OSA2.5 | Human biometeorology


This session “Human biometeorology” deals with the interactions between atmospheric conditions and humans beings in an interdisciplinary manner. The core question is how atmospheric conditions impact the well-being and health of humans, and how to transfer such knowledge in a widely understandable way in order to ensure the appropriate use of such kind of information. Atmospheric conditions include transient ones driven by weather patterns and long-term climatology but as well how potential climate change trends may affect these interactions.

In this context, the session will address issues concerning health, warning systems and measures in place to mitigate adverse impacts, and the models used to evaluate the heat load and cold stress on organisms. This will include the thermal component from the environment, weather sensitivity, actinic and chemical components of stress factors. Modelling studies and experimental studies on how environmental management, urban planning and design or traffic regulation can improve living conditions and decrease emissions are particularly welcome.

In addition, the session will consider the impacts of weather processes on human well-being and health. Since several methods are in use to compile bio-weather forecasts, we are looking forward to discussing such approaches and the way to convey such information to the public, but also to special target groups. Another aim is to describe ways, how climate data and information should be transferred and addressed for issues on tourism, recreation and other economic sectors.

The session will also address efforts to combine different environmental impacts on humans into one single index, as it is well known that humans react to the whole mix of atmospheric stimuli. Our aim is to improve the requested information and to look for more efficient ways of conveying the message on a regular basis in order to enable citizens to make the best use of such information in their everyday activities.

Conveners: Andreas Matzarakis, Tanja Cegnar | Co-conveners: Fiorella Acquaotta, Sorin Cheval
| Wed, 06 Sep, 14:00–17:15 (CEST)|Lecture room B1.08
| Attendance Thu, 07 Sep, 16:00–17:15 (CEST) | Display Wed, 06 Sep, 10:00–Fri, 08 Sep, 13:00|Poster area 'Day room'
Orals |
Wed, 14:00
Thu, 16:00

Orals: Wed, 6 Sep | Lecture room B1.08

The oral presentations are given in a hybrid format supported by a zoom meeting featuring onsite and online presentations. Alternatively, you can watch the session's live stream. The buttons to access the zoom meeting or live stream appear here just before the time block starts.
Chairpersons: Andreas Matzarakis, Tanja Cegnar
Onsite presentation
Danijela Kuzmanović, Gregor Skok, and Jana Banko

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 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 together with 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, on these stations, global solar radiation measurements are performed, making estimating the true value of UTCI more reliable. 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. The verification showed that the operational ALADIN model tends to overestimate the UTCI values. The overestimation is most pronounced in the morning when the mean error is about 8 °C. Also, a small percentage of cases have a very large error (up to 40 °C). We used two machine-learning methods to try to improve the forecasts of UTCI: linear regression and neural networks. Both methods have successfully reduced the error in the operational UTCI forecasts. Both 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.

How to cite: Kuzmanović, D., Skok, G., and Banko, J.: Improving the operational forecasts of outdoor UTCI with post-processing, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-4, https://doi.org/10.5194/ems2023-4, 2023.

Onsite presentation
Ilias Agathangelidis, Christos Giannaros, Elissavet Galanaki, Constantinos Cartalis, Vassiliki Kotroni, Konstantinos Lagouvardos, and Andreas Matzarakis

