The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from measured and observed meteorological data

Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing

The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effect of air temperature, humidity, wind, radiation, and clothes. It is increasingly used in many countries as a measure of thermal comfort for outdoor conditions, and its value is calculated as part of the operational meteorological forecast. At the same time, forecasts of outdoor UTCI tend to have a relatively large error caused by the error of meteorological forecasts. In Slovenia, there is a relatively dense network of meteorological stations. Crucially, at these stations, global solar radiation measurements are performed continuously, which makes estimating the actual value of the UTCI more accurate compared to the situation where no radiation measurements are available. We used seven years of measurements in hourly resolution from 42 stations to first verify the operational UTCI forecast for the first forecast day and, secondly, to try to improve the forecast via post-processing. We used two machine-learning methods, linear regression, and neural networks. Both methods have successfully reduced the error in the operational UTCI forecasts. Both methods reduced the daily mean error from about 2.6∘ C to almost zero, while the daily mean absolute error decreased from 5∘ C to 3∘ C for the neural network and 3.5∘ C for linear regression. Both methods, especially the neural network, also substantially reduced the dependence of the error on the time of the day.

High-resolution projections of outdoor thermal stress in the twenty-first century: a Tasmanian case study

To adapt to Earth's rapidly changing climate, detailed modelling of thermal stress is needed. Dangerous stress levels are becoming more frequent, longer, and more severe. While traditional measurements of thermal stress have focused on air temperature and humidity, modern measures including radiation and wind speed are becoming widespread. However, projecting such indices has presented a challenging problem, due to the need for appropriate bias correction of multiple variables that vary on hourly timescales. In this paper, we aim to provide a detailed understanding of changing thermal stress patterns incorporating modern measurements, bias correction techniques, and hourly projections to assess the impact of climate change on thermal stress at human scales. To achieve these aims, we conduct a case study of projected thermal stress in central Hobart, Australia for 2040-2059, compared to the historical period 1990-2005. We present the first hourly metre-scale projections of thermal stress driven by multivariate bias-corrected data. We bias correct four variables from six dynamically downscaled General Circulation Models. These outputs drive the Solar and LongWave Environmental Irradiance Geometry model at metre scale, calculating mean radiant temperature and the Universal Thermal Climate Index. We demonstrate that multivariate bias correction can correct means on multiple time scales while accurately preserving mean seasonal trends. Changes in mean air temperature and UTCI by hour of the day and month of the year reveal diurnal and annual patterns in both temporal trends and model agreement. We present plots of future median stress values in the context of historical percentiles, revealing trends and patterns not evident in mean data. Our modelling illustrates a future Hobart that experiences higher and more consistent numbers of hours of heat stress arriving earlier in the year and extending further throughout the day.

Thermal stress information as a tourism-oriented climate product: Performance analysis for selected urban destinations in Romania and Italy

The study addresses the characteristics of a climate service targeting tourists and discusses the evaluation of its products with a particular focus on the thermal stress information. Furthermore, an assessment of the impact of input data on the accuracy and relevance of the thermal stress product is presented. The thermal stress is expressed through UTCI (Universal Thermal Climate Index) and it is computed from UERRA regional reanalysis and E-OBS gridded dataset, for summer season during 2011-2018. The analysis targets 10 cities with different characteristics located in Romania and Italy. It focuses on the impact of three temperature-related input data (instantaneous temperature at 12:00 UTC, daily maximum and daily mean temperature) on the thermal stress intensity. The results show that differences up to 4 days in the pronounced thermal stress category may appear when employing daily maximum temperature compared to the use 12:00 UTC instantaneous temperature, while the use of daily mean temperature leads to strong underestimation of thermal stress in this category. The findings are of interest in defining the technical choices of products to be incorporated in a climate service for tourism in order to assure a good user uptake.

