This study explores the spatiotemporal variations in Land Surface Temperature (LST) and vegetation indices in relation to Local Climate Zone (LCZ) classification in a coastal, temperate climate city across multiple seasons. The study focuses on Cardiff, the capital and largest city of Wales, located only 2.4 km from the sea. The findings of this study extend our scientific understanding of the interrelations between LST and morphological and surface properties of the built environment and urban vegetation for various LCZ classes in Cardiff. Results showed a significant variation in Surface Urban Heat Island (SUHI) intensity in spring, summer, and winter. LST and Normalised Difference Vegetation Index (NDVI) were found to vary significantly across the LCZ classes demonstrating their association with the local urban form and morphology. For built-up areas, LCZ classes with lower vegetation cover and higher building density showed higher LST. For natural areas, LCZ F (Bare soil or sand) had higher LST than LCZ A (Dense trees). The high-density, built-up LCZ classes have a greater UHI compared to the natural classes. In addition, the results showed that LST and NDVI are significantly affected by the morphological and surface properties for each LCZ classes. Building surface fraction, impervious surface fraction and surface admittance were found to have a positive correlation with LST. Sky View Factor, surface albedo and pervious surface fraction, on the other hand, showed a negative correlation with LST. Opposite associations were found with the NDVI. Urban planners and designers will find the study useful to develop heat mitigation strategies while planning, designing, or improvising the new and existing urban areas in Cardiff. In addition, the LCZ map produced in this study for Cardiff using local expert knowledge will enable international comparison and testing of proven climate change adaptation and mitigation techniques for similar urban areas.

How to cite: Sharmin, T., Lannon, S., and Chappell, A.: Spatio-temporal variability of land surface temperature and vegetation indices within Local Climate Zone classes in Cardiff, Wales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8591, https://doi.org/10.5194/egusphere-egu23-8591, 2023.

The inverse S function can not only fit the spatial attenuation of construction land density, but also fit the spatial attenuation characteristics of various urban characteristics. Therefore, we assume that the inverse S-function curve is also applicable to the spatial variation law of urban LST. We hope to conduct an inverse S function model fitting analysis of the surface temperature of the three major cities in Beijing, Tianjin, Hebei, China's capital economic circle in 2001 and 2020 in winter, summer, day and night in eight periods to verify that they all conform to the characteristics of the function curve, and use the fitting parameters to analyze the urban development process and its impact on the thermal environment.

First, we draw concentric circles at intervals of 1KM from the center points of the three cities, and then extract the land surface temperature (LST) of each circle and process it dimensionlessly. Finally, the inverse S function model is fitted to all LST data, and the expression of the inverse S function is as follows. And combined with the characteristics of LST, the fitting parameters in the function are given corresponding meanings.

Analyzing the results of fitting parameters, LST conforms to the law of the reverse S-curve model in most cases.

Since the LST in the most periods can be simulated by the inverse S model, it is proved that their change law is that they first decrease slowly with the increase of the radius of the concentric circle, then decrease rapidly, and finally decelerate to zero.

The fit parameter "a" controls the slope of the curve. The larger "a" is, the faster the curve decays, indicating that the urban thermal environment is more compact.

The "a" of each city of winter is greater than that of summer.

Except for the smallest "a" in winter night in Beijing in 2020, the "a" in summer in 2001 was the smallest in other cities. The distribution of urban thermal environment in this period is the most scattered.

The "a" results for Beijing and Tianjin are similar every time, but Beijing has a wider range of values. Tianjin's is generally larger than them.

The fitting parameter "c" is the mean value of surface temperature at the city fringes.

The most cities are distributed between 0 and 0.2.

Only Tianjin Xiaye in 2020 reached 0.53. It shows that the temperature around Tianjin is on the high side during this period.

The fitting parameter "D" reflects the radius of the urban thermal environment.

The "D" of each city sample has increased to varying degrees, indicating that the urban high-temperature thermal environment has also expanded.

The thermal environment radii of Beijing and Shijiazhuang are the smallest at night in winter, while Tianjin is the smallest at night in summer.

The fastest growth rate was during summer nights, with each city adding more than 10 kilometers.

The slowest growth in Beijing is during the daytime in summer, while that in Tianjin and Shijiazhuang is during the night in winter.

