subjects matched for body mass, height, and body surface area had 50% lower local sweating\nrates, even though Ereq in W/m2 was similar (Schmidt et al., 2022). Others have quantified an age-\nrelated reduction in thermoeffector heat loss potential of ~4% per decade between ages 18 and 70\n(D’Souza et al., 2020). How does this compare with your model? On the whole body level, small or non-\nsignificant differences in heat balance between young and old are reported (Stapleton et al., 2014).\nImportantly, the Stapleton study was conducted at 40 degrees C and 15%rh at metabolic rates ranging\nfrom 300 to 500W. Your results (lines 166-169) seem to suggest that this should be impossible for older\nadults (65 yoa in Stapelton et al., 2014).\n5. Would use of the UTCI model be a better approach? It has recently been validated against empirical\ndata. Please see: Bröde P, Kampmann B. Temperature-Humidity-Dependent Wind Effects on\nPhysiological Heat Strain of Moderately Exercising Individuals Reproduced by the Universal Thermal\nClimate Index (UTCI). Biology (Basel). 2023 May 31;12(6):802.\nOverall, it seems that a small change in any one of many model assumptions could significantly alter\nyour results, interpretations, and conclusions."}, "author_response": "Point-by-point Response to Reviewers Comments:\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nReview of “ A physiological approach for assessing human survivability and liability to heat in a 2\nchanging climate” by Vanos, et al.\nThe authors integrate a physiological model of heat stress with climate projections, to enumerate how,\nsurvivability and livability at various activity levels relate to temperature humidity contributions. They\nalso consider people over 65, and shaded vs. sunlight conditions. The paper is generally very well-\nwritten, and with minor-to-major revisions I believe it will ultimately be an important contribution to the\nliterature and worthy of Nature Communications. There are however, some general and specific (line by\nline) concerns/comments, I have, which I outline below respectively.\nResponse: Thank you for these comments and helpful overview.\nGeneral/Major Comments\n1. The single biggest question, which I don’t feel particularly well-suited as a climate scientist to answer,\nis how much trust to put in their this study, based on a single physiological model and the Wolf\nreference. Everyone at this point knows at this point that a lot of people will be dying long before 35C\nwet bulb (see Horton et al. 2021 for example on humid heat and habitability) but the extent of your\ndownward revisions under high dry bulb low RH, and the absence of downward revision for high RH and\n‘low’ dry bulb T are…striking, and major departures from most prior work in a field that has built up a\nfair number of papers in a hurry. Here I should note that I myself have been burned by reviewers with\nblinders on, who told my co-authors our results, ~ ‘weren’t plausible’ without pointing to anything more\nthan their intuition. But I find myself feeling similarly about some aspects of these findings. I would feel\nbetter if these results were compared to other physiological models, results from (even critiqued)\nepidemiological studies, etc. Most fundamentally, the authors don’t really 1) discuss that their findings at\nleast to my mind, don’t align with experience and 2) offer explanations, based on what their model may\nbe missing.\nResponse: Thank you for this comment. The striking downward revision under the dry conditions is due\nto our model's ability to account for the limited capacity of humans to secrete sweat and, thus, support\nevaporative cooling, wherein people can only sweat so much per hour. Notice that in the Tw 35°C model,\nthe sweat loss is unlimited. In very hot and dry conditions, the prospect of survival is overestimated\nbecause the 35oC T model operates solely on the assumption that the climate (humidity) limits\nw\nevaporative heat loss potential rather than the physiological capacity to secrete sweat, which is well\nestablished in the physiological literature.\nMany climate researchers have used the 35°C wet bulb approach. Still, it has a minimal physiological\nbasis, and this concern is one of the reasons we set out on this study––to demonstrate that the\nassumption is very narrow and misses important aspects about people, behavior, and exposures, overly\nsimplifying the complexities of the human body (see Vanos et al., 2020). Our approach here uses a more\ncomplex and biophysical approach that accounts for physiological principles (not a pure physiological\n1\nmodel) to look at all the avenues of heat exchange as it relates to the person (including\nthermoregulatory impairments), the specific conditions, and activity, among other factors that this\nmodel would allow us to adapt in the future. The estimates are not a matter of opinion, nor are they\ndependent on the data reported from a single study, but are based on a rational model. Assuming a\nsingle threshold of wet-bulb temperature doesn’t allow for any of these considerations, and thus the\nprolific use of it––solely because it is simple to apply in climate models––is worrisome.\nIt may be that we do not clarify the following well enough within our paper. The main aim is to\ndemonstrate the differences in potential survival and livability outcomes if such a simplistic approach (T\nw\nof 35) is substituted with a model based on biophysical principles of human-environment heat exchange\nand\nTherefore, we clarify these two issues in the paper on Lines ~90–93.\n“Here, we demonstrate a new approach using physiological principles that align with human thermal\nresponses to heat (heat strain) to begin overcoming simplified approaches that miss important\nphysiological and behavioral factors of humans in the heat.”\nSecond, to address #1 and #2 in the comment, in the introduction and the discussion we have clarified\nwhy the findings from the 35°C wet-bulb temperature threshold studies do not align with more realistic\nscenarios (e.g., people are not always in the shade and laying down; ageing affects thermoregulation).\nreal-world experiences. We also offer explanations as to why these issues arise and what the 35˚C wet-\nbulb temperature model might be missing to offer an improved approach.\nThe following text is added on line 80–82:\nWithin the introduction: “The 35°C threshold approach cannot capture complexities and personal\ncharacteristics affecting human thermoregulation (e.g., body size, activity levels, or physiological\nrestrictions (such as sweating) to thermoregulation6,19), which can cause large errors in estimations.”\nWithin the discussion, the first paragraph of section 3.1 emphasizes the constraints of the popular T of\nw\n35°C threshold model.\nAlso, note that we have not used results from Wolf et al to develop our model. Rather, the Wolf data are\nmerely provided to illustrate some context using empirical data from an physiological study, which aligns\nquite well with our liveability model. Further, the Wolf et al. results also support the notion that the T\nw\nvalue for thermal compensability (our definition of liveability) is much lower than 35°C under dry\nconditions. Note that the Wolf study defined the critical limit as the point at which people tip into\nuncompensability (which is our definition of liveability). In contrast, we permit a certain rate of heat\nstorage for survivability, allowing a possible range of T increase until 43°C within a 3H or 6H\ncore\ntimeframe. We have made these factors more evident in the discussion on Lines 362–364:\n“Emerging empirical data from laboratory studies provide physiological support of our liveability model\nresults for young, healthy adults in shaded conditions. Wolf et al.63 define critical environmental limits as\nthe point at which subjects enter uncompensability (which is how we define liveability) see also Table 1)”\nWe have also included the Horton et al. (2021) paper as a citation in a couple of places to support\ndiscussion points, and additional physiological models cited within the discussion and Table 3.\ntemperature extremes. What for example should we make of all the outdoor, sun exposed elderly\npeople around the world who are surviving and performing basic activities at dry bulb T and RH\ncombinations your findings suggest should not be possible? Or in fig 3, all the 18-40 year olds who are\nable to do strenuous (running) activities outdoors at 86F and near-zero humidity in the absence of sun?\nDoesn’t one find 18-40 year olds able to actively play/dance in the sun at 86 and zero humidity?\nResponse: Thank you for this comment, as it helps us see where we may not be adequately explaining\nthe differences between survivability and liveability concepts. For Figure 3 (now Figure 4), the results\nrepresent liveability, which is the maximum SAFE internal metabolic heat production/physical activity\nthat a person can generate without a sustained positive rate of heat storage in the prevailing\nenvironment (or without exceeding the maximum rate of heat dissipation possible from the skin to the\nsurrounding environment). As such, above this threshold, the body will continuously store heat energy\ninside the body even with the body attempting to maximally shed heat through evaporation, and core\ntemperature will continually rise. While rises in core temperature may be manageable over a short\nduration and not pose a health threat, activities at levels above M are not sustainable for a prolonged\nmax\nperiod due to a progressively increasing heat stress risk (due to being in uncompensable heat stress). For\nexample, while dancing at 30oC with very low humidity in direct sunlight may be safe for relatively short\ndurations (e.g., ~30 mins), continuing to conduct this activity under these conditions will eventually pose\na health threat because of the progressive core temperature increases. The more an activity exceeds\nM for a given combination of temperature and humidity, the faster the core temperature will rise\nmax\n(and, therefore, the shorter the safe duration). Indeed, an 18–40-year-old can safely dance or run at\ntemperatures below about 35°C with low humidity for longer durations; higher humidities would result\nin them being able to do less at the same temperature.