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

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.

Evaluation of the ERA5 reanalysis-based Universal Thermal Climate Index on mortality data in Europe

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 - the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) - as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

Mean radiant temperature from global-scale numerical weather prediction models

In human biometeorology, the estimation of mean radiant temperature (MRT) is generally considered challenging. This work presents a general framework to compute the MRT at the global scale for a human subject placed in an outdoor environment and irradiated by solar and thermal radiation both directly and diffusely. The proposed framework requires as input radiation fluxes computed by numerical weather prediction (NWP) models and generates as output gridded globe-wide maps of MRT. It also considers changes in the Sun's position affecting radiation components when these are stored by NWP models as an accumulated-over-time quantity. The applicability of the framework was demonstrated using NWP reanalysis radiation data from the European Centre for Medium-Range Weather Forecasts. Mapped distributions of MRT were correspondingly computed at the global scale. Comparison against measurements from radiation monitoring stations showed a good agreement with NWP-based MRT (coefficient of determination greater than 0.88; average bias equal to 0.42 °C) suggesting its potential as a proxy for observations in application studies.

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.

Human cold stress of strong local-wind "Hijikawa-arashi" in Japan, based on the UTCI index and thermo-physiological responses

We investigated the cold stress caused by a strong local wind called "Hijikawa-arashi," through in situ vital measurements and the Universal Thermal Climate Index (UTCI). This wind is a very interesting winter phenomenon, localized in an area within 1 km of the seashore in Ozu City, Ehime Prefecture in Japan. When a strong Hijikawa-arashi (HA) occurred at 14-15 m s^-1, the UTCI decreased to - 30 °C along the bridge where commuting residents are the most exposed to strong and cold winds. On the bridge, most participants in our experiment felt "very cold" or "extremely cold." The UTCI of HA can be predicted from a multiple regression equation using wind speed and air temperature. The cold HA wind is also harmful to human thermo-physiological responses. It leads to higher blood pressure and increased heart rate, both of which act as cardiovascular stress triggers. Increases of 6-10 mmHg and 3-6 bpm for every 10 °C reduction in UTCI were seen on all observational days, including HA and non-HA days. In fact, the participants' body skin temperatures decreased by approximately 1.2 to 1.7 °C for every 10 °C reduction in UTCI. Thus, the UTCI variation due to the HA outbreak corresponded well with the cold sensation and thermo-physiological responses in humans. This result suggests that daily UTCI monitoring enables the prediction of thermo-physiological responses to the HA cold stress.

Occupational heat stress assessment and protective strategies in the context of climate change

Global warming will unquestionably increase the impact of heat on individuals who work in already hot workplaces in hot climate areas. The increasing prevalence of this environmental health risk requires the improvement of assessment methods linked to meteorological data. Such new methods will help to reveal the size of the problem and design appropriate interventions at individual, workplace and societal level. The evaluation of occupational heat stress requires measurement of four thermal climate factors (air temperature, humidity, air velocity and heat radiation); available weather station data may serve this purpose. However, the use of meteorological data for occupational heat stress assessment is limited because weather stations do not traditionally and directly measure some important climate factors, e.g. solar radiation. In addition, local workplace environmental conditions such as local heat sources, metabolic heat production within the human body, and clothing properties, all affect the exchange of heat between the body and the environment. A robust occupational heat stress index should properly address all these factors. This article reviews and highlights a number of selected heat stress indices, indicating their advantages and disadvantages in relation to meteorological data, local workplace environments, body heat production and the use of protective clothing. These heat stress and heat strain indices include Wet Bulb Globe Temperature, Discomfort Index, Predicted Heat Strain index, and Universal Thermal Climate Index. In some cases, individuals may be monitored for heat strain through physiological measurements and medical supervision prior to and during exposure. Relevant protective and preventive strategies for alleviating heat strain are also reviewed and proposed.