CL3.2.1

EDI
Urban climate, urban biometeorology, and science tools for cities

As the most evident example of land use and land-cover change, urban areas play a fundamental role in local to large-scale planetary processes, via modification of heat, moisture, and chemical budgets. With rapid urbanization ramping up globally it is essential to recognize the consequences of landscape conversion to the built environment. Given the capability of cities to serve as first responders to global change, considerable efforts are currently being dedicated across many cities to monitor and understand urban atmospheric dynamics and examine various adaptation and mitigation strategies aimed to offset impacts of rapidly expanding urban environments and influences of large-scale greenhouse gas emissions.

This session solicits submissions from both the observational and modelling communities examining urban atmospheric and landscape dynamics, processes and impacts owing to urban-induced climate change, the efficacy of various strategies to reduce such impacts, and techniques highlighting how cities are already using novel science data and products that facilitate planning and policies on urban adaptation to and mitigation of the effects of climate change. Emerging topics including, but not limited to, compounding impacts with urban COVID-19 outbreaks, citizen science and crowdsourcing, or urban-climate informatics, are highly encouraged.

Co-organized by AS2
Convener: Hendrik Wouters | Co-conveners: Sorin Cheval, Daniel Fenner, Matei Georgescu, Natalie TheeuwesECSECS
Presentations
| Wed, 25 May, 08:30–11:50 (CEST), 13:20–16:40 (CEST)
 
Room F2

Presentations: Wed, 25 May | Room F2

Chairpersons: Natalie Theeuwes, Daniel Fenner
08:30–08:35
Observations, machine learning and reconstructions
08:35–08:41
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EGU22-3249
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ECS
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Virtual presentation
Mahmoud Suliman and Mattias Winterdahl

Urban land cover (ULC) has been steadily expanding in Sweden over the last century. This expansion could potentially include areas in the vicinity of meteorological stations, and may, in turn, lead to increased urban heat island effects in the areas surrounding them. As observations form the basis of many climate studies, it is then important to investigate the potential influence of urban heat island effects on long-term trends in climatic observations. For the purpose of quantifying the change in ULC around meteorological stations, we developed a semi-supervised methodology that classifies the land cover based on single-band orthophotos, and then calculates the change in ULC around the stations. Using this methodology, we estimated the change in land cover in a 100 m radius around 48 Swedish meteorological stations during the period 1960-2019. The seasonal Mann-Kendall test, together with the Theil-Sen estimator and linear regression were applied on the stations’ long-term temperature and precipitation data in order to determine systematic differences in climatic trends between stations with varying degrees of ULC increase, and to explore the possible influence of urban heat islands. Initial results associate large increases in ULC with higher positive Theil-Sen estimator values for temperature observations, and negative linear regression slopes in precipitation observations, respectively (p < 0.001). Thus, the temperature increase has been more pronounced at meteorological stations experiencing substantial ULC increase. Conversely, these stations showed decreasing trends in precipitation. Overall, our results show a correlation between the change in ULC around climatic stations and their long-term trends in climatic observations, and suggest possible influences of urban heat island effects on observed climate data in Sweden.

How to cite: Suliman, M. and Winterdahl, M.: Investigating the impact of urban heat islands on long-term climatic observations in Sweden, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3249, https://doi.org/10.5194/egusphere-egu22-3249, 2022.

08:41–08:47
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EGU22-6218
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Virtual presentation
Uta Moderow, Valeri Goldberg, and Astrid Ziemann

Cities are currently becoming more densely built almost everywhere, thus reducing the possible amount of areas for public green spaces, which are even more relevant in light of climate change as they can mitigate thermal stress during hot summer days. Here, optimizing existing courtyards concerning their green structure might be an option in order to provide conditions of low thermal stress during these days. However, there is no vast amount of studies addressing this issue for temperate and cold climate and related typical urban structures by measurements. We present mobile measurements recorded in Erfurt (Germany) during a hot summer day in 2018. These measurements also covered three courtyards of different design and geometry. Differences in air temperature between the three courtyards were small, but larger differences in mean radiation temperature existed, which mainly contributed to differences in thermal stress for human beings. We used the Universal Thermal Climate Index (UTCI, Jendritzky et al. 2012; Błażejczyk et al. 2010) to assess human thermal comfort. Out of the three investigated courtyards the smallest courtyard with established trees showed the lowest thermal load providing conditions of no thermal stress almost throughout the whole day (UTCI range: 18°C – 28°C). Highest values of thermal stress were recorded for the most open spaced courtyard with a value of 31°C after midday. Thermal loads of the different courtyards were related to general aspects (size of courtyard, ratio of unvegetated and sealed areas to vegetated areas). However, the sample size is too small to draw general conclusions and underlines the necessity for further measurements. We hope that our work will help to broaden the base of available measurements for climatic conditions and typical urban structures for Middle Europe concerning courtyards.

References

Błażejczyk, K., Broede, P., Fiala, D., Havenith, G., Holmér, I., Jendritzky, G., Kampmann, B., and Kunert, A.: Principles of the New Universal Thermal Climate Index (UTCI) and its Application to Bioclimatic Research in European Scale, 14, 91–102, https://doi.org/10.2478/mgrsd-2010-0009, 2010.

Jendritzky, G., Dear, R. de, and Havenith, G.: UTCI—Why another thermal index?, Int J Biometeorol, 56, 421–428, https://doi.org/10.1007/s00484-011-0513-7, 2012.

How to cite: Moderow, U., Goldberg, V., and Ziemann, A.: Measuring thermal comfort of courtyards by mobile measurements - a case study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6218, https://doi.org/10.5194/egusphere-egu22-6218, 2022.

08:47–08:53
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EGU22-1802
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ECS
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Highlight
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On-site presentation
Eva Marques, Valery Masson, Philippe Naveau, Olivier Mestre, Vincent Dubreuil, and Yves Richard

An ever-growing portion of population lives in urban areas. Cities are expanding quickly and consequently, the urban heat island effect has become a major health concern to maintain city dwellers’ thermal comfort. For this reason, city planners want to access urban meteorological databases in local areas where specific attention is needed. With the growth of connected devices, it is possible to collect unusual but massive temperature measurements from people’s activities. In this article, we study temperatures measured by thermometers embedded in everyday personal cars. To assess the quality of such opportunistic data, we first detect factors deteriorating the measurement. After pre-processing, the measurement error is then estimated thanks to two weather station networks providing a local-scale reference through Dijon and Rennes cities, France. The overall aggregation of private car temperature measurements allows to estimate very precisely the urban heat island at a 200m resolution. We detect the cooling effect of parks in Rennes and Paris urban areas. In Barcelona and Dijon, we observe the impact of regional environments and the orographic effect on the urban heat island. With our method, similar maps can be made accessible to every interested city in western Europe to target critical areas and support urban planning decisions.

How to cite: Marques, E., Masson, V., Naveau, P., Mestre, O., Dubreuil, V., and Richard, Y.: Urban heat island estimation from crowdsensing thermometers embedded in personal cars, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1802, https://doi.org/10.5194/egusphere-egu22-1802, 2022.

08:53–08:59
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EGU22-13150
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ECS
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On-site presentation
Cosimo Peruzzi, Marie Ramel-Delobel, Thomas Coudon, Béatrice Fervers, Saverio De Vito, Grazia Fattoruso, and Pietro Salizzoni

Air pollution is a dramatic issue that grips the majority of densely populated cities in the world. It is nowadays quite evident that there is a relationship between air quality and some types of cancers (i.e. lung and bladder cancer), as reported by the International Agency for Research on Cancer (IARC 2012). Although the time spent commuting usually represents a small portion of a person's daily time (3-6%), it is responsible around for 21% of daily personal exposure and roughly 30% of the total inhaled dose (Dons et al. 2012). To gain information on this topic, we conducted an air quality measurement campaign (six weeks between November and December 2021) on three different routes within the metropolitan city of Lyon (France). These routes were chosen to be representative of different urban areas (e.g. city centre, periphery, vegetated areas). The measurements were taken two times for day (i.e. in the morning and the evening, in order to simulate the commuters round trip) using four different modes (walk, bike, car and public transport). Two different portable air quality sensors were used to measure the pollutants: the MONICA sensors (developed by ENEA, De Vito et al. 2021) that measure PM1, PM2.5, PM10, NO2, CO and O3 and the AirBeam 2 sensors (provided by ATMO AURA) that measure only the particular matters. The objective of this study is twofold: from one side to assess the exposure choosing different modes of commuting and, from the other side, to evaluate how the influence of the meteorological-climatic variables (e.i. temperature, relative humidity, precipitation, wind direction, wind speed, cloud cover, solar radiation and atmospheric boundary layer stability/instability) affect the air quality. Preliminary results show that private car users are generally affected by lower levels of air pollution with respect to the other modes (as expected, Okokon et al. 2017), but this is strongly influenced by the type of ventilation used (internal or external air recirculation, open and closed windows). 

 

Reference

De Vito, S., Esposito, E., Massera, E., Formisano, F., Fattoruso, G., Ferlito, S., ... & Di Francia, G. (2021). Crowdsensing IoT Architecture for Pervasive Air Quality and Exposome Monitoring: Design, Development, Calibration, and Long-Term Validation. Sensors21(15), 5219.

Dons, E., Panis, L. I., Van Poppel, M., Theunis, J., & Wets, G. (2012). Personal exposure to black carbon in transport microenvironments. Atmospheric Environment55, 392-398.

IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. (2012). Chemical agents and related occupations. IARC monographs on the evaluation of carcinogenic risks to humans100, 9–562.

Okokon, E. O., Yli-Tuomi, T., Turunen, A. W., Taimisto, P., Pennanen, A., Vouitsis, I., ... & Lanki, T. (2017). Particulates and noise exposure during bicycle, bus and car commuting: A study in three European cities. Environmental Research154, 181-189.

How to cite: Peruzzi, C., Ramel-Delobel, M., Coudon, T., Fervers, B., De Vito, S., Fattoruso, G., and Salizzoni, P.: Air pollution measurements during commuting in Lyon, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13150, https://doi.org/10.5194/egusphere-egu22-13150, 2022.

08:59–09:05
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EGU22-7855
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ECS
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Highlight
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On-site presentation
Ludovic Lelandais, Irène Xueref-Remy, Aurélie Riandet, Dufresne Marvin, Sauvage Stéphane, Pastra Sanne, Scheeren Bert, and Armengaud Alexandre

Urban areas are large sources of greenhouse gases and pollutants. CO2 source apportionment are of prerequisite for defining efficient mitigation strategy to reach the regional goal of carbon neutrality in 2050. It is yet challenging to document especially in a large and complex megacity such as Aix Marseille Metropolis (the 2nd biggest French city).  In the framework of the ANR COoL-AMmetropolis project, this work focuses on assessing the variability and composition of the CO2 urban plume in the Marseille city. Three years of continuous atmospheric measurements and one field campaigns carried on at the Longchamp station in Marseille, south-east of France (43° 18′ 20″ N, 5° 23′ 41″ E) are presented. This station is in an urban environment and is mainly influenced by traffic, residential and industrial emissions (source: ATMOSUD inventory). Beside air quality variables like Carbon dioxide (CO2), methane (CH4), black carbon, particulate matter (PM) chemical composition and nitrogen oxides (NOx) are continuously measured at this station to study the spatio-temporal variability of these compounds. A field campaign of one week in January 2020 has been performed to better infer the sources of CO2. One continuous carbon monoxide instrument and two volatile organic compounds analysers were deployed. Furthermore, about 60 air samples were collected for analysing the isotopic ratio and radiocarbon content of atmospheric CO2. Contributions from anthropogenic fossil fuel emissions and biogenic respiration are quantified. The analysis of the temporal co-variations of CO2 with co-emitted species, enhancement ratios and 13C isotopic ratio provide the identification and the contribution of fossil fuel emissions sectors. These results are also be used to verify regional inventories independently and highlights the main emission sectors contributing to the Marseille city center.

How to cite: Lelandais, L., Xueref-Remy, I., Riandet, A., Marvin, D., Stéphane, S., Sanne, P., Bert, S., and Alexandre, A.: Characteristics of the urban CO2 plume from Marseille city in the southern France : variability and sources identification using co-emitted species and isotopic ratios., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7855, https://doi.org/10.5194/egusphere-egu22-7855, 2022.