\nWe hope this helps clarify. Because of this question, we think the interpretation of the graphs can be\nimproved. Now for each graph in Figure 3, we have described the areas that are safely sustained (or\n“safe sustained activity”) for the given level of activity indicated by color, areas that are survivable but\nnot liveable (no activity possible without continuously storing heat internally), and the area of the graph\nthat is unsurvivable. We have also updated the caption on Figure 4 (and the similar supplemental\nfigures) to read:\n“Figure 4: Liveability estimates based on maximum safe metabolic rate (𝑴 ) that a person can\n𝒎𝒂𝒙\ngenerate without a sustained positive rate of heat storage even with a maximal thermoregulatory\nresponse. Results are presented across a range of air temperature and relative humidity for younger (a,\nc) and older adults (b, d) in shaded (top) or sun-exposed (bottom) steady-state environments. The 3-hour\nsurvivability line is shown in purple; constant T values are shown by the solid black lines until 37°C to\nw\navoid unrealistic conditions, with T =35°C shown by the thick black line. Activities by MET level range\nw\nfrom no activity Activities by MET level range from no activity (sitting ~1.5 METs), to housework (~3.0\nMETs), dancing (~5.0 METs), and heavy lifting (~7.0 METs). The hatched area indicates conditions that are\nsurvivable but not livable (i.e., people cannot increase their activity without continuously storing heat\ninside the body, which will lead to a continuous rise in core temperature, but heat stroke death after a 3-\nhour exposure would not occur). Icons indicate MET-equivalent activities according to Ainsworth et al.56\nCircles indicate critical T limits reported by Wolf et al.65 for minimal (~1.8 METs–filled circles) and light\nw\nphysical activity (~3.2 METs–open circles). Note: 1 MET = 58.1Wm-2, with 1.0 METs (~58 Wm-2)\ncorresponding to complete rest. See Figure S6-7 for vapor pressure and specific humidity on y-axis,\nrespectively. Icons provided by Icons8 (https://icons8.com).”\nTable 1 and the introduction.\nThese points seem even more problematic when one notes that the model used by the authors neglects\nother health issues that can limit sweating, and assumes nudity. How can this be explained?\nResponse: We do not neglect health issues; indeed, we highlight the importance of their representation\nin these kinds of studies. However, we cannot address all such health issues and the immense complexity\nof the human body in one paper. Given that sweating impairments due to age are robust and have been\nwell-documented in the literature, we choose to model in this current paper that constraint in\nthermoregulatory response. In the meantime, physiologists are still working to characterize the effects\nof health disorders on sweating, and thus we do not advance the model as far just yet to avoid\nspeculation (yet the model will be able to account for this in the future as research progresses). See the\nnew Table 3.\nWe only assume nudity for the survivability estimations, as this is where one would wear as little as\npossible and do nothing. Additionally, as nudity is the assumption for the T =35°C approach, we can\nw\nbetter compare our results with their approach (this is stated already in the main methods). Conversely,\nfor liveability, where we estimate maximum safe physical activity, we assume people are wearing light\nclothing (clo = 0.36 clo, light shorts and cotton T-shirt). These details are provided in the supplemental\nmaterials, and we have also added them to the main methods:\n“We also use a clothing insulation value of 0.36 clo (light shorts and cotton T-shirt) in the liveability\nanalysis.”\nFuture work can evaluate the sensitivity of clothing on liveability.\nFinally, to help ensure these distinctions are clear, we have added this information to Figure 1 (which\nuses to be Figure 7).\nsignificant improvement over the widely used Tw of 35oC by accounting\n1. Physiological constraints to sweat production in hot dry conditions\n2. Sweating restrictions due to ageing, which are the most wide scale thermoregulatory impairment in\nsociety\n3. Sun exposure\n4. Different morphology between different ages\n5. A physiologically plausible core temperature threshold for heat stroke\n6. The ability to behavioral adapt by reducing metabolic rate (in our liveability analysis)\nThe T of 35oC doesn’t account for any of these. We have listed these points in the section titled:\nw\n“Considerations of New Model Estimating Physiological Survivability Limits and Liveability”\nThe models also seems too sanguine about high RH and lower dry bulb temperatures. Does evidence\nreally suggest that 93F and 100 percent RH would be survivable for a 65+ in the sun?? Or that they could\ndo light walking in the sun at 79F and 100 percent humidity? These findings seem questionable too,\nalthough here it is easier to invoke things missing from the model perhaps, like pre-existing health\nconditions.\nResponse: If we focus on survivability for >65 years of age (Figure 2d), then yes, a person >65 years\nwearing no clothing and laying down not moving sun-exposed (which is partial sun in this case),\nlight air flow, having full access to water could survive at 90°F and 100RH for 6 hours. According to the T of 35°C\nw\napproach, a similar situation shows that any person could experience 95°F and 100 RH for 6 hours and\nsurvive without reaching heat stroke conditions (although cardiovascular strain would be very high).\nNotably, these are the thermal environments in which the two approaches agree relatively well,\nalthough the T of 35°C approach doesn’t account for radiative heat exchanges. We also note in the\nw\n5\ndiscussion that such a person, based on our model results, would likely move to an indoor or shaded\nlocation if they had access, which would be a better situation for them (Figure 2b).\nFurther, it is important to emphasize that our survivability model is using the same definition as\nSherwood and Huber, i.e., survival from the perspective of heat stroke (critical rise in Tcore). We do not\naccount for the prospects of survival due to the heat-related outcomes (e.g. CV strain)\nHowever, the second scenario provided in this comment (which is focused on liveability) suggests light\nwalking in the sun at 79°F and 100% humidity (Figure 4). In this case, that person who is 65+ can indeed\ndo light walking in the sun safely (assuming full replenishment of water and constant sweating)\nwithout a\nsustained positive rate of heat storage, which is similar to our response to the question above about\nFigure 4. We think we clarified the liveability definition, improved the annotations on the liveability\ngraphs in Figure 4, and updated the caption (see above).\nWe also recognize some very extreme values used to express the full range of T and RH, and we have\nair\nresponded about this in comment #3 from reviewer three below.\n2. (And related to ‘1’ above): Word count restrictions notwithstanding, in general more caveating and\ndiscussion are needed. For example, mention your assumption of very weak wind. While I am not asking\nyou to model other wind speeds, it seems insufficient to not mention your assumption in the main, and\nhow it could impact your assumptions about max cooling through sweating.\nResponse: Thank you for this comment. Ensuring our assumptions are clear is very important. We have\nworked through all comments herein to ensure that everything is clearer and specifically make better\nuse of Figure 1 (pasted above) to indicate the windspeed assumption (and other key assumptions) used.\nAll of this is also explicitly outlined in the methods, stated in the discussion, and future necessary\nresearch on windspeed is now in the new Table 3 too. Indeed, more cooling could occur through\nsweating as long as the physiological limitation to sweating are not exceeded. However, we feel that\nwhile of course the present model is subject to several assumptions, it is a major improvement on the\nlimitations of the pre-existing 35oC wet-bulb temperature model.\nIn general, the paper needs to talk more about smooth gradients, for example the idea that the 65 age\ncutoff you use is not a perfect binary. What about people with health conditions? What about people\nwith different constraints/goals in their activities (Horton et al. 2021)? Adaptation options like putting\ncold water on yourself? Note that I am not suggesting new analyses here. Rather that there is a chasm\nbetween the needs you articulate in the introduction, and the nice additions you address through this\nnice study. In the discussion, circle back to remind us how your study helps fill in some of the missing\npieces, but a chasm remains before anyone is able to fully model/understand all the factors that\ninfluence the relationship between humid heat and mortality/liveability.