Heat stress depends on a set of metereological variables, namely, air temperature, wind speed, air humidity and mean radiant temperature. In urban areas, wind speed and mean radiant temperature are strongly spatially hetereogeneous, at scales of few meteres, much smaller than the typical resolution of mesoscale models, which is of the order of one kilometer or several hundreds of meters. This is the main obstacle to produce reliable estimates of heat stress at city scale. In this contribution, we present a methodology, built over a set of microscale simulations, to represent subgrid scale variability of wind speed and mean radiant temperature, and as a consequence heat stress. The scheme is implemented in the multilayer urban canopy parameterization BEP-BEM embedded in the mesoscale model WRF (therefore called WRF-comfort), and it opens the way to the city scale evaluation of the impact of different adaptation/mitigation strategies on heat stress, something that is essential to plan liveable future cities in the context of a changing climate. This is illustrated with a series of simulations for a summertime period over the city of Madrid (Spain). Then main outcome of the study is that the time evolution and spatial variability of UTCI (the Universal Thermal Climate Index, one of the most used heat stress indexes) are strongly affected by the urban morphology, and that the spatial pattern of UTCI at city scale is only partially similar to the one of air temperature, and dissimilar to the one of Land Surface Temperature, as it can be seen from satellite, a variable often used to assess urban overheating.

How to cite: Martilli, A., Nazarian, N., Krayenhoff, S., Lachapelle, J., Lu, J., Rivas, E., Rodriguez-Sanchez, A., Sanchez, B., and Santiago, J. L.: Assessing heat stress with a mesoscale model. An application of WRF-comfort to Madrid, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1136, https://doi.org/10.5194/ems2024-1136, 2024.

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Urban green infrastructures can regulate microclimate and mitigate urban heat island (UHI) effects. In summer, urban parks offer cooler spots where citizens are protected from the heat of the city, more particularly in the evening and the night, when the UHI arises. During heatwaves, urban parks can therefore play a key role in addressing health risks. Previous research shows that urban vegetation has the potential to mitigate temperatures at the pedestrian level depending on park size, vegetation type, topography or local climate. However, little is known concerning the impact of meteorological conditions (wind, turbulence, cloudiness, UHI intensity, atmospheric stability) on the urban park cooling effect. The cooling along the vertical dimension remains also sparsely quantified. 

One of the aims of the PANAME (for PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch) intensive measurement campaign is to better understand and quantify the role of urban parks in regulating the microclimate during summer periods. The July 2023 special observation period (SOP) focused more particularly on investigating the horizontal and vertical cooling potential of four urban parks and woods of various sizes from late afternoon to early part of the night. The experimental set-up combined in situ surface measurements in parks and urban areas, such as profiling of the surface layer using quadcopter drones and soundings. For drone measurements, each urban park was associated with a nearby urban site, consisting in semi-enclosed to enclosed paved courtyards surrounded by buildings. Profiles were simultaneously undertaken in both urban/park environments from 16 to 20 UTC for each of the 21 days of measurements that took place for the 2023 SOP. This resulted in an innovative multi-source dataset currently being used to quantify and analyse the differences in surface and near-surface atmospheric cooling rates between an urban park and the nearby urban environment, as well as between different parks, but also to study the cooling potential related to meteorological conditions.

The first results show that the evening cooling is highly dependent on the meteorological conditions, which is in agreement with recent work establishing a link between park cooling efficiencies and weather types with contrasting UHI regimes. For some evenings, the surface park cooling between the late afternoon and the sunset can reach more than 3 K while it is often less than 1 K in the urban environment. For other meteorological conditions, the cooling rate is similar between park and urban environments. When the cooling is different between parks and urban environments, the park cooling extends vertically over several tens of meters, where a local inversion is found. For those types of meteorological conditions, significant cooling is also found in very small urban parks (less than 1 ha).

How to cite: Nagel, T., Rivollet, M., Sarah, W., Goret, M., Roberts, G., Lemonsu, A., Masson, V., Havu, M., Capo, J., Wurtz, J., de Munck, C., Haeffelin, M., Ribaud, J.-F., Kotthaus, S., and Dupont, J.-C.: Investigation of urban park cooling efficiency during summer in Paris with drones, sondes, and ground measurements, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-337, https://doi.org/10.5194/ems2024-337, 2024.

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Heat waves pose a significant risk to human health, particularly pronounced in urban areas due to the urban heat island (UHI) effect. Understanding the varying impacts of heat waves across different neighbourhoods within cities is vital, as well as recognizing the potential of urban vegetation in mitigating temperatures. The Heat and Health in Cities (H2C) project aims to enhance urban climate services to support proactive measures and policies addressing extreme heat risks in cities, with a specific focus on the Paris region. Employing a multi-source observational approach alongside numerical models, the project seeks to provide a more comprehensive assessment of environmental conditions, ranging from regional to neighbourhood scales. 

The main aim of this study is to examine the efficiency of parks and urban forests in mitigating air temperatures during summer periods including heat waves. Using the Meso-NH model, this study conducts simulations of discrete events occurring in 2022 and 2023 within Paris and the Ile-de-France region. Meso-NH, a non-hydrostatic research atmospheric model, is driven by atmospheric boundary conditions from the French convective-scale operational Numerical Weather Prediction model AROME-France. Coupled with Meso-NH is the land surface model SURFace EXternalized (SURFEX), incorporating the Town Energy Balance (TEB) model for urban elements combined with a high-resolution surface database. Simulations are based on three nested domains with respective grid resolutions of 1200 m, 300 m (over Paris region), and 100 m (over the city of Paris). Model validation of 2-m air temperatures is performed using data from the PANAME (PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch, https://paname.aeris-data.fr/) intensive measurement campaign. 

Previous works have established through the local observations the existence of weather types with contrasting UHI regimes resulting in distinct park cooling efficiencies. The aim of this study is to determine whether hectometric-scale modelling is able to replicate these observed results. The challenge is then to be able with modelling to study and better understand the microclimatic contrasts within the city, in particular the cooling effects generated by urban parks of various sizes and the factors contributing to their variability.

How to cite: Havu, M., Nagel, T., Wurtz, J., Masson, V., Rivollet, M., Haeffelin, M., Ribaud, J.-F., Kotthaus, S., Dupont, J.-C., and Lemonsu, A.: High-resolution modelling of park cooling efficiency during summer in Paris, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-418, https://doi.org/10.5194/ems2024-418, 2024.

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“Greenness is often associated with more attractive, healthful, and wealthy urban areas since vegetation increases the urban biodiversity and reduces summer temperatures. Some analyses have pointed out a relationship between neighborhood demographics and urban vegetation that has been referred to as “luxury effect” (Leong, Dunn, and Trautwein 2018) or tree gap (Visram 2021), from which wealthy residential areas benefit from greater vegetation cover and a lower intensity of the urban heat island effect. So, this contribution relates some of the urban features, derived from remote sensing, with the dynamic of the urban heat island of Madrid, and some socio-demographic parameters at census tract level, for the summers of the 2008-2017 period.

The remote sensing indices were calculated from Landsat 5 and Landsat 8 platforms (https://earthexplorer.usgs.gov/). The urban heat island of Madrid was studied using the “Climate variables for cities in Europe from 2008 to 2017” dataset, obtained from Copernicus (https://cds.climate.copernicus.eu/cdsapp#!/software/app-health-urban-heat-islands-current-climate?tab=app), combined with observed temperature data from the Spanish Meteorological Agency (AeMet) and the Regional and Local authorities (Ayuntamiento and Gobierno Regional de Madrid). Demographic data were retrieved from the Atlas de distribución de renta de los hogares (https://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736177088&menu=ultiDatos&idp=1254735976608) and the Municipality of Madrid (https://www.madrid.es/portales/munimadrid/es/Inicio/El-Ayuntamiento/Estadistica?vgnextchannel=8156e39873674210VgnVCM1000000b205a0aRCRD).

Analyses show that Madrid's UHI is particularly intense at night, while during daytime is much weaker. This can be explained by the thermal behavior of its urban periphery, which is mainly made up of agricultural areas with rainfed crops, suffering an intense daytime heating. It is also observed that the relationship between remote sensing indices and the urban temperatures varies depending on the information provided by the indices (vegetation, built-up or aquatic surfaces density) and the time of day. The "luxury effect" is not evident, as the relationship between vegetation, heat island and various sociodemographic indicators is statistically weak. As an urban space which has evolved from many decades, Madrid offers a remarkable spatial diversity in terms of income levels or demographic composition, although some risk neighborhoods can be delimited because of the coincidence of a high amount of vulnerable population (low income, senior population, migrants) and an intense urban heat island.”

How to cite: Toribio-Pérez, M., Conde-Oria, F., and Rasilla, D. F.: Luxury effect and Urban Heat Island: a reassessment in Madrid., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-468, https://doi.org/10.5194/ems2024-468, 2024.

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We describe features and results of a data system developed to allow timely access to data from novel modular atmospheric monitoring systems deployed in urban areas in multiple cities of different sizes, simultaneously. The ERC urbisphere project is collecting a wide range of atmospheric environmental data to improve weather and climate models, in order to assess the impact of cities on the atmosphere (e.g., aerosols, greenhouse gases) and human exposure to extreme events (e.g., heat waves, heavy precipitation, air pollution). Modular observing systems involving short-term deployments include customised automatic weather stations, Doppler and ceilometer lidars, scintillometers, balloon radio sounding and spectral imaging. Deployments range from streetlight-mounted to building roofs and indoors to mobile platforms (vehicles, drones). Together this creates challenges to synthesise across multiple sources of diversity.