The comprehensive assessment of the human bioclimate requires considering the four principal meteorological variables that affect the thermal environment (i.e. temperature, humidity, wind speed and global solar radiation). It also requires using data at spatial scales that are relevant to the population exposure. Meeting these requirements with the use of ground-based weather stations is usually unattainable at nation-wide level. This is partially due to the incomplete spatiotemporal availability of the relevant observational data (especially of global solar radiation), as well as to the fact that the monitoring stations are often present in locations (e.g. airports) that are not representative of the human-biometeorological conditions. Gridded climate data can be used to overcome the above issues. In view of this fact, here, we exploit regional reanalysis data to perform a long-term (1991-2020) analysis of the human thermal bioclimate and its trends in Greece. To this end, the Copernicus European Regional Reanalysis (CERRA) dataset, at 5.5 km spatial resolution, is used. The CERRA dataset is combined with population data to better reflect the thermal environment experienced by the people through a population-weighted approach at regional units or combinations thereof that are based on the NUTS-3 (Nomenclature of Territorial Units for Statistics-3) classification. The population data are further used to assess the thermal-related risk in terms of annual number of exposure person-days, focusing on bioclimatic extremes. The latter are expressed by an advanced human-biometeorological index, namely the modified physiologically equivalent temperature (mPET), which is computed with the use of the RayMan Pro model. Short-term acclimatization effects are considered for mPET by adjusting the extremes’ thresholds through the application of a 30-day Gaussian filter. The present work is performed in the frame of the HEAT-ALARM project and provides preliminary results of the above described analysis, highlighting that regional reanalysis data can be valuable for climate assessments in the context of human-biometeorology, especially when combined with the consideration of population exposure aspects.

How to cite: Agathangelidis, I., Giannaros, C., Galanaki, E., Cartalis, C., Kotroni, V., Lagouvardos, K., and Matzarakis, A.: Exploiting regional reanalysis data for assessing long-term trends of the human thermal bioclimate in Greece, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-154, https://doi.org/10.5194/ems2023-154, 2023.

Onsite presentation
Panagiotis T. Nastos, Stavros Solomos, Iliana D. Polychroni, Marina - Panagiota P. Nastou, and Stelios Zerefos

Climate change has led to national, regional and local adaptation measures. However, these measures are not usually implemented in a targeted way, i.e. in urban areas with the most significant problem, or they are not designed in the optimal way to have the maximum efficiency at local scale. Towards this perspective the evaluation of human thermal stress in different urban environments, using appropriate models at very high resolution is considered fully appropriate.

The assessment and quantification of the thermal comfort for selected urban districts within the wider Athens area, are performed by the application of PET (Physiologically Equivalent Temperature) and UTCI (Universal Thermal Climate Index) indexes, which are based on the energy balance of the human body. The above indexes are calculated with the computational fluid dynamics (CFD) model ENVI-met, at city scale (resolution 1 × 1m). Measurements from the nearest meteorological stations as well as sub-scaling of the ERA5 data of the European COPERNICUS service at a local scale of 1 × 1 km with the atmospheric model WRF, are used as input data to the CFD model. The simulations are evaluated using high spatial and temporal resolution measurements obtained by a bicycle equipped with meteorological sensors and by an unmanned aerial vehicle equipped with a thermal camera. Further, the input data for future runs are obtained from downscaling of the emission mitigation scenario (RCP4.5) and the extreme climate scenario (RCP8.5) with the WRF model.

The findings of the analysis will provide comprehensive actions in order to optimize the resilience of the urban environment to various climate change scenarios.

Acknowledgements: This research is co-financed by European Regional Development Fund  and Greek Operational Program “Competitiveness, Entrepreneurship & Innovation (NSRF 2014-2020), entitled “Bioclimatic urban design services for the sustainability and resilience of the urban environment in the context of climate change (BIOASTY)”

How to cite: Nastos, P. T., Solomos, S., Polychroni, I. D., Nastou, M.-P. P., and Zerefos, S.: Evaluation of human thermal stress within urban environments in Athens, Greece, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-605, https://doi.org/10.5194/ems2023-605, 2023.

Onsite presentation
Aleš Urban, Veronika Huber, Salomé Henry, Nuria Pilar Plaza, and Shouro Dasgupta

The work has been submitted on behalf of the members of PROCILIAS TG 3.11 and the MCC Collaborative Research Network.

Early heat warning systems and heat-health action plans have been considered as one of the crucial heat prevention measures (HPMs) to prevent heat related mortality. However, previous studies showed that beneficial effects of HWSs are not consistent across cities and more research is needed to assess the efficiency of HPMs.