Association between thermal stress and cardiovascular mortality in the subtropics

Hazardous thermal conditions resulting from climate change may play a role in cardiovascular disease development. We chose the Universal Thermal Climate Index (UTCI) as the exposure metric to evaluate the relationship between thermal conditions and cardiovascular mortality in Shenzhen, China. We applied quasi-Poisson regression non-linear distributed lag models to evaluate the exposure-response associations. 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. Referencing the 50th percentile of UTCI (25.4°C), the cumulative risk of cardiovascular mortality was 75% (RRlag0-21 =1.75, 95%CI: 1.32, 2.32) higher in the 1st percentile (3.5°C), and 40% (RRlag0-21=1.40, 95%CI: 1.09, 1.80) higher in the 99th percentile (34.1°C). We observed that individuals older than 65 years were more vulnerable to both cold and heat stress, and females were identified as more susceptible to heat stress than males. Moreover, increased mortality risks of hypertensive disease and cerebrovascular disease were observed under cold stress, while heat stress was related to higher risks of mortality for hypertensive disease and ischemic heart disease. We also observed a stronger relationship between cold stress and ischemic heart disease mortality during the cold season, as well as a significant impact of heat stress on cerebrovascular disease mortality in the warm season when compared to the analysis of the entire year. These results confirm the significant relationship between thermal stress and cardiovascular mortality, with age and sex as potential effect modifiers of this association. Providing affordable air conditioning equipment, increasing the amount of vegetation, and establishing comprehensive early warning systems that take human thermoregulation into account could all help to safeguard the well-being of the public, particularly vulnerable populations, in the event of future extreme weather.

Thermal responses of face-masked pedestrians during summer: An outdoor investigation under tree-shaded areas

During the SARS-CoV-2 (COVID-19) pandemic, most citizens were cooperative towards the face-masking policy; however, undeniably, face masking has increased complaints of thermal discomfort to varying degrees and resulted in potential health hazards during summer. Thus, a thermal comfort survey was conducted under tree-shaded areas generally preferred by pedestrians to explore the thermal response of face-masked pedestrians. Thirty-two subjects, with and without masks, participated in walking experiments, and their thermal parameters and physiological indicators were recorded; moreover, the subjects were asked to fill in subjective questionnaires. The results showed that although tree shades significantly reduced the average radiant temperature, dampness in the mask may cause some discomfort symptoms, among which intense sweating (54.55%) and tachycardia (42.18%) accounted for the largest proportion. Based on thermal indices, it could be concluded that face-masking does not significantly affect the thermal comfort of subjects walking in shaded areas. Notably, a 30-min walk in tree-shaded areas with face masking does not adversely affect human health or quality of life. Thus, the present assessment of the thermal safety of humans in shaded environments provides reference data for determining thermal comfort levels during outdoor walking with face masking.

Assessment of Summer Regional Outdoor Heat Stress and Regional Comfort in the Beijing-Tianjin-Hebei Agglomeration Over the Last 40 Years

Outdoor thermal comfort (OTC) is critical for public health, labor productivity, and human life. Growing extreme heat events caused by climate change have a serious impact on OTCs, especially in urban areas. Quantitatively characterizing and evaluating the spatiotemporal changes in OTCs are essential, and more applications are needed in urban agglomerations. Therefore, taking the Beijing-Tianjin-Hebei (BTH) urban agglomeration as the study area, this study aimed to quantitatively assess the summer regional OTC from 1981 to 2020. First, the Universal Thermal Climate Index (UTCI) was used as the indicator of daily thermal stress, and then a Composite Thermal Comfort Score was proposed to evaluate the long-term, summertime, regional OTC considering the extent, duration, and intensity of daytime and nighttime thermal stress. The results showed that (a) the increase in UTCI (0.32°C/10a at daytime and 0.21°C/10a at nighttime) and heat stress frequency (0.88 at daytime and 0.39 d/10a at nighttime) were manifested over BTH, indicating a worse OTC. Spatial and temporal heterogeneity was also demonstrated. (b) The general OTC showed a decreasing north-south gradient pattern. At daytime, the northern mountainous zone presented the best OTC, the southern plain zone, especially Hengshui, Langfang, and Cangzhou, showed the worst. At nighttime, the mountain-plain transition zone showed the best OTC, the northern mountainous zone showed the worst since more cold stress occurred. Our findings will be useful in informing climate change adaptation strategies to ensure urban resilience as extreme heat increases in the context of climate change.