Data are uploaded in near-time to a central data infrastructure via cell phone and IOT networks. A metadata system helps track the location and configuration of all deployed components and provides the backbone for processing instrument records into location-aware, convention-aligned and quality-assured data products according to FAIR. The data system provides services (e.g., APIs, Apps, ICEs) for inspection and computation by campaign participants. Workflow and design considerations also include collaboration tools that ensure attribution for multiple uses in near time by researchers, operational agencies and citizens.

We will demonstrate how the systematic, easily adoptable approach can simplify complex campaign workflows, for both modellers and observers. The showcase of the data system will use examples from outdoor/indoor temperature observations and spatial wind field observations from past and ongoing campaigns.

How to cite: Zeeman, M., Christen, A., Grimmond, S., Fenner, D., Morrison, W., Feigel, G., Plein, M., Sulzer, M., Looschelders, D., and Chrysoulakis, N.: Near-time atmospheric observations in urban areas: insights from concurrent operations in multiple cities, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-644, https://doi.org/10.5194/ems2024-644, 2024.

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The Urban Heat Island (UHI) effect has significant implications for human thermal comfort, urban ecosystems, and energy consumption. The COVID-19 global lockdown presented a unique opportunity to explore the impact of reduced air pollution emissions and Anthropogenic Heat Flux (AHF) on UHI. While some studies have proposed that the lockdown’s reduction in AHF led to a decrease in both Atmospheric UHI (AUHI) and Surface UHI (SUHI), these findings are susceptible to inherent uncertainties due to unaccounted weather variability and urban-rural dynamics.

Our research provides a comprehensive analysis of the lockdown’s impact on AUHI and SUHI in Prague, Czechia. We selected days with similar weather conditions and compared the mean SUHI using MODIS satellite imagery and AUHI based on air temperature data from Prague weather stations during the lockdown period from March to April 2020 with a reference period spanning March to April 2017-2019.

Our findings reveal that the lockdown period, compared to the reference period, was associated with a 15% (0.1 °C) reduction in SUHI in Prague’s urbanized areas and a 0.7 °C decrease in AUHI in the city center. Furthermore, we observed a 12% and 29% decrease in satellite-based aerosol optical depth and nitrogen dioxide, respectively. These observations support our hypothesis that the observed weakening of UHI effects is linked to the reduction in anthropogenic activities during the lockdown. In addition, our study shows the largest decrease in mean SUHI magnitude was in the periphery, an area characterized by predominantly rural land cover. This highlights the importance of considering urban-rural dynamics when attributing changes in SUHI to AHF.

In conclusion, our study provides additional insights into the role of reduced anthropogenic activities in UHI dynamics during the COVID-19 lockdown. It offers policymakers a comprehensive understanding of how the complex interplay between urban and rural microclimate dynamics influences the SUHI phenomenon.

How to cite: Dogan, T., Urban, A., and Hanel, M.: Temporal variations of urban heat islands during COVID-19 lockdown in Prague, Czechia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-739, https://doi.org/10.5194/ems2024-739, 2024.

EMS2024-739

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The recent reports issued by the Intergovernmental Panel on Climate Change (IPCC) emphasise the need to reconsider the design of urban built environments [1]. In the past twenty years, research has demonstrated that geometry parameters of urban street canyon play a significant role in influencing the microclimatic conditions and energy performance of the buildings within urban environments [2,3]. Urban canyon geometry affects the overall energy consumption of buildings and has the potential to reduce energy usage by as much as 30% for commercial structures and 19% for residential structures. Besides, the air and surface temperatures of urban street canyons are highly influenced by sunlight access, shadowing, and other factors. Canyon’s form and parameters, such as aspect ratio (H/W) and street direction, impact sun access, shading, and ventilation, which are also affected by length-to-height ratio (L/H). The aim of this paper is to assess whether geometric parameters of urban street canyons affect the microclimates and energy consumption in cold semi-arid climate. The research was carried out in Kayseri, Turkey, which has been developing city. According to those statistics, the real heating energy consumption in residential buildings ranges between 100 and 200 kWh/m 2 (the average is obtained as 175 kWh/m2) in Turkey. However, in European countries, this value is 100 kWh/m2, including energy use of heating, cooling and ventilation [4]. A total of 18 scenarios, including both configurations with and without space between buildings, were simulated. The scenarios varied in their aspect ratio, which is the ratio of height to width (H/W). There were three types of canyons: avenue canyons (H/W < 0.5), regular canyons (H/W = 1.0), and deep canyons (H/W > 2.0). Additionally, the scenarios differed in their length-to-height (L/H) ratio. There were three types of canyons based on this ratio: short canyons (L/H < 3.0), medium canyons (L/H = 5.0), and long canyons (L/H > 7.0) [5]. The performance of the canyon was evaluated by comparing the air temperature, on the hottest and coldest day of a typical year. In parallel to microclimate analysis, energy consumption analysis was carried out for a hypothetical case study building throughout the day and night. Envi-met and EnergyPlus are used as a computational tool. The comparative study will show how and to what extent urban canyon geometry parameters, in this case, contributes to modifying the magnitude of microclimate impact on daytime and nighttime energy loads.

Keywords: Street Canyon, Urban form parameters, Urban geometry, Energy performance

How to cite: Toren, B. I. and Sharmin, T.: Urban Geometry and Microclimate of Street Canyons in Cold Semi-Arid Climate, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-898, https://doi.org/10.5194/ems2024-898, 2024.

EMS2024-898

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One relevant effect of urbanization is the modification of atmosphere-surface interactions, which modulate urban microclimate and human thermal comfort. To quantify the impact of heat on the human body, more comprehensive biometeorological indices, such as the Universal Thermal Climate Index (UTCI), are commonly employed accounting for not only air temperature influence but also the variability of other relevant weather variables such as wind speed, air humidity and radiation. The irregularity of urban morphology (e.g. building height and layout) across the city leads to high spatial heterogeneity of the micrometeorological variables, in particular on wind speed and solar radiation (e.g. shading effects). Therefore, analyzing the impact of urban geometry and the past changes in urban land cover on heat stress contributes to understanding the potential risks that urban residents might face considering the future urban growth and future climate.

The purpose of the present work is to investigate the impact of urban development and climate on outdoor thermal comfort in Madrid for summer weather conditions under past and future climate. A modeling study is conducted using the Weather, Research and Forecasting (WRF) model adapted to estimate the heat and momentum exchanges between buildings and atmosphere (BEP-BEM urban scheme), as well as the recent development incorporated into BEP-BEM to quantify heat stress through UTCI values and its subgrid variability. Past urban scenarios are performed considering the realistic urban expansion and morphology from 1970 to 2020, and the expected urban development is used for the future scenario. The model evaluation is conducted against observations showing an overall good performance of the model in predicting near-surface meteorological parameters. Even though the urban layout has barely changed in the center of Madrid over the last 50 years, results show an increase in the UTCI values due to the influence of the surrounding urban expansion. In addition, these results show the relative contribution of urbanization and climate effects on the heat stress changes across the city under the past and future climates.

How to cite: Sanchez, B., Martilli, A., Santiago, J. L., Rivas, E., Martin, F., Royé, D., Carbone, J., and Yagüe, C.: Past and future changes in the spatiotemporal distribution of heat stress in Madrid, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-804, https://doi.org/10.5194/ems2024-804, 2024.

EMS2024-804

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While overall the global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2 radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. The anthropogenic origin is connected to large extent with the urban environment. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedbacks of global warming on emissions, e.g., permafrost thaw.

The main goal of the EC Horizon Europe project FOCI, is to assess the impact of key radiative forcers, where and how they arise, the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global Earth System Models and into Regional Climate Models, eventually coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world, with final emphasis to selected cities environment. We will develop new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. Mutual interactions of the results and climate services producers and other end-users will provide feedbacks for the specific scenarios optimization and potential application to support the decision making, including climate policy.

Coupled RCM-CTM modelling experiment strategies and preliminary results will be presented in addition to the contemporary status of the project.

How to cite: Halenka, T., Sokhi, R., and Finardi, S.: Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts: Where we are and where we go, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1088, https://doi.org/10.5194/ems2024-1088, 2024.

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Rapid urbanization, compounded by climate change, exacerbates temperatures in urban regions by intensifying the urban heat island (UHI) effect. This study explores the influence of urbanization patterns on urban microclimate in Turin, Italy, through numerical simulations. Various urban design scenarios were investigated using weather research and forecast models integrated with a multilayer urban canopy model (MLUCM) over the June 2019 heatwave period. High-resolution urban land use/land cover data derived from local climate zone (LCZ) maps generated through the World Urban Database and Access Portal Tools (WUDAPT) were utilized. Results indicate a significant impact of urbanization on UHI, demonstrating an average nighttime temperature reduction of 2.4°C and daytime temperature reduction of 1.6°C in urban areas when urban built-ups are replaced with vegetation. Replacement of compact-rise buildings alone notably impacts local climatic conditions, decreasing average temperatures by 1.75°C in the city center, with an overall urban temperature decrease of 0.9°C. Conversely, the substitution of industrial zones yields a 1.4°C average urban temperature decrease, with minimal impact in city centers (0.14°C reduction). Substituting compact-rise buildings with open-rise buildings slightly reduces urban nighttime temperatures and significantly reduces the critical velocity required to mitigate UHI. Furthermore, the adoption of open-rise buildings fosters enhanced wind flow in downstream rural areas, potentially contributing to a reduction in urban temperatures on windy days by facilitating ventilation and other cooling processes. This research emphasizes the critical role of specific urban features in mitigating UHI and improving thermal comfort. By strategically incorporating green spaces, open-rise buildings, and wind-channeling designs, urban planners can create more resilient and thermally comfortable cities.