The aim of this study is to better understand the ability of HPMs to prevent heat-related mortality across Europe. Via MCC network, we obtained daily mortality time series from 267 locations across 16 European countries in the period 1990-2018. Via partners in COST Action PROCLIAS, we collected information about HPMs from selected European countries. Based on the WHO criteria, we developed a classification of HPMs in individual cities and countries, regarding their complexity.

We employed a two-stage longitudinal study design, to assess the temporal changes in heat-mortality in individual countries and to quantify beneficial effects of HPM implementation. In the first stage, we used quasi-Poisson regression models coupled with distributed lag non-linear models to calculate an exposure-response function in each location in each three-year window of the study period. In the second stage, we employed a random effect mixed meta-regression model, to quantify the effects of implementation, methodological updates, and overall complexity of HPMs . Modifying effects of the spatial-temporal variability in heatwave intensity were also considered.

Results suggest that South and Western European countries with the most complex HPMs, that include detailed heat and health action plans, experienced the largest reduction of the heat-related mortality risk after HPM's implementation. However, the results were sensitive to timing of the main heat wave periods in each region. Findings of this study highlight the need for further development and improvement of heat prevention measures in Europe.

How to cite: Urban, A., Huber, V., Henry, S., Plaza, N. P., and Dasgupta, S.: Do heat prevention measures reduce the risk of heat-related mortality in Europe?, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-133, https://doi.org/10.5194/ems2023-133, 2023.

Onsite presentation
Andreas Matzarakis and Stefan Muthers

Heat Health Warning System (HHWS) provide information for general public and public health. In Germany, weather Forecast is used to predict heat episodes, which are associated with negative health impacts. Therefore, a heat balance model of the human body and an extracted equivalent temperature (Perceived Temperature) is applied. Thresholds for strong and extreme heat stress based on thermal perception classification are used and build the first approach of the HHWS. Furthermore, the threshold of strong heat stress includes a short term adaptation component and considers the previous thermal stress conditions of the last 30 days. The second step includes nocturnal conditions, based on forecasted minimum air temperature or a simulated maximum indoor temperature for typical houses. The indoor temperature is calculated also based on a urban heat model for cities with a population over 100.000 inhabitants. Both criteria are important for the decision about warnings for the present and next days. Warnings are generated by daily weather forecast automatically and are additionally confirmed or adjusted by a biometeorological forecaster. The warning is valid on county level considering several elevation classes. The heat warning is available as a map on the internet and registered users can receive information by a daily newsletter. A specific smartphone app is also available for general use. The main target groups are the public, nursing homes and ministries of the federal states and other authorities. The HHWS with his regional differentiation of heat stress warnings is also part of the heat health action plans in Germany. HHWS is main part of the Heat action Plans in Germany.

How to cite: Matzarakis, A. and Muthers, S.: The Heat Health Warning System in Germany  – As part of Heat Actions Plans, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-23, https://doi.org/10.5194/ems2023-23, 2023.

Onsite presentation
Marcel Gangwisch and Andreas Matzarakis

Global climate change and its thermal implications on cities makes it necessary to react with long- and short-term climate-adapted urban planning and action. This should be organised and implemented by municipalities as part of heat action plans, to minimise future risks of overheated city districts on the city dwellers and especially on vulnerable groups. The evaluation of the thermal impact, based on thermal indices (depicting human thermoregulation) is most important in order to allow for a safe and risk-minimised but also human-adapted urban planning. Out of more than 200 thermal indices, the three most important ones have emerged in the literature (Physiologically Equivalent Temperature, Universal Thermal Climate Index and Perceived Temperature). These indices contain the complete energy balance equation of a human body under prevailing meteorological conditions.

