Human activities, if continued at the current pace, are likely to cause global warming up to 1.5^oC by the middle of this century. Exceeding this threshold risks severe impacts from climate change. In tropical regions like India, heat stress, a physiological condition, is a growing concern due to the country’s geographic and demographic vulnerabilities.

The Global Climate Risk Index, which ranks countries by the impact of extreme weather, ranks India as highly susceptible to heat waves, droughts, and other climate hazards. India has witnessed a sharp increase in both the frequency and intensity of heat waves. Due to urbanisation and increasing climate variability, the number of Indian states experiencing heat waves rose from nine to 23 between 2015 and 2020, with average heatwave days increasing from 7.4 to 32.2.

Though related, heat waves and heat stress are distinct phenomena. Heat wave, as defined by the World Meteorological Organisation, is a period of at least five days where the daily maximum temperature exceeds the normal maximum by 5°C or more. In contrast, heat stress is a physiological condition wherein the body struggles to maintain a stable internal temperature due to excessive heat from metabolic or environmental sources, posing health risks if the heat cannot be dissipated. Low wind speeds, high ambient temperatures, and high humidity exacerbate heat stress, impairing thermoregulation. The human body aims to maintain an internal temperature of 37°C. However, extended exposure to high temperatures or high workloads can increase thermoregulatory systems, leading to severe stress.

The distinctions between heat waves and heat stress, along with the physiological and environmental factors influencing heat stress, provide a foundation for understanding its real-world implications.

Measuring heat stress

To quantify heat stress, researchers use approximately 40 thermal comfort indices, with the Wet Bulb Globe Temperature (WBGT) and Universal Thermal Climate Index (UTCI) being among the most prominent. WBGT, based solely on environmental variables like air temperature and humidity, is widely used in occupational settings. Researchers often rely on the daily maximum gridded air temperature (Tmax) dataset from the India Meteorological Department (IMD) for heat stress assessments in India.

While WBGT provides a direct measure of environmental conditions compared to simpler indices like the Heat Index or Humidex, it does not fully capture the additional strain from restricted sweat evaporation in high-humidity, low-wind conditions, a critical factor in India’s tropical climate.

In contrast, UTCI is a thermal comfort index which employs a thermo-physiological model, integrating air temperature, humidity, wind speed, mean radiant temperature, and clothing insulation to account for responses like blood flow and sweating. UTCI provides an estimation of the temperature that the human body would ‘feel’ under a given environmental condition and would differ from the recorded maximum and minimum temperatures at any location.

UTCI is classified into a 10-category scale with the index values in the range 9^oC to 26^oC representing normal conditions, and values above 32^oC and 46^oC representing strong and extreme heat stress conditions, respectively.

Changing nature of heat stress

In an analysis for this commentary, the authors have used UTCI data from the Climate Data Store (Copernicus Climate Change Service), which is operated by the European Centre for Medium-Range Weather Forecasts (ECMWF).

To analyse the changing nature of heat stress across India, this study calculates standardised Universal Thermal Climate Index (S-UTCI) values for each month and for each state of India for the period 1994-2024. The UTCI values are standardised by subtracting the 30-year mean from the actual value and dividing it by the corresponding standard deviation. The S-UTCI values always range between negative to positive values, have a zero mean and standard deviation of one, irrespective of the range of values, and hence allow comparisons between data from different states/months. To analyse the trends in S-UTCI values, the following categories are followed:

• S-UTCI < 0: Below average
• 0 ≤ S-UTCI < 1: No change in heat stress
• 1 ≤ S-UTCI < 2: Moderate change in heat stress
• S-UTCI >= 2: High change in heat stress
• UTCI >= 32°C: Strong to extreme heat stress

Comparison of the data over three decades shows that changing climatic conditions depict an accelerating change in heat stress across India over this period, with a pronounced shift from low to moderate/high change in heat stress levels. While citizens continue to experience absolute heat stress the summer months along with a significant increase, the monsoon months exhibit a widespread change in heat stress than summer in many states, driven by rising humidity, marking a significant transformation in India’s climate risk landscape.

This data is important from a policy perspective as all regions experiencing high change in heat stress are relevant to be considered for interventions, irrespective of whether the region was already heat-stressed or not. However, highly heat-stressed regions experiencing further moderate or high increases in heat stress would require greater attention in terms of interventions.

Trends in heat stress

Trends in heat stress across Indian states in summer (March-May) and monsoon (June-September) months are presented in the visualisation above. Comparing 1994, 2015, and 2024, it is evident that there is a significant increase in heat stress across almost all states in India over this period.

In 1994, most states showed below-average or no change in heat stress across all months, indicating relatively lower heat stress compared to the 30-year average. Two decades later, by 2015, there is a shift in heat stress values. Southern states like Andhra Pradesh, Tamil Nadu, and Karnataka frequently exhibit moderate and even high change in heat stress, while states like Goa, Rajasthan, and Madhya Pradesh also show moderate to high change in heat stress.

Another decade after that, by 2024, data shows that Rajasthan, Punjab, and Uttarakhand are the most severely affected states in the northwestern regions, showing heat stress change of moderate and high levels for most months. In contrast, in central India, Madhya Pradesh, Maharashtra, and Chhattisgarh did not report high change in heat stress even by 2024; they mostly show no or moderate change in the heat stress values. Tamil Nadu, Kerala, and Karnataka in the south show increasing heat stress in 2024, with more moderate and high values compared to others. During August and September of 2024, northeastern states such as Himachal Pradesh, Mizoram, Manipur, Tripura, Assam, and Sikkim (traditionally cooler regions) show a change to high heat stress in the monsoon months. India’s vast geographical and climatic diversity results in pronounced regional variations in heat stress.

While comparing summer (March-May) and monsoon (June-September), it is observed that many states report relatively higher heat stress during the monsoon compared to the summer, potentially due to higher humidity during the monsoon months. In terms of change in the heat stress, while in 1994 most states predominantly showed below average or no change in the heat stress across months, by 2015 there was a moderate increase, and by 2024 the shift is more predominant with moderate to high change in the heat stress across months for most states.

The data was also computed to show a 10-year average comparison between 1994 to 2003, and 2015 to 2024 as shown in the visualisation above. This depicts a substantial shift in India’s heat stress landscape. It has moved completely from below average to no change in heat stress values during the decade 1994 to 2003 to showing either no change or moderate change in heat stress during the decade 2015 to 2024, indicating an increase from below-average to moderate-high heat stress conditions.

Citation:

• Habibi, P., Razmjouei, J., Moradi, A., Mahdavi, F., Fallah-Aliabadi, S., & Heydari, A. (2024). Climate change and heat stress resilient outdoor workers: findings from systematic literature review. BMC public health, 24(1), 1711. https://doi.org/10.1186/s12889-024-19212-3
• Venugopal, V., Latha, P. K., Shanmugam, R., Krishnamoorthy, M., & Johnson, P. (2020). Occupational heat stress induced health impacts: A cross-sectional study from South Indian working population. Advances in Climate Change Research, 11(1), 31-39. https://doi.org/10.1016/j.accre.2020.05.009

R.P. Poonguzhali is a pre-doctoral fellow at IIM-Bangalore, and Brinda Viswanathan and K.S. Kavi Kumar are both professors at the Madras School of Economics, Chennai.

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Banner image: A man carrying a child covers their heads with a cloth to protect themselves from the heat in Jammu. (AP Photo/Channi Anand)

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