\nResponse: Thank you for this. We note that it’s unclear what we address versus what our new approach\nwill allow us or others to address in the future. Some of these ideas you mentioned are exactly the type\nof future work that could be done. However, as the first paper that demonstrates the entire model to a\nnew audience, as well as the proof-of-concept in climate models, we were careful not to overload it with\nnuance. With respect to ageing, it is true that a person will not suddenly have problems sweating on\ntheir 65th birthday, however it has been well demonstrated in the physiological literature that the effects\nof primary ageing on thermoregulatory capacity (primarily mediated through changes to sweating) are\nnot linear, and that marked decrements tend to emerge between the ages of 60 to 65 y. It is certainly\ntrue though that progressive aging effects are observed with further ageing and the current model does\n6\nnot capture this. However, by basing our “older” age group on parameters that most closely resemble\n~65 y, we are avoiding any potential exaggeration of the primary ageing effect on heat vulnerability,\nwhich we demonstrate to be quite pronounced even with our more conservative approach.\nTo address this concern, we think that Figure 1, the new Table 3, and the final paragraph added in the\nintroduction are vital. Also, in the introduction, we now have added “As an initial step” when we\nintroduce exactly what we do “i.e., As an initial step towards these advances, we apply a whole-body\nhuman heat exchange model to estimate heatstroke deaths and maximum/safe activity across two\nsubpopulation types (younger (~18-40 y) and older (>65 y) adults), considering sweat rate impairments\n(due to older age) and heat exposures in the sun or shade and across an array of air temperatures (T )\nair\nand humidity levels.”\nSecond, at the end of the discussion, we have added:\nLines ~389-392: “These analyses and discussion highlight the capabilities of our approach, and within the\nSupplemental Material (SM) we note the capabilities and current constraints of the model. Table 3\nindicates future work and capabilities of the model that will support addressing further gaps and\nshortcomings discussed in this study but not examined quantitively, requiring significant collaboration\namong disciplines.71”\nFinally, we have made it very clear in the conclusion precisely what gaps we fill and what may remain,\nas follows:\nLines 397–401: “This paper establishes a new physiological modeling approach for assessing human\nsurvivability and liveability across subpopulations (younger and older adults) and in sun or shade,\ndesigned to be suitable for application with global climate model output. Thus, we fill specific gaps\naround these factors across the full spectrum of temperature and humidity combinations, and introduce\na brand-new assessment to determine liveability.”\nTable 3: Future work to be accomplished and tests to run with the newly presented modeling approach to allow for\nnumerous analysis types and answers to larger questions.\nSub-Topic or Future Work/Next Steps based on model capabilities\nDiscipline\nCreate a catalogue of specific estimates of skin wettedness, skin temperature, and maximum\nsweat rates across population types, ages, medications intake, and health disorders/chronic\ndiseases.\nModeling the impact of personal cooling strategies, such as dousing or misting skin, electric\nfans, and foot or hand immersion in water.79,80\nConduct a sensitivity analysis of wind flow impacts within the liveability and survivability\nThermal models, and activity velocity impacts for liveability.\nPhysiology Model changes behavior based on thermal exposure (e.g., Vargas et al.81) and other\nphysiological attributes that affect adaptive behavior.\nCharacterize other measures of physiological heat strain, including cardiovascular and renal\nstrain (not only heat stroke, as modeled here).\nTest and model different clothing factors within the liveability and survivability models.\nEmpirically test maximum duration of intensity safe activities (M ) in different extreme\nmax\nenvironmental conditions and describe the changes in skin temperature and sweat rate over\n7\ntime and across the lifespan (e.g.,40,63,82) to allow for appropriate ranges and scaling factors\napplied within both liveability and survivability models.\nImprove the steady-state version of the model, as applied here, to account for changes\nwithin the 3–6H exposure in the variables assumed as constant.\nConduct experiments across a range of plausible biophysical parameters for uncertainty\nestimation and subsequent model application across different temperature/humidity\ncombinations along the survivability and liveability threshold curves.\nRun the present model using multiple GCMs and emissions scenarios to provide an ensemble\nof futures, addressing various sources of uncertainty, including that from both the biophysical\nand climate models (e.g., Petkova et al.83).\nObtaining regional or city-specific analysis of future heat stress with downscaled, bias-\ncorrected climate projections.\nClimate\nEvaluate time-of-emergence for different survivability and livability thresholds using single\nSciences\n(global climate) model initial-condition large ensembles (SMILEs).\nAssessing the relative importance of human population trends (increase in the number of\npeople, aging) versus climate change in future health burdens from extreme heat.\nQuantifying the probability of exceptional heat wave and/or mass heat fatality events over\ndifferent regions with different levels of climate change.\nDetermine the sources of differences between physiological models and epidemiological\nmodels to inform future model improvements.\nPublic Health Quantify compounding and cascading risks connected to heat and health, including\nheatwaves compounded by wildfires.\nEvaluate the extent to which different urban designs would alter liveability or survivability.\nLeverage the new modeling capabilities along with projected global demographics to better\ndetermine impact across a diverse population for public health preparedness.\nMost fundamentally, you need to be much clearer about which aspects of the gaps in our\nunderstanding/prior work your analysis addresses, and which ones it doesn’t. For example, lines 49-52\nread almost as legerdemain, that needs to be cleaned up. I think you can still make your overall point,\neven if it means adding a sentence or two, in a way that acknowledges that some\nepidemiological/econometric approaches (even with projections) have included humidity. See my\ncomments above about how you need to engage epidemiology/econometrics/empirical approaches a bit\nmore. This is one of the major branches of analysis in assessing heat impacts on health, so it needs\nsignificantly more attention here. This can help strengthen the case that a reader should instead trust\nyour single physiological model result!\nResponse: Thank you for this feedback, we definitely want to make sure that these aspects are very\nclear! We think the responses to the multiple comments above will help ensure it is clearly stated what\ngaps we do and do not fill. Regarding the examples from Lines 49-52 in the original draft, we have\nrevised that paragraph and the following to be more balanced regarding the benefits and limitations of\nepidemiology/econometric and physiology-based studies of heat-health outcomes. We also now are\nclearer that several epidemiological studies have considered humidity and include example citations to\nsuch studies, even though the current leading large-scale study finds a negligible role for humidity in\nheat-health outcomes. While the scope of this particular paper focuses on a new physiology-based\nmethod, we fully agree that both approaches (epidemiology/econometric vs physiology) play important\nroles in understanding the future impacts of heat. We also think it’s important to note that survivability\nmodels predict widespread death. Using historical epidemiological data to achieve that is not really\nrelevant because (thankfully) it has not happened yet.\nParagraphs on lines 51–58 now reads as:\n“Empirical approaches are based on real-life outcomes and the range of realistic living conditions, and\nthey can explore cumulative effects of exposures over multiple days. However, two limitations for climate\nchange projections include 1) assumptions needed to extrapolate results to warmer temperatures than\nobserved in the historical sample8 and 2) ambiguity regarding the role of humidity in heat-health\noutcomes.19 While some epidemiological studies find a relationship between mortality in the heat and\nhumidity11, most find minimal associations between humidity and heat-health outcomes12. Given that\nspecific humidity is robustly expected to increase with global warming, this is a key research gap for\nepidemiology-based projections of future heat stress.”\nLines ~60-66:\n“Physiology-based studies of future heat stress risk employ relationships between the thermal\nenvironment and health outcomes based on human energy balance considerations, with parameters\nconstrained by studies of physiologic processes. In contrast to epidemiology/econometric approaches,\nphysiology-based studies of heat-health outcomes consistently find a robust role for atmospheric\nhumidity in heat stress via its modulation of cooling from evaporation of sweat10. However, physiology\nstudies are limited in not directly observing extreme health outcomes, such as hospitalization or death,\nand employing idealized conditions from thermal chamber studies. A range of physiology-based metrics\nhave been employed to project future heat stress.”\nI think the Introduction is generally strong—well written, especially when describing gaps and limitations\nin prior work. That said, I needed a little more info before the paragraph on lines 88-92. Despite excellent\ntext before this paragraph, the 43C threshold still comes seemingly out of nowhere in the first sentence.