This contribution demonstrates the thermal vulnerabilities, strengths and similarities of the indices. Min-Max-Normalisation was applied to relate and spatially compare the indices, independently of the physical unit and range. Subsequent regression analysis revealed the relationship between each index in turn. In this context, the indices were calculated for the urban district Rieselfeld in Freiburg, Germany, using the numerical, urban microscale model SkyHelios. The model is suitable to predict the meteorological outdoor conditions of future building- and local climate- scenarios.

Our investigation showed that the different thermal indices are not so different and differ mainly in the areas where the modification of radiation and wind is most prominent. These are also precisely the zones in which automated clothing becomes a key driving factor and differs among the indices.

We want to emphasise, that in future it will be necessary to compare not only the thermal indices with each other, but also the underlying implementations of the indices and the higher-level urban microscale models. This will increase confidence of these models, providing additional information for future action in heat action plans.

How to cite: Gangwisch, M. and Matzarakis, A.: Normalisation of Thermal Indices in the Context of Urban Environments, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-30, https://doi.org/10.5194/ems2023-30, 2023.

Tea break
Chairpersons: Panagiotis Nastos, Andreas Matzarakis, Sorin Cheval
Onsite presentation
Jouke de Baar, Dante Spekken, Arno Swart, Elisa Benincà, Jesse Limaheluw, Lucie Vermeulen, and Gerard van der Schrier

Question. Interdisciplinary research is becoming an increasingly important aspect of climate and weather impact research. In this work, we present a case study to include high-resolution climatology in models for the spread of airborne infectious disease. 

Approach. To achieve this, we expand the collaboration between two institutions, the National Institute for the Public Health and the Environment (RIVM) and the Royal Netherlands Meteorological Institute (KNMI). In this research, we bring two developments together. The RIVM is focusing on modelling the spread of airborne infectious diseases and assess their risk to human health, while the KNMI is focusing on providing high-resolution weather and climate maps by blending official KNMI weather station data, crowd-sourced Weather Observation Website (WOW, https://wow.knmi.nl) data and static information like land use and population density. 

On a technical level, the high-resolution weather maps are based on multi-fidelity Bayesian regression kriging. The core of the disease spread model is a spatial transmission kernel, which estimates the probability of infection as a function of the distance from the source. However, in this basic form, this approach has some limitations, because it does not take into account the impact of other important factors as for instance meteorological and environmental variables. In the combined effort by RIVM and KNMI we aim to improve and extend the current framework of the disease spread model by including the high resolution weather maps into the spatial transmission kernel.  Importantly, since both the weather maps and kernel model quantify uncertainty we can properly propagate uncertainty by Bayesian principles in the disease model. Our hypothesis is that, when we bring these two lines of research together, the high-resolution weather maps can lead to better models of disease spread, by including crucial covariates. In addition, such research is an important opportunity to establish links between science and society, both on the crowd-sourced weather observations side as on the publicly relevant side of health impact. 

Preliminary results. Currently, we are developing the methodology to improve and combine these two approaches from different disciplines. In this presentation, we will present this methodology for combination of approaches, as well as preliminary results from the two lines of approach that we aim to combine. 

How to cite: de Baar, J., Spekken, D., Swart, A., Benincà, E., Limaheluw, J., Vermeulen, L., and van der Schrier, G.: Interdisciplinary approach to include the effect of weather and climate in models for the spread of airborne infectious diseases, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-170, https://doi.org/10.5194/ems2023-170, 2023.

Onsite presentation
Jordi Mazon, Irene Valdés, and Judit Castellà

The relationship between weather and some meteorological parameters with human behavior, and even, crime has been well-established by several studies (e.g. Anderson et al., 1995; Cohn, 1990; Mazon, 2013; Potgieter et al., 2022). The thermal disconfort due to high values of both temperature and water vapor in the atmosphere in summer and early autumn in the Mediterranean areas, mainly in the coast, leads to a persistent feeling of muggy weather conditions day and night, which might affect human behavior. Based on this hypothesis, an investigation has been performed to explore the relationship between the heat index and four different typologies of crime from the Catalan Regional Police daily database 2010 to 2019.  