09:05–09:11
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EGU22-10206
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ECS
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On-site presentation
Birgit Sützl, Dominik Strebel, Andreas Rubin, Aytaç Kubilay, Yongling Zhao, and Jan Carmeliet

Heat stress in the urban environment is the result of complex interactions between the different components of the built environment and the atmosphere. Different surface materials, heterogeneity in size, shape, density and arrangement of buildings, all influence the transport and storage of heat. Due to this extensive parameter space, numerical simulations of the urban microclimate often revert to simplified parametric morphologies like urban street canyons. To be able to simulate heat mitigation measures in a more realistic set-up, this ongoing research project aims to identify typical building morphologies that are associated with higher outdoor temperatures than comparable neighbourhoods.

The study uses summer daytime surface temperatures from the Landsat 8 high-resolution satellite data, averaged over the years 2013 - 2021, to identify urban neighbourhoods with potential for high heat stress. The surface temperature data over the test city Zurich shows clear cooling effects from water bodies like rivers and lakes, medium- and large-scale vegetated areas, while extensive railway infrastructure and large outdoor sports facilities with artificial turf induce high surface temperatures. These effects are indicated by clear correlations between the surface temperature and parameters such as the impervious surface cover, vegetation cover, and sky view factor, calculated from building-resolved data at neighbourhood scale.

However, the impact of building form is less clear and requires further analysis. An ongoing investigation applies a clustering analysis with several morphological parameters (plan- and frontal area indices of buildings, mean and maximum height of buildings, etc.) to neighbourhoods with high surface temperature, that reveals typical morphology features of several distinct urban neighbourhoods. Representative building geometries can then be selected from these groups to study the adaptation of neighbourhoods to heat stress, as well as to learn lessons for densification and the design of new urban developments.

How to cite: Sützl, B., Strebel, D., Rubin, A., Kubilay, A., Zhao, Y., and Carmeliet, J.: An urban morphology clustering analysis to identify local heat hotspots in cities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10206, https://doi.org/10.5194/egusphere-egu22-10206, 2022.

09:11–09:17
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EGU22-912
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ECS
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On-site presentation
Sarah Berk, Clare Goodess, and Manoj Joshi

As centres of human activity, cities contain over half the world’s population and this proportion is projected to increase to around 70 percent in 2050. The urban heat island (UHI) is a well observed phenomenon, where temperature in a city is warmer than the surrounding rural area.

The UHI is influenced by both the climate and the morphology of the city. Focusing on cities in the tropics and subtropics and those with a population of less than 1 million, this research explores the relationship between the UHI effect and climate. Cities in different climate zones are selected based on similar characteristics such as population, variation of elevation within the city and surrounding area, and proximity to water bodies. Satellite data, with global coverage, is used to quantify the SUHI of the chosen cities. Peak SUHI was calculated using the Gaussian Surface Approximation methodology and the mean SUHI defined as the mean land surface temperature of urban pixels minus the mean of the surrounding rural area.  

Statistical techniques including Multiple Linear Regression, Random Forest Regression and Gaussian Process Regression are used to find relationships between SUHI and variables such as vegetation greenness (EVI), evaporative fraction, precipitation, incoming solar radiation, and city area. 

How to cite: Berk, S., Goodess, C., and Joshi, M.: Investigating the influence of climate on Surface Urban Heat Island (SUHI) behaviour, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-912, https://doi.org/10.5194/egusphere-egu22-912, 2022.

09:17–09:23
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EGU22-4648
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ECS
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On-site presentation
Anna Tzyrkalli, Panos Hadjinicolaou, Katiana Constantinidou, and Jos Lelieveld

Local weather and climate conditions are affected by the presence of cities, through their perturbation of the surface energy balance. A well-know manifestation is the Urban Heat Island (UHI) in which land surface and near surface air temperatures are higher over a city compared to its rural surroundings. In this work, we explore the suitability of air temperature station records, in conjunction with urbanization data derived from land and population data, to provide credible urban-rural temperature differences for the MENA region.

Specifically, for air temperature we utilize daily and sub-daily time-series from the Integrated Surface Database (ISD), resulting in more than 300 station records for the MENA. We subsequently characterize the degree of urbanization of these stations using the gridded, 1km x km GHSL Settlement model (GHSL-SMOD) data that calculate 8 classes of urban and rural spatial entities from built-up area (Landsat) and population (CIESIN Gridded Population of the World) data. Examples of the derived UHI magnitude from the identified station pairs will be shown, and the associated assumptions and limitations of the followed approach will be discussed.

How to cite: Tzyrkalli, A., Hadjinicolaou, P., Constantinidou, K., and Lelieveld, J.: Utilising weather station (ISD), and satellite and population (GHSL-SMOD) datasets to estimate Urban Heat Island over locations in the Middle East and North Africa (MENA) region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4648, https://doi.org/10.5194/egusphere-egu22-4648, 2022.

09:23–09:29
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EGU22-11416
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ECS
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Virtual presentation
Ferdinand Briegel, Osama Makansi, Thomas Brox, Andreas Matzarakis, and Andreas Christen

We present a novel method to model spatial maps of mean radiant temperature (Tmrt) in complex urban areas using a special type of fully convolutional networks - U-Net - for image to image processing. Tmrt is one of the driving factors of daytime human thermal comfort and underlies great spatial and temporal variabilities, especially in complex urban areas. Various micro scale (building-resolving) models exist to model Tmrt in urban settings. However, these models are computational expensive, albeit to varying degrees. This means, study area and time might be limited depending on spatial and temporal resolution. While this is sufficient for case studies where micro-level processes are modelled for different neighbourhoods in limited time periods, accurate calculations over a long time period are not possible (e.g. downscaling global climate projections). To overcome these computational drawbacks of physical models, we present a U-net approach for modelling Tmrt in complex urban areas.

U-Nets are special types of encoder-decoder networks and allow precise image to image processing. In this study, Tmrt (at 1.1 m a.g.l.) is modelled by SOLWEIG model for 62 areas (500 x 500 m2) and on 54 days for the city of Freiburg, Germany. Training data is sampled randomly after clustering. The spatial and temporal input of SOLWEIG are in turn used as input features for the U-Net. The U-Net is trained on 56 areas and on 45 days and tested on the remaining areas and days. In addition, data from a Tmrt measurement campaign is used to validate SOLWEIG and U-Net model output.

Results indicate that the proposed U-Net approach is capable to provide Tmrt in complex urban areas sufficiently. A correlation of > 0.9 and a MAE of 1.53°C between SOLWEIG and the U-Net is observed. Results show a higher MAE during day than night, which can be partly explained by the difference of absolute Tmrt values at day and night, but also by more complex prediction conditions during day: cloud cover and thus varying radiation, but also low sun angle in the morning / evening. In addition, computing times for Tmrt map predictions are significantly faster than physical models. 

How to cite: Briegel, F., Makansi, O., Brox, T., Matzarakis, A., and Christen, A.: Modelling mean radiant temperature in complex urban areas using a convolutional network approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11416, https://doi.org/10.5194/egusphere-egu22-11416, 2022.

09:29–09:35
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EGU22-3355
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ECS
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Virtual presentation
Saud AlKhaled

Urban morphological attributes and surface properties can largely influence near-surface air temperatures. Unpacking such morpho-thermal relationships are of particular importance in hot urban desert (HUDs) cities given the already extreme thermal bioclimatic dynamics, urban-induced heating with rapid urbanization processes, and vulnerability of residents. Satellite-derived investigations may underestimate critical system dynamics of urban thermal stimuli found within sub-diurnal phenomena and sub-meter classifications. High resolution spatiotemporal measurements are therefore required to objectively assess latent magnitudes of heat mitigation and amelioration strategies. This study utilized the natural heterogeneity of morphometric predictors with fixed ground-based measurements in a representative neighborhood unit typology within Kuwait’s residential landscape to build a composite dataset of sub-hourly air temperature measurements with sub-meter morphological attributes. The presentation will share initial findings of the study and preliminary analysis of the drivers of heating/cooling rate’s association to defined morphological factors.

How to cite: AlKhaled, S.: Urban Morphometrics and Microclimate Responses in a Typical Residential Neighborhood of a Hot Urban Desert City, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3355, https://doi.org/10.5194/egusphere-egu22-3355, 2022.

09:35–09:41
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EGU22-3530
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ECS
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Virtual presentation
Guangzhao Chen, Yuan Shi, Chao Ren, and Edward Ng

Air temperature is a crucial variable in urban climate and relevant to many studies, such as urban heat islands, heat waves, climate change, energy consumption, and health-related heat exposure risk studies. Previous studies used land surface temperature (LST) and inversion methods to obtain air temperature maps with spatial detail or used weather station observations and spatial interpolation to obtain air temperature maps with high temporal resolution. However, fine spatial detail and high temporal resolution have not been resolved simultaneously. Moreover, there are differences in LST and air temperature definitions, which cannot be equated. Therefore, in this study, we carried out hourly air temperature mapping at 1-km resolution over a multi-year summer period for Guangdong Province, China, employing machine learning algorithms as well as meteorological and landscape data. The meteorological data were hourly observations from 86 weather stations in Guangdong containing variables such as air temperature, relative humidity, precipitation, barometric pressure, and wind speed. The landscape data were mainly from the landscape indices calculated based on local climate zone (LCZ) maps, mapped via Google Earth Pro and Google Earth Engine. Then, we employed the random forest (RF) algorithm for the hourly air temperature mapping. The validation results showed that the hourly air temperature maps achieved good accuracy from 2008 to 2019 with a mean R2 value of 0.8001. The importance assessment of the driving factors showed that meteorological factors, especially relative humidity, make the most outstanding contribution to air temperature mapping. Simultaneously, the landscape factors also played a non-negligible role. Further analysis revealed that the maps steadily maintained high accuracy at nighttime (20:00-7:00), which is the most critical period for studying urban heat islands. In addition, the air temperature patterns showed a correlation with the landscape. Air temperatures in contiguous mountainous areas with dense trees were significantly lower than those in the plains. Moreover, there is a correlation between nighttime air temperature changes and urban morphology, and urban-rural differences exist simultaneously. Air temperatures tend to fall more slowly in the core of metropolitan areas than in the urban fringe. Overall, this study employed machine learning to reliably improve the temporal resolution of air temperature mapping with more spatial detail. Furthermore, it reveals spatially explicit air temperature patterns in and around cities at different times in a day during the summer. In addition, it provides a new valuable and advantageous dataset for relevant applications.

How to cite: Chen, G., Shi, Y., Ren, C., and Ng, E.: Hourly air temperature mapping in Guangdong province utilizing machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3530, https://doi.org/10.5194/egusphere-egu22-3530, 2022.

09:41–09:47
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EGU22-2105
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ECS
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On-site presentation
Naika Meili, Athanasios Paschalis, Gabriele Manoli, and Simone Fatichi

Research quantifying urban-rural differences in humidity, the so called urban dry or moisture islands (UDIs, UMIs), has been mostly confined to case-studies of single cities or regions. An analysis of the typical diurnal and seasonal patterns of UDIs at larger scale is still missing even though changes in humidity can impact human well-being, building energy consumption, and urban ecology. In this study, we use a large data set (1089 stations) of globally distributed near surface air temperature and humidity measurements to quantify the typical diurnal and seasonal patterns of UDIs, which developed due to rapid urbanization in many parts of the world, using a time for space substitution. We distinguish between “relative” and “absolute” UDIs quantified as the urban-rural difference in relative and actual humidity measurements, respectively, to account for differences in their diurnal and seasonal patterns.

We find that absolute UDI is largest during daytime with the highest humidity decrease in the late afternoon hours, while relative UDI is generally largest at night. Peak relative humidity decrease occurs during the late evening hours with magnitudes of around -10 to -11% between 20-00 local time in summer. Both relative and absolute UDI are largest during the warm season. Separating the contribution of actual humidity decrease and change in temperature to the formation of relative UDI, we find that relative UDI is mostly caused by absolute UDI during daytime and by temperature, i.e., urban heat island (UHI), during nighttime. The quantification of UDIs, as presented here, is crucial for subsequent impact analyses of urbanization on outdoor thermal comfort, urban ecology, and building energy consumption.