\nAnd then in the second sentence we hear about maintaining core temperature, which leads one to\nwonder about the gray area between these two extremes. I don’t question the use of these two\nmeasures—we just need some added context before you introduce these two specific ‘lines in the\nsand’ after talking too us earlier about all the nuances that can render lines in the sand blurry (pre-existing\nhealth conditions, adaptations, etc.).\nResponse: Thank you for this feedback. We have tried to ensure this is not such a large jump between\nthe two paragraphs by having more flow when discussing heat stroke death at a T of 43°C. We also\ncore\nensure that it is clear that 43°C is a core temperature value, which is what we use in our model as heat\nstroke death.\nThe following has been added:\nLines 106-109: “A human would experience heat stroke death from hyperthermia on 99.9% of occasions\nwhen an individual’s core temperature (T ) exceeds 43°C32 (see Table 1). Thus, we define the limit of\ncore\nsurvivability as reaching T of 43°C in 3- or 6-hour exposure windows to allow for comparison with the\ncore\nT of 35°C assumption (heat stroke death after 6 hours).”\nw\nLines ~112–116: “The realistic final T value for the limits of survivability or liveability will differ by\nw\nperson and climate type (dry versus humid; sun versus shade), and thus is flexible (i.e., the limit will\ndiffer). Hence, while we state a final T at which heat stroke death will almost inevitably occur, our\ncore\n9\napproach does not assume a unique T threshold; rather, hundreds of T thresholds are possible\nw w\ndepending on differences in people and conditions modeled, with wide-ranging opportunities of the\nmodel in future research (Table 3).”\nAgain, your summary of what is needed, and the importance of more nuance in these studies is strong. It\nis just odd that you aren’t more precise about which of these many pieces you all chew off in your\nanalysis. Without a close read, once could easily assume your study addresses ALL the shortcomings of\nprior studies you have just (nicely) elucidated, rather than just a couple (important ones).\nResponse: Thank you for this suggestion. To address this, we added Table 3 to show future work,\nimproved the framework (now Figure 1) to show what we do in this study clearly, and added the below\nparagraph to the end of the introduction:\nLines 130-135: “An overview of environmental conditions, populations modeled, and assessment types\nexamined in the present study is provided in Fig.1, which displays the scenarios and tests this study\naccomplishes that were disregarded by other studies. We do not demonstrate the sensitivity of illness or\nhealth status (including acclimatization) in the population, activity velocity, personal cooling strategies,\nbody shape and size, or an ensemble of climate projections, all of which are needed in future work (Table\n3).”\nThe following is already stated after the goal in the introduction, on lines 121-123:\n“We focus on two subpopulation types (younger (~18–40 y) and older (>65 y) female adults), considering\nsweat rate impairments (due to older age) and heat exposures in the sun or shade and across an array of\nair temperatures (T ) and humidity levels.”\nair\nAlong similar lines, the critiques of prior work on lines 66-67 seem fair, but seem to promise more than\nyou deliver. For example, in contrast to prior authors, do you consider body size, or more than a single\n(age 65+)’ restriction to thermoregulation’? Why not say that you don’t?\nResponse: Indeed, we should say what we do explicitly and do not test in this study and what the model\ncapabilities are moving forward. As stated in a response above, now we provide the information of what\nwe DO versus what we DON’T address based on the gaps presented, stating that we take the “initial\nsteps” needed in this inaugural research paper to start to tackle this enormous interdisciplinary\nchallenge.\nThe following is added to the introduction:\n“An overview of environmental conditions, populations modeled, and assessment types examined in the\npresent study is provided in Fig.1, which displays the various scenarios and tests this initial study\naccomplishes that are disregarded by other studies. Specifically, we address sun versus shade, compare\nage (young versus old), allow for clothing and metabolic rate considerations (in the liveability analysis),\nand apply to two climate projections. We do not yet demonstrate the sensitivity of illness or health status\n(including acclimatization) in the population, activity velocity, personal cooling strategies, body shape\nand size, or an ensemble of climate projections, all of which are future work needed in the community\n(Table 3).”\n1 shows better what IS accomplished in the current study.\n3. I am trying to figure out how in the extremes of high T and low RH the downward revisions of the\ndanger thresholds relate/don’t relate to actual weather conditions (as opposed to theoretical or lab\nexperiment-driven conditions). Once temps get really high (e.g. 115+ F) on your figures, there currently\naren’t any RHs of 40 percent, for example. Along similar lines, does any literature suggest that anything\nlike 35C wet bulbs occur or will occur at low RH? In a sense my point is that not only does this paper\nfocus on a single physiological/human model, not only does it largely punt on describing humid heat\nepidemiology, but it also largely punts on describing the climatology of observed heat and humidity. It is\ncritical to know which combinations of T and RH are experienced and likely to be experienced. As a bare\nminimum revision, can we see reported combinations of T and RH somewhere, perhaps added to some\nof the existing figures 1-4?\nResponse: The graphs generally show combinations of temperature and humidity that are indeed\nreached in many areas of the globe. SM Figure S14 and S15 shows 3-H data for 2016-2025 across\nselected hot-humid and hot-dry locations, demonstrating that extremely hot and dry and extremely hot\nand humid combinations can be reached; those conditions will also become more likely in the future,\nand thus we need to be able to model the physiological impacts. Reviewing current literature on heat\nextremes, we note that the occurrence of T above 38oC is not very plausible, and thus remove any\nw\nisotherms above that level. That change has been done for all graphs. The election of T 38oC is based on\nw\nthe report of some very limited T 35oC occurrences already (Raymond et al 2020) and assuming that 3oC\nw\nwould be a reasonable threshold to encompass conditions reached in hot and humid tropical locations\nwith future warming, given work showing that extremes of wet bulb temperature in the tropics scale\nclosely with tropical mean tropospheric temperatures (Zhang et al 2021). Finally, we must remember\nthat although some conditions may not be reached much outdoors, they could be reached indoors in\nfactories, mines, etc.\nIn the discussion, we now refer to the SM figure that shows these conditions, as well as state the\nfollowing with two new citations:\n“Results encompass current and future extreme heat (see SM Figure S14-S15 for current ranges) across\nvery hot and dry and very hot and humid situations with risk increasing, or expected to increase, in parts\nof the world.32,34”\nWe also have added the following sentence in the results:\n“Results are shown for moderate to very extreme combinations of temperature and humidity that may\nbe reached at times today, both indoors and outdoors, but more frequently in the future.32”\nAlso, in the supplemental material, we mask out areas of the water vapor and specific humidity graphs\nwith RH >100% (non-plausible conditions).\nWe do not feel we need to describe the climatology or epidemiology of heat and humidity when many\nother papers have done so, many of which we refer to in how we justify the need for this work as well as\ndiscuss the connections to other literature and global impacts. Doing as such would deter us from our\ngoal, and we also do not have the space. Also, with respect to humidity, it has not been identified as a\n11\nstrong predictor of heat-health outcomes to date (see Baldwin et al., 2023), possibly because those who\ndo die in from heat are very physiologically vulnerable and perhaps have blunted sweating ability.\nFinally, with respect to the model, it is indeed one physiological model with numerous inputs. It can be\nthought of like a weather or climate model with many input variables or starting points. With humans,\nthere’s not one human*, but there is one set of fundamental principles (like climate models) to follow. So\nwe can model various types of humans with our one model by using different variables for age, sex, body\nsize, clothing, sweat rate, acclimatization, etc. etc. In the end, we will be able to make “ensembles” of\nmany types of humans with the one model.\n*Note that the Tw of 35oC approach does assume there’s only one type of human all of same body size,\nsex, etc.\nCitations we have used and added:\nChristidis, N., Mitchell, D. & Stott, P.A. Rapidly increasing likelihood of exceeding 50 °C in parts of the\nMediterranean and the Middle East due to human influence. npj Clim Atmos Sci 6, 45 (2023).\nRaymond, C., Matthews, T., & Horton, R. M. (2020). The emergence of heat and humidity too severe for\nhuman tolerance. Science Advances, 6(19), eaaw1838.\nZhang, Y., Held, I. & Fueglistaler, S. Projections of tropical heat stress constrained by atmospheric\ndynamics. Nat. Geosci. 