Heat index
The heat index, also known as the apparent temperature, is a calculated measure that combines air temperature and relative humidity to represent the perceived temperature felt by the human body in shaded conditions, accounting for the reduced efficiency of sweat evaporation in humid environments.[1] Developed in 1979 by meteorologist R. G. Steadman as part of an apparent temperature table incorporating human physiological responses, it was adopted by the National Weather Service (NWS) following extensive research to better communicate heat stress risks.[2] The index is particularly relevant in warm climates where high humidity exacerbates heat's impact, as it can make conditions feel significantly hotter than the actual air temperature—for instance, at 100°F with 55% relative humidity, the heat index reaches 124°F, while at 15% humidity it drops to 96°F.[1] The heat index is computed using a multiple regression equation derived from Steadman's foundational work and refined by Lans P. Rothfusz in 1990 through the NWS Technical Attachment SR 90-23, with the core formula expressed as:HI = -42.379 + 2.04901523×T + 10.14333127×RH - 0.22475541×T×RH - 0.00683783×T² - 0.05481717×RH² + 0.00122874×T²×RH + 0.00085282×T×RH² - 0.00000199×T²×RH²,
where T is the air temperature in °F and RH is the relative humidity in percent; adjustments apply for low humidity (below 13%) or high humidity (above 85%) in specific temperature ranges to improve accuracy, with an overall error margin of ±1.3°F.[3][1] This metric is valid primarily for temperatures above 80°F and assumes shaded exposure, as direct sunlight can elevate the effective heat index by up to 15°F.[1] In practice, the NWS uses heat index values to issue public warnings, categorizing risks based on potential health effects from prolonged exposure or physical activity, as heat is the leading cause of weather-related deaths in the United States. From 1979 to 2003, heat claimed an average of 175 lives annually and over 8,000 total—more than those from hurricanes, lightning, tornadoes, and floods combined.[2] Recent studies indicate heat-related deaths have increased, exceeding 1,300 annually in the U.S. as of the 2010s–2020s.[4] The classification system includes: [1] Regions like the Central Plains and mid-Mississippi Valley experience the highest heat index values due to warm temperatures and proximity to moisture sources such as the Gulf of Mexico, with climatological studies showing varying frequencies of extreme events (e.g., heat index ≥105°F occurs 0.61% of summer days in Des Moines, Iowa).[2]
Fundamentals
Definition
The heat index is a measure of how hot it actually feels to the human body when relative humidity is factored in with the current air temperature, providing an "apparent temperature" that reflects perceived thermal conditions on exposed skin.[5] This metric quantifies the combined effect of heat and moisture in the air, which can make environments feel significantly warmer than the thermometer reading alone.[6] In contrast to the dry-bulb temperature, which solely measures the sensible heat of the air without considering moisture, the heat index serves as a "feels-like" temperature by incorporating relative humidity's role in altering human heat perception.[5] High humidity levels saturate the air, slowing the evaporation of sweat from the skin and thereby diminishing the body's primary cooling mechanism.[7] Humans regulate body temperature mainly through perspiration, where sweat evaporates to dissipate heat, but this process becomes less effective in humid conditions, leading to a higher heat index value that better indicates the true thermal burden on the body.[5] The heat index concept stems from foundational biometeorological research, including work by R.G. Steadman in 1979 that integrated physiological responses to temperature and humidity.[8]Importance
