The Universal Thermal Climate Index (UTCI) is a comprehensive metric designed to quantify the combined effects of temperature, humidity, wind speed, and solar radiation on human thermal comfort.

The UTCI represents a significant advancement in the field of biometeorology, aiming to provide a holistic understanding of thermal comfort by considering multiple environmental variables simultaneously. Recognizing that human perception of temperature is influenced by various factors beyond just air temperature, the UTCI incorporates additional parameters such as humidity, wind speed, and solar radiation. This multidimensional approach is crucial for accurately assessing thermal stress and its impacts on human health and well-being. Indeed, it stands as an enhancement over existing indices like the heat index and wind chill. Actually, these traditional indices often fail to capture the complex interplay of environmental factors affecting human perception of temperature.

The development of the UTCI began around 2000 when the International Society of Biometeorology (ISB) established a Commission on UTCI. This was followed by the launch of a COST Action. The aim was to create a comprehensive metric that could accurately quantify the combined effects of different weather factors on human thermal comfort. The UTCI-Fiala model, which forms the basis of the UTCI, was then published in 2012. This marked a significant advancement in the field of biometeorology, providing a more holistic understanding of thermal comfort by considering multiple environmental variables simultaneously.

The Universal Thermal Climate Index (UTCI) is based on the Fiala model, a multi-node thermos-physiological model that simulates heat transfer and temperature regulation in the human body. After extensive validation against human thermos-physiological experimental observations, the Fiala model was selected to form the basis of the UTCI.

Similarly to the Physiologically Equivalent Temperature (PET) model, which estimates the heat exchange between the human body and the surrounding environment, the UTCI (°C) is an equivalent temperature defined as the air temperature of a reference environment with 50% relative humidity (RH, %) (but vapor pressure (VP, hPa) not exceeding 20 hPa), with still air and mean radiant temperature (Tmrt, °C) equaling air temperature, which produces the same dynamic physiological response with the actual environment.

On the other hand, PET (°C) represents the air temperature at which the human body would exchange the same amount of heat under standard conditions, considering factors like clothing insulation and metabolic rate. PET is based on the Munich Energy-balance Model for Individuals (MEMI) and is defined as the air temperature at which, in a reference environment (Tmrt = Tair, WS = 0.1 m·s−1, VP set to 12 hPa), the heat balance of the human body (metabolic rate of 80 W, i.e., light activity; heat resistance of clothing 0.9 clo) is maintained with skin and core temperatures equal to those under the environmental conditions being assessed.

The UTCI, based on an advanced multi-node thermoregulatory model (Fiala model), incorporates factors like clothing insulation and metabolic rate (as the PET) with multiple environmental variables and conditions, thus providing a universal index appropriate for thermal assessments in all climates, seasons, and scales. With respect to the PET, UTCI is independent of individual characteristics such as age or gender.

Unlike traditional indices, which focus primarily on the air temperature or wind speed alone, the UTCI offers a more comprehensive evaluation of thermal comfort. This is particularly important in assessing outdoor conditions where individuals are exposed to multiple environmental stressors simultaneously. Whether it’s extreme heat in urban areas or cold and windy conditions in polar regions, the UTCI offers a unified framework for evaluating thermal stress and guiding adaptive strategies to mitigate its adverse effects.

In addition to its utility in assessing current thermal conditions, the UTCI also serves as a valuable tool for climate change research and urban planning. By projecting future climate scenarios and analyzing their potential impacts on human health and comfort, policymakers and urban designers can make informed decisions to enhance resilience and mitigate the effects of extreme weather events. Furthermore, the UTCI can inform the design of outdoor spaces, buildings, and infrastructure to optimize thermal comfort and promote sustainable urban environments.

Overall, the Universal Thermal Climate Index represents a significant advancement in our ability to understand and mitigate the impacts of thermal stress on human populations. Its multidimensional approach and global applicability make it a valuable tool for researchers, policymakers, and urban planners striving to create healthier and more resilient communities in the face of changing climates.

 

UTCI AND THERMAL STRESS

 

The Universal Thermal Climate Index (UTCI) plays a pivotal role in assessing human thermal comfort and thermal stress. When UTCI values are high, they can trigger heat stress and discomfort. On the other hand, low UTCI values can evoke a feeling of coolness, particularly in shaded areas or during the night. Extremely low UTCI values, however, can result in cold stress.