14, 133–137 (2021). https://doi.org/10.1038/s41561-021-00695-3\n4. One GCM, one RCP is a problematic. For Nature Communications, I think you need to include more\nmodels in the main, and probably another RCP in the Supplement. Note that these additions would not\nstarve the follow up study you refer to about sources of uncertainty, in a field with so many possible\npermutations (Petkova et al. 2014, for example.)\nResponse: Thank you for this comment. Based on this and a related comment from reviewer 2, we have\nadded another RCP and another model in the paper, and thus now have assessed liveability using the\nfollowing models and scenarios from CMIP6: GFDL ESM4 and MPI ESM1.2 following SSP2-4.5 and SSP5-\n8.5. These revisions affect Figures 6 and 7 in the main manuscript (including captions),\nmanuscript text in Section 4.4, and SM Figures S9-S13. The results from both models are qualitatively\nsimilar for both the global maps and assessments of particular locations. However, as expected, there\nare greater decreases in liveability for SSP5-8.5, related to the steeper increases in carbon emissions\nover the next century. We agree that a more extensive suite of GCMs and scenarios would be useful to\nexplore in future work (as mentioned in Table 3 above). Still, we hope that this present analysis serves as a\nvaluable proof-of-concept for this initial paper, focused predominately on describing and demonstrating\nthe capabilities of the physiological model.\nAs part of this change, the methods have also been updated.\nLine by line comments\nLiability’ in title to ‘Liveability’\nResponse: Thank you for catching this. We have also changed the spelling from livability to liveability,\nwhich is the more preferred version.\nsentence. As written, it seems like they only apply to livability not survivability.\nResponse: We have moved the “in sun or shade” portion up, but we only do the projected climates for\nliveability, so leave that with #2.\nIntroduction\nIs the term ‘heatstroke death’ sufficient here? (I am wondering if there are other kinds of heat related\ndeaths you mean to include that are not captured by the term ‘heatstroke death’)?\nResponse: Yes, it is sufficient in this case because the methods used here for survivability and those\nusing the Tw of 35oC assume a rise in core temperature to critical limits that would cause a heat stroke\ndeath. While cardiovascular deaths and kidney failure are two other common causes of heat death, we\nare not modeling those in the survivability portion of this study. These differences between the types of\ndeaths are stated in the introduction starting on line 100 where we discuss this and state:\n“This study and related studies assessing survivability limits (e.g.,12,14.16) estimate deaths arising from\ncritical high core temperatures. A complex cascade of events30,31 ultimately leads to multi-organ\nfailure,3.310 and often death31. Hence, we model heat stroke deaths (hyperthermia) and do not model the\ntwo other common types of heat-related deaths: death from cardiovascular collapse and renal failure\nand collapse, acknowledging that heat stroke deaths are a fraction of total excess heat-related deaths.”\nFurther, in the supplemental material we state:\n“This paper and others using limits to adaptability or survivability frameworks focus on heat stroke\ndeaths (hyperthermia) and do not model the two other common types of heat-related deaths: death\nfrom cardiovascular collapse and renal failure and collapse, acknowledging that heat stroke deaths are a\nfraction of total excess heat-related deaths.”\nTo make it more evident in the main paper, we have added the following sentence:\nLine ~102-104: “Hence, we model heat stroke deaths (hyperthermia) and do not model the two other\ncommon types of heat-related deaths: death from cardiovascular collapse and renal failure and\ncollapse.”\nThis sentence also allows for better flow into discussing the critical thermal maximum of 43oC, which was\na comment above.\nPenultimate paragraph—clarify that you mean an individuals aging, rather than the average age of\nhumans (or more to the point the number and age of older people) going up in the future\nResponse: Thank you. We have clarified that we mean older age.\n‘3.2’ at first use in heading to 2.2’\nResponse: Thank you. Fixed.\n‘3.3 at first use in a heading to 2.3’\nResponse: Thank you. Fixed.\nI feel Figures 1 through 4, while all excellent, are so similar stylistically and content-wise similar as to\n13\nargue for making a hard decision to move at least one of them (possibly two of them) to the\nsupplement.\nResponse: We feel these are all important and show very different things, so we have left these four, but\nto reduce the number of figures, we have moved Figure 8 to the supplemental material.\nLine 273:’Plan’ to ‘Plain’\nResponse: Thank you for catching that. Fixed.\nFigure 3: Give us a better sense, through examples in the text of what levels of activity different values of\n‘Met’ correspond to. Figure 3 is nice in this regard, but say more in the main text.\nResponse: This is a great idea. We have updated the text in the results to give more context when\nreferring to specific MET levels, and have added some more specific examples in the caption of Figure 3.\nAlso do the icons, like running, assume no rest during 3 hours?\nResponse: Correct, it implies a continuously sustained intensity in the activities while maintaining a core\ntemperature at a steady state. There is no attached duration for the safe activity in the primary liveability\nanalysis, just an intensity. For determining areas of survivability but NOT liveability (hence full rest)—\nshown by the hatched areas—we needed to include a duration component. Therefore, the 3H duration\nin the graph is only to display the exposures of people during rest and storing heat due to\nuncompensable heat stress, when the survivability limit for 3H of heat storage is not reached. For areas\nto the left of the hatched areas, the representative duration of the activity to remain compensable will\ndepend on steady sweating conditions, skin temperature and thermal environment. If a person’s activity\nlevel greatly exceeds M , the body will be in a state of continuous heat storage (uncompensable heat\nmax\nstress), and in danger; then, they need to slow down the activity or move to a colder environment. We\nhave ensured that this continuous effort and steady state of environmental and corporal assumptions\nare explicit in the methods and caption of Figure 4.\nFigure 5a: why are some areas showing reduced MET?\nResponse: Many areas show reduced MET because we are demonstrating how much LESS work people\ncan sustain safely (without a continuing rise in T ) as the conditions will change in these locations\ncore\nbetween today (contemporary) and end-of-century, assuming no additional forms of adaption to heat\nare used. Therefore, due to heating, many places will have conditions where only reduced work ability is\npossible. Based on this comment and the next, we have updated the Figure 6 caption as follows to avoid\nconfusion and make sure it doesn’t appear counterintuitive. We have also changed the legend in the\nmaps so that the largest M decreases are displayed as the largest negative values at the lowest\nmax\nfraction of the color palette.\nWe added the following to Figure 6 caption:\n“Activities by MET level range from no activity (sitting ~1.5 METs), to housework (~3.0 METs),\ndancing (~5.0 METs), and heavy lifting (~7.0 METs).“\nFigure 5b: worth exploring why Bangladesh has the lowest values. I think of this area as closer to high RH\nlow dry bulb than many of the other humid heat hotspots around the world like the Indus Valley for\nexample. Given your findings (high dry bulb at low RH is more dangerous than most researchers have\nrealized) this is somewhat counterintuitive. Can you look into some explanations? (Maybe GCM\nresolution, maybe the sheer number of days per year is a more dominant term in your model [maybe\nBangladesh has a lot of pretty oppressive days, rather than having the individual days that are the most\nextreme], etc.).\nconditions, meaning that the conditions are very oppressive because of magnitude and frequency, as you\npointed out. In the supplemental material, Figure S12 shows the percent of time with T>25C). In\nBangladesh, in the current decade it’s around 50% and will increase (to ~60-70% depending on the SSP\nand scenario). Also, focusing only on that warm time, the relative frequencies in the 2D histograms\n(Figure 7) shows a predominancy of very humid conditions (above 80% RH between 28 and 32C). This is\nwhy in Figure 6b and e, results show that people can do less in the decade average. So the colors over\nBangladesh show that it is actually one of the worst locations when it comes to heat and humidity\nbecause the maximum activity that can be done at the of the century is very low and for a high\nproportion of time. We have to clarified this in the caption so that it doesn’t come off as\ncounterintuitive.\nFigure 6 caption: ‘Dix’ to ‘Six’\nResponse: Thank you for catching that. Fixed.\nFigure 7: I think this should be much earlier in the paper.\nResponse: Thank you for this suggestion. We were thinking it should go with the methods, but since the\nmethods come after the results and discussion in this journal, we have found a way to make it appear\njust after the introduction.\nFigure 8 caption: Is ‘wittedness’ intended? Especially if you are constrained in your number of Figures,\nthis is a very logical figure to move to the Supplement.\nResponse: Thank you for catching that. This should not be “wittedness”. We have fixed it to say\nwettedness. Also, thank you for this suggestion about the figure. We have moved it to supplemental\nmaterial, where we detail the full model.\nMethods 4.4. did you bias correct for cities? If not, it is OK, but you should say so.