In the first stage of the research, violent crimes in Catalonia during the period 2010-2019 has been analysed, with the aim of finding whether periods with a high rate of crimes are mainlyin summer, and with a lower rate in winter. Various types of crimes of aggressive nature were examined, and those that positively responded to the hypothesis proceeded to the second stage. An analysis of the summer periods of those typologies of crimes that passed the first stage were analysed in the second part, in which arelationship between days with higher crime and days with a higher heat index (muggy weather) was explored.

The results suggest that a relationship does exist between violent crimes and muggy weather conditions as three of the four typologies of violent crimes vary with weather seasons: crimes increase when summer arrives and there is a drop in winter in criminal offenses such as bodily harm, tortures, and against sexual freedom.

Nevertheless, in the second stage of the research, results are not that clear. Crimes of torture give confusing results which leads to the conclusion that these do not hold a relationship with the heat index. However, the other two typologies show that there is a higher probability of a correspondence between peak days of crimes and days with a higher muggy weather level. Therefore, there seems to be a relationship between violent crimes and muggy weather conditions, specifically in the typologies of crimes that involve bodily harm and crimes against sexual freedom and indemnity.



Anderson CA, Deuser WE, DeNeve KM, 1995. Hot temperatures, hostile affect, hostile cognition, and arousal: tests of a general model of affective aggression. Personal Soc Psychol Bull 21(5):434–448.

Cohn EG, 1990. Weather and crime. Brit J Crim 30(1):51–64. DOI: https://doi.org/10.1093/oxfordjournals.bjc.a047980

Potgieter A, Fabris-Rotelli IN, Breetzke G. et al., 2022. The association between weather and crime in a township setting in South Africa. Int J Biometeorol 66, 865–874. https://doi.org/10.1007/s00484-022-02242-0

Mazon J., 2013. The influence of thermal discomfort on the attention index of teenagers: An experimental evaluation. Int J Biometeorol 58(5). https://doi.org/10.1007/s00484-013-0652-0








How to cite: Mazon, J., Valdés, I., and Castellà, J.: Exploring the influence of thermal discomfort due to muggy weather conditions on violent crimes and aggressive behavior in Catalonia (Spain) in the period 2010-2019., EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-167, https://doi.org/10.5194/ems2023-167, 2023.

Onsite presentation
Ekaterina Batchvarova and Zoya Mateeva

The climate is an essential factor for human bio-comfort and health. Since ancient times, people have used the climate's resources for their health, but at the same time, they have sought ways to cope with climate hazards. Nowadays, bioclimatic issues are gaining even greater importance, given the drastic increase in extreme climate events. There is a growing need for a deeper understanding of these events, the ways and mechanisms by which they affect the biostatus of the human organism, as well as the ways to deal with this problem at the individual and societal level. This report examines the main bioclimatic hazards in Bulgaria and their possible direct and indirect effects on human health. Direct are the effects of heat waves and ice episodes, intense precipitation and floods, strong winds, storms, avalanches, UV radiation overdoses, and contrasting weather changes. On the other hand, weather and climate indirectly affect our health through their influence on the air we breathe, the water we drink, the food we consume, and the ecosystems that surround us. The report also comments on some climate-sensitive diseases – respiratory, cardiovascular, and infectious (borne by water, food, air, and vectors). Socio-economic parameters of the society and of the individual have an important bearing on the intensity and number of these climate-related health consequences. Here they are considered as an index of health vulnerability in the country tracked for the period 1995-2020. On the other hand, this report also pays attention to the country's bioclimatic resources, with a view to using them to optimize human health. These are solar, thermal, air, wind, and cryogenic resources.The utilization of bioclimatic resources and dealing with bioclimatic hazards in Bulgaria are issues embedded in a number of state policies at the national and local level. This report sheds light on the main goals, priorities, and measures set out in the National Strategy for Adaptation to Climate Change. (Funding information: The study is supported by the National Science Fund of Bulgaria, Contract КП-06-ДК1/1).