How to cite: Zhang, X., Roca Cladera, J., and Arellano Ramos, B.: Research on the effect of urban territorial expansion on thermal environment using the inverse S-function curve- Taking Beijing-Tianjin-Hebei China Capital Economic Circle as an Example, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15292, https://doi.org/10.5194/egusphere-egu23-15292, 2023.

Urban anthropogenic heat has a direct impact on urban climate. However, due to a warm feedback loop, the attributions of urban anthropogenic heat in urban area are unclear. This research carried out an attribution analysis of anthropogenic heat index (AHI) derived from remote sensing over global 1386 cities to investigate the contribution of 13 environmental variables to global urban anthropogenic heat based on GEE environment. 13 independent variables are categorized the groups of human activities, land morphology, vegetation, climate and atmospheric environment on anthropogenic heat. The results show that although human activities are considered as the main source of the anthropogenic heat, other factors have more impacts on the anthropogenic heat pattern in the urban area due to the feedback loop of urban thermal environment. Climate played a leading role in the impacts on anthropogenic heat with a contribution rate of 30-50% in most background contexts. The impact rate of human activities and landforms on anthropogenic heat accounts for 20% in most background scenarios. The findings of this research can contribute to the solution of mitigating urban anthropogenic heat and expanded the research scope of urban anthropogenic heat in the urban area.

How to cite: Wu, H. and Huang, B.: Attributes analysis of global urban anthropogenic heat index with multi-sources remote sensing data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16489, https://doi.org/10.5194/egusphere-egu23-16489, 2023.

There is often a lack of meteorological stations in cities, which makes it difficult to examine their microclimate. Alternatively, it is possible to get around this by fixing measuring instruments on bicycles and traversing through the city to observe spatial patterns in the urban canopy layer. The "traverse" approach enables insight into the spatial variation of air temperature in relation to urban form.

In this research, air temperature measurements were carried out using bicycles and an IoT MF-300 instrument with a synchronized GPS receiver and a temperature probe under different weather conditions throughout 2021 and 2022 in Zagreb, Croatia. The GPS receiver's high sensitivity and position accuracy allowed measurements in places like urban canyons and dense foliage environments. The routes were carefully designed to pass through morphologically diverse parts of Zagreb to emphasize the heat characteristics of the city's microclimate. We specifically analysed the spatial distribution of air temperature and land surface temperature (LST) during a heat wave event on the 24^th of June 2021. On that day mobile measurements were conducted between 10:30 and 11:15 AM local time to match the LST measurements of the Landsat-8 satellite that overpassed Zagreb at approximately 10:45 AM. Additional measurements were carried out in other seasons and at different times of the day.

Results show thermal differences between surface types and urban forms. During a heat wave event, air temperatures reached up to 35 °C, and LST was above 40 °C, which are high temperatures considering the time of measurement. However, mobile measurements showed that city parks can be even 3 °C cooler compared to densely built-up city areas. Due to the high response time of the instrument, the effect of microscale city properties, such as tree lines, was also observed. These results indicate the cooling effect of green areas in Zagreb and the importance of their preservation for heat load reduction and mitigation of the negative effects of the urban heat island.

How to cite: Žgela, M. and Herceg Bulić, I.: Urban heat load assessment in Zagreb, Croatia: a multi-scale analysis using mobile measurements and satellite imagery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-290, https://doi.org/10.5194/egusphere-egu23-290, 2023.

Detailed knowledge about the intra-urban air temperature variability within a city is crucial for the implementation of adaptation strategies to counteract the negative effects of urban heat stress. Various methods to model urban-rural temperature differences exist, but they often only cover certain periods (heatwave, hot day) or meteorological conditions (sunny and calm) due to computational limitations or limited data availability. Land use regressions, which are usually based on fine scaled measurements and high resolution spatiotemporal data, are one promising method to overcome those limitations and to conduct daily urban temperature fields.

In the city of Bern, Switzerland, a very dense urban temperature network (about 1 station per 1.5 km²) is operated since summer 2018. With that detailed information on temperature and publicly available land use and meteorological data, different land use regression types with a differing degree of complexity were tested in the recent past. One main outcome of the application of the method in Bern is an urban temperature dataset that covers the temperature distribution of all nights of the metropolitan area of the summers 2007 to 2022 with a resolution of 50 meters. In this talk, we would like to present the different models applied in Bern, analyze the potential of land use regression approaches in urban climate studies, and discuss possible applications of the dataset regarding urban planning and heat stress studies.