How to cite: Meili, N., Paschalis, A., Manoli, G., and Fatichi, S.: Diurnal and Seasonal Patterns of Urban Dry Islands Quantified with a Global Dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2105, https://doi.org/10.5194/egusphere-egu22-2105, 2022.

09:47–09:53
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EGU22-2679
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ECS
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Highlight
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Virtual presentation
Judi (Yehudit) Lax, Hadas Saaroni, and Colin Price

As urbanization continues to grow, it is expected that by 2050, the currently 55% of the world population living in urban areas will reach 68% (UN, 2016). The 'Urban Heat Island' is the most studied phenomenon in urban areas, but changes are expected also in the atmospheric humidity regime (Ziv & Saaroni, 2011). Generally, an urban dry island has been noted in previous studies (Luo & Lau, 2019).

Following the authors' findings in the field of hygroelectricity (Lax, Price & Saaroni, 2020)– energy extracted from isolated metals exposed to high relative humidity (RH) conditions – as spontaneous voltage accumulated on isolated metals starting from RH > 60%, investigation of suitable regions with high RH and its durations is needed. Such analysis is also applicative for numerous aspects, related to negative impacts caused by high RH, i.e., thermal comfort & health aspects, when associated with high temperatures, allergies related to dust mites & mold, fungi & bacteria survival, corrosion development, etc. However, high RH has advantages as well, moist-reliant renewable energies and moist harvesting for drinking water (Shen et. al., 2020). This is especially relevant in a warming world due to climate change.

Our study explored the climatology of the world's largest 33 mega-cities; High RH distribution & duration spells are analyzed on a seasonal & annual scales, based on a minimum of 10-years hourly data. Moreover, for cities with several stations, a spatial comparison is performed. The atmospheric variables included are not only the cities' RH, but also the specific humidity, dry and wet bulb temperatures and heat load. Cities are ranked in terms of their potential contribution to the above-mentioned technologies on the one hand and to their disadvantages in terms of human comfort on the other. Finally, we propose a tool to determine the potential of these cities for moist-reliant technologies.

How to cite: Lax, J. (., Saaroni, H., and Price, C.: Humidity regime in the world's mega cities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2679, https://doi.org/10.5194/egusphere-egu22-2679, 2022.

09:53–09:59
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EGU22-971
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ECS
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Virtual presentation
Dragan Milošević, Branislava Lalić, Stevan Savić, Benjamin Bechtel, Mark Roantree, and Simone Orlandini

Reliable and sufficient knowledge on environmental conditions delivered from micrometeorological and microclimatological data plays a central role in assessing and modelling trends and effects of climate change and adverse weather on the environment. Enormous efforts have already been made to centralise data from ground-based and satellite measurements and to make them available for public use. However, beyond specific initiatives, they are still missing one very important component – micrometeorological data, i.e. data addressing meteorological conditions of microenvironment that is open and available for various application potentials and user groups.

Micrometeorological data are usually collected as part of scientific projects and observational networks developed for different purposes, but they often “languish” in reports and institutional data storages. To address this shortfall, FAIRNESS Cost Action will establish micrometeorological knowledge share platform (Micromet_KSP) to communicate: a) compiled inventory of available and quality proven micrometeorological in situ data sets on the European level and beyond, b) measurement and data management recommendations designed to meet FAIR principles and avoid temporal and spatial gaps, c) examples of rural and urban FAIR data sets and d) Q&A exchanged between Action members, stakeholders, specialised user groups and general public.

FAIRNESS targets are, primarily, networks of Automated Weather Stations installed in urban, sub-urban and rural areas which are in charge of dedicated projects, specialised agencies, regional or national government offices for specific applications in the sectors of urban-, forest-, and environmental meteorology and agrometeorology. Addressing identified challenges requires an effective transboundary network of researchers, stakeholders, and civil society to identify and fill knowledge gaps, standardize, optimize, and promote new environmental-tailored measurement and control procedures, enhance research effectiveness and improve dissemination.

FAIRNESS consortium includes 65 partners from 28 countries in Europe, Asia, Australia, and North America, and invites interested stakeholders and/or data contributors to join the project during its realization (2021-2025).

How to cite: Milošević, D., Lalić, B., Savić, S., Bechtel, B., Roantree, M., and Orlandini, S.: FAIRNESS Project - FAIR NEtwork of micrometeorological measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-971, https://doi.org/10.5194/egusphere-egu22-971, 2022.

Coffee break
Chairpersons: Jessica Keune, Hendrik Wouters
Parameter databases, model development and evaluation
10:20–10:26
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EGU22-6213
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ECS
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On-site presentation
Jonas Kittner, Matthias Demuzere, Gerald Mills, Christian Moede, Dev Niyogi, Jasper van Vliet, and Benjamin Bechtel

There is a scientific consensus on the need for spatially detailed information on urban landscapes at a global scale to support a range of environmental services, as cities are acknowledged as places of: intense resource consumption and waste generation and foci of population and infrastructure that are exposed to multiple hazards of natural and anthropogenic origin. In the face of climate change, urban data is also required for future urbanisation pathways and urban design strategies, in order to “lock in” long-term resilience and sustainability, protecting cities from future decisions that could undermine their adaptability. Eventually, these global form-based, contextually specific urban planning and urban design strategies are the ultimate guarantors of successful life cycle costs, payback, and liveability. Moreover, these strategies are needed to identify the relevant data for planning and climate on neighbourhood, city and global scales, and to become part of a basic infrastructure to support a host of studies on exposure to environmental hazards, energy demand, climate adaptation and mitigation solutions and human health, as examples. 

Therefore, a more holistic urban landscape description is required, that goes beyond the urban mask and that enables the assessment of the spatial impact of urban planning decisions that will alter urban canopy parameters (UCPs) and their climate outcome. 

The global Local Climate Zone (LCZ) map presented here serves this purpose, as the LCZ typology is the only universal classification that can distinguish urban surfaces on a holistic basis, accounting for the typical combination of micro-scale land-covers and associated physical properties, all being the consequence of historic urbanisation patterns that reflect local terrain, culture, economy, etc. The 100m resolution global LCZ map is generated by feeding an unprecedented amount of labelled training areas (partly sourced from the LCZ Generator - https://lcz-generator.rub.de/) and earth observation imagery into lightweight random forest models. Its quality is assessed using the default bootstrap-based cross validation alongside a thematic benchmark for 150 selected functional urban areas using independent global and open- source data on surface cover, surface imperviousness, anthropogenic heat and building height.

Complementing the single cities‘ LCZ maps accessible via the LCZ Generator, the global LCZ map for the first time reveals the world‘s intra-urban heterogeneity heterogeinity. In addition, as each LCZ type is associated with generic numerical descriptions of key UCPs, parameters critical to model atmospheric responses to urbanisation, the availability of this globally consistent and climate-relevant urban description is an essential prerequisite for developing fit-for-purpose integrated climate-sensitive urban planning policies.

How to cite: Kittner, J., Demuzere, M., Mills, G., Moede, C., Niyogi, D., van Vliet, J., and Bechtel, B.: A global Local Climate Zone map: revealing intra-urban heterogeneity., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6213, https://doi.org/10.5194/egusphere-egu22-6213, 2022.

10:26–10:32
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EGU22-1513
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ECS
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On-site presentation
Tim Nagel, Robert Schoetter, Victor Bourgin, Valéry Masson, and Emma Onofri

To prepare future urban climate modelling and numerical weather prediction at the hectometer scale in cities with heterogeneous morphology and high-rise buildings, urban climate models have to be coupled at multiple levels with atmospheric models. Vertical profiles of the building drag coefficient and the urban mixing length need to be specified to parametrize the effect of the buildings on the flow. Building-resolving micro-scale simulations can be employed to derive these quantities.

In the present contribution, micro-scale large-eddy simulations of eleven Local Climate Zone (LCZ) based urban morphologies with various building plan and frontal density are used to provide velocity, sectional drag coefficient and mixing length reference vertical profiles for the urban environment. The micro-scale simulations, which are of 1-m resolution in both horizontal and vertical directions, are performed with the MesoNH meteorological research model. This model represents explicitly the obstacles with the Immersed Boundary Method and accounts for the impact of the large-scale turbulence structures on the urban canopy thanks to dynamical downscaling and embedded numerical domains using the grid nesting method. The micro-scale results show that, contrary to traditional assumptions, the velocity profile is generally not exponential and the mixing length is not constant in the urban canopy. This is in agreement with more recent research. The results also show that the building frontal density seems to be a key parameter for the shape of the velocity profile, within and directly above the urban canopy.

The sectional drag and mixing length profiles are then used to propose a new LCZ-based parametrization for the wind dynamics in the urban environment when using the Meso-NH model at the hectometer scale. The results show that the proposed parametrization is more efficient than the current one, consisting in a constant drag coefficient and no specific modification of the turbulent mixing length scale in the urban environment. These results open new perspectives to better parametrize the dynamic effects of real urban areas at the hectometer scale.

How to cite: Nagel, T., Schoetter, R., Bourgin, V., Masson, V., and Onofri, E.: Toward a Local Climate Zone-based drag and mixing length parametrization for the urban environment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1513, https://doi.org/10.5194/egusphere-egu22-1513, 2022.

10:32–10:38
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EGU22-11468
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ECS
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Virtual presentation
Megan Stretton, Robin Hogan, and Sue Grimmond

Urban schemes in weather and climate models often characterise urban structures in a grid cell using the mean building height and street width. This does not capture the sub-grid vertical variability that impacts fluxes. The vertical distribution of wall area and building heights are ideally required but are often unavailable in cities globally. In this work, building footprint and height data from six cities are used to parameterise the geometry with varying levels of detail of input data.

We conclude the vertical distribution of buildings can be parameterised using a function of mean building height and surface building plan area. Comparisons of the parameterised building plan area fraction with height to ‘true’ data (2 km x 2 km resolution) show 90% of the profiles have bias errors (BE) of < 0.03 (‘true’ values are: 0.05 – 0.55).

Building horizontal size (or effective building diameter, D) has a six-city mean of ~21 m. As D is impacted by normalised building edge length and building plan area, we use it to parameterise building edge length. The derived D parameterisations have normalised BE (nBE) < 16%, but without total wall area as an input the nBE increases to 26%.

The combined parameterisations are used with the radiative transfer model SPARTACUS-Urban to simulate total absorption of shortwave (SW) radiation and effective SW albedo. The latter is impacted 2-10% (cf. simulations using ‘true’ data). Larger errors occur when simulating  within-canyon absorption fluxes. Larger errors also occur when fewer morphology inputs are used, with total wall area having the most benefit.

We conclude urban vertical variability can be acceptably characterised for numerical weather prediction using three parameters: surface building plan area, mean building height, and effective building diameter.

How to cite: Stretton, M., Hogan, R., and Grimmond, S.: Characterising the vertical structure of buildings for use in atmospheric models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11468, https://doi.org/10.5194/egusphere-egu22-11468, 2022.

10:38–10:44
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EGU22-5793
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ECS
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On-site presentation
Francesca Bassani, Valeria Garbero, Davide Poggi, Luca Ridolfi, Jost von Hardenberg, and Massimo Milelli

Since Howard (1833) first suggested that air temperatures recorded in urban areas are higher than in the surrounding countryside, there have been hundreds of studies of the Urban Heat Island (UHI) phenomenon, which is due to the different thermal properties between urbanized and natural lands, anthropogenic heat emissions, human-induced pollution and limited wind blowing among buildings. The impervious land cover type and the presence of sheltering constructions trap heat during the day and release it during the night,  resulting in higher night-time temperatures. The UHI intensity is commonly computed as the difference between an urban and a rural measurement site and, therefore, the definition of station pairs is a crucial task for its evaluation. To this end, we propose a powerful method capable of highlighting the thermal pattern typical of each weather station: the Mean Temperature Difference (MTD) method. Principal Component Analysis (PCA) is adopted to cluster similar thermal behaviours, allowing an objective classification of the stations. The strength and novelty of this data-based approach, which employs hourly temperature measurements, lays in the fact that any preliminary assumption about the landscape characterizing each station (i.e. urban or rural) is not needed, making it less arbitrary and more objective than other methods. The application of the proposed method to the metropolitan area of Turin (Italy) shows that the joint use of MTD with PCA yields reliable and easily interpretable results, also in an area with complex morphology (orographic and hydrographic heterogeneity, different land uses, etc.). Once the best urban and rural pairs have been identified, the characteristics of the Urban Heat Island are shown, highlighting its seasonal and daily properties.