How to cite: Batchvarova, E. and Mateeva, Z.: Climate and Human Health, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-617, https://doi.org/10.5194/ems2023-617, 2023.

Onsite presentation
Andreas Matzarakis and Kathrin Graw

Weather sensitivity describes reactions of the human body related to the current weather and especially to changes in weather. A clear scientific  definition of weather sensitivity does not exist. Positive impacts, as well as effects on mood, are rarely mentioned. Weather sensitivity occurs mainly in temperate latitudes or climates, as this is also where most rapid changes in weather conditions occur or are present. Scientifically based data on the prevalence of weather-associated complaints and symptoms as well as impairment of well-being have been obtained from population surveys on weather sensitivity in Germany since the 1950s. This analysis focuses on the findings from the representative population survey of 2021 and relates the results to the surveys of 2013 and 2001. The “Institut für Demoskopie Allensbach”, on behalf of the German Meteorological Service, interviewed a representative sample of 1080 German citizens. Based on respondents’ self-assessment, the proportion of individuals who said the weather had an impact on their health was 46% in 2021, compared to 50% in 2013 and 54% in 2001. Elderly and chronically ill individuals are more likely to suffer from weather sensitivity than the average population. Women are more affected than men. The most common complaints of weather sensitivity are headaches/migraines, exhaustion/general fatigue, limited activities, and abnormal fatigue. The decrease in the proportion of weather-sensitive humans may be related to greater health awareness and improved health care. Preventive measures, such as going outdoors and dosed exposure of the body to different weather, as well as avoiding other stresses, can train the body’s ability to regulate itself and help  to make it less susceptible to weather sensitivity.

How to cite: Matzarakis, A. and Graw, K.: Weather Sensitivity Surveys in Germany, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-24, https://doi.org/10.5194/ems2023-24, 2023.

Online presentation
Ferenc Ács, Erzsébet Kristóf, Zsófia Szalkai, and Annamária Zsákai

Fog is one of the special weather phenomena of the Hungarian lowlands in autumn and winter. It has been studied from many points of view (for example frequency, type, predictability), but not yet from the point of view of human thermal load. The aim of this work is to fill this gap. We observed a total of 132 fog events at Martonvásár (Hungary, Central Transdanubian region) in the period 2017-2023. During our observations, we documented the period of its existence, air pressure, air temperature, air humidity and wind speed. Based on the meteorological and human (body mass, body length, sex, age, person walking at a speed of 1.1 m/s) data, we estimated the thermal load of the foggy environment using a clothing thermal resistance (rcl)-operative temperature model. The model is very simple, based on the calculation of the energy balance of the human body covered with clothing. The main results are as follows. In the fogs that cause the greatest lack of heat, the rcl is around 2.5 clo, the operative temperature is around -7 ℃.  In fogs with a much smaller heat deficit, the rcl is around 0.5 clo, and the operative temperature is around 15-17 ℃. In the vast majority of cases, rcl varies between 1-2 clo. We were able to make sure that the thermal load of the fog is mostly determined by the temperature and radiation conditions. Further observations are needed. For instance, one should observe the smallest thermal deficit, in which fog can still exist.

How to cite: Ács, F., Kristóf, E., Szalkai, Z., and Zsákai, A.: Human thermal load in the fog in the Hungarian lowland, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-446, https://doi.org/10.5194/ems2023-446, 2023.