How to cite: Burger, M., Gubler, M., and Brönnimann, S.: Modeling daily urban temperature fields using land use regression approaches, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1476, https://doi.org/10.5194/egusphere-egu23-1476, 2023.

Urban heat is a local scale warming effect associated with urban areas where most of the world's population live. Due to the scarcity of air temperature (Ta) data, urban heat studies have been mostly focused on Land Surface Temperature (LST) extracted from satellite imagery and a quantitative understanding of how LST interacts with Ta within a city is still lacking. Using crowdsourced weather station data in Sydney, Australia, combined with high resolution satellite images and urban datasets (such as Local Climate Zone (LCZ) and building-level urban data), we explore the interaction between Ta and LST, and their intra-urban variabilities during different seasons. We found that LST and Ta have different characteristics and their dependency varies by season and LCZ. When exploring the relationship between Ta, LST, and variables describing the urban structure, such as building fraction, the correlation between LST and urban structure was stronger and more seasonal dependent than the Ta-urban form relationship. Moreover, stronger correlations between LST and Ta were observed in the less built-up areas within the city. We also found that the determinants of LST variability are different from the contributing factors of Ta. These findings provide new insights for quantitatively investigating surface and canopy urban heat and their relationship with land cover, providing fit-for-purpose information to mitigate the adverse effects of urban overheating at local and global scales. 

How to cite: Naserikia, M., Hart, M. A., Nazarian, N., Bechtel, B., and Nice, K. A.: Understanding within-city interaction between surface and air temperatures, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10461, https://doi.org/10.5194/egusphere-egu23-10461, 2023.

How to cite: Mitchell, T. D. and Fry, M. J.: The use of crowdsourced observations to build climate grids and assess urban heat hazard., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14110, https://doi.org/10.5194/egusphere-egu23-14110, 2023.

Due to climate change and urbanization, the world's population is increasingly exposed to extreme heat, posing a threat to public health. Despite people spending ~90% of their time indoors, heat effects in buildings have been studied far less than outdoor heat island effects. This study aims to observe, understand and model the behaviour of indoor air temperatures (T_in) during summer heat. As a proof of concept, we present and analyse up to 27 years of individual T_in timeseries of seven citizen weather stations (CWS) across the Netherlands. First, we find that typically T_in increases slower, but also cools down slower than T_out with a lag difference of ~130 minutes in the diurnal cycle. We demonstrate that nocturnal indoor human thermal comfort (HTC) can be worse than outdoor HTC even for days after a heatwave.

Second, to model T_in behaviour, we simulate six-hour changes in T_in behaviour with a physics-based statistical model by Vant-Hull et al. (2018) that has an outdoor conduction, indoor conduction and solar transfer component. Preliminary results of this computationally-fast model for each of the seven houses are promising, showing on average a R-squared of 0.74 and a root mean squared error of 0.13 K. Third, in the next research steps, we are also interested in how T_in may evolve due to climate change. We will study this by converting the T_in measurements to 2050 and 2085 values based on the Royal Netherlands Meteorological Institute 2014 climate scenarios (or 2023 if available).

Finally, we will scale up our proof-of-concept analyses to 100 indoor CWS placed in Amsterdam. The participating households receive a CWS for three years to measure their indoor climate – temperature, relative humidity, CO₂ concentrations – in the bedroom and living room. Based on our insights, we will make recommendations for climate-sensitive urban design to reduce indoor heat stress.

How to cite: Peerlings, E. and Steeneveld, G.-J.: Hot weather impacts on urban indoor air temperature assessed through citizen science observations in the Netherlands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7886, https://doi.org/10.5194/egusphere-egu23-7886, 2023.

The wind speed varies significantly within a neighborhood due to building and vegetation size and position. A good estimation of these spatial variations is useful for several applications (outdoor thermal comfort, air pollution, building energy consumption and thermal comfort, etc.) but might be time-consuming using Computational Fluid Dynamic tools and difficult to produce for non experts.