How to cite: Pauly, L. and Ferrero, E.: Numerical Experimentation to Study the Influence of Various Urban Features on Microclimate Using Different Urban Scenarios , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-210, https://doi.org/10.5194/ems2024-210, 2024.

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Methane is a primary greenhouse gas with a relatively short lifetime in the atmosphere (~ 12 y), making it a candidate for mitigation efforts aimed at improving the climate in the near future.

Urban areas account for ~2% of our planet’s surface, but they host more than half of the world’s population and a series of potential CH₄ source systems (e.g., natural gas distribution, landfills, sewages, and in some cases, natural or artificial wetlands). The role of urban areas in the global atmospheric CH₄ budget is, however, uncertain.

Our understanding of the exact CH₄ emission systems and related emission factors in urban areas is still limited (and unknown in Romania).

In Cluj-Napoca, the second-biggest city in Romania, our study aims at identifying potential urban sources for CH₄emissions via direct detection of CH₄ at potential emission sites (opposed to atmospheric monitoring, as generally done).

Our study aims to investigate potential sources in three major urban systems (natural gas distribution networks, sewage system, and aquatic systems).

We used a highly sensitive laser CH₄ sensor based on Tunable Diode Laser Absorption Spectrometry (TDLAS) with a resolution of ± 0.1 ppmv.

Preliminary data show that 86% of the natural gas end-use points (74 measured) release CH₄ into the atmosphere, 51% of the SEWAGE manholes (126 measured) are net sources of methane, and the aquatic systems (river and ponds, 50 sampling sites) are all oversaturated with dissolved CH₄ and represent potential sources.

Due to both natural and anthropogenic CH₄ sources, Cluj-Napoca can be considered a hybrid methane source. This approach helps in reducing the ambiguity in the attribution of CH₄ sources when only atmospheric CH₄ monitoring is performed.

This study can advance our understanding of CH₄ release in urban areas and serve as the first national systematic-based approach that can be replicated to effectively take advantage of all available resources. It will also serve as a reference for future research on CH₄ in the urban area.

How to cite: Hmoudah, M. and Baciu, C.: Investigating emissions of methane (CH4) to the atmosphere in Cluj-Napoca urban area , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-223, https://doi.org/10.5194/ems2024-223, 2024.

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How to cite: Vurro, G., Martilli, A., Hadjinicolaou, P., and Carlucci, S.: Quantifying the impact of extreme heat and adaptation strategies on urban air conditioning use and energy consumption in Nicosia, Cyprus. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-18, https://doi.org/10.5194/ems2024-18, 2024.

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How to cite: Outten, S., Raffaele, F., Zazulie, N., and Vandeskog, S. M.: Stakeholder relevant hazard indices in Euro-CORDEX models developed under the EU- Impetus4Change project, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-355, https://doi.org/10.5194/ems2024-355, 2024.

EMS2024-355

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City dwellers are increasingly exposed to summer heat due to climate change and urbanization. Summer heat, which causes heat stress, is intensified especially at night in urban areas and is projected to become more extreme due to climate change. City dwellers are not just increasingly exposed to this heat outdoors but mainly indoors, as they spend the majority of their time inside their homes. However, observational and modelling studies on indoor heat stress are relatively scarce, especially concerning the interconnections between indoor and outdoor climatic conditions.

This study observes, analyses, and models the evolution of indoor air temperature during Dutch summer heat using two unique crowdsourced datasets. The first dataset consists of long observational records, spanning up to 27 years, from citizen weather stations (CWS) located in seven residences across the Netherlands. This dataset provides insight into the benefits of long-term observations at residences. The second dataset consists of indoor CWS placed by us since 2022 in 100 residences across Amsterdam. This dataset offers insight into the benefits of measuring in a large number of residences.

Conventional high-resolution building energy models are commonly validated in controlled settings. In contrast, our study utilizes real-world residences inhabited by individuals, thereby capturing actual occupant behaviour. Moreover, crowdsourced indoor climate observations, just like ours, often lack supplementary data such as building characteristics and occupant behaviour. Therefore, we adopt an analysis and modelling approach only taking indoor temperature as an input parameter of the residence. We demonstrate that indoor temperature typically warms up more slowly than outdoor temperature but also cools down more slowly. The seven residences in the first dataset had, on average, a lag difference of approximately 260 minutes in the diurnal cycle during summer. Indoor temperature also remained higher than outdoor temperature for up to 5 days after a heatwave. For the 100 residences in the Amsterdam dataset, the analysis results will be presented. To model indoor temperature evolution, we simulated daily changes in indoor temperature evolution with a physics-based statistical model. The model includes outdoor conduction, indoor conduction, and solar transfer components, calculated from indoor temperature observations and outdoor temperature, solar irradiance, and wind observations. Results of this computationally-fast model for the seven residences are promising, with on average a mean absolute error of 0.43 K day^-1 during summer. Preliminary results suggest a higher model performance for modelling of the warming of the residences compared to the cooling. The model results for the 100 residences will be presented, providing insight into the variability in model performance for indoor temperature in Amsterdam.

The study's findings illustrate the high potential of the model applied to crowdsourced observations to promote understanding of the fundamental processes influencing indoor temperature response to summer heat.

How to cite: Peerlings, E. and Steeneveld, G.-J.: Unravelling indoor temperature response to summer heat through long-term crowdsourced observations in Dutch residences, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-559, https://doi.org/10.5194/ems2024-559, 2024.

EMS2024-559

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As a consequence of global warming, heat waves become longer lasting, more frequent, and more intense in extratropical regions. Summer heat stress often occurs simultaneously with drought events causing compound impacts in the affected region. In order to analyze such coincidences in a mid-latitude continental, Central/Eastern European city (i.e., Budapest, the capital of Hungary with 1.7 million inhabitants), local temperature and humidity conditions provided by satellite data, are evaluated. So, the unique 22-year-long time series of continuous measurements from the MODIS instrument on NASA's Terra and Aqua satellites was used to study the surface urban heat island (SUHI) pattern, surface temperature and humidity in detail.

A significant warming trend can already be identified in the surface temperature data during the period of 2001-2022. The analysis of summers shows that the SUHI intensity decreases as the rural area around the city becomes warmer, especially in July and August. When less water is available in the rural area in a drought event, the lack of latent heat thus facilitates the warming of the surface temperature in the rural area as well, as in the urban area, because these conditions are unable to reduce the surface temperature via the latent heat as usual. This way, the SUHI intensity is mainly determined by the rural surface temperature. The SUHI is very weak during summers with frequent and intense heat waves and droughts, due to the fact that the land surface temperatures are very high in both urban and rural areas resulting in very little difference between the built-up area and the vegetation-covered surrounding. This phenomenon is analyzed in the present study in detail for the years 2003, 2007, and 2022, when intense heat waves occurred in the region. Such detailed analysis aiming to understand the complex environmental processes in the urban environment is essential in order to develop effective adaptation strategies to the upcoming challenges of climate change, which will probably result in increasing frequency and persistence of heat waves and droughts in the future, with adverse effects to the quality of the life of the urban population.

Acknowledgements: Research leading to this study has been supported by the Hungarian National Research, Development and Innovation Fund (under grant K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).

How to cite: Pongrácz, R. and Dezső, Z.: Analysis of the compound impact of heat waves and droughts in the urban environment, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-623, https://doi.org/10.5194/ems2024-623, 2024.

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Extreme weather events such as heat waves and heavy precipitation are already having an impact on urban areas around the world, and their frequency and/or intensity are expected to increase as a result of ongoing global warming. Local decision-makers need high-resolution urban climate information to plan and adapt tomorrow's cities. This information needs to be tailored to their needs and to different geographical contexts (e.g. by representing mountainous areas, coastal lines or city characteristics). It must also be appropriate in terms of time scale (e.g. from a particular extreme event to climatological timescales) and cover the range of uncertainties. Today, regional climate information is often derived from Global Climate Models (GCMs) that are downscaled to the local scale using statistical tools, or Regional Climate Models (RCMs) such as those used in the CORDEX initiative. Long-term RCM simulations reach horizontal resolutions of the order of ten kilometers and offer added value in certain respects compared with their driving GCM, but these resolutions are not sufficient in certain specific contexts such as cities, or in highly heterogeneous mountainous areas or along coastlines. The latest generation of RCMs, known as Convection Permitting Regional Climate Models (CPRCMs), now achieve resolution down to the kilometer scale and can be used to better represent these heterogeneous land surfaces, potentially offering new insights into local climate change. Here, we analyze simulations carried out as part of the CORDEX Flagship Pilot Study on Convection (3 km). We first investigate the CPRCMs’ ability to represent the historical urban climate of different European cities, compared with their lower-resolution counterparts. We then study the evolution of various urban climate impact indicators in the future under a high-emissions scenario. We analyze the effects of the increased resolution, choice of urban parameterizations, land cover representation approaches (dominant versus fractional cover approaches) and land cover datasets. Finally, we compare the range of uncertainties displayed by the new high-resolution simulations against the previous CORDEX ensemble.

How to cite: Le Roy, B. and Rechid, D.: What can high-resolution regional climate simulations tell us about the future urban climate of European cities?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-880, https://doi.org/10.5194/ems2024-880, 2024.