The heat index plays a crucial role in weather forecasting and public safety by providing a measure of how hot it actually feels to the human body, enabling authorities to issue timely advisories and warnings. The National Weather Service (NWS), part of the National Oceanic and Atmospheric Administration (NOAA), adopted the heat index in 1979 to assess sultriness and has since integrated it into operational forecasts for heat alerts.[5] This application directly influences public behavior, such as scheduling outdoor activities during cooler periods, and impacts energy consumption patterns by informing decisions on air conditioning use during peak heat periods.[9] In occupational safety, the heat index serves as a key metric for protecting workers from heat-related illnesses, particularly in high-risk sectors like construction and agriculture. The Occupational Safety and Health Administration (OSHA) uses the heat index in tools like the OSHA-NIOSH Heat Safety Tool to assess risks and recommend measures such as rest breaks, hydration, and acclimatization for heat index values of 80°F or higher.[10][11] A proposed heat standard, as of November 2025, would establish initial triggers at 80°F and high-heat triggers at 90°F heat index with escalating protections.[12] Urban planners incorporate metrics like the heat index to assess urban heat island effects and support mitigation strategies, such as increasing green spaces and using cool roofing materials to alleviate heat stress in cities.[13][14] Globally, the heat index concept extends beyond the United States, with adaptations like Australia's apparent temperature, developed by the Bureau of Meteorology, which similarly combines air temperature and humidity to gauge thermal comfort and issue heat health alerts.[15] As climate change drives more frequent and intense heat events—evidenced by rising numbers of high heat index days since 1979—the index's importance grows for vulnerable populations worldwide, underscoring its role in proactive risk management. As of 2025, with ongoing climate change, organizations like the World Meteorological Organization have emphasized heat index-like metrics in global heat action plans.[16][17]History and Development
Origins
The concept of the heat index traces its roots to earlier efforts in the mid-20th century to quantify thermal discomfort, particularly through the Temperature-Humidity Index (THI), which emerged from agricultural research in the 1950s. Originally developed by biometeorologist E. C. Thom in 1959 as a measure of human comfort combining air temperature and humidity, the THI was soon adapted for livestock management to assess heat stress in dairy cattle and other animals, reflecting its initial focus on practical applications in humid farming regions.[18] The modern heat index was formally introduced in 1979 by Robert G. Steadman, a researcher at Colorado State University, in his seminal paper published in the Journal of Applied Meteorology. Steadman's work built on physiological models of human heat regulation, incorporating factors such as clothing insulation and body mass to create a more nuanced index of "sultriness"—the perceived discomfort from combined high temperatures and humidity—aimed at improving public awareness of humid heat risks in regions like the U.S. Midwest and Southeast, where such conditions frequently affect daily life and outdoor activities.[8][19] That same year, the National Oceanic and Atmospheric Administration (NOAA) adopted Steadman's framework for operational use by the National Weather Service (NWS), marking the heat index's early integration into public weather forecasting to better communicate the combined effects of heat and humidity beyond simple temperature readings. This adoption emphasized its role in enhancing safety advisories for vulnerable populations in humid climates.[5]Evolution and Standardization
Following the initial development and adoption of the heat index in 1979, the National Oceanic and Atmospheric Administration (NOAA) and the National Weather Service (NWS) refined it during the 1980s and 1990s to enhance its practical application in weather forecasting. By 1990, NWS meteorologist Lans P. Rothfusz formalized the core equation in a technical attachment (SR 90-23), standardizing its calculation for operational use and enabling consistent issuance of heat advisories based on projected values.[20] Refinements included explicit adjustments for environmental exposure, such as adding up to 15°F to shaded heat index values when in direct sunlight, to reflect real-world conditions more precisely. This period also saw the index's full integration into NWS routine forecasts, where it became a key component for alerting the public to heat stress risks during summer months. Further updates in the 2000s, including adjustments for extreme temperature and humidity conditions, improved the formula's accuracy. In the 2000s and 2010s, the heat index evolved further through its incorporation into broader climate assessment tools and digital platforms. Climate models began routinely projecting future heat index trends, revealing substantial increases in extreme values under various emissions scenarios; for instance, a 2019 study using Coupled Model Intercomparison Project Phase 5 (CMIP5) data forecasted four- to twenty-fold rises in population exposure to heat index days exceeding 37.8°C (100°F) by mid-century in the United States.