How to cite: Bassani, F., Garbero, V., Poggi, D., Ridolfi, L., von Hardenberg, J., and Milelli, M.: MTD: a new powerful method to select urban-rural pairs for Urban Heat Island quantification applied to Turin, Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5793, https://doi.org/10.5194/egusphere-egu22-5793, 2022.

10:44–10:50
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EGU22-12883
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Virtual presentation
Siarhei Barodka, Tsimafei Schlender, Natallia Darozhka, Ilya Bruchkouski, Aleh Baravik, Milvari Alieva, Natalia Zhukovskaya, Yauheniya Yarash, Maksim Birukou, and Tatsiana Tabalchuk

This study is devoted to analysis of Urban Heat Island (UHI) and Urban Pollution Island (UPI) effects in Minsk, Belarus by means of high-resolution atmospheric urban modelling. We present first results of our implementation of the WRF-BEP+BEM modelling system for Minsk with two different approaches to urban morphology: one involving the Local Climate Zones (LCZ) methodology and the other being based on direct representation of urban parameters on the model grid. For that purpose, we combine satellite remote sensing data with geoinformation systems (GIS), centralized city planning databases and Open Street Maps (OSM) vector data to implement description of land use / land cover for Minsk urban territory and the surrounding area along with a representation of buildings data and other urban parameters with a level of detail necessary for high resolution modelling (500 m, 300 m and 100 m grids). Different configurations of the WRF-BEP+BEM modelling system are then used to perform a series of  simulations involving various meteorological conditions over Minsk, Belarus to investigate manifestations of the UHI and UPI effects. In modelling results validation special emphasis is made on analysis of surface temperature parameters and near-surface atmospheric circulation, the latter being important for atmospheric pollutants transport in the urban area. For validation, we use observational data of surface temperature, wind fields and atmospheric pollution from ground-based measurements (including both regular meteorological stations and crowdsourced data from citizen weather stations) and satellite remote sensing for Minsk urban area and the surrounding region. Analysis results reveal the degree of applicability of each approach to urban morphology representation in WRF-BEP+BEM for Minsk and similar urban territories on high-resolution modelling grids.

How to cite: Barodka, S., Schlender, T., Darozhka, N., Bruchkouski, I., Baravik, A., Alieva, M., Zhukovskaya, N., Yarash, Y., Birukou, M., and Tabalchuk, T.: High-resolution WRF-BEP+BEM modelling of urban heat island and urban pollution island effects for Minsk, Belarus with different approaches to urban morphology representation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12883, https://doi.org/10.5194/egusphere-egu22-12883, 2022.

10:50–10:56
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EGU22-9195
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ECS
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Virtual presentation
Ricard Segura, Scott Krayenhoff, Alberto Martilli, Alba Badia, Carme Estruch, Sergi Ventura, and Gara Villalba

The application of nature-based solutions in urban areas to mitigate the harmful effects of urban overheating and to make cities more resilient to heat waves has gained the attention of city planners and researchers in the last decades. Street trees are an important driver of street microclimate through shadowing and transpiration cooling, which are key components in the improvements of thermal comfort. While several observational campaigns have been carried out in low and medium-density residential areas, little research has been focused in highly-compact city centres, where the impact of built elements on the local climate is expected to be stronger. In this context, Urban canopy models (UCM) with integrated trees are useful tools because they represent the impact of street trees on neighbourhood-scale climate, resolving the interactions between buildings, trees and the atmosphere. These models enable the assessment of outdoor human thermal exposure for diverse urban morphologies and allow the evaluation of greening scenarios.

In this study, we present the results of a micrometeorological measurement campaign inside the city of Barcelona (Spain) for two cloud-free summer days. Vehicle transects were completed along two parallel streets with different tree densities but identical street geometry, recording upward and downward radiation fluxes, air temperature and humidity. Assessment of urban tree impacts on microclimate is supplemented by meteorological simulations using the multi-layer UCM Building Effect Parameterization with Trees (BEP-Tree), which considers the vertical variation of the combined impacts of vegetation and building on urban canopy layer climate. Comparing observed pedestrian level air temperatures between the two canyons, we can see that the impact of tree densities varies with the regional weather, with air temperatures up to 2.7 oC higher in the street with low tree density compared to the one with denser trees for a day with the wind direction perpendicular to the direction of the streets. The BEP-Tree simulations demonstrate good agreement with the observations in terms of temperature and radiation, and they are able to capture the different diurnal evolution of temperature and radiation between the two streets.

How to cite: Segura, R., Krayenhoff, S., Martilli, A., Badia, A., Estruch, C., Ventura, S., and Villalba, G.: Observational and numerical evaluation of the pedestrian-level microclimatic effect of street trees in a highly-compact city, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9195, https://doi.org/10.5194/egusphere-egu22-9195, 2022.

10:56–11:02
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EGU22-4769
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ECS
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On-site presentation
Robert Maiwald, Simone Wald, Ivo Suter, Dominik Brunner, André Butz, and Sanam Vardag

More than 60% of global greenhouse gases are produced in urban areas. Urban areas therefore exhibit an immense mitigation potential, which needs to be fully exploited to limit climate change.  In order to monitor the effectiveness of mitigation measures, local decision makers require sub-urban data on the spatio-temporal distribution of greenhouse gases. The GRAMM/GRAL model is capable of calculating high-resolution (10m) wind fields over long time periods by using a “catalogue approach”. The model is therefore well suited to support mitigation efforts in cities.

GRAMM/GRAL is composed of the mesoscale model GRAMM and a coupled computational fluid dynamics (CFD) model GRAL. GRAMM calculates meteorological wind fields by solving the Reynolds-Averaged-Navier-Stokes (RANS) equation. In the catalogue approach, the model GRAMM calculates about 1000 wind fields with 100 m resolution each with a different set of atmospheric stabilities, wind speeds and directions. The CFD model GRAL uses these wind fields as input at the boundaries and calculates higher resolution (10m) wind fields taking the flow around buildings into account. Passive tracers may be released within the GRAL model to simulate their dispersion using a Lagrangian particle dispersion approach. A time series of wind fields and concentrations can be obtained by matching measured and simulated wind fields. This matching procedure saves computational costs and therefore enables the analysis of longer time periods.

In this study, we characterize the GRAMM/GRAL model performance in Heidelberg and compare modelled and measured wind fields in an urban setting for a period of three months. In general, we find a good agreement between modelled and simulated wind direction. Wind speeds can be simulated with a root-mean square difference of about 1.0 m/s and a mean bias of about 0.6 m/s. We find that the number of wind stations influences the overall model performance, which is in accordance to Berchet et al. (2017).

We further present an outlook on possible set-ups of an inversion scheme to estimate greenhouse gas fluxes from a hypothetical measurement network. To this end, we utilize the high-resolution model GRAMM/GRAL to simulate CO2 concentration in the urban atmosphere and plan to approximate CO2 fluxes using regularized least-square approaches as well as machine-learning methods. We discuss remaining challenges such as background CO2 and biogenic CO2 fluxes.

How to cite: Maiwald, R., Wald, S., Suter, I., Brunner, D., Butz, A., and Vardag, S.: High-resolution meteorological simulations in Heidelberg using GRAMM/GRAL model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4769, https://doi.org/10.5194/egusphere-egu22-4769, 2022.

11:02–11:08
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EGU22-12446
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ECS
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Virtual presentation
Annette Straub, Christoph Beck, and Andreas Philipp

Within the scope of the research project “Strategies for Reduction of Critical Urban Climate Load Situations in Augsburg” (MIKA), which is part of the research programme "Urban Climate Under Change” [UC2], the LES model PALM-4U is applied in the medium-sized city of Augsburg, Southern Germany. As a first aim of the project, simulations with focus on air temperature have been performed. The simulations cover a large part of the city and its surroundings (approx. 8x6 km), and two areas of special interest are resolved in more detail. Meteorological boundary conditions are provided by the COSMO-D2 model. Two different summer days have been selected for the simulations. One day has anticyclonic conditions, is part of a heat wave and, thus, thermal stress is expected in the city. The other day, which serves as a reference day, has moderate temperatures and more mixed conditions than the day with heat stress. Furthermore, it is part of an intense observation period (IOP), which means that vertical profiles of air temperature and humidity have been measured at different sites in the city each hour with unmanned aerial vehicles (UAV) accompanied by mobile measurements with a bicycle. This is favourable for evaluating the model results.

This contribution presents some first results of the evaluation and comparison of these two PALM-4U simulations.

How to cite: Straub, A., Beck, C., and Philipp, A.: Simulation of thermal conditions in Augsburg, Southern Germany, using PALM-4U, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12446, https://doi.org/10.5194/egusphere-egu22-12446, 2022.

11:08–11:14
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EGU22-5074
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ECS
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Virtual presentation
Xiaoxiong Xie, Zhiwen Luo, Sue Grimmond, Ting Sun, and Lewis Blunn

Natural ventilation is widely used for low-carbon building design. Its potential is influenced largely by the building’s micrometeorological context. Traditionally, weather data used in building energy simulation are observed at rural sites which are far from the site of interest and not representative of the area’s surroundings. Here we combine the Surface Urban Energy and Water Balance Scheme (SUEWS) and the building energy simulation tool, EnergyPlus, to predict the natural ventilation potential (NVP) in buildings located in urban areas in five representative Chinese cities in different climate zones. The meteorological data required by EnergyPlus (e.g. air temperature, relative humidity, wind speed profile) are modelled by SUEWS. The dense urban areas (building fraction λP = 0.6) have an overall warmer and less windy environment compared to rural areas. In summer, the urban-rural natural ventilation hour differences are -3% to -85% (cf. rural) across all climates, while in spring/autumn differences are -25% to 42%. The method is intended to improve the accuracy of NVP prediction using EnergyPlus in cities.

How to cite: Xie, X., Luo, Z., Grimmond, S., Sun, T., and Blunn, L.: Predicting natural ventilation potential in idealised urban neighbourhoods across Chinese climate zones, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5074, https://doi.org/10.5194/egusphere-egu22-5074, 2022.

11:14–11:20
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EGU22-3434
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ECS
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Virtual presentation
Shreya Banerjee, Ariane Middel, and Subrata Chattopadhyay

Informal settlements in developing countries have distinct socio-ecological, ethnocultural, and economic patterns. People spend a significant amount of time in these outdoor spaces and modify them with lightweight shade materials (encroachments) according to their needs. We seek to investigate how accurately the 3 Dimensional Computational Fluid Dynamics (CFD) software ENVI-met models Relative Humidity (RH) in the streets of such heterogeneous urban forms in tropical Mumbai and Kolkata in India. Three neighborhoods with similar forms and functions were chosen in each city after (Banerjee et al., 2021), (Banerjee et al., 2020) to perform 12 microclimate simulations (12 hours) in summer and winter. Partial encroachments were modeled using the single z-wall feature of ENVI-met. This is the first study to validate ENVI-met seasonal RH simulations in complex neighborhoods geometries, i.e. an elevated vehicular corridor, a large riverbank, and temporary encroachments.

The research concludes that few studies have validated RH so far. Our validation study reports ENVI-met thoroughly overestimates RH in most cases. In Mumbai, Fashion Street has significant greenery and a Gymkhana nearby, attributed to high RH during the morning hours, especially in hot-humid summers. Naturally, RH decreases with an increase in Air Temperature (Ta). For Dadar, in summer, the deep canyon has the highest RH. This pattern is opposite to the observed summer Ta and Mean Radiant Temperature (Tmrt) pattern in Dadar in both seasons. For Mallickghat, RH decreases with increasing Ta. For both seasons, the deep canyon shows the highest RH profile due to the lack of wind flow in the canyon caused by the blockage of river wind by built structures. In Kumartuli, the deep canyon has the highest RH for both seasons, due to the lack of adequate wind flow from encroachment imparted roughness and trapped moisture in the canyon. This agrees with existing studies that show vegetation or other elements of roughness can block the wind flow or ventilation within a canyon. This deviation may be attributed to boundary conditions assumptions such as a neutrally stratified atmosphere, which is not always valid in cities with strong radiative input such as Kolkata and Mumbai. For Mallickghat, our result shows ENVI-met can predict RH well for a shallow canyon (R sq. = 0.77), although for the deep canyon, the RH prediction ability of ENVI-met is lower (R sq. = 0.59). Similar RH patterns between deep and shallow canyons in both neighborhoods may be due to anthropogenic heat-related discrepancies in deep canyons that can completely change the pattern of ambient RH. Overall, the study concludes that ENVI-met predicts RH well as the correlation between the measured data and simulation demonstrates consistency.