EMS2024-880

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Cities play a fundamental role in climate at local to regional scales through modification of heat and moisture fluxes, as well as affecting local atmospheric chemistry and composition, alongside air-pollution dispersion. Vice versa, regional climate change impacts urban areas and is expected to increasingly affect cities and their citizens in the upcoming decades. Simultaneously, the share of the population living in urban areas is growing and is projected to reach about 70 % of the world population by 2050. This is especially critical in connection to extreme events, for instance, heat waves with extremely high temperatures exacerbated by the urban heat island effect, in particular during night-time, with significant consequences for human health. Thus, cities are becoming one of the most vulnerable environments under climate change.

Additionally, from the perspective of recent regional climate model development with increasing resolution down to the city scale, proper parameterization of urban processes plays an important role to understand local/regional climate change. The inclusion of the individual urban processes affecting energy balance and transport (i.e. heat, humidity, momentum fluxes, emissions) via special urban land-surface interaction parameterization of local processes becomes vital to simulate the urban effects properly. This will enable improved assessment of climate change impacts in cities and inform adaptation and/or mitigation options, as well as adequately prepare for climate-related risks (e.g. heat waves, smog conditions, etc.). Actually, IPCC is preparing the Special Report on Cities and Climate Change in 7th assessment cycle, where these aspects will be considered.

We introduced this topic to the CORDEX platform aiming to provide regional climate downscaling, within the framework of so-called flagship pilot studies on challenging issues and gaps in regional climate change knowledge. The main aims and progress of this activity will be presented, especially preliminary analysis of Stage-0 experiments using case studies of heat wave and convection episode within ensemble simulations for City of Paris by models from different groups over the world.

How to cite: Halenka, T., Langendijk, G., and Hoffmann, P.: CORDEX Flagship Pilot Study URB-RCC: Urban Environments and Regional Climate Change, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1084, https://doi.org/10.5194/ems2024-1084, 2024.

EMS2024-1084

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Air pollution is threatening human health worldwide, especially in urban areas. Legislative actions have successfully decreased pollutant concentrations in European countries. However, while exhaust emissions from road traffic have decreased over the last decades, non-exhaust emissions remain and tend to increase. 
In this study, tyre and brake wear emissions are quantified applying a bottom-up model for the city of Hamburg in 2018. Their dispersion and contribution to total particulate matter (PM) concentrations are investigated with the urban scale chemistry transport model EPISODE-CityChem. For this purpose, EPISODE-CityChem 1.8 has been extended to include six new particle components. These are tyre and brake wear in the three size classes: PM_2.5, PM_2.5-10 and PM₁₀₊, airborne particles with a diameter of over 10 µm. The emission factors for PM₁₀ for tyre and brake wear from the National Atmospheric Emission Inventory of the UK are used as a starting point to derive the emission factors for the new particle classes. These are combined with the mass size distribution of the total suspended particles from EMEP.
PM concentrations at traffic stations show a higher monthly mean contribution of tyre and brake wear to the total PM_2.5 and PM₁₀ than at urban background stations. The contribution of tyre and brake wear to the total PM_2.5 concentrations varies throughout the months between 9% and 16% at traffic stations and between 2% and 6% at urban background stations.
The particle concentrations from tyre and brake wear vary locally and seasonally, which could be a difficulty in adhering to the recommended guideline values for particle concentrations, especially since the inner city of Hamburg experiences considerable PM concentrations caused by tyre and brake wear emissions.
The results of this study can be transferred to other large European cities with high traffic volumes and can help to understand the problem's scope, as measurements rarely differentiate between particles caused by exhaust vs. non-exhaust emissions.

How to cite: Samland, M., Badeke, R., Grawe, D., and Matthias, V.: Estimation of particle concentrations from tyre and brake wear in an urban environment, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-923, https://doi.org/10.5194/ems2024-923, 2024.

EMS2024-923

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Cool roofs have higher solar reflectance and thermal emissivity than conventional roofs, decreasing the temperature of buildings during sunlight hours. This benefits the buildings (reducing the cooling loads) and the environment (improving the outdoor thermal comfort) during summer. However, cool roofs' impact on outdoor air quality is not well known.

Computational Fluid Dynamic (CFD) models allow the evaluation of environmental improvement measures at very high spatial resolution. Nevertheless, microscale studies combining outdoor thermal comfort and air quality at district or city scales have been scarce in the literature due to the computational cost involved.

The objective of this work is to estimate the impact of cool roofs on outdoor thermal comfort and air quality at the district scale. For this purpose, a CFD model is used considering:

• atmospheric flows through a URANS (Unsteady Reynolds-Averaged Navier-Stokes) approach
• traffic-related NO_X dispersion as a passive scalar
• thermal loads using a complete radiation model (solar radiation, radiation from the environment, transmission through non-opaque surfaces, and emission from non-transparent surfaces)
• thermal and optical properties of the building envelope
• energy storage in walls, floors and roofs (in glazing is negligible) through a non-steady state conjugate heat transfer model between the outdoor and indoor

Firstly, some scenarios of the COSMO experiment (Kawai et al., 2007) are simulated to evaluate the model performance. Finally, the cool roof impact is estimated during 24 hours of a heat wave episode in a district of Madrid (Spain), characterized by a regular morphology (aligned blocks of H=15 m and H/W=1).

Results show that cool roofs modify the urban meteorology (mean radiant temperature, air temperature, wind speed and turbulent kinetic energy), decreasing the Universal Thermal Climate Index, UTCI, at pedestrian height, especially upstream and during hours of higher irradiance. However, depending on the wind speed, cool roofs can generate thermal inversions at building height affecting the pollutant dispersion within the streets. This fact increases the pollutant concentration at pedestrian height.

How to cite: Rivas Ramos, E., Martilli, A., Santiago del Río, J. L., Meier, F., Sánchez Sánchez, B., and Martín Llorente, F.: Impact of cool roofs on thermal comfort and air quality at street level during a heat wave episode in Madrid, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-764, https://doi.org/10.5194/ems2024-764, 2024.

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The most significant environmental health risk for the European population is air pollution, especially for people living in urban areas. Fine particulate matter (PM), a mixture of aerosols with an aerodynamic diameter less than or equal to 2.5 μm, is among the pollutants with the most critical threat to human health in European urban areas. Despite the substantial spatial and temporal variability of the chemical composition of fine PM in Central Europe, it is generally dominated by organic matter and secondary inorganic aerosols, with organic matter being the main contributor to total submicron PM.

Modeling organic aerosol using chemical transport models (CTMs) has been problematic for decades, with CTMs often underestimating its concentrations. Potential sources of this deficiency in CTMs include:

(1) simplifying assumptions applied in the model description of organic aerosol,

(2) uncertainties in the model mechanisms describing gas phase chemistry since these mechanisms determine the concentrations of gaseous precursors of secondary organic aerosol,

(3) missing emissions of intermediate-volatility and semivolatile organic compounds (IVOCs and SVOCs) in emission inventories used in CTM simulations.

In this work, we focused on investigating the impacts of these sources of uncertainty on the concentrations of organic aerosol in six large cities of the Central European region (Prague, Vienna, Budapest, Berlin, Munich, and Warsaw). For this purpose, we performed a series of model simulations employing an offline coupled modeling framework consisting of the Weather Research and Forecast (WRF) Model and the Comprehensive Air quality Model with Extensions (CAMx) on the Central European domain with a horizontal resolution of 9 km for the period covering the years 2018 and 2019. More specifically, we focused on assessing the influence of two mechanisms for organic aerosol (SOAP, 1.5-D VBS), three mechanisms of gas-phase chemistry (CB6r2, CB6r5, and SAPRC07TC), and several different source-specific parameterizations of IVOCs and SVOCs.

How to cite: Bartík, L., Huszár, P., Karlický, J., and Vlček, O.: Modeling secondary organic aerosol over urban areas of Central Europe: uncertainties linked to different mechanisms and parameterizations, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-232, https://doi.org/10.5194/ems2024-232, 2024.

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Recently, Kulmala et al. (2021) proposed that in eastern China, a cluster of megacities could be classified as one huge continuous urban area – a gigacity. Already now about 10% of the global population is living in the Chinese Gigacity confined roughly by the lines Shanghai-Xian-Beijing. Gigacity region has huge areas of increased surface roughness and urban heat and pollution islands. These together can strongly influence the local scale meteorology (Ding et al., 2016; Kokkonen et al., 2019).

There are essentially three different meteorological pollution regimes in the Chinese gigacity area having different driving processes of haze: 1) strong synoptic scale winds, leads to effective ventilation of the urban areas and transports local emissions to areas outside gigacity, frequent new particle formation (NPF) due to low condensation sink with sufficient amount of precursor gases available, 2) weak synoptic scale winds, local circulation with clear diurnal cycle is dominating (e.g., mountain-valley and land-sea breeze), local emissions with frequent NPF events together with weakening boundary layer dynamics (BLD) are deteriorating the air quality and slowly pushes the conditions towards the next regime, and 3) haze formed through a mixture of long-range transport, NPF, and local emissions, suppressed radiative driven local circulation (e.g., mountain-valley breeze) and BLD, stagnant conditions with no effective ventilation and the air quality is deteriorating further.

Moreover, boundary layer dynamics – as well as meteorological conditions in general – are interlinked with the pollution regimes, e.g., changes in meteorological or pollution conditions might cause shifts in either way in different regimes described.

We are utilizing continuous, comprehensive observations of atmospheric composition and fluxes from two flagship stations in the gigacity region: the SORPES in Nanjing (Ding et al., 2016) and the BUCT-AHL in Beijing (Liu et al., 2020). In addition, the national meteorological and air quality networks will enable spatial analyses together with reanalysis data.