Posters: Thu, 7 Sep, 16:00–17:15 | Poster area 'Day room'

Display time: Wed, 6 Sep 10:00–Fri, 8 Sep 13:00
Chairperson: Andreas Matzarakis
Onsite presentation
Martin Novak, Martin Hynčica, and Simona Procházková

The universal thermal climate index (UTCI) is a widely used index evaluating stress caused by meteorological conditions on humans. The index combines the four meteorological elements: temperature, humidity, wind speed, and mean radiant temperature. The UTCI index can be gained from observed data, however, its calculation is also incorporated in several reanalyses. Here, the comparison of the index for the Czech Republic is made between two reanalyses, that is, the ERA5 and Aladin reanalyses. The ERA5 reanalysis is a global dataset produced in a much coarser resolution (approximately 27 km), whereas the Aladin reanalysis is adjusted for the Czech Republic with the finer resolution of 2.7 km. Hence, we analyze and compare both datasets between 1989 and 2020 for the Czech Republic. Firstly, both reanalyses are interpolated on the same grid with a 7.1 km grid step. Subsequent comparison reveals a large similarity between both reanalyses, probably due to the fact that ERA5 is a control dataset for the Aladin reanalysis. The general climatology of UTCI for the Czech Republic is presented in both reanalyses. Furthermore, trends of UTCI over the 30year period are calculated for the whole country as well as for selected interesting sites. A detailed examination is given to the differences between eastern and western parts of the country to evaluate impact of the rising continentality of climate toward east. The dependence of UTCI on altitude in both reanalyses is determined as well. Finally, trends between rural and urban areas are compared to asses trends of UTCI in urban heat islands. The results of this work will be used in the future for bioclimatological mapping of the Czech Republic.

How to cite: Novak, M., Hynčica, M., and Procházková, S.: Analysis of UTCI in the Czech Republic: a comparison of two reanalyses, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-479, https://doi.org/10.5194/ems2023-479, 2023.

Onsite presentation
Eva Plavcova, Ales Urban, Hana Hanzlikova, and Jan Kysely

Extreme weather events pose various significant impacts on society, including human health. The objectives of our analysis are: (1) to identify weather patterns that are associated with excess mortality, and (2) to assess how the frequency of these patterns may change in future climate scenarios using regional climate model simulations. We build upon our previous study that revealed winter extreme events linked to excess mortality and their intensified impacts from their compound occurrences (Plavcová and Urban, 2020). High-quality long-term mortality time series data from 1982 to 2020 is utilized to identify meteorological phenomena linked to significant excess mortality in the Czech Republic. Our analysis focuses on sudden changes in various meteorological parameters (such as temperature and pressure) and their compound occurrences during both winter and summer seasons.

Subsequently, we analyze projected changes in the frequencies of these extreme weather events using an ensemble of EURO-CORDEX regional climate model simulations for the end of the 21st century. We acknowledge a significant role of future adaptation of human society to changing weather conditions resulting from global climate change remains uncertain, although it plays a significant role. Nonetheless, concern for human health is one of the most compelling motivation to study the effects of climate change. Our findings provide insights into how the occurrence of weather events linked to mortality risk may evolve under future climate scenarios, and may help to develop mitigation and adaptation strategies to manage health risks linked to extreme weather. 

  • Plavcová E, Urban A (2020) Intensified impacts on mortality due to compound winter extremes in the Czech Republic, Sci. Total Environ., 746, Article 141033, 10.1016/j.scitotenv.2020.141033

How to cite: Plavcova, E., Urban, A., Hanzlikova, H., and Kysely, J.: Extreme weather linked to excess human mortality in projections of future climate, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-413, https://doi.org/10.5194/ems2023-413, 2023.

Onsite presentation
Theodoros Economou, Daphne Parliari, and Jonilda Kushta

The latest Intergovernmental Panel on Climate Change (IPCC) report estimates that the global mean temperature increase will be up to 5.4°C. One of the most affected areas globally is the Eastern Mediterranean and Middle East (EMME), a wide and highly diverse region, identified as a hotspot that is warming twice as fast compared to the global increase. Climate change, in conjunction with poor air quality are two key factors impacting human health. In this work, we use flexible statistical modeling approaches to quantify the joint effect of temperature, humidity and air quality on human mortality for the city of Thessaloniki in Greece. In this work we briefly expose the statistical methodology we propose, and how it was used to quantify the joint effects of temperature, humidity and air quality over prolonged periods of exposure, on human mortality.