\nResponse: We did not for this particular paper. This has been added in section 4.4 to the methods.\nReferences\nHorton, R. M., de Sherbinin, A., Wrathall, D., & Oppenheimer, M. (2021). Assessing human habitability\nand migration. Science, 372(6548), 1279-1283.\nPetkova, E. P., Vink, J. K., Horton, R. M., Gasparrini, A., Bader, D. A., Francis, J. D., & Kinney, P. L. (2016).\nTowards more comprehensive projections of urban heat-related mortality: estimates for New York City\nunder multiple population, adaptation, and climate scenarios. Environmental health perspectives.\nReviewer #2 (Remarks to the Author):\nThe manuscript focuses on assessing survivability and livability by applying physiological and biophysical\nprinciples. The authors suggest that the 35oC Tw threshold underestimates the risks for older adults.\nThey also suggest that the risk continues to increase in a changing climate.\nI have two major concerns with the manuscript. First, the authors use only a single GCM and a single\nscenario that fails to capture the range of future climate uncertainties. Secondly, the authors extract\ncity-level data from a pretty coarse resolution GCM. The majority of GCMs in CMIP6 are still pretty\n15\ncoarse resolution including the GFDL-ESM4 model that the authors have used. Using GCM data to draw\nsuch conclusions can be misleading given that it fails to capture various city-specific features and will\nhave substantial biases. From the title of the manuscript, it looks like the authors are trying to evaluate\nthe survivability and livability in a changing climate, and therefore, using single coarse resolution GCM is\nnot justified. A minor comment- it should be “livability” and not “liability” in the title.\nResponse:\nFirst, thank you for catching the error in the title. We have also changed the spelling from livability to\nliveability, which is the more preferred version.\nSecond, the example with the GCM is intended as a proof-of-concept or case study to demonstrate the\ncapabilities of the physiological model, but we see that there is a need to show more than just one\nmodel and scenario with the new method to build confidence. Following your comment and one by\nanother reviewer, we have added another RCP and another model in the paper, and thus now have\nassessed liveability using the following models and scenarios from CMIP6: GFDL ESM4 and MPI ESM1.2\nfollowing SSP2-4.5 and SSP5-8.5. These revisions affect Figures 6 and 7 in the main manuscript,\nmanuscript text in Section 4.4, and SI Figures S9–S13. The results from both GCMs are qualitatively\nsimilar for both the global maps and assessments of particular locations. However, as expected, there\nare greater decreases in liveability for SSP5-8.5, which have steeper increases in the carbon emissions\nover the next century. We acknowledge that a more extensive suite of GCMs and scenarios would be\nuseful to explore in future work, including a more comprehensive climate change uncertainty analysis\n(as mentioned in Table 3 above), but hope that this present analysis serves as a valuable proof-of-concept\nfor this initial paper focused predominately on describing and demonstrating capabilities of the\nphysiological model.\nThanks also for noting the significant limitations of GCMs when looking at particular cities. We agree that\nascertaining results for specific cities can be tricky with relatively coarse GCM output and that ideally,\nsuch data would be bias-corrected prior to analysis. However, we still think there is a utility to\ncontextualizing the effects of aging against the distribution of temperatures for particular locations (as in\nFigure 7). Given this, we retain that analysis, but have revised Climate Analysis methods text (line 503) to\nsay we explore the distribution of liveability in present and projected future conditions in particular\nregions across the globe, as opposed to specific cities. Additionally, the addition of the second GCM,\nwhich has similar results for this analysis, adds some confidence regarding the robustness of the results.\nWe also acknowledge that future work should conduct similar analyses for particular cities using\ndownscaled, bias-corrected projections (as mentioned in Table 3 above). Please see relevant text\nrevisions in lines 533 to 535. We hope this provides a middle ground that adequately addresses the\nreviewers’ comments.\nReviewer #3 (Remarks to the Author):\nOVERALL:\nThe goal of the paper by Vanos et al. was to improve upon the modeling of survivability and livability\nlimits of humans exposed to increasingly hot environments due to climate change. In many ways the\nauthors succeed in their goal of advancing upon earlier modeling efforts. The authors, in particular,\nextend survivability and livability limits to very hot and very dry environments and attempt to show\ndifferences between young and old. Other advantages are mentioned (contingencies for disease states,\nacclimatization status, body size, fitness, etc.) but not described. The work submitted is in many ways\nmasterful, but there are numerous potential problems with the many assumptions made and as a result\n16\nthe interpretations also appear problematic – even incorrect. A model such as the UTCI, validated\nagainst empirical data (such as Brode and Kampmann, 2023), may be a better approach? Questions and\ncomments follow for consideration.\nResponse: Thank you for these overarching and helpful comments.\nFirst, we indeed state the potential of our approach to address aspects like body size, fitness,\nacclimatization status, and disease states but do not specifically test these in the given paper. Thus, we\nhave ensured it is clearer what we demonstrate in the current paper (age group differences, sun versus\nshade, sweat rates, use with climate projections) versus what the model has the ability to do in the\nfuture based on how the new methodology is set up. We also direct you to Reviewer 1’s comment #2\nabove with a similar request.\nSecond, for the UTCI, please refer to response #5 below. Briefly, the available regressions from the UTCI\ndo not allow for studies motivated to be made for different types of people (e.g., age, standard body\nsize, clothing assumptions, metabolic rate, walking speed) and thus are unsuitable for the given goals of\nthis work.\nFinally, we hope that our responses below and to the two other reviewers help provide more\nunderstandable interpretations of the data so that they do not seem problematic. We notice that\ndirecting this article to various types of disciplines, while important, could result in some\nmisunderstandings of terms, purpose, and assumptions within the paper, and we have attempted as best\nas possible throughout the paper to avoid such instances.\nMINOR:\nLine 1: Title - liability should read livability.\nResponse:\nThank you for catching this. We have also changed the spelling from livability to liveability, which is the\nmore preferred version.\nLines 183, 191: A decrease in Mmax of 0.2-0.26 METS does not seem like an appreciable difference (10-\n20% can be the measurement noise for METS). Can the authors better contextualize how this matters to\nhuman health, economic burden, etc.?\nResponse: This is a nice idea. Note that the global median of the Mmax decreases (GFDL model) for SSP\n2-4.5 is -0.25 METs, and for SSP 5-8.5 is -0.64 METs. Both results are representative of conditions >25oC.\nWe have added the following for context:\nLines ~346: “These changes could represent a slightly lowered productivity (e.g., less crops harvested, the\nneed for extra workers) or decreased activity performed, with economic or health consequences.58–60\nWhile quantifying these consequences is beyond the scope of the present paper, this should be the focus\nof future research.”\nLine 372: Did you mean reference #30 for this statement? Reference #67 I understand.\nResponse: Thank you for catching that. We mean Cramer and Jay (2019). This is fixed.\nLimes 3890-403: It would be helpful for those interested to introduce the average height and weight used\nto arrive at the 1.60 m2 (young) and 1.78 m2 (old) (supplementary information) values that appear to\nhave been used for the calculations represented in all the tables and graphs. Were these population\nmedian values for height and weight in young and old populations?\nResponse:\nIndeed, these were population mean values for young healthy women and older women. We used the\naverage for women since studies rarely look at women (they always use the averages for men). The\nmodel can be used for any height and weight.\nWe have added the following info and citations to the SM (references are based on the SM reference\nlist).\n“These surface areas arrive from Eq. 7 and are based on global average height for women8 (~1.62m) and\naverage weight data based on ExposFacts9,10 and the EPA Exposure Handbook11 (using NHANES data) to\nensure a more representative global average, resulting in ~57kg for young female and ~74kg for older\nfemale.”\nNote we also have made sure it clearer throughout all of the text that the values are for young women,\nnot overall adults.\nLine 406: It does not seem reasonable to use a nude body for survivability (how many people would be\nnude?) but minimal clothing for livability. I understand wanting to compare your results to previous\nwork, but the buck should stop somewhere? Or consider using nude estimates for livability as well?