We are focusing especially on: 1) how boundary layer dynamics and local and synoptic scale meteorological conditions affect haze severity and vice versa, 2) the effect of gigacity heat and pollution islands and surface roughness on atmospheric circulation and precipitation. Our preliminary results have shown e.g. that in Beijing the radiative effect of haze on the BLH has a strong seasonal behaviour with a dependence on the surface heat fluxes. The effect was strongest during autumn, winter and spring months when the decrease of BLH was 40–56 % due to the haze.

Ding et al., Geophys Res Lett, 43, 2873-2879, 2016.

Kokkonen et al., Atmos Chem Phys, 19, 7001-7017, 2019.

Kulmala et al., Atmos. Chem. Phys., 21, 8313-8322, 2021.

Kulmala et al., Environ Sci Atmos, 2, 352-361, 2022.

Liu et al., Big Earth Data, 4, 295-321, 2020.

How to cite: Kokkonen, T., Ciarelli, G., Xia, M., Liu, Y., Yan, C., Nie, W., Ding, A., Kerminen, V.-M., Petäjä, T., and Kulmala, M.: The interactions of multiscale meteorology and haze in the Chinese gigacity, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-928, https://doi.org/10.5194/ems2024-928, 2024.

EMS2024-928

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Large fractions of atmospheric aerosols, both locally and globally, relevant to air quality and climate are produced via new particle formation (NPF; Kerminen et al., 2018; Chu et al., 2019; Kulmala et al., 2021). Kulmala et al. (2021) showed that NPF and secondary aerosol formation contribute to over 2/3 of the haze particle number and over 80% of the corresponding mass in Beijing.

We combine the following tools to find out physical and chemical mechanisms of atmospheric NPF: i) targeted laboratory experiments, ii) comprehensive in situ observations, iii) comprehensive vertical observations, iv) satellite remote sensing and v) multi-scale modelling.

We investigated a closure on sub-6 nm atmospheric aerosol particles and clusters showing that present observations can detect a major fraction of existing atmospheric clusters (Kulmala et al. 2022a). Our second finding, based on long-term measurements in four very different environments, was that even on days traditionally considered as non-event days (no observed NPF), “quiet NPF” occurs with formation rates between 2–20% of traditional NPF event days (Kulmala et al. 2022b). Thirdly, we investigated the growth of newly-formed particles into sizes relevant to climate and air quality using simulations in two different environments: 1) Beijing, a megacity in China, and 2) SMEAR II station, a boreal forest in Finland. Our simulations for Beijing showed that NPF is capable of giving large contributions of haze particle mass and number concentrations (Kulmala et al. 2022c). The results indicate that reducing primary particle emissions may not decrease PM pollution effectively in heavily polluted environments without simultaneous reductions for precursor gases responsible for NPF and subsequent particle growth. At SMEAR II, we simulated the role of NPF in the Continental Biosphere-Atmosphere-Cloud-Climate (COBACC) feedback mechanism (Kulmala et al. 2023). We found that outside the periods when NPF events tend to be rare at SMEAR II, NPF gives a dominant contribution to both condensation sink and cloud condensation nuclei concentration – the two most relevant quantities in the COBACC feedback mechanism. As a side product of our observations, we found surprisingly low variability in growth rates of newly formed particles in both Beijing and SMEAR II. This points toward a potentially important role of multiphase reactions causing the bulk growth of newly formed atmospheric particles – a phenomenon that needs to be investigated in more detail in the future.

Chu, B. et al., Atmos. Chem. Phys., 19, 115–138, 2019.

Kerminen et al., Environ. Res. Lett., 13, 103003, 2018.

Kulmala et al., Faraday Discuss., 226, 334–347, 2021.

Kulmala et al., J. Aerosol Sci., 159, 105878, 2022a.

Kulmala et al., Front. Environ. Sci., 10, 912385, 2022b.

Kulmala et al., Environ. Sci.: Atmos., 2, 352-361, 2022c.

Kulmala et al., Boreal. Env. Res., 28, 1-13, 2023.

How to cite: Kulmala, M. and the Working group: The impact of atmospheric new particle formation on air quality, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-935, https://doi.org/10.5194/ems2024-935, 2024.

EMS2024-935

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Climate change and air quality research are closely related research areas that have often been investigated with different objectives. However, addressing both topics as a joint approach can lead to synergies and help to avoid counteracting effects, where mitigating one may exacerbate the other. The convergence of methods and approaches is necessary to consider on the one hand the climate trend and forcing in mitigation scenarios applied by the air quality community and on the other hand to better understand and describe the impact of short-lived climate pollutants on the regional climate.

The project FOCI aims to analyse non-CO2 forcings on both climate and air quality and therefore requires a joint approach. A core task of the project is the application of regional climate and urban scale models driven by global earth system models to describe continental to urban scale air quality under present and future climate conditions. The results of these processes will be used to investigate possible mitigation and adaptation scenario options.

The present and future anthropogenic emissions required for such model investigations need to be consistent with CMIP6 historical climate reconstruction and future scenario simulations. CMIP6 has been based on CEDS emissions that are therefore the necessary reference for FOCI activities. One critical aspect is that pollutants considered in CEDS do not include particulate matter (PM2.5 and PM10), but only its black carbon (BC) and organic carbon (OC) components. This is understandable considering the objective for which CEDS has been built, but it would cause a significant underestimation of particulate matter concentrations and raises the need to define a method to estimate the non-speciated PM2.5 and PM10 emissions from the available information.

In order to derive PM emissions for CEDS we investigate a number of approaches based on the use of different proxies from the EDGAR database. In particular, we consider the feasibility of deriving PM2.5 from BC and OC as the main components of fine particulate matter. For emission sectors where BC and OC is not available in the emission inventories, we explore the possibility of using alternative proxies including NOx. By combining the different approaches we derive PM2.5 emissions for CEDS at a spatial grid resolution of 0.1 degree and compare these for each main emissions sector.

These estimated dataset of consistent CEDS and particulate matter emissions are used in the FOCI project numerical models to describe continental to urban scale air quality under present climate conditions. We also discuss the implications of employing our approach to derive consistent emissions for particulate matter in conjunction with SSP emission data for projections to ultimately evaluate the impact of key radiative forcers on climate and societal systems.

How to cite: Grawe, D., Alyuz, U., Arghavani, S., Boorman, P., Finardi, S., Halenka, T., Radice, P., Samland, M., Sokhi, R., and Troccoli, A.: Harmonisation of historical and future emission data for climate and air quality modelling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-973, https://doi.org/10.5194/ems2024-973, 2024.

EMS2024-973

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This study models the dispersion of historic air pollution from pottery kilns in the Roman city Augusta Treverorum (Trier). It aims to improve the understanding of their impact on urban air quality during different historical phases. Utilizing archaeological data on pottery locations and historical urban growth patterns, we simulated air pollution levels across the city, focusing on periods before and after the relocation of pottery kilns from various sites spread out over the settlement area to a confined pottery district near the Mosel River. This district is locate in the southwest corner of the city, which is striking as this position is upwind to the city center for the most frequent wind directions along the valley axis. All modern smoke-emitting industry accordingly is found in the opposite northeastern part of the city.

For the simulation we used the German regulatory pollution dispersion model AUSTAL, driven by weather data from the European reanalysis. The sources were modeled after measurements taken during experimental pottery production by LEIZA, Mains in a reconstructed kiln. We found that pollution from the sites spread out over the city predominantly affected the city's northern half, where significant buildings such as the Emperor's Palace and temples were located. The production sites in the pottery district, in contrast, have been impacting the southern part of the city, that must have been a predominantly residential area. This impact is rather independent from the location of a kiln inside the pottery district. The results suggests that this pattern is not a random outcome, but a result urban planning decisions in Augusta Treverorum that were influenced by air pollution, demonstrating a historic example of industrial activity's environmental implications.

How to cite: Drüe, C.: A Simulation Study Air Pollution Impact from Roman Potteries in Augusta Treverorum (Trier), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-999, https://doi.org/10.5194/ems2024-999, 2024.

EMS2024-999

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Oxygenated volatile organic compounds (OVOCs) affect the formation of atmospheric ozone (O₃), secondary organic aerosol (SOA), and free radicals, and have complex sources such as anthropogenic and biogenic direct emissions and through series of secondary oxidation reactions of nonmethane hydrocarbons (NMHCs). However, understanding sources of OVOCs in the atmosphere still has large uncertainties. In this study, an improved OVOC source apportionment model was developed by principal component analysis (PCA) and multiple linear regression (MLR) based on the online monitoring of NMHCs and OVOCs in a dense urban agglomeration in the winter. The modelled concentrations were in good agreement with the measured concentrations (R²=0.56-0.97). The concentrations of major OVOCs, except for 2-methylacrolein, were greatly affected by anthropogenic sources (15.8-76.8%) and secondary generation (0.0-51.7%), while transport and natural sources contributed to 0.0-26.8% and 0.0-32.0%, respectively. The selection of isoprene as the natural tracer led to an underestimation of the OVOC species from primary emission and an overestimation from natural sources. In addition, photochemical reactions significantly reduced the simulation accuracy of the model for NMHCs in the afternoon, with the R² of 0.60 ± 0.23, which was lower than the overall value of 0.82 ± 0.11. However, the R² for OVOCs (0.83±0.14) did not decrease significantly in the afternoon due to the compensation of secondary oxidation. Furthermore, the concentration gradient distribution of the species gradually changes from a normal distribution to an exponential normal distribution with a decrease in concentration, the accuracy of the model was influenced by the degree of matching between tracer and species concentration gradient as species concentration change. Developing models with additional tracers at different concentration levels may enhance the robustness of the OVOC source apportionment model without increasing its complexity.