The UTCI is commonly represented on a scale with index values in degrees Celsius and corresponding thermal stress levels, as shown in the table below:

 

UTCI Equivalent Temperature (°C)	Thermal Stress Level
> +46	Extreme heat stress
+38 to +46	Very strong heat stress
+32 to +38	Strong heat stress
+26 to +32	Moderate heat stress
+9 to +26	No thermal stress
0 to +9	Slight cold stress
-13 to 0	Moderate cold stress
-27 to -13	Strong cold stress
-40 to -27	Very strong cold stress
< -40	Extreme cold stress

Demographic factors such as age, health status, and fitness level can significantly affect an individual’s susceptibility to thermal stress. For example, older adults and individuals with chronic health conditions may be more vulnerable to heat stress due to physiological changes associated with aging and disease. Similarly, individuals with lower fitness levels may have a reduced capacity to dissipate heat, increasing their risk of heat-related illnesses. Therefore, these demographic factors interact with UTCI values in determining thermal comfort and stress, highlighting the importance of risk assessments and interventions.

The importance of UTCI becomes evident in its ability to aid in comprehending and alleviating outdoor thermal stress, thereby improving human comfort and health across diverse climatic conditions. Monitoring UTCI is vital not only in designing outdoor spaces that foster comfort and well-being but also in preventing heat-related illnesses.

Research has established a link between UTCI and heat-related health hazards. Furthermore, a correlation between UTCI and heat-related mortality has been observed.

• Heat-related Health Risk: An analysis of mortality data from 17 European countries revealed a complex relationship between UTCI and death counts, which depends on each country’s bio-climate. The study showed that mortality rates tend to rise under conditions of moderate to severe thermal stress, marked by UTCI values exceeding 26 and 32 °C. The UTCI’s effectiveness in tracking mortality trends is highlighted by its correlation with the 2003 European heatwave.
• UTCI and mortality: A study found that during the summer months, a consistent correlation exists between an increase in UTCI and a rise in daily mortality rates, hospital admissions, and road accidents. However, the immediate effects of UTCI changes are not uniform, and they vary significantly for each 4.6°C increase in UTCI. Interestingly, the study also revealed that the impact of UTCI on mortality rates is more distinct among hospital patients compared to the total number of hospital admissions. This suggests that the UTCI has a stronger influence on the health outcomes of those already hospitalized.

Understanding and managing thermal stress is a multifaceted challenge that requires considering physiological, demographic, environmental, and climatic factors. As our climate continues to change, these considerations will become increasingly important in ensuring the health and well-being of populations worldwide.

 

MEASURE OF OUTDOOR UTCI

 

The UTCI is a bioclimatic index that describes the physiological comfort of the human body under specific meteorological conditions. It takes into account not just the ambient temperature but also other variables like humidity, wind, and radiation. These factors significantly affect our physiological reaction to the surrounding environment.

The UTCI provides an estimation of the “apparent” temperature that our body would feel under a given environmental condition specified by the air temperature, wind, humidity, and radiation. This apparent temperature is, in reality, the temperature that a reference environment, defined by fixed values of humidity, wind, and radiation, should have in order to produce in our body the same physiological reaction as the one produced by the initial given environment.

To calculate the UTCI, 4 environmental variables are required:

• 2m Air Temperature: This is the temperature of the air at 2 meters above the ground. It is measured using a standard thermometer placed at the specified height.
• 2m Dew Point Temperature or Relative Humidity: The dew point temperature is the temperature at which the air becomes saturated with water vapor. When the air temperature cools to the dew point, dew can form as the air can no longer hold all of its water vapor. It is measured using a hygrometer. Alternatively, relative humidity, which is the amount of moisture in the air compared to the maximum amount the air can hold at that temperature, can be used.
• Wind Speed at 10m Above Ground Level: An anemometer is used to measure the speed of the wind 10 meters above the ground.
• Mean Radiant Temperature (MRT): MRT is the average temperature of the objects surrounding a point, weighted by the amount of radiation exchanged between that point and those objects. It can be measured using a globe thermometer, which is a thermometer placed inside a hollow copper sphere painted black to absorb all radiant heat.

The process of converting these environmental measures to UTCI values is accessible thanks to publicly available calculation algorithms and scripts. These algorithms take the input from the sensors and compute the UTCI values based on a model of human thermoregulation.

The UTCI calculation is based on the UTCI-Fiala model, which combines a dynamic thermoregulation model of the human body together with a temperature-varying clothing insulation model. This model describes distinct states depending on different ambient factors.

The Fiala approach for calculating the UTCI involves the use of a 6th-order polynomial equation, which is a mathematical representation of the relationship between the required environmental variables and the UTCI.

In the Fiala approach context, the equation coefficients are determined based on empirical data and the specifics of the human thermoregulation model used. The environmental variables measured by the sensors (air temperature, dew point temperature or relative humidity, wind speed, and mean radiant temperature) are input into this equation, and the output is the calculated UTCI value.