Optimal Strategy on Radiation Estimation for Calculating Universal Thermal Climate Index in Tourism Cities of China

The Universal Thermal Climate Index (UTCI) is believed to be a very powerful tool for providing information on human thermal perception in the domain of public health, but the solar radiation as an input variable is difficult to access. Thus, this study aimed to explore the optimal strategy on estimation of solar radiation to increase the accuracy in UTCI calculation, and to identify the spatial and temporal variation in UTCI over China. With daily meteorological data collected in 35 tourism cities in China from 1961 to 2020, two sunshine-based Angstrom and Ogelman models, and two temperature-based Bristow and Hargreaves models, together with neural network and support vector machine-learning methods, were tested against radiation measurements. The results indicated that temperature-based models performed the worst with the lowest NSE and highest RMSE. The machine-learning methods performed better in calibration, but the predictive ability decreased significantly in validation due to big data requirements. In contrast, the sunshine-based Angstrom model performed best with high NSE (Nash–Sutcliffe Efficiency) of 0.84 and low RMSE (Root Mean Square Error) of 35.4 J/m² s in validation, which resulted in a small RMSE of about 1.2 °C in UTCI calculation. Thus, Angstrom model was selected as the optimal strategy on radiation estimation for UTCI calculation over China. The spatial distribution of UTCI showed that days under no thermal stress were high in tourism cities in central China within a range from 135 to 225 days, while the largest values occurred in Kunming and Lijiang in southwest China. In addition, days under no thermal stress during a year have decreased in most tourism cities of China, which could be attributed to the asymmetric changes in significant decrease in frost days and slightly increase in hot days. However, days under no thermal stress in summer time have indeed decreased, accompanying with increasing days under strong stress, especially in the developed regions such as Yangze River Delta and Zhujiang River Delta. Based on the study, we conclude that UTCI can successfully depict the overall spatial distribution and temporal change of the thermal environments in the tourism cities over China, and can be recommend as an efficient index in the operational services for assessing and predicting thermal perception for public health. However, extreme cold and heat stress in the tourism cities of China were not revealed by UTCI due to mismatch of the daily UTCI with category at hourly scale, which makes it an urgent task to redefine category at daily scale in the next research work.

Spatial Differences in Outdoor Thermal Comfort during the Transition Season in Cold Regions of China

This study investigates the differences in outdoor thermal comfort in different spatial types over long-term observations during the transition season in a cold region. Using the Universal Thermal Climate Index (UTCI) as an evaluation index, subjective questionnaires and field surveys were conducted on thermal comfort in three different typical outdoor environments (sunlight, tree shade and building shade) in Dalian (Northeast China). The results demonstrated the following: (1) Air temperature and mean radiant temperature were the dominant meteorological factors affecting outdoor thermal comfort in Dalian. (2) The main thermal sensation recorded in the transition season was “slightly cool”. Over time, the human thermal sensation experienced a gradual transition from “hot” to “cold”. (3) Compared with direct sunlight, the average UTCI decreased by 6.6 and 3.5 °C for building shade and tree shade environments, and the neutral UTCI in Dalian was found to be 18.8 °C. Subjects were most sensitive to the thermal environment in building shade, then in tree shade and the least in sunlight. (4) When UTCI ≥ 21.9 °C, the thermal acceptability rate in building shade remained the highest; when 10.2 °C ≤ UTCI < 21.9 °C, it was highest in tree shade; and when the UTCI < 10.2 °C, it was highest in sunlight. This study verifies the UTCI applicability in the transition season in cold regions and analyzes the spatial differences in human thermal comfort. These differences play a positive role in developing optimization strategies for outdoor thermal environments, improving environmental satisfaction and facilitating pedestrian outdoor activities.

Human thermophysiological models: Quantification of uncertainty in the output quantities of the passive system due to uncertainties in the control equations of the active system via the Monte Carlo method