How to cite: Zou, Y., Guan, X., Flores, R., Yan, X., Fan, L., Deng, T., Deng, X., and Ye, D.: OVOCs source analysis based on an improved source apportionment model and its influencing factors: A case study of a dense urban agglomeration in the winter, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-93, https://doi.org/10.5194/ems2024-93, 2024.

EMS2024-93

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The urban population is particularly affected by the consequences of climate change. The increasing frequency and intensity of extreme weather events such as heat, drought, extreme precipitation and flooding has significant negative effects on human comfort, well-being, health and mortality rate. Sustainable urban development therefore requires the implementation of climate change adaptation measures as well as the acceptance, activation and participation of urban dwellers. The feasibility and effectiveness of climate change adaptation measures vary spatially due to the given local conditions. Additionally, the awareness, ability and willingness to act and pay differ between social milieus. The aim of this study is to analyse how a difference in the milieu-related willingness to act and operational ability to implement climate change adaptation measures affects the heat mitigation potential in two neighbourhoods in the city of Cologne/Germany with a significantly different social milieu composition. To investigate the relationship between the degree of willingness to act and the cooling effects of technical and nature-based solutions for heat mitigation, scenario analyses are performed using the physically-based, 3D gridded urban microclimate model ENVI-met for a neighbourhood in Cologne Suedstadt which is dominated by the social milieus of performers, post-materialists, neo-ecologists and conservatives. The model was parameterized based on field measurements and remote sensing data, and has been validated by a setup quality-controlled, densely-distributed microclimate sensor network in the study area. The agent-based scenarios represent a different percentage of residents willing to implement climate change adaptation measures in their living environment. These measures include facade greenings, roof greenings, cooling building materials and light surfaces. To identify the microclimate sensitivity, a scenario with a willingness to act of 0%, 25%, 50%, 75% and 100% of all dwellers in the neighbourhood is designed in the model domain. Simulation results show that the willingness to act has a significant influence on the cooling effect and thus the heat mitigation potential in this study area. In future research, the willingness to act in this upper-middle class neighborhood will be compared to a neighbourhood in Cologne Muelheim which has a significantly different social structure and is dominated by consumer-hedonism and traditional milieus. It will also be investigated how citizen science approaches, participation and activation measures can change the willingness to act and the acceptance of climate change adaptation measures in these contrary urban neighborhoods. 

How to cite: Eingrüber, N., Schneider, K., Nehren, U., and Dlugoß, V.: Climate change adaptation through citizen participation: Simulation of the effect of willingness to act on the heat mitigation potential in urban neighborhoods with different social milieu composition , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-547, https://doi.org/10.5194/ems2024-547, 2024.

EMS2024-547

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As Climate Change challenges threaten future quality of life, urgent action to mitigate CO2 emissions as well as to adapt to current and future risks is mandatory. Cities are crucial for both areas: mitigation, because 2/3 of the world wide population live in urban areas and thus cause XX emissions; adaptation: because the settlements structure, mainly sealed areas, enhances the negative effects of climate change. Within the Horizon Europe Research and Innovation Action KNOWING [1] climate mitigation pathways, which represent timelines of specific interventions, are compiled for different regions.

Urban areas are a core region type within KNOWING as they are particularly vulnerable towards climate change. Over the past years cities have responded by defining strategies regarding mitigation and adaptation that identify measures for specific sectors. Although there is vast knowledge with respect to future impacts and possible mitigation and adaptation measures within different sectors (e.g. transport, energy, etc.), implementation remains inadequateExisting strategies often tackle the different sectors separately, thus ignoring possible spill-over and rebound effects of one measure taken to other areas

KNOWING develops a framework for defining Climate Mitigation Pathways based on understanding and integrated assessment of climate impacts, adaptation strategies and societal transformation. The modelling framework will be used to assess the interrelations between potential risks of climate responses, i.e., public and private adaptation and mitigation strategies. For instance, the installation of air conditioning can improve living conditions inside, but it also has a two-fold negatively impact due to its heat and CO2 emissions.

To quantify the interrelations, the chosen comprehensive approach builds upon a system dynamics (SD) model for quantifying cross-sectoral influences of measures taken in different sectors (e.g., energy, mobility, land use, construction, agriculture) affecting the overall emission budget. Therefore, specific so-called domain models for mitigation (e.g. energy demand model MAED-City, energy supply IES-opt) and adaptation (e.g. urban climate PALM4U, flooding model SFINCS, ICM-Infowork) are applied, fed with high resolution (5x5km) WRF input data. Based on this systems perspective, mitigation pathways along optimised combinations of interventions in the different sectors are developed. The framework also includes a coping behaviour model that provides guidance on how measures can be implemented in an equitable way to enable a just and broadly supported transition.

How to cite: Bügelmayer-Blaschek, M., Millonig, A., and Zach, M.: Climate Mitigation Pathways for Cities – enabling a just transition through quantified actions?, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-606, https://doi.org/10.5194/ems2024-606, 2024.

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How to cite: Soler, J., Martinez, M., Goler, R., Bügelmayer-Blaschek, M., Schneider, M., and Hochebner, A.: Climate risks in cities – how flooding and heat prevention can be tackled holistically. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-765, https://doi.org/10.5194/ems2024-765, 2024.

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The subject of this project is centered in the adaptation to climate change during heat waves in the 21st century in the area of Grenoble, France. The adaptation measures concern urban planning, such as the vegetation of the city, the increase of the albedo of buildings, design of water bodies distribution and others. Particular attention is paid to the impact of these measures on air quality. The objective is to determine, the urban planning to be implemented to combat the increase in temperatures due to climate change.

This work relies on the widely used open-source atmospheric numerical model WRF (Weather Research and Forecast). First, a calibration run is performed over a past heat wave event in the valley for verification and obtention of the conditions that produce higher fidelity results contrasted with real measures of the event. This involving especially the land cover description and model parametrization. After, an analog model run over a future heat wave event in 2052 extracted from climate projections. This is used as a control run to compare with different results, where adaptation scenarios to combat climate change are applied.

For the study of different urban planning scenarios, the WRF model is used coupled with the model BEP+BEM (Building Effect Parametrization + Building Energy Model), developed by Alberto Martilli, with whom we work in collaboration. This model parametrizes the urban-atmosphere interaction with a high-level representation of the city that allows for designing different scenarios regarding the land cover, the albedo and the urban canopy.

The location of the study makes this project of great interest as well as computationally challenging, due to the mountainous area and steeps slopes surrounding the city. These results will be of great interest to local communities and policy makers as they will inform future decisions on urban planning and will contribute to the attractiveness of cities.

How to cite: Gabeiras, J., Staquet, C., and Chemel, C.: Adaptation scenarios to climate change during heatwaves in the Grenoble metropolitan area, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1082, https://doi.org/10.5194/ems2024-1082, 2024.

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The effects of climate change have never been as pronounced as they are now, however, simultaneously, urban areas are experiencing additional local-scale anthropogenic effects due to the modification of the natural environment. Consequently, urban heat islands form, amplifying the heat load in the cities and heightening the vulnerability of citizens to heat-related issues.

In the context of Europe, the fastest-warming continent in the world, significant impacts on living conditions will occur as a result of numerous climate risks. Furthermore, in a recently published European Climate Risk Assessment, heat risk is identified as one of the two main risks for which urgent action is needed. However, implementing mitigation measures in urban areas is often slow, highlighting the need to employ geospatial technologies to aid the process.

To address this issue, we identified high heat risk areas and heat-resilient zones in the city of Milan, Italy. High-resolution geospatial datasets, including remotely sensed imagery and official/crowd-sourced in-situ data, were utilised for producing a heat risk index. Main known drivers of heat risk were used as predictors, such as land surface and air temperature, vegetation fraction, surface material composition and others.

The produced heat risk maps were overlayed with population data, selecting the locations of public institutions most used by vulnerable populations - schools, retirement homes, and public health institutions. Institutions’ surroundings have been investigated based on urban geometry, considering their micro-urban morphology and at the neighbourhood scale with local climate zones. Moreover, the research examined the frequency of extreme temperatures occurring in various areas of the city over time and put it in relation to vulnerable population data.

Through detailed analysis of city-scale heat risk, the study has identified the main hotspots and cool spots within the city. The research findings are critical for vulnerable populations facing high heat risks, enabling targeted and straightforward implementation of appropriate heat mitigation measures. Finally, the utilisation of high-resolution geospatial information and multiscale datasets can aid city planners, providing them with crucial scientific insights for informed decisions.

How to cite: Žgela, M., Vavassori, A., and Brovelli, M. A.: A geospatial approach for heat risk estimation by integrating remotely sensed and ground-based data in Milan, Italy, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-727, https://doi.org/10.5194/ems2024-727, 2024.

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Wind flow predictions in realistic urban areas are sensitive to a wide range of governing parameters such as building resolution, wind incidence, urban morphology, and underlying topography to list a few. In this study, we quantify the impact of the level of detail (LoD) of the urban built environment and the inflow direction (θ) on wind-safety for urban-air mobility using a Reynolds-Averaged Navier-Stokes (RANS) simulation framework. To isolate the effect of LoD and θ, we chose the TU Delft campus (radius of ~ 1 km) and the city of Den Haag (radius of ~ 1.5 km) as representative urban environments that contain a variety of urban fabric and incident wind conditions.

The simulation framework consists of steady state Reynolds-Averaged Navier-Stokes simulations using a second-order accurate finite volume formulation that solves the governing equations using the SIMPLE algorithm at 5-degree resolution (i.e., 72 θ’s over a 360-degree range) with a reference wind velocity of 5 m/s at 10 m above the ground. In addition to varying the inflow wind direction, we also compare two LoD’s, specifically, LoD1.2 (lower quality of building resolution, industry standard for wind engineering simulations) and LoD2.2 (higher quality of building resolution), resulting in a total of 288 simulations.