Banerjee, S., Middel, A., & Chattopadhyay, S. (2020). Outdoor thermal comfort in various microentrepreneurial settings in hot humid tropical Kolkata : Human biometeorological assessment of objective and subjective parameters. Science of the Total Environment, 721, 137741. https://doi.org/10.1016/j.scitotenv.2020.137741

Banerjee, S., Middel, A., & Chattopadhyay, S. (2021). A regression-based three-phase approach to assess outdoor thermal comfort in informal micro-entrepreneurial settings in tropical Mumbai. International Journal of Biometeorology. https://doi.org/https://doi.org/10.1007/s00484-021-02136-7

How to cite: Banerjee, S., Middel, A., and Chattopadhyay, S.: Validating ENVI-met for Relative Humidity (RH) in high-density temporary encroachment spaces in the streets of tropical Indian megacities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3434, https://doi.org/10.5194/egusphere-egu22-3434, 2022.

11:20–11:26
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EGU22-5144
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Virtual presentation
Sichan Du, Lu Zhuo, Elizabeth J. Kendon, Dawei Han, Ying Liu, Jiao Wang, and Qin Wang

In the twenty-first century, extreme weather events leading to flooding and heat waves, have become one of the most severe challenges in urban areas, especially under the circumstances of local climate change and rapid urbanisation. In the future, cities are going to encounter more severe natural disaster risks and understanding how these could combine with modification of the urban environment (for example through adoption of green infrastructure) is critical for decisions relating to mitigation and adaptation to climate change. Green infrastructure is a subset of resilient infrastructure, which may mitigate the adverse effects caused by extreme weather and contribute to regulating urban climate. In addition, high-performing green spaces bring additional benefits for society in terms of health and wellbeing. The Weather Research and Forecasting (WRF) model is a numerical weather prediction system supporting both atmospheric research and operational forecasting. Within this modelling system, there is the possibility to modify parameters according to various urban areas within the WRF-Urban configuration. In this study, Newcastle upon Tyne (a UK city with the benefit of a lot of observational sensor data) is selected as an initial target city for identifying the optimal WRF configuration by varying the model resolution, domain size and nesting strategy. Future work will explore the influence of implementing green infrastructure in the context of climate change and urbanisation, then extending this analysis to London.

How to cite: Du, S., Zhuo, L., Kendon, E. J., Han, D., Liu, Y., Wang, J., and Wang, Q.: WRF Simulations on the Impacts and Responses of Extreme Weather Events: From the Perspectives of Climate Change and Urbanisation over UK Cities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5144, https://doi.org/10.5194/egusphere-egu22-5144, 2022.

11:26–11:32
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EGU22-10015
Towards the improvement of the representation of the Paris urban heat island in ERA5 using offline SURFEX-TEB (v8.1) simulations and the METEOSAT land surface temperature product
(withdrawn)
Pedro M M Soares, Miguel Nogueira, Frederico Johannsen, Alexandra Hurduc, Sofia Ermida, Daniela Lima, and Emanuel Dutra
11:32–11:38
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EGU22-1517
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ECS
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Virtual presentation
Gaby Langendijk, Diana Rechid, and Daniela Jacob

Urban decision makers rely on evidence-based climate information tailored to their needs to adequately adapt and prepare for future climate change impacts. Regional climate models, with grid sizes between 50-10 km, are a useful outset to understand potential future climate change impacts in urban regions. The recently developed convection-permitting models have grid sizes less than 5 km, and better resolve smaller scale atmospheric processes such as convection, and its interactions with the land surface, by also better representing complex terrain, for instance cities. This study investigates how the convection-permitting resolution affects the simulation of climate change conditions in the urban-rural context, demonstrated through three impact cases: influenza spread and survival; ragweed pollen dispersion, and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041-2050) under emission scenario RCP8.5. Taking the Berlin region as a testbed, the findings show that the change signal reverses for the 3 km compared to the 12.5 km grid resolution for the impact cases pollen, and mold, which indicates an added value. More pollen days are projected in Berlin under future climate conditions. Less mold days can be expected, but longer consecutive periods, under future climate conditions. For influenza, the convection-permitting resolution intensifies the decrease of influenza days, nevertheless longer periods of consecutive influenza days are found under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts for urban regions to support decision makers, and in order to build the resilient cities of tomorrow. 

 

How to cite: Langendijk, G., Rechid, D., and Jacob, D.: Improved models, improved information? Exploring how climate change impacts pollen, influenza, and mold in Berlin and its surroundings, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1517, https://doi.org/10.5194/egusphere-egu22-1517, 2022.

11:38–11:44
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EGU22-7046
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On-site presentation
Harro Jongen, Mathew Lipson, Ryan Teuling, Sue Grimmond, and Gert-Jan Steeneveld

The development of urban areas impacts the local climate and hydrology. Cities have been modelled with an array of models with different complexities. These models are called urban land surface models (ULSM) and focus on radiation, and turbulent sensible and latent heat fluxes. Grimmond et al. (2010) evaluated these models finding that the latent heat flux is the most challenging to simulate. This flux is part of both the energy balance and water balance, as the latent heat flux is the energy equivalent of the mass evapotranspiration. Thus, the hydrological circumstances may be crucial to correctly model the turbulent heat fluxes. However, the representation of the water balance in these models has not been the focus of a multi-model evaluation. As a part of the follow-up project to the work by Grimmond et al. and Urban-PLUMBER we evaluated the representation of the water balance in ULSMs with varying complexity and representation of the water balance. It is difficult to evaluate the water balance fluxes against observations, as not all terms are observed. For example, changes in water storage require knowledge of the state of all the individual stores (e.g. soil moisture, detention ponds). Analysis of 14 models shows a large spread in the magnitude of the individual water balance fluxes. The rate of reduction of the latent heat flux/evapotranspiration during periods without rainfall varies widely between models, consistent with literature (e.g. Jongen et al., 2022). Initial analysis suggests that models that simulate the water balance and conserve mass are more likely to accurately simulate turbulent heat fluxes. It is thus crucial that both the water and energy balance are accounted for in future urban model improvements.

How to cite: Jongen, H., Lipson, M., Teuling, R., Grimmond, S., and Steeneveld, G.-J.: Crucial consistency of the water balance in urban land surface models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7046, https://doi.org/10.5194/egusphere-egu22-7046, 2022.

11:44–11:50
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EGU22-3188
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ECS
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Virtual presentation
Yiqing Liu, Zhiwen Luo, and Sue Grimmond

Buildings are a major source of anthropogenic heat emissions, impacting energy use and human health in cities. The difference between building energy consumption and building anthropogenic heat emission magnitudes and time lag and are poorly quantified. Energy consumption (QEC) is a widely used proxy for the anthropogenic heat from buildings (QF,B). Here we revisit the latter’s definition. If QF,B is the heat emission to the atmosphere due to human activities within buildings, we can derive it from the changes in energy balance fluxes between occupied and unoccupied buildings. Our derivation shows the difference between QECand QF,B is attributable to a change in the storage heat flux induced by human activities (ΔSo-uo). Using building energy simulation (EnergyPlus) we calculate the energy balance fluxes for an isolated building with different occupancy states. The non-negligible differences in diurnal patterns between QF,B and QECcaused by thermal storage. With this definition negative QF,B can occur as human activities reduce heat emission from buildings but are associated with a larger storage heat flux. Building operations (e.g., open windows, use of HVAC system) modify the QF,B by affecting not only QEC but also the ΔSo-uo diurnal profile. This study demonstrates the difference between QF,B and QEC and the proposed new method for estimating QF,B could provide data for future parameterization of both anthropogenic heat and storage heat fluxes from buildings.

How to cite: Liu, Y., Luo, Z., and Grimmond, S.: The difference between building anthropogenic heat flux and building energy consumption, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3188, https://doi.org/10.5194/egusphere-egu22-3188, 2022.

Lunch break
Chairpersons: Natalie Theeuwes, Hendrik Wouters, Harro Jongen
Interactions and feedbacks
13:20–13:26
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EGU22-13410
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Virtual presentation
Lucian Sfica, Claudiu Cretu, Pavel Ichim, Iuliana-Gabriela Breaban, and Robert Hritac

The increasing accessibility to high resolution land surface temperature (LST) data unbalances recently the investigation of the urban heat island (UHI) towards approaches based on these remote sensing tools. However, for a holistic assessment of UHI, a need of comparison of the resulted surface urban heat island (SUHI) with the air urban heat island(AUHI) remains of great interest. In our study we respond to this demand by taking to account all the MODIS LST images and their corresponding synchronous air temperature observations from 9 in-situ monitoring points evenly distributed over the city of Iași for 2013-2020. This way, using a total of 2901 satellite images, the main diurnal and seasonal characteristics of clear-sky SUHI have been outlined for Iași city.

The results obtained describe accurately the intensity of the SUHI, but also its relation with the urban land use categories. During summer season in daytime the spatial extent of SUHI reaches its maximum, SUHI being bounded by the 35°C isotherm in direct relation with the highest imperviousness ratio. In the winter season instead, SUHI is almost absent during the day especially due to the high frequency of temperature inversions in this area. Also, the geometry of SUHI tends to be compact and regular during the nighttime and more irregular during the daytime, as a result of the higher and more complex energy input.

The comparison with the in-situ observations indicates that the differences between SUHI and AUHI are highest during the daytime in spring and summer, when LST is 5 to 7°C higher than the air temperature in classical sheltered conditions, while during winter no major difference can be observed. For the nighttime the LST is 1 to 3°C lower than air conditions regardles of the seasons. The analysis is detailed with the influence of land use categories and imperviousness ratio on SUHI, but also on the difference between SUHI and AUHI. As well, using a k-means atmospheric circulation classification we identified the weather patterns that are capable to increase both the SUHI intensity, and the difference between SUHI and AUHI.

How to cite: Sfica, L., Cretu, C., Ichim, P., Breaban, I.-G., and Hritac, R.: Differences between surface and air urban heat island for clear sky conditions in Iasi city (Romania) and their relation with atmospheric circulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13410, https://doi.org/10.5194/egusphere-egu22-13410, 2022.

13:26–13:32
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EGU22-2250
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On-site presentation
Jan Karlický, Peter Huszár, Michal Belda, and Tomáš Halenka

The urban heat island (UHI) is well-known phenomenon, however, also other meteorological field are significantly affected by urban environment. The WRF and RegCM regional climate models with various setting were used to determine overall weather and climate alteration due to urban surfaces. Simulations were run on 9 km domain covering the center of Europe and time area of years 2015 and 2016. Validation of results was performed by E-OBS, ECAD and MODIS data. The urban effects were studied for 10 chosen big cities across domain, nearly all studied variables manifest statistically significant differences in urban areas. Cloud cover is increased in cities mainly in summer afternoons, together with sub-grid-scale precipitation. Specific humidity is decreased during day-time in summer and also in winter. In view of differences between models, the urban effects are more pronounced in WRF than in RegCM model. Finally, as a generalization of UHI and similar phenomena defined already, we can define urban meteorology island (UMI) as a single phenomenon covering all specific features as UHI as components of UMI.

How to cite: Karlický, J., Huszár, P., Belda, M., and Halenka, T.: The impact of urban areas on various meteorological variables: The “urban meteorology island”, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2250, https://doi.org/10.5194/egusphere-egu22-2250, 2022.