Uncertainty propagation analysis in the Fiala thermophysiological model is performed by the Monte Carlo Method. The uncertainties of the output quantities of the passive system, due to imported uncertainties in the coefficients of the control equations of the active system, caused by the variation of the experimental data, are computed. The developed and implemented in-house code is accordingly validated. The effect of the input uncertainties, in each of the four main responses (shivering, vasodilatation, vasoconstriction, sweating) of the active system, is separately examined by simulating the human exposure from neutral conditions to cold and hot environments. It is predicted that the maximum output uncertainties of the response mechanisms may be of the same order of magnitude as the imported ones, while the corresponding maximum uncertainties in core and skin temperatures always remain less than 2%. The maximum absolute deviations of the rectal (core) temperatures from their estimated mean values may be up to 0.72 °C and 0.22 °C, due to input uncertainties in shivering and sweating respectively, while the corresponding deviations due to uncertainties in vasomotion processes are negligible. The deviations, particularly the ones due to shivering, are significant, since differences of a few tenths of a degree may have large impact in human health. The maximum absolute deviations of the skin temperatures are 0.42 °C in the hands due to uncertainties in shivering and 0.69 °C in the feet due to uncertainties in vasodilatation. These deviations are less significant than the core ones, but they may still affect human thermal sensation and comfort. The present analysis provides a better insight in the dynamic response of the model and indicates which response mechanism needs to be further investigated by more accurate estimates in order to improve model reliability. It can be also applied in other human thermophysiological models.

A high-spatial-resolution dataset of human thermal stress indices over South and East Asia

Thermal stress poses a major public health threat in a warming world, especially to disadvantaged communities. At the population group level, human thermal stress is heavily affected by landscape heterogeneities such as terrain, surface water, and vegetation. High-spatial-resolution thermal-stress indices, containing more detailed spatial information, are greatly needed to characterize the spatial pattern of thermal stress to enable a better understanding of its impacts on public health, tourism, and study and work performance. Here, we present a 0.1° × 0.1° gridded dataset of multiple thermal stress indices derived from the newly available ECMWF ERA5-Land and ERA5 reanalysis products over South and East Asia from 1981 to 2019. This high-spatial-resolution database of human thermal stress indices over South and East Asia (HiTiSEA), which contains the daily mean, maximum, and minimum values of UTCI, MRT, and eight other widely adopted indices, is suitable for both indoor and outdoor applications and allows researchers and practitioners to investigate the spatial and temporal evolution of human thermal stress and its impacts on densely populated regions over South and East Asia at a finer scale.

Quantifying the cooling effect of rain events on outdoor thermal comfort in the southern coastal stations of the Caspian Sea

Pleasant outdoor thermal conditions depend on a wide range of climatic elements. The impact of rainfall events, as important climatic elements, on providing thermal comfort, has been less explored in the available literature. The work presented herein investigates the impact of Rainy Days as well as a Day Prior to (D_prior) and a Day Post rain (D_post) events on thermal conditions in the southern coastal region of the Caspian Sea. In this study, rainfall events during 1961-2017 observational period were categorized based on their intensity. Then, human thermal comfort during non-rainy (sunny) and rainy days was estimated and compared by using the radiation-driven Physiological Equivalent Temperature (PET) index, Universal Thermal Climate Index (UTCI) and Perceived Temperature (PT) index. Furthermore, difference between the average of thermal conditions in rainy days compared to a day prior and a day post rain events was calculated separately for comfort, cold and heat stress thresholds of each bioclimatic index. Finally, the correlation between the average of indices for rainy days and the frequency of rainfall events of each specific year was computed. Results suggested that overall average of studied indices for all rainy days is lower than the average for days prior and post the rain events. PET index has shown to be most impacted and reduced as a result of rain events and therefore more indicative of a cool ing effect. The observed difference in total average of PET in rainy days compared to non-rainy days were 8.30 °C, 5.86 °C and 8.85 °C for Babolsar, Rahst and Gorgan stations, respectively. Generally, the cooling effect of rain events on the temperature for a day prior rain events is higher than a day post rainfall. Finally, the trend analysis on rainy days in the studied period revealed that the average of bioclimatic indices in western stations (Babolsar and Rasht) are increasing whereas a decreasing trend was observed for Gorgan as more of an eastern station.

An Assessment of Tourism Climate Comfort in the China–Pakistan Economic Corridor

Pleasant climates can be divided into two types: the comfortable summer climate and the comfortable winter climate, but existing studies rarely pay attention to the distribution characteristics and differences between the two types of climate. This study investigates the spatial distribution of comfortable summer and winter climates in the China–Pakistan Economic Corridor (CPEC) and their differences based on the European Centre for Medium-Range Weather Forecasts Re-Analysis-Interim (ERA-interim) reanalysis data from 1979 to 2018. The Universal Thermal Climate Index was used to analyze climatic suitability. The findings are as follows. First, the comfortable summer climate regions of the CPEC were mainly distributed in Khyber Pakhtunkhwa in Pakistan and some regions of Xinjiang in China and also sporadically distributed in high altitude mountains, such as the western plateau area. The comfortable winter climate regions were mainly distributed in vast areas except for Karakoram and nearby areas. Second, there are a few regions with dual attributes of comfortable summer and winter climates in CPEC. Third, according to the calculation and comparison of the regional area of different climate comfort levels in summer and winter, it is found that the comfortable summer climate is scarcer in CPEC and is a monopoly resource. The comfortable winter climate is widely distributed, belonging to the ubiquitous resources. These findings can be helpful for the tourism development of local climate resources.