URock is a Python library that has been developped within UMEP, a city-based climate service tool integrated as plug-in in the free and open source QGIS software. It is based on the Röckle approach already used in non open source softwares such as QUIC-URB and SkyHelios: first an initial wind field is set according to empirical laws derived from wind tunnel observations; second the mass air flow is balanced minimizing the modifications of the initial wind field. This method is less accurate than traditional CFD method but quicker and simple to implement for non specialists. This work presents the evaluation of URock against wind tunnel observations.

Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 896069.

How to cite: Bernard, J., Lindberg, F., and Oswald, S.: Quick calculation of wind field in urban area within a free and open source GIS: evaluation of the URock model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16480, https://doi.org/10.5194/egusphere-egu23-16480, 2023.

During the last decade, atmospheric measurement networks in urban areas have become important drivers for global pollution and greenhouse gas (GHG) mitigation. For city stakeholders to effectively plan GHG emissions mitigation measures and to monitor changes in emissions, GHG concentration data both, from measurements and simulations on high resolution, are required, but still lacking in most cities. The accurate simulation of high-resolution dispersion in urban areas enables the interpretation of concentration measurements as well as quantitative estimates of local emissions in an inverse modelling framework.

High-resolution dispersion simulations on neighborhood scale are generally computationally costly, preventing the analysis of long time periods. To overcome this limitation, we use the coupled GRAMM/GRAL model which is computationally efficient due to a ‘catalogue approach’. GRAMM/GRAL is composed of the mesoscale model GRAMM, solving the Reynolds Averaged Navier Stokes equations for an outer domain (resolution 100 m), and the computational fluid dynamics model GRAL for an inner domain (resolution 10 m). We run GRAMM for 1008 different wind situations differing in synoptic wind forcing and stability class. GRAL is initialized by the GRAMM fields and calculates wind fields taking the flow around buildings into account.  A time series of hourly, 10 m resolved wind fields and concentrations can be obtained by matching catalogued, simulated wind fields with measurement of a local wind measurement network (‘catalogue approach’).

Here, we evaluate the GRAMM/GRAL model in the urban area of Heidelberg for 12 months. 14 wind measurement stations within the inner GRAL domain enable a thorough evaluation of GRAL for yearly time periods and for a 12x12 km² area under challenging topography. Our evaluation also includes wind profile measurements (up to 200 m) from a LIDAR. We find good agreement between modelled and simulated wind directions. Wind speeds can be simulated with an overall root-mean square difference of about 1 ms^-1 and a mean bias of about -0.3 ms^-1. Measurement sites with poorer model representation are located in the forest or the outer domain with coarser resolution. We conclude that GRAMM/GRAL is capable of simulating high-resolution wind fields in urban areas of complex topography. We showcase first dispersion simulations for carbon dioxide in Heidelberg.

How to cite: May, M., Wald, S., and Vardag, S. N.: Comprehensive analysis of high-resolution dispersion simulations in urban area using the GRAMM/GRAL model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3458, https://doi.org/10.5194/egusphere-egu23-3458, 2023.

The mitigation of urban microclimatic deficiencies as a result of the urbanized environment receives increasing attention by cities, municipalities and the planning community. Priority areas for the implementation of multi-beneficial climate change adaptation measures and the development of mitigation plans need to be identified. Therefore modelling methods producing good results while only requiring moderate data input and computational effort are needed for the widespread application in planning processes. In this study, we test the rapid fine-scale methodology for simulating urban bioclimatic conditions in a 2D environment that was previously introduced by Back et al. (Back et al., 2021). The original methodology uses high resolution land cover classification (Hiscock et al., 2021) from multi-spectral aerial imagery, digital elevation data, and a vector layer of buildings to calculate land surface temperature (LST), mean radiant temperature (MRT), and the Universal Thermal Climate Index (UTCI). We apply this methodology to the rural municipality of Feldbach, Austria, using commercially and openly available satellite imagery. The simulated data is validated against the publicly available monitoring data from the WegenerNet climate station networks (Fuchsberger et al., 2022), which provides high spatial and temporal resolution measurements. The results are evaluated regarding the agreement of relative spatial differences of the simulated variables with the observed data. To be suitable for the identification of priority areas for the implementation of climate change adaptation measures, the methodology is expected to accurately reflect the spatial variability of the simulated variables.

Project supported by ESA Network of Resources Initiative.