[21] Post-2010, the proliferation of smartphones led to widespread integration of heat index calculators in mobile weather applications, such as those from The Weather Company, allowing real-time user access to localized "feels-like" temperatures and safety alerts. These updates were particularly highlighted in responses to major events, including the 2021 Pacific Northwest heat dome, where heat index values surpassed 110°F amid record-breaking temperatures, prompting enhanced NWS forecasting tools like experimental HeatRisk maps to better communicate multi-day heat impacts. Internationally, the heat index has influenced thermal stress metrics, though adaptations vary by region. In Europe, it informed the development of the Universal Thermal Climate Index (UTCI) in the early 2000s, a more comprehensive biometeorological index that builds on similar principles but incorporates wind and solar radiation for broader applicability in heat-health risk assessments across the continent. Asian meteorological services have adopted heat index-like measures for heatwave monitoring, with applications in South and Southeast Asia to evaluate humid heat exposure in densely populated areas, as seen in analyses of events like the 2023 April heatwave over India and Bangladesh. The World Health Organization (WHO) has referenced heat index principles in its heat-health guidance since updates in the late 2010s, emphasizing its role in defining thresholds for public health interventions in vulnerable regions. In 2025, the NWS implemented enhancements to heat communication products as part of its Hazard Simplification Project, renaming Excessive Heat Watches and Warnings to Extreme Heat Watches and Warnings to simplify messaging and improve public understanding of hazardous heat conditions.[22]Calculation Methods
Core Formula
The core formula for computing the heat index (HI) is a multiple regression equation developed by the National Weather Service (NWS) to approximate the apparent temperature felt by humans in shaded conditions with light winds.[20] This equation stems from Robert G. Steadman's 1979 biometeorological model, which integrates human physiology and clothing science to solve heat balance equations for the body, accounting for processes like sweat evaporation, radiation, convection, and conduction.[8] Steadman's work produced tables of "apparent temperatures" under standard conditions (e.g., 1.6 kPa vapor pressure, 180 W/m² metabolic activity, and typical summer clothing), and the NWS formula regresses these values specifically for air temperatures (T) of 80°F or higher.[20][8] The primary equation is: \begin{align*} \text{[HI](/page/HI)} &= -42.379 + 2.04901523\, [T](/page/Temperature) + 10.14333127\, \text{[RH](/page/RH)} \\ &\quad - 0.22475541\, [T](/page/Temperature) \cdot \text{[RH](/page/RH)} - 0.00683783\, [T](/page/Temperature)^2 - 0.05481717\, \text{[RH](/page/RH)}^2 \\ &\quad + 0.00122874\, [T](/page/Temperature)^2 \cdot \text{[RH](/page/RH)} + 0.00085282\, [T](/page/Temperature) \cdot \text{[RH](/page/RH)}^2 \\ &\quad - 0.00000199\, [T](/page/Temperature)^2 \cdot \text{[RH](/page/RH)}^2 \end{align*} where T is the dry-bulb air temperature in degrees Fahrenheit and RH is the relative humidity as an integer percentage (without the % sign).[20] The multiple regression analysis yielded a standard error of the estimate of approximately ±0.7°F within the fitted range of 80–112°F and 40% ≤ RH ≤ 85%, but the overall estimated error of the equation is ±1.3°F.[20] For relative humidity outside the 40–85% range when the temperature is between 80°F and 112°F, adjustments are applied to the HI value from the primary equation:- If RH < 13%: HI = HI − [3.398 + 1.486 × T − 12.78] + (RH / 100) × [17.27 × T − 289.6]
- If RH > 85%: HI = HI + [(RH / 100) × (6.387 × T − 117.4) − (0.0175 × T + 1.187) × ((RH / 100) × 6.387 × T − 117.4 − 42.379) + 8.665 × 10^{-4} × T × ((RH / 100) × 6.387 × T − 117.4 − 42.379)^2 − 2.073 × 10^{-6} × T^2 × ((RH / 100) × 6.387 × T − 117.4 − 42.379)^2], but simplified approximations are often used, such as adding up to 4–6°F for high RH.[3]
- Constant: -42.379
- $2.04901523 \times 90 = 184.411
- $10.14333127 \times 65 = 659.317
- -0.22475541 \times 90 \times 65 = -1{,}314.819
- -0.00683783 \times 90^2 = -55.386
- -0.05481717 \times 65^2 = -231.603
- $0.00122874 \times 90^2 \times 65 = 646.932