\nResponse: We use a conservative approach. This is the same assumption (i.e., a person being nude) by\nusing the T of 35oC thresholds, so we have them nude to make a direct comparison. It is our position\nw\nthat if a person is suffering from excessive heat stress to the extent that their survival is threatened,\nremoving clothing to allow for more heat loss would be a plausible adaptive behaviour. In terms of the\nclothing selected for our liveability analysis, it is our position that for an environment to be considered\n“liveable\" in most parts of the world, estimations of heat transfer must account for at least some\nclothing – otherwise our estimates would define conditions that are only “liveable” is everyone is nude,\nwhich does not seem especially useful. Please also see the new Table 3, which provides other future\nwork where we can test clothing changes with the model.\nReferences: There are a number of references with errors in them. Please review and edit.\nResponse: Thank you for noticing this. We have reviewed and updated references for accuracy\nthroughout.\nTable 2: The lower Tw limit at lower humidity seems strange without the context of the very high\naccompanying air temperatures.\nResponse: This is a great point. We have added the corresponding air temperature to Table 2 and the\nSupplemental Table. Also, note that the horizontal lines in Figure 3 help readers see the T value at the\nair\ngiven RH to result in the final Tw limit. We have also ensured that the section describing this table is\nupdated with corresponding air temperature values.\nThis addition is now provided in Table 2 caption (“…along with corresponding air temperature. Each\nhumidity level is also by the horizontal lines on Figure 3.”) and we have made this fact clearer within the\nw\n90, and 100%.”) \nFigures 1-4: Where are environmental conditions projected to rise to 50 degrees C or more to make\nthese projections less theoretical and more meaningful?\nResponse: We have provided this context in the results for examples, but there are many regions where\ntemperatures are or have already risen (and are projected to rise) to 50 degrees or more. So we extend\nthe graph this far to be able to quantify those conditions. For example, an article by Christidis et al.\n(2023) shows a rapidly increasing likelihood of exceeding 50 °C in parts of the Mediterranean and the\nMiddle East in the future, and thus we need to be modeling these conditions. We have cited this paper\nin the study and stated our reasoning for the ranges we have selected to ensure we are reaching\nconditions that the future may hold for some locations.\nChristidis, N., Mitchell, D. & Stott, P.A. Rapidly increasing likelihood of exceeding 50 °C in parts of the\nMediterranean and the Middle East due to human influence. npj Clim Atmos Sci 6, 45 (2023).\nhttps://doi.org/10.1038/s41612-023-00377-4\nFigure 6: Can the authors explain the y-axis probability?\nResponse: Thanks for catching this. The y-axis in the histogram refers to the relative frequency of the\nM values for each histogram bin (i.e., percent of the total values that fall in each bar range). This is\nmax\nalready addressed in the graph, and the new label says “Relative frequency (%)” not probability.\nSupplemental Material and Model Assumptions:\nEquation 20: How is Smax determined? Is it simply Ereq?\nResponse: Thank you for catching that. We have added the values for Smax and the studies that\ndetermined them. The values are: 0.75L/hr (18-40 years) and 0.51 L/hr (65+ years). These have been\nadded, as follows, after equation 20:\n“where S is 0.75L hr-1 (18–40 years) and 0.51 L hr-1 (65+ years)18…” (Morris et al., 2019).\nmax\nWe are being quite conservative about the prospect of survivability with the sweat rates we have\nchosen, as there is such a variation in the population. Higher sweat rates would shift our line a bit closer\nto the Tw of 35oC line. Also note that we are also saying that these sweat rates are sustained for up to 6\nhours without any dehydration effect, so we do not want to be overestimating sustained sweat rate.\nWe are being quite conservative about the prospect of survivability with the sweat rates we have\nchosen, as there is such a variation in the population. Higher sweat rates would shift our line a bit closer\nto the Tw of 35oC line. Also note that we are also saying that these sweat rates are sustained for up to 6\nhours without any dehydration effect, so we do not want to be overestimating sustained sweat rate.\nMAJOR:\nLine 389: The premise for using 43 degrees C for survivability is justified by citing the range (41-47), but\n40.8 degrees C was the average exertional heat stroke temperature observed in more than 100 military\ncases (see Figure 5-3 in:\n(https://armypubs.army.mil/ProductMaps/PubForm/Details.aspx?PUB_ID=1024722). Is 43 degrees C\nmore applicable for passive heat stroke? Should a distinction be made between passive and exertional\nheat stroke? Which are you modeling, specifically? Both? A more justified value ~41 degrees C could\ndrastically change your results and interpretations.\npeople are at rest. The 43oC is quite a well-established upper limit (thermal maximum) in the literature.\nIndeed, it may be much lower (such as the example that the reviewer helpfully cites), yet there is a large\nrange among people, and often with passive heat stroke cases, the actual T reached is unknown.\ncore\nThus, we are aware our 43oC is very conservative (i.e., it is likely that most people will suffer heatstroke\nbelow this value), which may offset any concerns about us not being liberal enough with sweat rates. As\nan important note, the Sherwood and Huber 35 oC T model would result for a 6-H exposure in a T of\nw core\n48-50˚C depending on body size. Yet as that is the model used across most studies in this space currently,\nwe hope this work provides a large incremental improvement upon these assessments.\nMoreover, as stated in our methods already, “the translation from heat storage to T between our\ncore\nphysiological approach and the 35°C T limit is not the primary driver of their differences; if it were, the\nw\n“3-h shaded” model (dotted blue line, Fig.2a) would overlap the 35°C T (thick solid black) line. Instead,\nw\nsubstantial differences persist, especially above T of ~45°C.”\nair\nReference: Bouchama, A. et al. Classic and exertional heat-stroke. Nat Rev Dis Primers 8, 1–23 (2022).\nLines 432-436: I am not sure I understand S = 0 in this explanation. Heat storage could and would take\nplace to elevate body temperature (from 37 degrees C) to a new but stable baseline (e.g., 37.5, 38.0,\n38.5,…). Why must no heat storage be assumed (not realistic)?\nResponse: We regret we were not clearer in our original submission. We are not saying cumulative\n(absolute over time) heat storage is 0, but that a rate of heat storage of ~0 can be attained. While there\ncould be an elevated steady-state core temperature after activity commences, once thermoregulatory\nresponses are engaged, core temperature will reach a steady-state plateau. We have improved the\nclarity on this in section 4.3.\nSupplemental Material and Model Assumptions:\n1. Is airflow 1 m/s used in both survivability and livability scenarios? In Figure 3, a MET value of 2.5\n(walking) arguably creates airflow around a person equal to ~1 m/s, but jogging at 7.5 METS would be\nmore like ~2.25 m/s. Riding a bicycle at 5 METS would produce an airflow of ~5 m/s, completely ablating\nthe insulative air boundary layer. The under-estimation of airflow will have important effects on your\ninterpretations that rely so heavily on evaporative cooling.\nResponse: We use 1m/s wind speed for both. One reason is to match better with Sherwood and Huber.\nFor survivability, the person sedentary, so self-generated air velocity is <0.2 m/s. This would always be\nthe case for someone laying down and allows our results to be comparable to the T of 35oC approach.\nw\nThe airflow is held constant to differentiate between the impacts of the temperature, humidity, and solar\nconditions on the survivability line. For the liveability analysis, we also use the 1m/s and do not alter\nactivity speed either, and we agree more robust incorporation of activity speed would be a useful area\nfor future work (as noted in the new Table 3), but is beyond the scope of the goals of this paper. We’ve\nmade sure these points are clear in the SM.\n2. Mean Tsk is set to 35 degrees C. Though it may align with other publications, mean Tsk can be easily\n36 or 37 degrees c in very hot air (40 to 50 degrees C), especially when globe temperature is higher still.\nSome military models use 36 degrees C or establish a scaling factor for the best gradient. This too will\npotentially impact your interpretations and calculus as dry heat gain is somewhat exaggerated.\ninitial study based on the literature consensus that mean vasodilated Tsk of 35oC, but also the Tw of\n35oC wet bulb threshold model by Sherwood and Huber uses a Tsk of 35oC assumption as well. Hence, it\nallows us to compare this approach, which is one of the main goals. These reasons, with citations, are\nalready provided in the SM modeling information.\nNevertheless, we certainly acknowledge that this is limitation and we have included this as a major area\nof future research and application using ranges and scaling factors in the new Table 3.\n3. The skin wettedness values employed of 0.50 to 0.65 seem too low, especially 0.50 (e.g., Candas et al.,\n1979; Ravanelli et al., 2018). This makes a huge potential difference to Emaxlim. Can the authors provide\njustification for such small values? If 0.65 to 0.85 were used, how would this impact your results? I\nsuspect greatly.\nResponse: We initially were trying not to overestimate skin wettedness so we used lower values but in\nreviewing the literature, we agree that 0.65 and 0.85 are more appropriate based on Candas 1979 and\nMorris 2021. We have now changed these values in the analyses and repeated all modeling runs.