Back, Y., Bach, P. M., Jasper-Tönnies, A., Rauch, W., & Kleidorfer, M. (2021). A rapid fine-scale approach to modelling urban bioclimatic conditions. Science of The Total Environment, 756, 143732. https://doi.org/10.1016/j.scitotenv.2020.143732

Fuchsberger, J., Kirchengast, G., Bichler, C., Leuprecht, A., & Kabas, T. (2022). WegenerNet climate station network Level 2 data [Text/csv,application/x-netcdf]. Wegener Center for Climate and Global Change, University of Graz. https://doi.org/10.25364/WEGC/WPS7.1:2022.1

Hiscock, O. H., Back, Y., Kleidorfer, M., & Urich, C. (2021). A GIS-based Land Cover Classification Approach Suitable for Fine‐scale Urban Water Management. Water Resources Management, 35(4), 1339–1352. https://doi.org/10.1007/s11269-021-02790-x

How to cite: König, A., Pichler, M., and Muschalla, D.: Validation of a 2D modelling approach for urban microclimatic conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7691, https://doi.org/10.5194/egusphere-egu23-7691, 2023.

Urban areas are known to be exposed to higher temperatures than rural areas making urban citizens particularly vulnerable to extreme heat events. Large eddy simulation (LES) models can simulate micrometeorological heat transport and mixing processes by directly resolving large-scale turbulence. These models can be used to simulate urban development strategies aiming at mitigating the adverse effects of heat waves in cities by analyzing their influence on urban microclimate. Despite their use in formulating recommendations for city planning, these models are often not validated with observed meteorological data. We here present results from conducting a model-observation comparison for a mid-size city in Germany. Model simulations were computed with the LES model PALM4U run at two different resolutions (Δx,y,z = 5 and 20 m) and evaluated against observations from a network of microweather stations for a heat wave in 2019 reaching maximum near-surface air temperatures of 37 °C.

During daytime, differences between observed and modeled near-surface air temperatures were small (-3.8 to 1.1 K, mean = 0.9 K), but much larger during night-time and the early morning transition. The latter findings can be explained by an overestimated modeled ground heat flux resupplying too much energy offsetting the radiative cooling leading to overestimated modeled air temperatures by up to +9 K (mean = 5.3 K). Further, results showed that in areas where the actual urban structure is reproduced well by the model resolution, differences between observed and modeled wind speeds were lower. Our findings indicate that a spatial resolution smaller than the mean building height produce more accurate model results for wind speeds. Many differences in model-observation intercomparison are explained by an overestimated modeled turbulent kinetic energy (TKE) causing inflated turbulent mixing in the air, which leads to distorted model output particularly for the urban nocturnal boundary layer.

How to cite: Späte, E., Sungur, L., Schneider, J., Babel, W., and Thomas, C. K.: Simulating an extreme heat event in a mid-sized city in Europe: validating and analyzing the relevance of spatial resolution in the urban LES model PALM4U with an observation network, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15015, https://doi.org/10.5194/egusphere-egu23-15015, 2023.

Climate change and a rapidly increasing urban population make cities more vulnerable to hazardous weather events. The need for a better understanding of meteorological processes and an improvement of the weather prediction system in an urban environment is crucial to mitigate these impacts and protect the population. 

The “Paris Olympics” international Research and Demonstration Project, endorsed by WMO, aims at improving meteorological research in urban meteorological processes and weather forecasting systems at 100m resolution. It mainly focuses on extreme weather events in urban areas such as urban heat islands and thunderstorms. Several study cases have been proposed. They are golden cases observed during the PANAME2022 field campaign in Paris and they represent interesting weather situations to test numerical weather prediction capacities.

The objective of this study is to investigate through the selected cases, the influence of Paris’s urban environment on thunderstorms. An ensemble of hectometric simulations is built using the Meso-NH research atmospheric model initialized and forced by the members of the AROME-EPS ensemble prediction system which has a 1.3 km horizontal resolution. For each case, two sets of ensemble simulations are performed; to identify the main processes driving the interactions between urban environment and thunderstorms: one with a fine-scale surface description of the city (using a multi-layer urban scheme) and another one where the urban surface is replaced with vegetation.

The first results show that it remains challenging to correctly simulate the location of thunderstorms. Nevertheless, the ensemble technique combined with urban and non-urban city description is effective to discriminate random effects from real trends on  the urban environment impacts on thunderstorms.