First, we assessed the effect of θ resolution on the prediction capabilities of the wind-rose weighted directionally-averaged peak wind velocities (U_a) and found that when compared to the 5-degree resolution cases with 10-, 15-, and 20-degree resolution, there is a selection bias on how accurately high-wind regions are predicted. Specifically, when the U_a is computed using 5- and 15-degree resolution, there is a better agreement as opposed to the 10- and 20-degree resolution case. These results suggest that even with a minimum resolution of 10-degree’s (for θ) the peak U_a locations can be subject to a selection bias for both, simple and relatively complex wind-roses. Next, we studied the effect of varying LoD’s and found that LoD2.2 shows substantially different peak U_a regions when compared to LoD1.2. Directly comparing these two LoDs, we find that minimally LoD2.2 should be used for cases where peak U_a are of interest at approximately 10-20 m height above the ground which are of most interest in terms of urban air mobility.

This work represents a systematic review of the effect of wind incidence direction and level of detail on the flow prediction capabilities in realistic urban environments. We anticipate that our findings will be useful to urban planners and engineers working to improve the air-quality, wind comfort, and explore the possibilities of UAV’s as a potential mode of last mile mobility within the urban-air space, to list a few.

How to cite: Patil, A. and Garcia-Sanchez, C.: Understanding the impact of varying geometry level of detail in multi-direction urban RANS simulations tailored for urban air-mobility viability., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-354, https://doi.org/10.5194/ems2024-354, 2024.

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The interaction between urban microclimate and building energy balance is pivotal in comprehending urban thermal behavior, with buildings' energy use contributing to waste heat that affects the intricate mass and momentum transactions characteristic of urban microclimates. Large-Eddy Simulation (LES) models have improved insights into these complex dynamics due to increased computational power. However, complexities and data uncertainties in real urban settings may compromise LES accuracy. Therefore, understanding model sensitivity to input data uncertainties is crucial for assessing potential deviations and prioritizing data collection parameters.

This study scrutinizes the PALM model 6.0's sensitivity to building typologies and parameters within a residential quarter of Bochum, Germany, examining the trade-offs of modeling detail. Four divergent scenarios are considered. The baseline scenario presupposes homogeneity in building types across the model domain. The second scenario applies PALM’s standard building categories, predominantly delineating four types aligned with building age and building use. The third scenario encompasses an array of 28 building typologies, integrating the TABULA archetypes from the IEE Project 'Typology Approach for Building Stock Energy Assessment'. The first three scenarios maintain a consistent level of architectural specificity within the parent and the child domain, configured as a nesting structure. The fourth scenario distinguishes itself by combining PALM's predefined standard building typologies within the parent domain with the 28 distinct TABULA archetypes within the child domain. ​The underlying hypothesis suggests that increasing the detail in building parameters can potentially amplify the realism of urban environment simulations and augment the accuracy of the results. However, such advancements come with heightened computational demands and more extensive data requirements. The study emphasizes the importance of balancing these considerations to ascertain the most advantageous degree of detail, tailored to various simulation pursuits.

How to cite: Nowzamani, N., Maronga, B., van der Linden, L., and Bechtel, B.: Analyzing the Sensitivity of the LES PALM Model to Building Parameters Using an Archetype-Based Approach, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-382, https://doi.org/10.5194/ems2024-382, 2024.

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Gaps in urban meteorological time series are a widely known phenomenon, occurring in all sorts of urban datasets, ranging from crowd-sourced data till urban climate networks. These gaps cause a problem, since they complicate the analysis and further use of the dataset. Various gap-filling techniques exist to tackle gaps in meteorological time series, including the debiasing of ERA5 reanalysis data. Unfortunately, the evaluation of these ERA5 debiasing techniques are often performed separately and limited to rural locations. Since the ERA5 bias is highly pronounced for urban locations, a good understanding of the performances of the debiasing techniques with respect to urban data is crucial to obtain accurate gap-filling estimates.

To gain a better insight into the most optimal gap-filling techniques for urban temperature time series, we compared five techniques, including three different debiasing techniques that employ a learning period and time window to take into account the seasonal and diurnal characteristics of the ERA5 temperature bias. The evaluation, which is performed by filling manually constructed gaps, shows that small gaps are ideally filled by linear interpolation, while for larger gaps the best performance is obtained through the ERA5 debiasing techniques. For urban locations, the results indicate that it is crucial to correct for the ERA5 bias. We also investigated the most optimal length and placement of the learning period and time window, although the settings of these parameters do not seem to have a significant impact on the gap-filling performance. Based on these results, we designed a gap-filling algorithm that efficiently fills a series of gaps in urban temperature time series by selecting the most optimal gap-filling procedure for each gap. This newly designed algorithm is able to successfully reproduce the urban heat island effect, although a small over- or underestimation might occur.

How to cite: Jacobs, A., Top, S., Vergauwen, T., and Caluwaerts, S.: Filling gaps in urban temperature observations by debiasing ERA5 reanalysis data, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-492, https://doi.org/10.5194/ems2024-492, 2024.

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Urban areas face unprecedented challenges due to the combination of growing cities and climate change, with impacts ranging from heatwaves and extreme precipitation to sea-level rise and urban flooding. Artificial surfaces in cities and the differences in the surface structure cause urban areas to overheat significantly compared to rural areas and lead to a high inner-city air temperature variability. As climate change and heat forcing increase, the urban heat island effect will intensify in the future. Understanding the future climate scenarios is crucial for effective planning of adaptation and mitigation strategies.

Climate projections referred to as Global Climate Models (GCMs) and Regional Climate Models (RCMs) do not accurately represent urban-scale climate variables. Computational constraints and limitations in simulating the complexity of earth system processes limit the spatial resolution of climate projections to the order of 10 – 100 km and the time resolution to a daily basis. Hence, climate models are not able to fully resolve the urban heat island effect and the urban air temperature variability which occur on a micro-scale.

This work highlights the importance of downscaled climate prediction data to capture localized effects and uncertainties associated with urban areas. Downscaling climate models to building-level is done by combining the meteoblue City Climate Model (mCCM) - a dynamic statistical downscaling model - with climate projections in the framework of the sixth phase of the Coupled Model Intercomparison Project (CMIP6).

The mCCM is based on a high-resolution model grid with a horizontal resolution of 10 m. It resolves the differences in the surface energy budget and help understanding the air temperature variability and dynamics in an urban environment. The model is fully driven by surface texture parameters derived from high-resolution satellites and meso-scale NWP models. In this framework, the climate signal of CMIP6 data is added to the hourly air temperature time series of the mCCM. This allows the calculation of temperature-related climate indices on a high-resolution grid of 10 m for future time periods and various SSP scenarios. Furthermore, this approach allows to estimate the probability that certain climate indices such as e.g., number of tropical nights, or number of hot days reach a critical threshold.

Enhancing the mCCM with climate predictions creates a reliable information basis for city planners, decision makers, and companies. It helps cities become more resilient, sustainable, and adaptable in the face of a changing climate, ultimately improving the quality of life for urban residents.

How to cite: Bader, N., Zurfluh, N., Shin, J., and Schlögl, S.: Enhance the meteoblue City Climate Model by Climate Projections to assess Urban Climate Hazard, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-639, https://doi.org/10.5194/ems2024-639, 2024.

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Radiative exchange in the complex 3-D urban geometry is a crucial physical process for the urban heat island, building energy consumption, and outdoor human thermal comfort. Urban canopy models calculate radiative exchange by simplifying both urban morphology (e.g. by an infinitely-long street canyon or a regular array of square blocs) and radiative transfer physics. Radiative exchanges are usually calculated with the radiosity method assuming that there is vacuum in the urban canopy layer and that urban materials have a broadband Lambertian reflectivity. This introduces systematic biases, since uniform radiosity on surfaces is assumed and because the distribution of wall-to-wall and ground-to-wall distances corresponds to the simplified morphologies and is therefore systematically different to the one in real districts. Furthermore, it is difficult to take into account a variety of building height, urban vegetation with complex shape, and physical processes like specular reflections by windows, spectral materials, and interaction of radiation with air, aerosols, or clouds in the urban canopy layer. The urban radiation model SPARTACUS-Urban is based on a more realistic hypothesis of urban morphology (exponential distribution of wall-to-wall and ground-to-wall distances), and tree geometry (cylinders). It solves radiative transfer with the Discrete Ordinate Method. This allows to take into account more complex urban geometry and the mentioned physical processes. The urban canopy model Town Energy Balance (TEB) is coupled with SPARTACUS-Urban and the new TEB-SPARTACUS is available in the open-source land surface model SURFEXv9.0. TEB-SPARTACUS keeps the geometrical simplicity of the original TEB, which is that there is no variety of building and tree height at grid point scale. The TEB-SPARTACUS results for the direct and diffuse solar, and the terrestrial urban radiation budget are evaluated for procedurally-generated urban morphologies mimicking the Local Climate Zones (LCZ). Evaluation is made by comparison with results of the newly-developed Monte-Carlo-based reference model HTRDR-Urban. HTRDR-Urban can produce reference results of radiative flux densities in complex urban geometries, including spectral and specular materials, trees with individual leaves, and the participating atmosphere. It is shown that TEB-SPARTACUS improves the solar and terrestrial urban radiation budget for all LCZ, the improvement of radiative observables can be up to 10% of the downwelling solar radiation. A considerable improvement is found for the partitioning between the direct solar radiation absorbed by the walls and the ground. This might help to improve the simulated building energy consumption, and outdoor human thermal comfort. TEB-SPARTACUS also simulates better the impact of trees on the urban radiation budget since it better represents the tree edges. Therefore, TEB-SPARTACUS could help to improve the simulated evapotranspiration or CO₂ uptake by urban trees.