More specifically, we utilize data on all-cause but also cause-specific daily mortality and model this as a function of temperature, humidity, ozone, PM10 and nitrogen dioxide – all measured from monitoring stations in Thessaloniki. We implement the well-established framework of Distributed Lag Models (DLMs) as Generalized Additive Models (GAMs), to capture the complex interactions between the aforementioned exposures on the risk of mortality. Such models capture the exposure effect through time and thus enable understanding into how prolonged periods of poor air quality and heat stress affect human health. Results confirm the intuition that exposure to extreme heat and humidity in conjunction with poor air quality significantly increases the risk of mortality. This increase in risk varies considerably by case-of-death and also by age group. We show how the type of air pollutant results in different risk profiles, but also that there are correlations across the pollutants that affect the risks.

How to cite: Economou, T., Parliari, D., and Kushta, J.: Using statistical approaches to quantify the synergy of heat stress and air pollution on human mortality for a Mediterranean city, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-69, https://doi.org/10.5194/ems2023-69, 2023.

Onsite presentation
Katerina Pantavou, Kostas Lagouvardos, and Vassiliki Kotroni

Thermal indices are valuable tools for assessing thermal environments linked to applications related to architecture, planning, tourism, energy conservation and health. They combine meteorological variables into a single value which can be assigned to a category of an assessment scale expressing the predicted degree of human thermal discomfort, sensation or stress. The assessment scales include one indifference (neutral) category and negative and/or positive categories of increasing intensity of thermal feeling. The numerous indices that have been developed makes the selection of a suitable one for a specific application a complex issue. The aim of this study was to assess the effectiveness of several commonly used thermal indices for their operational use in weather applications in the Mediterranean climate of Greece. Hourly data (2010-2021) of air temperature (Tair, oC), relative humidity (Rh, %), wind speed (WS, m/s) and global solar radiation (SR, W/m2) recorded in 15 weather stations across the Athens metropolitan area of the Automatic Weather Stations Network of the National Observatory of Athens were used to calculate the indices. The indices should follow the following criteria: (a) be currently in common use, (b) be easily estimated operationally, i.e., short estimation time using Tair, Rh, WS and SR, and (c) provide exploitable results. Apparent temperature (AT), Heat Index (HI), Humidex (HU), Normal Effective Temperature (NET), Physiologically Equivalent Temperature (PET), Universal Thermal Climate Index (UTCI), Wet-Bulb Globe Temperature (WBGT) and Wind Chill Index (WCI) were identified as the most commonly used thermal indices in research and by weather services around the world. PET showed the highest computational demand compared to the other indices. At the first step, NET, PET and UTCI were assessed as more suitable for the climate of Athens (compared to AT, HI, HU, WBGT and WCI), extending their predictions to the entire range of their assessment scales. NET and PET tended to classify more often than UTCI thermal conditions in the negative categories of their assessment scales (67.8%-NET and 62.1%-PET versus 36.8%-UTCI; p<0.001) while most of UTCI values were classified in the neutral category (48.9%-UTCI versus 15.6%-NET and 15.1%-PET; p<0.001). Finally, more heat wave days were classified in accordance to Tair by NET (86.8%) and UTCI (84.5%) compared to PET (70.5%; p=0.014). According to the results of this study, NET and UTCI could be suggested as the best candidate indices for operational use in the climate of Athens, Greece.

How to cite: Pantavou, K., Lagouvardos, K., and Kotroni, V.: Assessment of thermal indices for the operational evaluation of thermal conditions in Athens, Greece, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-48, https://doi.org/10.5194/ems2023-48, 2023.