How to cite: Forster, A., Masson, V., and Augros, C.: Study of the urban effect of Paris on several thunderstorm cases in 2022, using hectometric ensemble simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3249, https://doi.org/10.5194/egusphere-egu23-3249, 2023.

Increasing urbanization and its implication for human health, outdoor thermal comfort, air quality or energy consumption necessitate a need for high-resolution urban modelling. In this study, we evaluate uSINGV, a coupled urban-atmosphere research model used by the Singapore Meteorological Service, for four clear-day over Singapore using two different spatial resolutions of 300 and 100 m, respectively. The model is modified to incorporate urban morphology and land use/land cover datasets which are based on European Space Agency climate change initiative data (ESA CCI) at 300 and local datasets at 100 m spatial resolution. The evaluation is carried out for near-surface variables such as temperature, specific humidity, wind speed, and turbulent surface fluxes using Kling-Gupta efficiency (KGE'), root mean square error (RMSE) and mean absolute error (MAE) as model evaluation metrics. Results suggest that temperature and specific humidity are similar for 300 m and 100 m spatial resolution. On the other hand, for 100 m (300 m), the 10 m wind speed has a KGE’ of 0.45 (0.15), RMSE of 0.69 (1.42) m/s, and MAE of 0.55 (1.26) m/s, hence showing improvements from 300 to 100 m spatial resolution. In addition, sensible heat flux for 100 m resolution simulations is closer to observations, while latent heat flux is overestimated. Overall, uSINGV is able to produce reliable simulations at 100 m spatial resolution, thereby showing promise for improved understanding of detailed urban climate processes.

How to cite: Patel, P., Chen, S., Dipankar, A., Roth, M., Lean, H., Zhang, H., and Moise, A.: Comparison of 300 m and 100 m uSINGV clear-day simulations for Singapore, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10849, https://doi.org/10.5194/egusphere-egu23-10849, 2023.

The urban environment and climate change are essential factors to consider for applications involving urban planning and human health. Although these factors influence estimations of energy consumption and thermal comfort, buildings in France are still generally designed and renovated without accounting for these specific conditions but by considering present rural weather conditions. The first objective of this study is to develop an approach to explore building design and renovation choices while accounting for the urban environment and climate change. The second objective is to find which design and renovation choices are relevant to improve thermal comfort and reduce energy consumption (and therefore GHG emissions).

First, we use observations and simulations of weather conditions in several cities of France (representing different climatic zones), for the present and future climate (2050), to analyze urban conditions and estimate energy consumption. Second, we run building simulations for rural and urban situations, and for present and future climate conditions, to investigate the effect of the urban environment and climate change on the operation of buildings, and the effect of building scenarios on the urban climate.

How to cite: Blond, N., Breton, F., Micolier, A., and Mendez, M.: A modeling approach to address building energy consumption and thermal comfort under urban climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14169, https://doi.org/10.5194/egusphere-egu23-14169, 2023.

How to cite: Vurro, G., Constantinidou, K., and Hadjinicolaou, P.: Comparison of urban canopy models (UCMs) over the area of Nicosia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5473, https://doi.org/10.5194/egusphere-egu23-5473, 2023.

This study summarizes the inter-comparison of three urban canopy models that are able to derive local-scale urban air temperature from rural atmospheric data and urban land use and built form characteristics at an hourly resolution. The focus of this presentation are the findings of the sensitivity analysis and the lessons learned in the process. The evaluated models are the Urban Weather Generator (UWG), the Vertical City Weather Generator (VCWG), the Surface Urban Energy and Water Balance Scheme (SUEWS). The evaluation is done against a two-week-long air temperature and relative humidity measurement conducted in the neighborhood of Újlipótváros in Budapest, Hungary. 
 
The study found a good agreement between modeled and observed air temperature values with a root mean square error (RMSE) remaining between 1–2ºC when calculated for the entire period. However, when separated per day- and nighttime, as well as per cyclonic and anticyclonic periods, the RMSE of the models increased up to 2–3ºC—particularly when calculated for nighttime and/or for anticyclonic periods. The sensitivity analyses shed light on additional shortcomings in the models. It revealed UWG’s low sensitivity to trees and vegetation. In this regard, especially the presence of trees in the urban canopy were not captured by the model. The analysis also found discrepancies regarding VCWG’s model physics, as the model responded to the increase in shortwave radiative forcing with decreasing air temperatures. The study will conclude with a set of recommendations for model developers and users.