13:32–13:38
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EGU22-3245
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Virtual presentation
Numerical analysis of the contemporary interaction between the Phoenix Metro Area Urban Boundary Layer and the local thermo-topographical circulation 
(withdrawn)
Aldo Brandi
13:38–13:44
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EGU22-12345
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ECS
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On-site presentation
Saloni Sharma and Amit Kumar Mishra

The continuous heat release over cities/urban areas during night owing to urban heat island effect causes turbulent mixing and sustained supply of moisture and cloud condensation nuclei to the boundary layer. This sustained supply of moisture helps in persistence of low-level clouds over these urban areas as compared to rural/suburban areas during night. The various dynamical process including cloud formation, transport and dispersion of moisture and pollutant at boundary level at night time is highly influenced by the nocturnal low-level jets .These nocturnal low-level jets are found to be stronger over urban . These low-level jets are associated with high vertical wind shear production which enhances the turbulent mixing below boundary layer and plays a critical role in formation of nocturnal stratus clouds. In this study we have identified the vertical location of low-level jets using radiosonde data.  We get two peak for the frequency of occurrence of low-level jets, first at around 500-1000 m (boundary-level jets) and another at 1500 m altitude for winter, pre-monsoon, monsoon and post-monsoon seasons. We have also shown the diurnal (morning and evening) variation in the low-level jet frequency for these four seasons. The measurements from radiosonde in this study are taken at 05:30 am Local time (00:00 UTC) and 5:30 pm (12:00 UTC). We have also identified the types of clouds classified on the basis of number of layers over the study areas and associated it with the occurrence of low-level jets.

How to cite: Sharma, S. and Mishra, A. K.: Occurrence of low-level jets and multi-layer clouds over various urban agglomerations located in Indo-Gangetic Plain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12345, https://doi.org/10.5194/egusphere-egu22-12345, 2022.

13:44–13:50
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EGU22-7478
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ECS
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Highlight
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On-site presentation
Clinton T.F. Chiu, Kai Wang, Athanasios Paschalis, Tohid Erfani, Nadav Peleg, Simone Fatichi, Natalie Theeuwes, and Gabriele Manoli

Urbanization modifies heat, moisture and energy budgets at the land surface, resulting in significant urban-rural differences. A consequence of land conversion to the built environment is the higher air and surface temperatures in cities compared to their rural surroundings, the so-called urban heat island (UHI) effect.  A few studies have also analysed the impact of cities on atmospheric humidity, the so-called urban dry island (UDI) effect, and observational evidence have revealed enhanced cloud cover and intensified rainfall events over large metropolitan areas. However, the impact of UHI and UDI on convection triggering is still a matter of enquiry. The understanding of how urban-induced change in the surface energy budget affects the diurnal evolution of the boundary layer temperature and humidity profiles is crucial to investigate the formation of convective clouds over cities.

We propose an analytical zero-order model of the Atmospheric Boundary Layer (ABL) to quantify the impact of surface and free atmosphere conditions on UHI, UDI, and convection triggering. The model is shown to reproduce field observations from the BUBBLE experiment in Basel (Switzerland) and is used to investigate the crossing between the ABL height and the lifting condensation level (LCL) as a proxy for the triggering of convective clouds. Our results confirm that urban areas are generally warmer and drier compared to rural counterparts, thus increasing both ABL and LCL heights. There is a range of free atmosphere conditions for which changes in urban imperviousness can impact convection triggering but surface warming alone cannot explain the observed enhancement of cloud cover over cities.

How to cite: Chiu, C. T. F., Wang, K., Paschalis, A., Erfani, T., Peleg, N., Fatichi, S., Theeuwes, N., and Manoli, G.: Land and atmospheric conditions regulating urban heat and dry islands and their impact on convective cloud formation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7478, https://doi.org/10.5194/egusphere-egu22-7478, 2022.

13:50–13:56
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EGU22-12683
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ECS
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On-site presentation
Sofia Fellini, Annika Vittoria Del Ponte, Marilina Barulli, Luca Ridolfi, Lionel Soulhac, Massimo Marro, and Pietro Salizzoni

The exacerbation of the urban heat island due to global warming poses a serious risk to the health of citizens. Furthermore, the alteration of the urban microclimate affects air quality with an expected increase in the concentrations of harmful pollutants. Greening cities is an effective tool to mitigate these effects. However, the effect of tree planting in urban street canyons is still a debated topic. Despite their positive effect on temperature and their filtering action, trees can hinder air circulation thus limiting pollutant removal processes. In this context, it is essential to understand and model the effect of trees on the ventilation of street pollutants, heat and moisture . To this end, we present in this work the results of an experimental campaign conducted in a wind tunnel. An urban geometry with a street canyon perpendicular to the wind direction was reproduced. A linear source of passive scalar simulated the emission of pollutants from vehicular traffic. Reduced scale trees have been conceived to mimic a realistic aerodynamic behaviour. We investigated four different configurations of vegetation density: a street with no trees, two trees in the middle of the street, two rows of scattered trees and two dense rows of trees. Concentration and velocity measurements were performed in order to characterize the transfer processes of pollutants inside the street and to estimate a bulk vertical exchange rate. Results show that the presence of trees alters the concentration field in the street with a progressive shift from a nearly two-dimensional to a three-dimensional field. Despite the significant spatial variation in concentration, the presence of trees does not alter the overall efficiency of the ventilation as the vertical bulk exchange velocity remains almost constant in the different configurations. The statistical analysis of the turbulent concentration signal gives other insights in the transfer processes. The turbulent signal measured in different positions of the cavity and for different tree density follows a Gamma distribution with constant fluctuation intensity suggesting an almost universal behaviour within the canyon and providing a powerful modelling tool. Finally, combined measurements of concentration and velocity allows to measure the turbulent mass fluxes at the roof height and investigate their spectrum therefore enlightening the effect of trees on typical scales of motion.

How to cite: Fellini, S., Del Ponte, A. V., Barulli, M., Ridolfi, L., Soulhac, L., Marro, M., and Salizzoni, P.: Turbulent transfer and concentration statistics in a street canyon with tree planting, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12683, https://doi.org/10.5194/egusphere-egu22-12683, 2022.

13:56–14:02
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EGU22-4581
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Highlight
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Virtual presentation
Guowei Yang

Whether the urban heat island (UHI) is affected by air pollution in urban areas has attracted much attention. By analyzing the observation data of automatic weather stations and environmental monitoring stations in Beijing from 2016 to 2018, we found a seasonally dependent interlink of the UHI intensity (UHII) and PM2.5 concentration in urban areas. PM2.5 pollution weakens the UHII in summer and winter night, but strengthens it during winter daytime. The correlation between the UHI and PM2.5 concentration has been regulated by the interaction of aerosol with radiation, evaporation and planetary boundary layer (PBL) height. The former two change the surface energy balance via sensible and latent heat fluxes, while the latter affects atmospheric stability and energy exchange. In summer daytime, aerosol-radiation interaction plays an important role, and the energy balance in urban areas is more sensitive to PM2.5 concentration than in rural areas, thereby weakening UHII. In winter daytime, aerosol-PBL interaction is dominant, because aerosols lower the PBL height and stabilize atmosphere, weaken the heat exchange with the surrounding, with more heat accumulated in the urban areas and the increased UHII. Changes in evaporation and radiation strengthen the relationship. At night, the change of UHII more depends on the energy stored in the urban canopy. Aerosols effectively reduce the incident energy during daytime, and the long-wave radiation from the buildings of urban canopy at night becomes less, leading to a weakened UHII. Our analysis results can improve the understanding of climate-aerosols interaction in megacities like Beijing.

How to cite. Yang, G., Ren, G., Zhang, P., Xue, X., Tysa, S. K., Jia, W., Qin, Y., Zheng, X., and Zhang, S.: PM2.5 Influence on Urban Heat Island (UHI) Effect in Beijing and the Possible Mechanisms, Geophys Res Atmos, 126, https://doi.org/10.1029/2021JD035227, 2021.

How to cite: Yang, G.: PM2.5 influence on Urban Heat Island (UHI) effect in Beijing and the possible mechanisms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4581, https://doi.org/10.5194/egusphere-egu22-4581, 2022.

14:02–14:08
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EGU22-3931
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ECS
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Virtual presentation
Irena Nimac, Ivana Herceg-Bulić, Maja Žuvela-Aloise, and Matej Žgela

Combined with global warming, urban areas are in additional danger of extreme heat due to the well-known urban heat island (UHI) phenomenon. In this study, the effect of the North Atlantic Oscillation (NAO) on urban heat load in Zagreb (Croatia) is investigated using ground measurements from meteorological station Zagreb-Maksimir, as well as an urban climate model MUKLIMO_3. NAO impact in both winter (wNAO) and summer (sNAO) seasons are analysed in terms of indirect (lagged) and direct effects on the urban heat load. The strongest increase in heat load is detected when positive wNAO is followed by negative sNAO, while the opposite situation is associated with heat load decrease. NAO impact is the weakest for situations with the same wNAO and sNAO polarity due to their opposing effects on climate parameters over investigated area. Besides changes in the total heat load, differences in UHI intensity are also found. Results indicate soil moisture as one of potential physical links between NAO and the heat load. The combination of positive wNAO and negative sNAO supports dry and warm conditions over the Zagreb area and vice versa. In situations with extended dry period, green areas experience stronger increase in heat load than densely built-up regions. Therefore, cooling efficiency of vegetation can be modified with NAO through the processes that include precipitation, temperature and soil moisture. This was confirmed by additional modelling experiments considering standardized precipitation evapotranspiration index (SPEI). These findings are additionally confirmed using land surface temperature data from Landsat-8 satellite. Results of this study demonstrate that irrigation of green urban areas should be included in UHI mitigation measures, particularly for situations when seasonal forecasts indicate long-lasting warm and dry conditions.

Nimac, I., Herceg-Bulić, I., Žuvela-Aloise, M. and Žgela, M. (2022), Impact of NAO and SPEI conditions on summer urban heat load – a case study for Zagreb. Int J Climatol. Accepted Author Manuscript. https://doi.org/10.1002/joc.7507

How to cite: Nimac, I., Herceg-Bulić, I., Žuvela-Aloise, M., and Žgela, M.: How does North Atlantic Oscillation modify summer urban heat load in Zagreb (Croatia)?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3931, https://doi.org/10.5194/egusphere-egu22-3931, 2022.

Extremes, impacts and climate services
14:08–14:14
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EGU22-9654
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ECS
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Highlight
Lorenzo Mentaschi, Grégory Duveiller, Grazia Zulian, Christina Corbane, Martino Pesaresi, Joachim Maes, Alessandro Stocchino, and Luc Feyen

Urban temperatures are generally higher in cities than in their non-urbanized surroundings, both during day and night. This phenomenon, known as the Urban Heat Island effect, represents a hazard, as it exacerbates heat-related illnesses and mortality. Its intensity can be estimated from remote sensing retrievals of Land Surface Temperature (LST), and in such conditions it is usually referred to as Surface Urban Heat Island (SUHI). Past global studies analyzed this phenomenon in terms of urban and/or annual/seasonal means, but the impact on human health depend on short-term heat stress experienced locally. On the other hand, local studies are often performed on time-limited and not always representative empirical cases, employ different types of measurements and methodologies, making them difficult to intercompare. Moreover, they cover extensively a few developed areas, such as Northern America, Europe and Eastern Asia, leading to a knowledge gap with respect to less studied regions.

To fill this gap, here we developed a high resolution (1 km) dataset of observations of day and night SUHI based on 18 years of MODIS Aqua imagery, which offers an unprecedented insight into the short-time and short-range behavior of the Urban Heat Island. Our results show that 3-day SUHI extremes are on average more than twice as high as the warm-season median SUHI, with local exceedances up to 10 K, and with hotspots of intense heat and relatively cooler areas are clearly observable within the same city. Furthermore, over this period, SUHI extremes have increased more rapidly than warm-season medians, and averaged worldwide are now 1.04 K or 31% higher compared to 2003. This can be linked with increasing urbanization, more frequent heatwaves, and greening of the earth, processes that are all expected to continue in the coming decades.

These data provide clear evidence of the importance of high space-time resolution in studying the Urban Heat Island and the threat it poses. They can be used in a range of applications, from the day-by-day assessment of urban heat, to the calibration of models of the urban climate (Mentaschi et al., 2022).

 

References

Mentaschi, L., Duveiller, G., Zulian, G., Corbane, C., Pesaresi, M., Maes, J., Stocchino, A. and Feyen, L.: Global long-term mapping of surface temperature shows intensified intra-city urban heat island extremes, Glob. Environ. Chang., 72, 102441, doi:10.1016/j.gloenvcha.2021.102441, 2022.