Spatial-Temporal Pattern Changes of UTCI in the China-Pakistan Economic Corridor in Recent 40 Years

This paper investigated the spatial and temporal variations of the Universal Thermal Climate Index (UTCI) of the China-Pakistan Economic Corridor (CPEC) from 1979 to 2018. The European Centre for Medium-Range Weather Forecasts Re-Analysis-Interim (ERA-Interim) reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) is selected for UTCI calculation in the region and analyzed by a linear trend and correlation analysis. The results showed that (1) the UTCI of CPEC is decreased with the increase of latitude and altitude. There is obvious spatial heterogeneity in the seasonal scale and the spatial distribution of different thermal stress categories. (2) UTCI generally exhibited a positive trend of 0.33 °C/10a over the past 40 years, and the seasonal variation characteristics of UTCI show an upward trend in all four seasons, of which spring is the fastest. On the space scale, the growth trend has significant spatial variations. (3) Temperature has a positive correlation with UTCI. The influence of temperature on UTCI is greater than that of wind speed. The results of this study will be helpful for regional planning and also contribute to comprehending the characteristics of the thermal environment in CPEC.

Accuracy of Mean Radiant Temperature Derived from Active and Passive Radiometry

The concept of the mean radiant temperature (Tmrt) allows the study of radiative exchanges between a human and its environment. It presupposes that the radiant effects on the person of the actual environment, which is generally heterogeneous, and the virtual environment, which is defined as homogeneous, are identical. ISO 7726 specifies the required accuracy in Tmrt as input of rational thermal indices, outdoors ±5 (K). Tmrt accounts for the radiant heat absorbed by skin/clothing from the shortwave (SW) and longwave (LW) spectral bands. Most of the radiant components are isotropic. However, there are anisotropic SW components; namely the direct irradiance and under clear or partly obstructed skies a significant circumsolar fraction (fcs) in the diffuse irradiance. Both originate from the close proximity of the solar disk. This study highlights the effect of fcs on Tmrt. In the scope of human biometeorology a standing body posture is standard. For unidirectional irradiances its radiant cross-section varies dependent on the solar altitude. Active radiometry in deriving Tmrt is based on measured irradiances. One method is the Klima-Michel-Modell (KMM) that uses readily available measurements from standard meteorologically radiant observations. KMM references Fanger’s area projection factors that are derived from precise measurements of real humans. Thus, KMM serves as reference in evaluation of further methods. One is the six-directional instrument (Tmrt,r,6−Dir). Slightly simplifying a standing human, it represents a subject as a rectangular solid. Tmrt,r,6−Dir is derived based on measured irradiances incident on the vertical and horizontal planes. In passive radiometry the energy balance equation of a black globe thermometer is solved that leads to Tmrt,Tg,BG. fcs significantly impacts Tmrt with noticeably reduced values for high and increased for low solar altitudes. Hence, accounting for fcs is essential for the accuracy of Tmrt. For KMM an extension to an existing algorithm is provided in order to include fcs into the Tmrt calculation that results in Tmrt,r,KMM. For Tmrt,r,6−Dir the radiant cross-section of the solid depends to a minor extent on its azimuth relative to the solar azimuth. As a result Tmrt,r,6−Dir slightly scatters compared to Tmrt,r,KMM. However, it remains within ±2 (K). Tmrt,Tg,BG compared to Tmrt,r,KMM complies only at night with the ISO 7726 bin of ±5 K. Tmrt,Tg,BG significantly overestimates Tmrt,r,KMM during the daytime, because of its greater SW absorptance compared to skin/clothing and to a smaller extent because the standing posture is represented by a sphere. Particularly in sunny conditions, Tmrt,Tg,BG is subject to considerable variance. Thus, outdoors during the daytime, Tmrt,Tg,BG is unable to serve as an appropriate input for the calculation of rational-based thermal indices.