\nWe have made these updates to the detailed methods in the supplemental material while also\nrecognizing in Table 3 that future work should vary the sweat loss between subpopulations to account\nfor a range of cooling potentials.\n4. There is a major emphasis on how age impacts the results of the model, but little explanation is given\nfor why. Reference #15 is cited for age negatively impacting Emaxwet. However, while reductions in\nvasomotor and sudomotor function have been convincingly demonstrated to occur with aging,\ntranslation to heat balance on the whole body level is less clear. For example, men 45 years older than\nyounger subjects matched for body mass, height, and body surface area had 50% lower local sweating\nrates, even though Ereq in W/m2 was similar (Schmidt et al., 2022). Others have quantified an age-\nrelated reduction in thermoeffector heat loss potential of ~4% per decade between ages 18 and 70\n(D’Souza et al., 2020). How does this compare with your model? On the whole body level, small or non-\nsignificant differences in heat balance between young and old are reported (Stapleton et al., 2014).\nImportantly, the Stapleton study was conducted at 40 degrees C and 15%rh at metabolic rates ranging\nfrom 300 to 500W. Your results (lines 166-169) seem to suggest that this should be impossible for older\nadults (65 yoa in Stapelton et al., 2014).\nResponse: The results on Line 166-169 in the original manuscript were referencing liveability, which is\nabout sustaining a certain rate of physical activity over a long period without seeing a sustained positive\nrate of heat storage. So we are not saying the activities are impossible, just that they are not possible\nwithout having a continuously rising T . So indeed, under very hot and dry conditions (45oC and 10%\ncore\nRH), an older adult would not be able to do more physical activity than 1.5 METs without a sustained\npositive rate of heat storage. This does not mean they cannot do any physical activity (they can do bouts\nof activity), but they should not do it for an extended period.\nRelated to the question of why age impacts E , this relates to the fact that the peripheral sensitivity to\nmax\nacetylcholine, which is responsible for sweating, is reduced with primary aging on average across the\nbody. This reduces the overall 𝜔 , which reduces 𝐸 . Thank you for bringing up the Stapleton\n𝑚𝑎𝑥 𝑚𝑎𝑥𝑤𝑒𝑡\nstudy. It seems that there was not much difference in the results between middle-aged (mean age 49)\n21\nand older males (mean age 65), but there was a difference with the young males (mean age 21). So,\nthose findings support our paper here. Further, the Stapleton study is on people exercising in\nintermittent bouts (300W, 400W, 500W, as mentioned in the comment). Our survivability analysis looks\nat full rest (~100W), so we don’t’ think the Stapleton results are comparable for survivability. However,\nreferring to liveability, our analysis isn’t too far off that of the Stapleton paper, where at the same RH and\nT , (40C and 15%), we say M is ~2.3–3.0METs. In the Stapleton paper, the lowest intensity was ~300W\nair max\nor 3.5Mets. Thus, we feel it is a decent agreement. This study has also been cited as an example of\nphysiologic comparisons in Table 3.\nAlso, to clarify, we aren’t looking at progressive effects of age, just a categorical young and old group\ncomparison, which is a significant advancement on the existing models used in survivability analyses.\n5. Would use of the UTCI model be a better approach? It has recently been validated against empirical\ndata. Please see: Bröde P, Kampmann B. Temperature-Humidity-Dependent Wind Effects on\nPhysiological Heat Strain of Moderately Exercising Individuals Reproduced by the Universal Thermal\nClimate Index (UTCI). Biology (Basel). 2023 May 31;12(6):802.\nOverall, it seems that a small change in any one of many model assumptions could significantly alter\nyour results, interpretations, and conclusions.\nResponse: We do not believe the UTCI wouldn’t be better. Indeed, the model may be more sensitive to\ncertain changes than others due to how different humans respond to heat. However, some fundamental\nissues in not using it is that all UTCI estimations are for a young and healthy 73.5 kg man, with 1.86 m2 of\nbody surface area and 14% body fat working a metabolic rate of 3 METs. It is, therefore, unable to\ngenerate any heat stress risk assessments for women, anyone at rest (most likely activity in a survival\nscenario), or older adults (who are at most risk). We also cannot use it for the liveability analysis because\nwith UTCI we can’t back calculate the MET.\nBeing able to look at diverse populations is one of the main reasons we set out to do this paper and\nmodel different types of people. However, we also recognize that certain assumptions, such as skin\nwettedness, may change our result as we change the value, yet such values can’t even be modified in the\nUTCI. We have used the best values that we have from the literature and chamber studies and ensure\nthat we remain conservative in our assumptions, similar to that of the studies applying the wet bulb of\nthe 35oC approach. In recognizing this fact, numerous chamber experiments are going on in multiple\ncountries working to address these specific values of skin wettedness, skin temperature, and sweat rate\nin different populations at different critical temperatures so that the types of modelling and approaches\nused (such as in this paper) here can be more accurate. The flexible approach we have developed will\nallow that in the future. Overall, we have used the values that 1) we are most confident in from the\nliterature that is justifiable to use (with full citation support), and 2) tried to use assumptions (currently)\nthat allow us to compare with the T of 35oC survivability model, with the full future model capability of\nw\nvarying these by person and in space or time with the approach we have created. Others will be able to\ndo the same thing with the model, and the model can be even more complex for additional types of\npeople once more human subjects' chamber data are available. It is a clear example of interdisciplinary\nresearch coming together to drive new questions and capabilities.\nReviewer #1 (Remarks to the Author):\nThe authors have sufficiently addressed my concerns, in what to my mind is an excellent revision. As a\nminor quibble, I feel they have overstated the degree to which the literature has tended to claim 35C\nwet bulb is the be all and end all survivability threshold. I also felt that my initial critique of their\npresentation of their model results as lacking sufficient caveats led in their rebuttal to an assumption\nthat I thought 35C wet bulb (or relying on wet bulb only in general) was a superior approach. That\ncertainly is not my view--I was just hoping to bring out more caveats about their approach, something\nthe authors have now added. My sense is that reviewer three may at the end of their comments have\nbeen on to something that could use a little more caveating, but as that material (human physiology and\nheat shedding) is far outside my areas of expertise, I defer to Reviewer 3.\nReviewer #2 (Remarks to the Author):\nThe authors have successfully responded to each of the reviewer's comments resulting in a significant\nimprovement of the manuscript Therefore, I recommend the manuscript for publication.\nReviewer #3 (Remarks to the Author):\nI appreciate the efforts at revision and responses of the authors. I have no further questions or\ncomments.\nResponse to Reviewers:\nReviewer #1 (Remarks to the Author):\nThe authors have sufficiently addressed my concerns, in what to my mind is an excellent revision. As a\nminor quibble, I feel they have overstated the degree to which the literature has tended to claim 35C\nwet bulb is the be all and end all survivability threshold. I also felt that my initial critique of their\npresentation of their model results as lacking sufficient caveats led in their rebuttal to an assumption\nthat I thought 35C wet bulb (or relying on wet bulb only in general) was a superior approach. That\ncertainly is not my view--I was just hoping to bring out more caveats about their approach, something\nthe authors have now added. My sense is that reviewer three may at the end of their comments have\nbeen on to something that could use a little more caveating, but as that material (human physiology and\nheat shedding) is far outside my areas of expertise, I defer to Reviewer 3.\nResponse:\nThank you for this helpful feedback. It seems we may have overdone our comments on trying to create\nclarity for the reviewer regarding the use and applicability of the wet-bulb, and we have stated the\ncaveats now too much. To address this comment, we have reviewed the entire paper and areas where\nthe caveats and nuances are discussed and reduced the amount to which we state these concerns\n(reducing repetition) to balance things out more. Now we feel we have reached somewhere in between\nour initial submission 1 and submission 2, thus finding a happy medium on this topic. This is now\nreflected in the final article and has allowed us to also shorten the manuscript slightly.\nReviewer #2 (Remarks to the Author):\nThe authors have successfully responded to each of the reviewer's comments resulting in a significant\nimprovement of the manuscript Therefore, I recommend the manuscript for publication.\nResponse:\nThank you. We are glad the reviewer is happy with the improvements.\nReviewer #3 (Remarks to the Author):\nI appreciate the efforts at revision and responses of the authors. I have no further questions or\ncomments.\nResponse:\nThank you. We are glad the reviewer is happy with the improvements."}]

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