- $0.00085282 \times 90 \times 65^2 = 324.285
- -0.00000199 \times 90^2 \times 65^2 = -68.103
Meteorological Factors
The heat index calculation assumes shaded conditions with light winds (typically less than 6 mph) and no direct solar radiation, providing a baseline for perceived temperature in calm environments. Exposure to direct sunlight increases the effective heat index by approximately 15°F (8°C) due to additional radiant heat load on the body. In contrast, shaded areas maintain the standard heat index value, reducing the risk of overestimation in forested or urban shaded settings. Cloud cover similarly mitigates solar exposure, effectively lowering the heat index by limiting incoming radiation, though its impact varies with coverage density and is often approximated through shade adjustments. Wind speed plays a key role in modifying the heat index through enhanced convective cooling and evaporation from the skin; higher wind speeds can reduce the perceived heat, particularly in humid conditions by promoting sweat evaporation, though this effect diminishes in very dry air where wind may exacerbate dehydration, and the heat index does not directly incorporate wind effects.[5][24][25] Beyond air temperature and relative humidity, the heat index integrates closely with other moisture metrics for accuracy. Dew point temperature serves as an alternative input to relative humidity, offering a more stable measure of absolute moisture content that directly influences evaporation rates and thus the heat index value. Wet-bulb temperature, which combines temperature and humidity effects on a wetted thermometer, relates indirectly as it informs humidity calculations but is primarily used in complementary indices like the wet-bulb globe temperature for solar-inclusive assessments. Urban heat islands amplify the heat index in densely built environments by elevating local air temperatures 1.8–5.4°F (1–3°C) above rural surroundings, intensifying humidity-trapped heat through reduced vegetation and increased impervious surfaces.[26][27] Standard measurements for heat index inputs rely on psychrometers at weather stations, which use dry-bulb thermometers for air temperature and wet-bulb thermometers for humidity via evaporative cooling to compute relative humidity. Automated sensors, including capacitive hygrometers and thermistors, have largely replaced manual psychrometers in modern networks like the NOAA Cooperative Observer Program for precise, continuous data collection. In the 2020s, advancements in satellite-derived humidity data from instruments like the Advanced Baseline Imager on GOES-16/17 satellites enable high-resolution retrievals of atmospheric water vapor profiles, improving heat index estimates over remote or data-sparse regions by integrating near-real-time moisture observations with ground validations.[28][29]Reference Values
Numerical Table
The numerical table below presents heat index values derived from official National Oceanic and Atmospheric Administration (NOAA) charts, interpolated linearly for air temperatures in 5°F increments from 80°F to 130°F and relative humidity levels from 40% to 100% in 10% increments. These values represent the apparent temperature felt by the human body in shaded conditions, accounting for reduced evaporation due to humidity.[30] To use the table for forecasting or real-time assessment, identify the current or predicted air temperature along the rows and the relative humidity along the columns; the value at their intersection is the heat index. This facilitates rapid evaluation of potential heat stress without performing complex calculations. Note that the table is in Fahrenheit, as standardized by U.S. meteorological services; for Celsius equivalents, convert by subtracting 32 and multiplying by 5/9. Direct sunlight may increase the effective heat index by up to 15°F, and the values assume calm winds.[30]| Air Temperature (°F) | 40% RH | 50% RH | 60% RH | 70% RH | 80% RH | 90% RH | 100% RH |
|---|---|---|---|---|---|---|---|
| 80 | 81 | 83 | 85 | 88 | 91 | 94 | 97 |
| 85 | 89 | 92 | 96 | 100 | 104 | 109 | 113 |
| 90 | 96 | 101 | 106 | 112 | 119 | 126 | 134 |
| 95 | 101 | 109 | 116 | 125 | 134 | 143 | 153 |
| 100 | 105 | 115 | 125 | 135 | 149 | 161 | 174 |
| 105 | 109 | 122 | 135 | 147 | 163 | 179 | 191 |
| 110 | 113 | 128 | 142 | 156 | 173 | 189 | 203 |
| 115 | 117 | 134 | 150 | 165 | 183 | 200 | 217 |
| 120 | 121 | 139 | 157 | 173 | 193 | 210 | 229 |
| 125 | 125 | 144 | 165 | 181 | 203 | 220 | 242 |
| 130 | 128 | 149 | 172 | 188 | 213 | 230 | 254 |