How to cite: Schoetter, R., Hogan, R., Caliot, C., and Masson, V.: Coupling the Town Energy Balance with the urban radiation model SPARTACUS-Urban and evaluation with a Monte-Carlo-based reference model, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-49, https://doi.org/10.5194/ems2024-49, 2024.

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The summer of 2022 has experienced several heat waves that were observed over Paris area by a unique network of instruments set up as part of several measurement campaigns gathered under the PANAME 2022 label. In particular, Advanced remote sensing instruments were deployed in a network of unprecedented detail to gather novel profile observations of temperature, wind and aerosol, allowing to characterize the vertical, spatial and temporal variabilities of the atmospheric boundary layer.

The first analyses of these observations were able to highlight the complexity of the processes involved to explain the spatial and temporal variability of temperatures measured during the heat waves of June and July. In particular, marked differences between urban and rural areas are noted, and a high variability in boundary layer heights exists over the period. Wind Doppler lidar and microwave radiometers show the establishment of nocturnal low level jets on some nights and the entrainment of warm tropospheric air in the boundary layer at the end of the period in July when the warmest temperatures were measured. The summer 2022 campaign has also been complemented by a summer 2023's one.

The aim of this study is to take advantages of this observational network to better assess the ability of the WRF model torepresentthespatialandtemporalvariabilitiesof urban heatwavesattheresolution of 3km, which is the horizontal resolution used to perform convective-permitting climate simulations. An assessment of the capability of these simulations to study the interactions between climate and urban areas is needed to ensure that vulnerability of cities to climate change and the implementation of specific adaptation policies to make cities more resilient to extreme events can be evaluated with this tool. A set of simulations(3km) was carried out with different configurations and physical parameterizations to test the sensitivity of the WRF model. In particular the role of a better description of cities using WUDAPT dataset and the activation or not of an urban scheme - which makes it possible to better take into account the urban effects related to the density of buildings, their heat capacity, their roughness etc...- will be analyzed.

How to cite: Bastin, S., Kotthaus, S., Fita, L., Lalonde, M., and Haeffelin, M.: Ability and Sensitivity of WRF configurations in climate mode to represent urban heat waves' characteristics observed over Paris area during summers 2022 and 2023, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-876, https://doi.org/10.5194/ems2024-876, 2024.

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Air temperature (Ta) plays a crucial role in numerous applications, including studies on physical stress conditions and understanding phenomena such as urban heat island (UHI). Ta measurements, acquired from in situ sensors often distributed unevenly, are limited in describing the spatial temperature field pattern. On the other hand, land surface temperature measurements (LST) obtained from geostationary satellites provide a more detailed spatial overview, but represent a different variable. In this work, a method based on machine learning algorithms is presented for converting LST detected from geostationary satellites MSG, into air temperature. To perform the conversion, a gradient boosting algorithm, which is part of the tree-structured family of machine learning algorithms, was implemented. The method is applied to LST and Ta data available for the city of Rome (Italy) during the summers of 2019 and 2020. The Ta data are sourced from 17 weather stations, predominantly consisting of amateur stations whose quality has been verified. Using predictive variables such as instantaneous LST and with delays ranging from 1 to 4 hours, along with other parameters like altitude, imperviousness, land cover, tree cover, grassland, NDVI, and temporal parameters such as time of day, Ta was estimated, designated as the target variable, at points where no in situ measurement sensors are available. The Ta predicted by the model exhibits an average error of 1.2°C during the daytime and 0.8°C at night. This model output has improved the accuracy and spatial resolution of temperature pattern analysis across the city of Rome, compared to analyses based solely on in situ measurements. Furthermore, the spatiotemporal pattern of the UHI, which can now be measured at high resolution, aligns well with the expected pattern.

How to cite: Cecilia, A., Casasanta, G., Petenko, I., Conidi, A., and Argentini, S.: A machine learning algorithm for converting land surface temperature to air temperature and testing in the determination of the urban heat island effect over the city of Rome, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-927, https://doi.org/10.5194/ems2024-927, 2024.

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One of the big challenges that the EU has proposed is the mission of 100 cities to become carbon neutral by 2030, and the whole continent by 2050. One of the key points to know is how many CO2 can capture the whole urban tress in a year. This amount of absorption depends on several parameters (type of tree, age, water requirement, …), being weather conditions during the whole year the most relevant. The amount of CO2 captured by a tree can be estimated by using different models. The method and equation proposed by Shadman et al. (2022) has been used in the Co-Carbon Trees Measurement project. This is a citizen science project developed in several cities in the metropolitanean area of Barcelona. The results of the pilot developed in the city of Viladecans (67.000 inhabitants, 15 km south to Barcelona) is presented. In this project more than 700 student measured around 1300 trees in a morning, which data allow to take a magnitude of the carbon captured by the 20.000 trees in the city, and so to know how far is the city to become, a carbon neutral. The project proposes repeat yearly this measurement in the same trees, to calculate the CO2 captures in a year, and to link with some annual meteorological parameters like average temperature and precipitation.

Shadman, S., Khalid, P. A., Hanafiah, M. M., Koyande, A. K., Islam, M. A., Bhuiyan, S. A., … & Show, P. L. (2022). The carbon sequestration potential of urban public parks of densely populated cities to improve environmental sustainability. Sustainable energy technologies and assessments, 52, 102064.

How to cite: Mazon, J. and Jaumà, A.: The citizen science project Co-Carbon Trees Measurement: quantifying the CO2 captured by urban trees, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-374, https://doi.org/10.5194/ems2024-374, 2024.

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Increasing urbanization requires a better understanding and representation of urban effects and urban canopy processes in weather and climate modelling at various scales. In this work, an urban canopy parameterization (UCP) based on an extended nudging approach is presented. The UCP is implemented in the mesoscale model METRAS with a horizontal resolution of 500 m. The city of Hamburg with heterogeneous surfaces was chosen as the study area. Urban canopy information for Hamburg, including building height and building surface fraction (i.e., the ratio of the surface area occupied by buildings to the total plan area), obtained from the 3D city model of Hamburg LoD1 (Level of Detail 1). were used as input for the UCP.

Model results show that the urban canopy parameterization based on an extended nudging approach can reproduce urban effects on the wind and temperature fields. For example, the UCP can simulate the wind reduction effects due to canopy obstacles in different model levels, with the largest wind reduction simulated in the urban areas with highest values for building surface fraction (densely built areas). In addition, the urban heat island effect as simulated with the single layer flux aggregation scheme in METRAS, was enhanced using the urban canopy parameterization, with the highest intensities in the densely built areas. The results suggest that nudging is a useful tool for modeling aerodynamic and thermodynamic urban effects, which are both important components in understanding the urban environment. Additionally, nudging is an approach that is relatively easy to implement or already implemented in many models. It can be applied to a variety of urban scenarios and resolutions and thus can be a simple approach to better represent urban effects in global-scale weather and climate models.

How to cite: Cheng, G. and Schlünzen, K. H.: Using a simple parameterization for representing the effect of heterogeneous urban canopies in atmospheric models, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-182, https://doi.org/10.5194/ems2024-182, 2024.

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The Eastern Mediterranean and Middle East (EMME) region exhibits continuously accelerated warming, posing a significant threat to cities within this area and thus increasing their vulnerability to climate change. Regional Climate Models (RCMs) serve as valuable tools for climate simulations, but when the focus is given to the urban thermal environment the resolution of their output results is not sufficient. Downscaling techniques can be utilized to improve the spatial resolution of the RCMs and, hence, bridge this gap between the regional and the local scale. The downscaling techniques can be divided into two main categories, the dynamical (DD), and the empirical/statistical (ESD). While DD relies on physical schemes, its computational demands pose challenges for long-term simulations contrary to the ESD which is computationally inexpensive. In this study, both the DD and the ESD techniques are applied to downscale the 2m air temperature from the regional to the local scale for the city of Nicosia, the capital of Cyprus. Concerning the DD, the Weather Research and Forecasting (WRF) model is used to downscale  the ERA5 re-analysis in three different domains, over the EMME region, Cyprus, and Nicosia, with a spatial horizontal resolution of 12km×12km, 4km×4km, 1km×1km respectively, over a 5-year historical period (2008-2012). Detailed information on the urban characteristics is incorporated into the WRF model through the coupling of the Single Layer Urban Canopy Model (SLUCM) as well as with the utilization of the state-of-the-art land use/land cover CGLC-MODIS-LCZ dataset. The ESD utilizes the generated database of the WRF model to establish statistical relationships between the regional and the local scale for the same period by employing advanced machine learning techniques, including Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR). A detailed comparative analysis between the two downscaling techniques as well as an evaluation of the simulation results against observation data from two meteorological stations are performed to assess their accuracy in estimating the air temperature over Nicosia.

Key Words: WRF model; dynamical downscaling; statistical downscaling; urban climate modeling; Local Climate Zones

How to cite: Koutroumanou-Kontosi, K., Cartalis, C., and Hadjinicolaou, P.: A Comparative Analysis of Dynamic and Statistical Downscaling Techniques to Bridge the Gap Between the Regional and the Local Scale: Case Study for Nicosia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-106, https://doi.org/10.5194/ems2024-106, 2024.

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