 

How to cite: Mentaschi, L., Duveiller, G., Zulian, G., Corbane, C., Pesaresi, M., Maes, J., Stocchino, A., and Feyen, L.: Daily mapping of global surface temperature reveals intensified local extremes of Surface Urban Heat Island, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9654, https://doi.org/10.5194/egusphere-egu22-9654, 2022.

14:14–14:20
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EGU22-6438
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ECS
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Virtual presentation
Xu Zhang, Josep Roca Cladera, and Blanca Arellano Ramos

In the context of global warming, frequent extreme climate events, especially high temperature heat waves and global warming, lead to an increase in the frequency and intensity of heat waves. At the same time, due to changes in climatic and hydrological characteristics, extreme precipitation and drought events closely related to people's lives frequently occur. This research studies the heat waves and extreme precipitation events from 1971 to 2020 in the Mediterranean coast of Spain, mainly in the Barcelona metropolitan area, and analyzes their main causes and influencing factors. It is of great significance to formulate improved policies and protection mechanisms in the future to promote sustainable urban development. We selected 8 different meteorological observatories as primary climate data sources in the provinces of Barcelona and Valencia, Alicante, Murcia and Almeria respectively. Using the OLS model, we estimated the global warming at each temperature by the cosine formula     from the analysis of the daily average temperature, maximum temperature, and minimum temperature for each observation point. As a result, stations with higher average temperatures had lower estimates of their warming. The performance of global warming varies greatly between day and night, and is more pronounced at night than during the day. Raval is the only sample with negative values. We taken 1971-2000 as the observation period, and use the 95% percentile to judge extreme climate. It was found that the frequency of heat waves increased year by year, and the number of heat waves occurred at night was significantly higher than that during the day. The precipitation on a heat wave night is generally higher than that on a heat wave day, but the heat wave is usually accompanied by drought. However high humidity is high during the heatwave in central Barcelona. The occurrence of extreme precipitation decreases, with a higher density of heavy rainfall in the southern region than in Barcelona. In addition, extreme precipitation has made an outstanding contribution to the annual precipitation, up to 88.47%. Finally, various regression models are established to analyze the possible factors affecting extreme climate. High latitudes and long distances from the sea promote heatwaves during the day and can also prolong the number of days that they last. Heatwave nights are more frequent in high latitudes, but staying away from the ocean and high altitude can improve it. In addition, global warming and precipitation are supporting factors for high temperature heat waves. The frequency of extreme precipitation is directly proportional with latitude and mean precipitation, and is inversely correlated with distance and altitude from the sea and daily maximum temperature. There is no obvious relationship between extreme precipitation and daily maximum precipitation.

How to cite: Zhang, X., Roca Cladera, J., and Arellano Ramos, B.: Research on Extreme Weather Events in Spain - Analysis of high temperature heat wave and extreme precipitation in the Mediterranean Coast of Spain and Barcelona, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6438, https://doi.org/10.5194/egusphere-egu22-6438, 2022.

14:20–14:26
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EGU22-4464
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ECS
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Highlight
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On-site presentation
Tugba Dogan and Aleš Urban

Episodes of extremely high temperatures (heatwaves) are associated with an increased risk of human mortality. People living in cities are at the most significant risk of heat-related mortality due to the urban heat island effect. Although most studies investigate the impact of heat stress on mortality in a city as a whole, the magnitude of the heat stress in a particular part of the city depends on its physical characteristics.

Our study aims to investigate spatio-temporal links between the spatial distribution of the surface urban heat island intensity (SUHII) and heatwave-related mortality in Prague, the Czech Republic. We will analyse daily all-cause mortality in ten Prague districts between 2001 and 2010. A mortality baseline in each district will be determined using generalized additive models adjusted for long-term trends and seasonal and weekly cycles. Relative deviations from the baseline mortality will be calculated to quantify excess mortality during heat waves, defined as periods of at least three consecutive days with a mean daily temperature higher than the 95th percentile of the annual distribution. Six major heatwaves will be selected to investigate the links between the spatial distribution of SUHII and heat wave-related mortality. Daily MODIS land surface temperature images will be used to analyse the spatio-temporal changes in SUHII during the major heatwaves. Spatial statistics tools in ArcGIS will be used to investigate the spatio-temporal patterns.

Our study hypothesizes that the spatial distribution of heat-related mortality is associated with the distribution of SUHII during the major heatwaves. Due to climate change, the frequency and intensity of heatwaves are expected to increase, and the urban heat island intensity is likely to increase in response to heatwaves. The results of our study will help to identify areas in Prague with the most significant impact of urban design on heat-related mortality. This information is vital for identifying hot spots of heat-related mortality and developing strategies to mitigate heat stress in the city.

How to cite: Dogan, T. and Urban, A.: Links between the spatial distribution of the surface urban heat island and heat-related mortality in Prague, Czech Republic, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4464, https://doi.org/10.5194/egusphere-egu22-4464, 2022.

14:26–14:32
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EGU22-7205
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ECS
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Highlight
Oscar Brousse, Charles Simpson, Owain Kenway, and Clare Heaviside

The impact of cities on the local climate is a well-known and -studied phenomenon. In particular, cities increase local air temperature, particularly at night, and creating what is called the urban heat island (UHI). The UHI in the UK’s capital city of London was one of the first to be quantified by Luke Howard around 1830. Since then, many studies have measured, or modelled, the impact of urbanization on local temperatures, and considered the potential impacts on heat-related mortality. Nevertheless, these studies are often: i) focused on short-time periods – e.g., constrained to few days of heatwave; ii) lack spatial density and/or representativity of measurements; or iii) don’t report a method that would make their results and outcomes comparable to other cities.

Our aim is to make coherent spatio-temporal estimations of the burden that cities bring in terms of heat-related mortality. To achieve this, we ran two 3-months (June to August) regional climate simulations at 1 km horizontal resolution using the Weather and Research Forecasting (WRF) which consist of two simple scenarios: with and without the city. For both scenarios, the model was parameterized using the new standardized WUDAPT-TO-WRF python tool. In the natural scenario, surrounding natural pixels from MODIS were considered most probable land covers and replace the city. In the urban scenario, urban canopy parameters were obtained from the European Local Climate Zones (LCZ) map. We used the complex three-dimensional Building Effect Parameterization urban canopy model with its Building Energy Model (BEP-BEM) to represent the urban effect in the urban scenario. The simulations were run for the 2018 summer and its 4 heatwaves over London and the south east of England. The model was evaluated for its urban scenario against a variety of earth observations and meteorological measurements from official and crowd-sourced data. Finally, we bias-corrected the urban and the natural scenario using an innovative method that relies on official automatic and citizen weather stations. This way, me make sure that the calculated heat anomaly induced by the city is as representative as possible , and allows us to quantify the proportion of heat related mortality which we attribute to the urban heat island in London.

Our study is considered one of the first to model a whole seasonal impact of a city on its local climate using a highly complex urban canopy model and a standardized method of parameterization. Our bias-correction method is also expected to provide key perspectives on the joint utility of modelled and crowd-sourced weather data for heat-related epidemiological studies.

How to cite: Brousse, O., Simpson, C., Kenway, O., and Heaviside, C.: Modelling the urban heat island of London, and implications for heat-related mortality during the 2018 summer heatwave, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7205, https://doi.org/10.5194/egusphere-egu22-7205, 2022.

14:32–14:38
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EGU22-5182
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ECS
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Virtual presentation
Hang Yin, Laxmi Sushama, and Bernardo Teufel

Despite extensive efforts in the past few decades, it still remains a big challenge to reach a coherent and concrete conclusion on how urbanization modifies precipitation for differently located and configured cities. To investigate the impacts of urbanization on summer precipitation characteristics over Montreal, the second most populous city in Canada, two sets of high-resolution numerical simulations using the Global Environmental Multiscale (GEM) model, for consecutive summers (2015-2019), one with detailed urban representation using the Town Energy Balance (TEB) model and one without TEB, are used in this study.

To validate the performance of GEM, the simulation results are directly compared with observations from Environment and Climate Change Canada weather stations, spread across the city. Results show that GEM is able to capture the general climate characteristics such as diurnal cycles of 2-meter air temperature, relative humidity, 10-meter wind pattern, and precipitation intensity distribution reasonably well over Montreal. Comparison of the two sets of simulations shows that urbanization induces a general reduction of the total summer precipitation amount over Montreal due to decreased evapotranspiration caused by land surface modification. Results also suggest an increasing tendency of extreme precipitation amount at higher temperatures in the simulations with TEB, catalyzed by enhanced surface convergence and moisture supply. Additional sensitivity experiments helped understand how urbanization has impacted the management of various engineering systems, such as road infrastructure.  

How to cite: Yin, H., Sushama, L., and Teufel, B.: Impacts of urbanization on summer precipitation and management of engineering infrastructure systems for Montreal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5182, https://doi.org/10.5194/egusphere-egu22-5182, 2022.

14:38–14:44
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EGU22-8558
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ECS
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Highlight
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On-site presentation
Alexander Pasternack, Ines Langer, Henning W. Rust, and Uwe Ulbrich

Large cities and urban regions are highly sensitive to impacts caused by extreme meteorological events (e.g. heavy rainfall). As problems caused by hazardous atmospheric events are expected to intensify due to the anthropogenic climate change, planning of adequate adaptation measures for urban infrastructure is needed. Planning adaptation measures does not only require further research on potential impacts in a changing climate as a basis, but also a check of the practical feasibility for stakeholders. 

Under the BMBF research program “Urban Climate Under Change” ([UC]²), we relate heavy precipitation events over Berlin to the respective fire brigade operations. Here, the precipitation data are based on temporally high resolved radar data. The fire brigade operation data are available on time and location, but the number of recorded events is small, and their distribution is highly overdispersive compared to a Poisson model. To account for this problem we apply a two part hurdle model with one part modeling the probability of the occurrence of fire brigade operations and one part modeling the actual number of operations given that at least one operation occurs. In the corresponding statistical models the parameters of the distributions are described by additive predictors, which are based on precipitation duration and intensity as well as building density. With a fire brigade dataset covering the years 2002 - 2013 we already could show with a cross validation setup that both the occurrence model and the model for the number of operations significantly outperform the reference forecast of the climatology for certain areas over Berlin. For this study we are able to investigate the behaviour of both statistical models for an extended dataset including the years 2018 - 2020. Morevover we examine the effects of the orography as additional predictor on the statistical models, since sinks may have an importent influence on fire brigade operations w.r.t. water damage.

How to cite: Pasternack, A., Langer, I., Rust, H. W., and Ulbrich, U.: Statistical modeling of fire brigade operations with respect to extreme precipitation events over Berlin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8558, https://doi.org/10.5194/egusphere-egu22-8558, 2022.

Coffee break
Chairpersons: Nektarios Chrysoulakis, Matei Georgescu, Sorin Cheval
15:10–15:16
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EGU22-11268
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ECS
Mikhail Varentsov, Timofey Samsonov, Pavel Kargashin, Pavel Konstantinov, Anastasia Shurygina, and Yulia Yarinich

The problems of climate change, high-impact weather phenomena and human thermal comfort in urban areas nowadays receives more and more attention not only from urban scientific community, but also from professionals in related fields as well as from general public.

Today, publicly available weather-focused web services and applications experience rapid development and expansion. However, such services focused on urban climate are very rare and have limited usability. In this presentation, we share our experience in development of web-mapping application for urban climate monitoring & research for Moscow megacity in Russia. We aim to develop the web-application which provides observation-based evidence about current and historical weather conditions and human thermal comfort in Moscow region. Such application could be a valuable tool not only for urban climate researchers, but also for citizens planning their outdoor activity, weather and climate enthusiasts, weather-focused media, popularization of science, school and university education, etc.

Previously, we have developed a prototype of such web-mapping application, which collects and maps observations at official weather stations and crowdsourced observations at Netatmo citizen weather stations (Varentsov et al., 2020).  Application backend includes software for automated data collection, PostgreSQL database, data preprocessing tools (quality control for Netatmo data, spatial interpolation, simple model for on-the-fly calculations of Universal Thermal Climate Index representing human thermal comfort), GIS-server Geoserver for showing raster data. The application frontend is based on the OpenLayers web mapping library. The database is accessed by using the supplementary Node.js server application.