The UTCI website (https://www.utci.org/) offers an online calculation tool with access to the FORTRAN code for computing the UTCI using the regression polynomial. Also, the 6th-order polynomial equation is available as a Python script as implemented within the Ladybug/Comfort tools.

TOOLS TO SIMULATE UTCI

 

The Universal Thermal Climate Index is a comprehensive index that assesses the thermos-physiological effects of the atmospheric environment. It considers all significant heat exchange mechanisms. Currently, some software/tools capable of simulating UTCI are:

• UMEP for QGIS: Urban Multi-scale Environmental Predictor (UMEP) is an extensive plugin designed for urban climate and climate-sensitive planning applications. It is integrated with QGIS, a popular open-source Geographic Information System (GIS) software. UMEP includes a pre-processor, a processor, and a post-processor and allows for the creation of workflows for various analyses, such as solar radiation modeling, MRT, and UTCI.
• Ladybug for Grasshopper: Ladybug is a plugin for Grasshopper, a graphical algorithm editor integrated with Rhino’s 3-D modeling tools. It allows visualizing and analyzing weather data, supporting decision-making during the early stages of design. Ladybug also supports the evaluation of initial design options through solar radiation studies, view analyses, sunlight-hours modeling, and UTCI, among others. Ladybug imports standard EnergyPlus Weather files (.EPW) into Grasshopper. It provides a variety of 2D and 3D interactive climate graphics.
• RayMan software: RayMan stands for “radiation on the human body,” and it includes thermal indices such as PET, SET*, PT, UTCI, and mPET. The software can calculate these indices using various meteorological and geometrical data. It’s worth noting that RayMan is often used in applied meteorology and climatology, landscape and ecological planning, urban meteorology and climatology, health, recreation and tourism, education and teaching, academic research, and governmental and administrative use.
• Thermofeel: Python library that can calculate UTCI. It requires 2m temperature and mean radiant temperature in Kelvin, relative humidity (calculated using 2m dew point temperature in Kelvin), and 10-meter height wind speed in m/s. It returns the universal thermal climate index in Celsius.
• Copernicus UTCI Explorer: UTCI Explorer by Copernicus is another tool that can be used to explore UTCI. It allows worldwide daily and monthly UTCI (and MRT) gridded maps download with spatial resolution of 0.25° x 0.25° from 1940 to 2023.

The Universal Thermal Climate Index is a key indicator of heat stress. It stands as a strategic tool that can guide decision-making in a variety of fields to promote human comfort, health, and well-being in the face of rising temperatures due to climate change. Its universal nature makes it applicable in diverse geographical and climatic contexts, contributing to its broad utility and relevance. UTCI has a wide range of applications in various fields, including urban planning, urban design, environmental studies, policy design, and health response to heat stress.

• Urban Planning and Urban Design: In the realm of urban planning and urban design, the UTCI can be used to assess the thermal comfort of outdoor spaces. This can guide the design of public spaces, such as parks, urban canyons, and squares, to ensure they provide a comfortable environment for people throughout the year. For instance, the placement of trees and buildings can be optimized to provide shade and reduce heat stress during the summer months.

• Environmental Studies: In environmental studies, the UTCI can be used to monitor and predict the impact of climate change on human thermal comfort. By integrating UTCI into climate models, researchers can forecast future thermal conditions and identify areas that will be most affected by increasing temperatures. This can inform mitigation and adaptation strategies, such as the development of urban green spaces to reduce the urban heat island effect.

• Policy Design: In policy design, the UTCI can inform the development of heat-health warning systems and urban heat management plans. Policies can be designed to trigger specific actions when UTCI thresholds are exceeded, such as the activation of cooling centers and the distribution of water to vulnerable populations. Moreover, urban heat management plans can incorporate UTCI to prioritize interventions in areas with the highest heat stress.

• Health Response to Heat Stress: In the context of health response to heat stress, the UTCI can be used to identify populations at risk during heat waves and to guide public health interventions. For example, it can help determine when to issue heat warnings, where to open cooling centers, and how to target resources to protect the most vulnerable, such as the elderly, children, and those with chronic illnesses.

• Sustainable Urban Mobility Planning: UTCI can be integrated into sustainable mobility planning to create a more sustainable and comfortable urban environment. By considering thermal comfort in mobility planning, cities can encourage active mobility, reduce reliance on motorized transportation, and contribute to environmental sustainability.