Is There a Need to Integrate Human Thermal Models with Weather Forecasts to Predict Thermal Stress?

More and more people will experience thermal stress in the future as the global temperature is increasing at an alarming rate and the risk for extreme weather events is growing. The increased exposure to extreme weather events poses a challenge for societies around the world. This literature review investigates the feasibility of making advanced human thermal models in connection with meteorological data publicly available for more versatile practices and a wider population. By providing society and individuals with personalized heat and cold stress warnings, coping advice and educational purposes, the risks of thermal stress can effectively be reduced. One interesting approach is to use weather station data as input for the wet bulb globe temperature heat stress index, human heat balance models, and wind chill index to assess heat and cold stress. This review explores the advantages and challenges of this approach for the ongoing EU project ClimApp where more advanced models may provide society with warnings on an individual basis for different thermal environments such as tropical heat or polar cold. The biggest challenges identified are properly assessing mean radiant temperature, microclimate weather data availability, integration and continuity of different thermal models, and further model validation for vulnerable groups.

Coupling of urban energy balance model with 3-D radiation model to derive human thermal (dis)comfort

While capabilities in urban climate modeling have substantially increased in recent decades, the interdependency of changes in environmental surface properties and human (dis)comfort have only recently received attention. The open-source solar long-wave environmental irradiance geometry (SOLWEIG) model is one of the state-of-the-art models frequently used for urban (micro-)climatic studies. Here, we present updated calculation schemes for SOLWEIG allowing the improved prediction of surface temperatures (wall and ground). We illustrate that parameterizations based on measurements of global radiation on a south-facing vertical plane obtain better results compared to those based on solar elevation. Due to the limited number of ground surface temperature parameterizations in SOLWEIG, we implement the two-layer force-restore method for calculating ground temperature for various soil conditions. To characterize changes in urban canyon air temperature (T_can), we couple the calculation method as used in the Town Energy Balance (TEB) model. Comparison of model results and observations (obtained during field campaigns) indicates a good agreement between modeled and measured T_can, with an explained variance of R² = 0.99. Finally, we implement an energy balance model for vertically mounted PV modules to contrast different urban surface properties. Specifically, we consider (i) an environment comprising dark asphalt and a glass facade and (ii) an environment comprising bright concrete and a PV facade. The model results show a substantially decreased T_can (by up to - 1.65°C) for the latter case, indicating the potential of partially reducing/mitigating urban heat island effects.

The predictability of heat-related mortality in Prague, Czech Republic, during summer 2015-a comparison of selected thermal indices

We compared selected thermal indices in their ability to predict heat-related mortality in Prague, Czech Republic, during the extraordinary summer 2015. Relatively, novel thermal indices-Universal Thermal Climate Index and Excess Heat Factor (EHF)-were compared with more traditional ones (apparent temperature, simplified wet-bulb globe temperature (WBGT), and physiologically equivalent temperature). The relationships between thermal indices and all-cause relative mortality deviations from the baseline (excess mortality) were estimated by generalized additive models for the extended summer season (May-September) during 1994-2014. The resulting models were applied to predict excess mortality in 2015 based on observed meteorology, and the mortality estimates by different indices were compared. Although all predictors showed a clear association between thermal conditions and excess mortality, we found important variability in their performance. The EHF formula performed best in estimating the intensity of heat waves and magnitude of heat-impacts on excess mortality on the most extreme days. Afternoon WBGT, on the other hand, was most precise in the selection of heat-alert days during the extended summer season, mainly due to a relatively small number of "false alerts" compared to other predictors. Since the main purpose of heat warning systems is identification of days with an increased risk of heat-related death rather than prediction of exact magnitude of the excess mortality, WBGT seemed to be a slightly favorable predictor for such a system.