Current stage of development includes several new tasks. Firstly, we plan to increase the timespan of historical data available in the application by 2005-2022. Secondly, we plan to develop interactive tools for data analysis, including time series plots and temporal averaging. Finally, we plan to supplement the application by the catalogue of illustrative weather events, such as cases with intense urban heat island, extreme precipitation, and dangerous thermal stress, and to provide popular description of such cases. The recent version of web-application under development is available at http://carto.geogr.msu.ru/mosclim2/.

Acknowledgements: Development of web-application was supported by Russian Geographic Society under grant No. 03/2021-Р. Selection of intense precipitation cases for catalogue of illustrative weather events was supported by the grant of President of Russian Federation for young PhD scientists No. МК-5988.2021.1.5. Data analysis performed by Mikhail Varentsov was also funded by Non-commercial Foundation for the Advancement of Science and Education INTELLECT.

Reference: Varentsov M. I., Samsonov T. E., Kargashin P. E., Korosteleva P. A., Varentsov A. I., Perkhurova A. A., & Konstantinov P. I. (2020). Citizen weather stations data for monitoring applications and urban climate research: an example of Moscow megacity. IOP Conference Series: Earth and Environmental Science, 611(1), 012055. https://doi.org/10.1088/1755-1315/611/1/012055

How to cite: Varentsov, M., Samsonov, T., Kargashin, P., Konstantinov, P., Shurygina, A., and Yarinich, Y.: Development of a web-mapping application for urban climate monitoring & research: experience from Moscow, Russia , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11268, https://doi.org/10.5194/egusphere-egu22-11268, 2022.

15:16–15:22
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EGU22-11749
Sorin Cheval, Alexandru Dumitrescu, Adrian Irașoc, Monica-Gabriela Paraschiv, Vlad Amihăesei, and Darren Ghent

Heat-related hazards pose major risks to our cities and the projected climate changes indicate substantial increases in impacts, and a better understanding of the interactions between environmental changes and human health are particularly critical for improving the living quality in urban areas in the climate change context. The considerable progress of monitoring, modelling, and analysing methods has addressed the increasing demand for enhanced accuracy, finer resolution, and better accessibility of climate products and services, including the specific needs of the built-up areas.

This study informs the present Heat Hazard-Risk (HHR) over the 262 cities of Romania using a risk matrix approach that aggregates the hazard triggered by high temperatures (i.e. Land Surface Temperature), and elements of vulnerability associated with the structure (i.e. Local Climate Zones - LCZ), and population density (i.e. number of inhabitants per 100 m2 in each urban area).

The MODIS LST_cci products used in this study are customised TERRA_MODIS_L3C and AQUA_MODIS_L3C daily day/night 0.01° resolution data on an equal angle latitude/longitude data over Romania produced within the project LST_cci+ (CCI Land Surface Temperature, 2020), and covering the period 2000-2018. The LCZ values were extracted from a European database characterizing the urbanised landscapes derived within the World Urban Database and Access Portal Tools (WUDAPT) project. The population density was retrieved from the Joint Research Centre (JRC) database.

Generally, the HHR is higher in the central parts of the cities, but industrial and residential areas contribute to high-risk values towards the marginal perimeters too. The size and the industrial profile of a city impact the extent of the heat risk. For example, the biggest cities in the southern areas hold the most extended areas at risk at the country level. The land cover is a significant factor that controls the thermal hazard risk in the urban areas of Romania: the highest HHR values correspond to the discontinuous urban fabric, industrial and commercial units, and construction sites, while the lowest values stand for the urban forest, and water bodies.

This study has received funding from the European Space Agency (ESA) within the framework of the Land Surface Temperature project under the Climate Change Initiative (LST_cci), contract number 4000123553/18/I-NB.

How to cite: Cheval, S., Dumitrescu, A., Irașoc, A., Paraschiv, M.-G., Amihăesei, V., and Ghent, D.: A country scale assessment of the heat hazard-risk in the urban areas of Romania, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11749, https://doi.org/10.5194/egusphere-egu22-11749, 2022.

15:22–15:28
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EGU22-6365
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ECS
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On-site presentation
Zeting Li, Gerald Mill, Matthias Demuzere, and Benjamin Bechtel

Cities are major drivers of climate change and are especially at risk from projected changes, such as more frequent and enhanced flood and heatwave events. Many of these hazards are elevated for cities because of their topographic settings (e.g., low-elevation and close to coasts) and urban layout (e.g., impervious fraction), the details of which are unique to each city. While there have been studies of the impact of climate change on cities, these have generally examined exposure in individual cities to projected changes or of urbanized landscapes to one change, such as sea-level rise. This research uses the Local Climate Zone (LCZ) map of Europe as a framework to examine city-based mitigation and adaptation options at a continental scale. The LCZ scheme describes types of urban landscapes and their physical properties that can be used to assess degrees of hazard exposure. These data will be combined with other publicly available geographic datasets on projected climate changes, topography, population, greenhouse gas emissions, etc., to provide a large-scale evaluation of urban risk and responses.

How to cite: Li, Z., Mill, G., Demuzere, M., and Bechtel, B.: Evaluating urban risks in Europe using publicly available continental-scale data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6365, https://doi.org/10.5194/egusphere-egu22-6365, 2022.

15:28–15:34
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EGU22-2488
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Highlight
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On-site presentation
Nektarios Chrysoulakis, Zina Mitraka, Mattia Marconcini, Tomas Soukup, Mario Dohr, David Ludlow, Birgitte Holt Andersen, Dirk Lauwaet, Christian Feigenwinter, Alessandra Gandini, and Jürgen Kropp

A major challenge for the urban community is the exploitation of Earth Observation (EO) in dealing with the multidimensional nature of urban sustainability towards enhancing urban resilience, particularly in the face of climate change. Here, we present how the H2020 funded project CURE (Copernicus for Urban Resilience in Europe) synergistically exploits Copernicus Core Services, to develop cross-cutting applications for urban resilience. CURE provides the urban planning community with spatially disaggregated environmental information at local scale, as well as a proof-of-concept that urban planning and management activities towards enhancing the resilience of cities can be supported by four Copernicus Core Services, namely, the Land Monitoring Service (CLMS), the Atmospheric Monitoring Service (CAMS), the Climate Change Service (C3S) and the Emergency Service (EMS).

CURE improved analysis methods for addressing specific dimensions of urban resilience, enabling its integration into operational services in the future, related to climate change adaptation and mitigation, healthy cities and social environments and energy and economy. Thus, CURE has the potential to reveal novel scientific insights on the exploitation of Copernicus for urban resilience and policy development, thereby generating new EO opportunities. CURE is built on Data and Information Access Services (DIAS), as s system integrating these cross-cutting applications, capable of supporting downstream services across Europe, addressing also its economic feasibility. CURE has resulted in information capacity presenting current state of cities against drivers (land use, green areas, energy use etc.) and pressures (pollution, emissions, floods, etc.) and help in assessing their overall impact (quality of life, health, economic damage, etc.) that will enable cities to prepare an evidence and knowledge based response (i.e., better plans, local actions and new policies).

The contribution of CURE mainly concerns: online platform for combining Core Services to support urban resilience planning; uniform data for large samples of urban areas both within region and across regions in Europe; consistent measurements across European cities, including synergies between Copernicus core products and third-party data; different approaches and models for better information on urban from and function at different spatial and temporal scales; and assimilation of users’ knowledge with technical data and benchmarking; fostering of innovation. The innovation potential of CURE lies on the exploitation of the Copernicus offer in the domain of urban resilience, by developing cross-cutting applications combining products from CLMS, CAMS, C3S and EMS with third-party data, as well as by developing a system for integrating these applications, enabling its incorporation into operational applications and downstream services in the future.

More information on CURE evolution at: http://cure-copernicus.eu

How to cite: Chrysoulakis, N., Mitraka, Z., Marconcini, M., Soukup, T., Dohr, M., Ludlow, D., Holt Andersen, B., Lauwaet, D., Feigenwinter, C., Gandini, A., and Kropp, J.: Copernicus for Urban Resilience in Europe: Intermediate results from the CURE project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2488, https://doi.org/10.5194/egusphere-egu22-2488, 2022.

15:34–15:40
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EGU22-7891
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Highlight
Antje Katzschner and the ZURES II

Heat waves are one of the most often experienced impacts of climate change. In recent years, there has been a significant increase in heat extremes during the summer months. According to the German Weather Service (DWD), the three hottest summers in measured history were all in the 2000s: In Germany, the summers of 2003, 2018 and 2019.

The Federal Ministry of Education and Research (BMBF) funded project ZURES II – Application and continuation of future-oriented climate and vulnerability scenarios in selected instruments and planning processes – aims to apply methods for urban development targeting heat stress resilience to planning processes of the City of Ludwigsburg. By identifying and evaluating climate change and future changes in social vulnerability in the City of Ludwigsburg, it was possible to link the previously juxtaposed concerns of climate and social urban development. A constant dialogue with municipal representatives in Ludwigsburg resulted in the recognition of urban development plans as a key instrument to achieve an integrative perspective – considering the processes of changes in climate and urban society together.

The primary goal of the continuation phase is thus to strengthen urban resilience and adaptation to heat stress through an integrated planning framework with information on urban society and climate, and to overcome the isolated consideration of social and climatic aspects through transdisciplinary application research. This aim is to be achieved in dialogue with the city and citizen participation measures.

Communicating dimensions of vulnerability

The proposed contribution is an integrated approach of different communication strategies from both the observational (surveys on household and city level) and modelling perspective (urban climate map), examining urban planning processes, the efficacy of various strategies to reduce heat stress, and measures highlighting how the city of Ludwigsburg is already using science data and products from the research project ZURES that facilitate planning and policies on adaptation to heat stress. A special focus will be on the communication of different vulnerabilities and how the project addresses the fundamental question of what constitutes a meaningful basis of information for sustainable and resilient urban development, especially with regard to resilience to heat stress. Up to now, climate analyses and scenarios have often been used to determine risks and adaptation needs as a basis for information. However, this practice is not entirely innovative, as it is unlikely, for example, that the population in 2030 or 2050 will be the same as in 2019. Therefore, the ZURES project aims to develop small-scale vulnerability and risk assessments, which includes further development of climate modelling as well as advancing methodologically innovative scenario techniques to describe future vulnerability to heat stress.

How to cite: Katzschner, A. and the ZURES II: Communicating dimensions of vulnerability with respect to heat stress, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7891, https://doi.org/10.5194/egusphere-egu22-7891, 2022.

Adaptation, policy and scenarios
15:40–15:50
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EGU22-8744
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solicited
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Highlight
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Virtual presentation
E. Scott Krayenhoff, Timothy Jiang, Alberto Martilli, Christian Moede, and Matthias Demuzere

Future urban climates are likely to warm substantively in coming decades as a result of climate change, and greater heat wave severity is anticipated. Moreover, the urban heat island contributes additional heat, especially during evening and night. Infrastructure-based heat reduction strategies can reduce canopy air temperatures during daytime, and to some extent at night. These strategies also have several additional effects beyond air temperature reduction. Here, we apply an early coupling of the WRF mesoscale model with the BEP-Tree urban canopy model to simulate extreme heat events representative of both contemporary and projected future climates for the metropolitan region of Toronto, Canada. Urban and non-urban land cover is derived using the state-of-the-art LCZ Generator methodology. Subsequently, the effectiveness of heat mitigation strategies, including highly reflective surfaces and vegetation, is quantified for the future scenario in the context of the increase in heat wave intensity. Specifically, the neighbourhood- and city-scale climate impacts of street trees across the diurnal cycle are quantified, and the diurnal progression of their local climate effects is discussed with reference to their modifications to multiple physical processes in the canopy. Effects of all heat mitigation strategies on canopy climate, building energy use, and thermal comfort indices are evaluated.

How to cite: Krayenhoff, E. S., Jiang, T., Martilli, A., Moede, C., and Demuzere, M.: Assessment of infrastructure-based reductions of future heat wave intensity with advanced mesoscale modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8744, https://doi.org/10.5194/egusphere-egu22-8744, 2022.

15:50–15:56
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EGU22-7671
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ECS
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Highlight
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Virtual presentation