RELATED LINKS AND ADDITIONAL RESOURCES

• Universal Thermal Climate Index (UTCI): The official website of the Universal Thermal Climate Index (UTCI) provides information about the index, its applications, and resources.
• What is UTCI?: An introduction to the Universal Thermal Climate Index (UTCI) by the Copernicus Climate Change Service (C3S) and its significance in evaluating thermal comfort and stress.
• Progress Report on UTCI: Report by the International Society of Biometeorology (ISB) discussing the Universal Thermal Climate Index, its calculation methods, and applications in biometeorological research.
• International Society of Biometeorology (ISB): The International Society of Biometeorology (ISB) is an organization dedicated to promoting the interdisciplinary field of biometeorology.
• UTCI ISB Cost Action: Information about the COST Action project related to the Universal Thermal Climate Index (UTCI), promoted by the ISB, which focuses on enhancing understanding and applications of UTCI.
• UTCI ISB Cost Action Documents: Resources related to the Universal Thermal Climate Index (UTCI), including documents and publications available for download.
• Biometeorology at the University of Wisconsin-Milwaukee: Information about the biometeorology program at the University of Wisconsin-Milwaukee, focusing on research and education in the field.
• UTCI-Fiala Model: The UTCI-Fiala model underpins the UTC index, predicting human responses to outdoor conditions. This paper outlines its algorithms, including internal heat transfer and environmental exchange, validated against real data.
• Validation of UTCI-Fiala Model: This study provides a rigorous evaluation and validation of the UTCI with respect to various physiological models. It concludes that the UTCI-Fiala model most accurately predicted human thermal responses across a wide range of environmental conditions. Validation experiments demonstrated the model’s capability to adequately predict human physiological responses, with mean deviations of 1.35 ± 1.00°C for mean skin temperature and 0.32 ± 0.20°C for core temperature.
• UTCI-10 years of Applications: Since its inception in 1999, the UTCI has aimed to provide a universal indicator for bioclimatic and biometeorological applications. Over a decade, international collaboration, including Action 730 of the COST program, ensured the UTCI accurately represents human body heat exchange across climates.
• Comparison of UTCI to selected thermal indices: This paper compares the UTCI with other thermal indices. It points out that UTCI excels in representing diverse climates and is highly sensitive to changes in temperature, solar radiation, wind, and humidity, capturing temporal variations and subtle meteorological differences effectively.
• Thermal sensation and climate: This study examines how climate affects thermal adaptation by correlating climate normal annual air temperature with calibrated thermal indices’ scales. Results indicate that UTCI and PET thresholds increase with the city’s normal annual air temperature.
• Heat-related Health Risk: The Universal Thermal Climate Index (UTCI) effectively indicates heat-related health risks in Europe. It shows increased heat stress and correlates with higher mortality rates when exceeding certain thresholds. Its relevance was confirmed during the 2003 European heatwave.
• UTCI and mortality: This paper analyzes the seasonal and spatial relationship between UTCI and mortality, morbidity, and road accidents. Results show that higher UTCI is associated with immediate rises in morbidity and mortality in summer and lagged decreases in other seasons.
• Thermal Stress and Cardiovascular Mortality: This study evaluates the relationship between thermal conditions, using UTCI, and cardiovascular mortality. The findings suggest that cardiovascular mortality risks were significantly increased under heat and cold stress, and the adverse effects of cold stress were stronger than heat stress.
• UTCI in High-Resolution Urban Climate Modeling: Understanding the interplay of physical, social, and environmental factors in urban areas is crucial for assessing human thermal comfort. Modeling thermal comfort in outdoor urban settings presents a significant challenge for urban climate research.
• Applications of UTCI in Biometeorology: This book is an essential guide to the UTCI, the leading tool for assessing outdoor thermal comfort. It is of interest to urban planners, architects, engineers, and anyone interested in human well-being in cities.
• UTCI and Urban Environment: ENVI-met simulation of thermal comfort and UTCI, along with eight urban indicators. Findings show positive correlations between thermal comfort and impervious surface, green area ratio, and sky openness, while negative correlations were found with building density, floor area ratio, and shadow hours.
• PET: This paper discusses the importance of weather information in daily life and the need for data applicable to thermal comfort and clothing choices. It introduces the PET, based on the MEMI model, which accurately models human thermal conditions.
• PET Index Revised Model: Information about the revised model of the Physiological Equivalent Temperature (PET) index for enhanced assessment of thermal comfort.
• A Modified PET: This paper introduces mPET, a new thermal index overcoming PET’s limitations by better handling humidity and clothing variability. Comparison with MEMI suggests that mPET provides more realistic temperatures during cold stress.

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*Images from

https://www.semanticscholar.org/paper/The-Universal-Thermal-Climate-Index-UTCI-in-use-Broede-Jendritzky/94d40243579884e480dd2b55c7410185df9e8bd0