Comparison of health risks by heat wave definition: Applicability of wet-bulb globe temperature for heat wave criteria

Despite the active applications of thermal comfort indices for heat wave definitions, there is lack of evaluation for the impact of extended days of high temperature on health outcomes using many of the indices. This study compared the impact of heat waves on health outcomes among different heat wave definitions based on thermal comfort and air temperature. We compared heat waves in South Korea (cities and provinces) for the warm season for 2011-2014, using air temperature, heat index (HI), and web-bulb globe temperature (WBGT). Heat waves were defined as days with daily maximum values of each index at a specified threshold (literature-based, the 90th and 95th percentiles) or above. Distributed lag non-linear models and meta-analysis were used to estimate risk of mortality and hospitalization for all-causes, cardiovascular causes, respiratory causes and heat disorders during heat wave days compared to non-heat wave days. WBGT identified 1.15 times longer maximum heat wave duration for the study periods than air temperature when the thresholds were based on 90th and 95th percentiles. Over the study period, for heat waves defined by WBGT and HI, the Southwestern region showed the highest total number of heat wave days, whereas for air temperature the longest heat wave days were identified in the southeastern region. The highest and most significant impact of heat waves were found by WBGT for hospitalization from heat disorders (Relative risk = 2.959, 95% CI: 1.566-5.594). In sensitivity analyses using different structure of lags and temperature metrics (e.g., daily mean and minimum), the impacts of heat waves on most health outcomes substantially increased by using WBGT for heat wave definitions. As a result, WBGT and its thresholds can be used to relate heat waves and heat-related diseases to improve the prevention effectiveness of heat wave warnings and give informative health guidelines according to the range of WBGT thresholds.

Assessment of the climatic potential for tourism in Iran through biometeorology clustering

This study presents a spatiotemporal analysis of bioclimatic comfort conditions for Iran using mean daily meteorological data from 1995 to 2014, analyzed through Physiological Equivalent Temperature (PET) index and Universal Thermal Climate Index (UTCI) indices, and bioclimatic clustering. The results of this study demonstrate that due to the climate variability across Iran during the year, there is at any point in time a location with climatic condition suitable for tourism. Mean values demonstrate maxima in bioclimatic comfort indices for the country in late winter and spring and minima for summer. Seven statistically significant clusters in bioclimatic indices were identified. Comparing these with clustering performed on PET and UTCI, the maximum overlaps between the two indices. In the following, the outputs of this research showed that most appropriate bioclimatic clustering for Iran includes seven clusters. These clustering locations according to climatic suitability for tourism provide a valuable contribution to tourism management in the country, particularly through marketing destinations to maximize tourist flow.

Comparison of UTCI with other thermal indices in the assessment of heat and cold effects on cardiovascular mortality in the Czech Republic

We compare the recently developed Universal Thermal Climate Index (UTCI) with other thermal indices in analysing heat- and cold-related effects on cardiovascular (CVD) mortality in two different (urban and rural) regions in the Czech Republic during the 16-year period from 1994–2009. Excess mortality is represented by the number of deaths above expected daily values, the latter being adjusted for long-term changes, annual and weekly cycles, and epidemics of influenza/acute respiratory infections. Air temperature, UTCI, Apparent Temperature (AT) and Physiologically Equivalent Temperature (PET) are applied to identify days with heat and cold stress. We found similar heat effects on CVD mortality for air temperature and the examined thermal indices. Responses of CVD mortality to cold effects as characterised by different indices were much more varied. Particularly important is the finding that air temperature provides a weak cold effect in comparison with the thermal indices in both regions, so its application—still widespread in epidemiological studies—may underestimate the magnitude of cold-related mortality. These findings are important when possible climate change effects on heat- and cold-related mortality are estimated. AT and PET appear to be more universal predictors of heat- and cold- related mortality than UTCI when both urban and rural environments are of concern. UTCI tends to select windy rather than freezing days in winter, though these show little effect on mortality in the urban population. By contrast, significant cold-related mortality in the rural region if UTCI is used shows potential for UTCI to become a useful tool in cold exposure assessments.

Might outdoor heat stress be considered a proxy for the unperceivable effect of the ultraviolet-induced risk of erythema in Florence?

Erythema is the most familiar short-term symptom of human skin associated with overexposure to unperceivable ultraviolet radiation (UV). However, people are able to perceive the warm infrared component of the solar radiation by means of thermal (dis)comfort. This study investigated the potentiality of perceived outdoor heat stress as a valuable proxy for the unperceivable effect of UV-induced risk of erythema in a Mediterranean city. Meteorological data and UVB (280-320nm) measurements were obtained for the 2004-2012 period by a weather station located in the municipality of Florence. Continuous measurements of erythemally effective UV (UVEry) were performed by means of a broadband temperature-corrected radiometer with the spectral response close to the erythemal action spectrum. Hourly UVEry doses were expressed as Standard Erythemal Doses (SEDs). The newly developed Universal Thermal Climate Index (UTCI), that represents the state-of-the-art of outdoor thermal (dis)comfort evaluation, was also assessed. Descriptive analyses of the hourly distribution per month of the frequencies of days with heat stress and UVEry exceeding 2.0, 3.0, 4.5 and 6.0 SEDs were carried out based on the general skin-type characteristics. The association between UVEry and UTCI was analyzed by a two-way contingency table approach. The probability of UVEry exceeding specific SED thresholds when heat stress occurs was often significantly higher than the same probability when no heat stress is perceived. Furthermore, increased magnitudes of the ratios, ranging from the very sensitive to the minimally sensitive skin types, were also found. However, during several months, too many days occur without any signs of heat discomfort, even when people may be exposed to relevant doses of harmful UVEry for the skin of various phototypes. These findings underlie the need for public health authorities to provide differentiated advice per month in relation to potential UV skin damage in the city of Florence.

The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from numerical weather prediction and regional climate model simulations

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to -21°C (9°C) for Tmrt and up to -6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.

The Universal Thermal Climate Index UTCI compared to ergonomics standards for assessing the thermal environment

The growing need for valid assessment procedures of the outdoor thermal environment in the fields of public weather services, public health systems, urban planning, tourism & recreation and climate impact research raised the idea to develop the Universal Thermal Climate Index UTCI based on the most recent scientific progress both in thermo-physiology and in heat exchange theory. Following extensive validation of accessible models of human thermoregulation, the advanced multi-node 'Fiala' model was selected to form the basis of UTCI. This model was coupled with an adaptive clothing model which considers clothing habits by the general urban population and behavioral changes in clothing insulation related to actual environmental temperature. UTCI was developed conceptually as an equivalent temperature. Thus, for any combination of air temperature, wind, radiation, and humidity, UTCI is defined as the air temperature in the reference condition which would elicit the same dynamic response of the physiological model. This review analyses the sensitivity of UTCI to humidity and radiation in the heat and to wind in the cold and compares the results with observational studies and internationally standardized assessment procedures. The capabilities, restrictions and potential future extensions of UTCI are discussed.

UTCI--why another thermal index?

Existing procedures for the assessment of the thermal environment in the fields of public weather services, public health systems, precautionary planning, urban design, tourism and recreation and climate impact research exhibit significant shortcomings. This is most evident for simple (mostly two-parameter) indices, when comparing them to complete heat budget models developed since the 1960s. ISB Commission 6 took up the idea of developing a Universal Thermal Climate Index (UTCI) based on the most advanced multi-node model of thermoregulation representing progress in science within the last three to four decades, both in thermo-physiological and heat exchange theory. Creating the essential research synergies for the development of UTCI required pooling the resources of multidisciplinary experts in the fields of thermal physiology, mathematical modelling, occupational medicine, meteorological data handling (in particular radiation modelling) and application development in a network. It was possible to extend the expertise of ISB Commission 6 substantially by COST (a European programme promoting Cooperation in Science and Technology) Action 730 so that finally over 45 scientists from 23 countries (Australia, Canada, Israel, several Europe countries, New Zealand, and the United States) worked together. The work was performed under the umbrella of the WMO Commission on Climatology (CCl). After extensive evaluations, Fiala's multi-node human physiology and thermal comfort model (FPC) was adopted for this study. The model was validated extensively, applying as yet unused data from other research groups, and extended for the purposes of the project. This model was coupled with a state-of-the-art clothing model taking into consideration behavioural adaptation of clothing insulation by the general urban population in response to actual environmental temperature. UTCI was then derived conceptually as an equivalent temperature (ET). Thus, for any combination of air temperature, wind, radiation, and humidity (stress), UTCI is defined as the isothermal air temperature of the reference condition that would elicit the same dynamic response (strain) of the physiological model. As UTCI is based on contemporary science its use will standardise applications in the major fields of human biometeorology, thus making research results comparable and physiologically relevant.