How to cite: Gal, C.: A model inter-comparison and sensitivity analysis of three urban canopy models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15513, https://doi.org/10.5194/egusphere-egu23-15513, 2023.

Snowfall and snow depth are important elements of the climate system which can have a significant impact on the transport sector, local economy, water resources and local thermal regime.

This study aims to identify the future trends of snowfall and snow depth in the most important urban areas in Romania, based on high-resolution regional climate models (RCM) data, made available through the EURO-CORDEX, and bias-corrected RCM simulations available în the RoCliB dataset. Ten different regional climate models with a target resolution of 10 km and two emission scenarios were considered, namely the moderate (RCP4.5) and business-as-usual (RCP8.5) scenarios. The study covers the interval from 2021 to 2100.

In order to predict the future snow depth, snow cover duration and snowfall amounts based on the available parameters from the RCM simulations, it was necessary to identify the complex relationship between snowfall, snow melting, temperature and precipitation. In order to do this, we first extracted the ERA5 reanalysis data from 1981 to 2020 for each urban area, and then employed a Bayesian Regularized Neural Network (BRNN). The resulting model was used to predict the future variables for all major urban areas in Romania.

A general trend of decreasing snowfall amounts, mean snow depth and snow cover duration was observed for all analyzed areas and for both emission scenarios. Important regional variations were also observed, with some areas no significant change for the 2021 – 2050 interval compared to the observation period, which could be explained mostly by the increasing winter precipitation predicted by the RCM simulation. The results also showed an increased possibility of some years virtually lacking any snow cover and snowfall precipitation, especially after 2050 in the business-as-usual scenario (RCP8.5). However, an increased variability was also observed, with extreme snowfall events remaining possible even in the latter half of the study interval.

How to cite: Hrițac, R., Sfîcă, L., Breabăn, I.-G., and Amihăesei, V.-A.: The expected effect of climate change on snowfall amounts and snow depth in the major urban areas of Romania, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12497, https://doi.org/10.5194/egusphere-egu23-12497, 2023.

According to NASA's temperature record, Earth in 2021 was about 1.1 degrees Celsius warmer than the late 19th century average, the start of the industrial revolution. The rate of Global Warming (GW), however, differs across different regions of the planet. The Mediterranean is one of the "hotspots" of climate change, with more prominent temperature increases throughout the 20th and 21st centuries (Giorgi 2006). Since the mid-20th century, the average temperature over the Mediterranean has been increasing above the global average. The recent temperature record reveals an annual mean temperature for the entire basin that is approximately 0.4°C above the global mean (Lange 2021). This increase is even higher on the Spanish coast, which has experienced increases of more than 2°C (Arellano 2022).

The aim of this paper is to analyze the warming process in the main Spanish urban areas since unified records were kept in the early 1970s. For this purpose, the evolution experienced by temperatures between 1971 and 2022 in 21 meteorological stations representative of all the Spanish Autonomous Communities is analyzed. Barcelona, Madrid, Valencia, Zaragoza, Seville, Malaga, Bilbao, Valladolid, Ciudad Real, Badajoz, Asturias, Corunya, Ourense, Murcia, Logroño, Palma de Mallorca, Las Palmas de Gran Canaria and Santa Cruz de Tenerife, are studied.

The results show that, if on a global scale temperatures have risen 0.94°C since 1971, the increase in the main cities of peninsular Spain has been 2.17°C. And 2022 will be the warmest year on record. The research carried out differentiates the evolution experienced by maximum and minimum temperatures, showing that the continental influence is mainly manifested in the increase of maximum temperatures, while in the area of Mediterranean influence, the increase of minimum temperatures is more pronounced. On the other hand, the Cantabrian and Atlantic coasts, as well as, above all, the Canary Islands, show less pronounced increases, below 2°C.

The study also presents the heat and cold waves (Serra 2022) experienced by the cities studied. Diurnal heat waves (DHW) have increased from 0.6 per year per weather station in the decade 1971-1980, to 1.71 in 1981-1990, 1.81 in 1991-2000, 2.72 in 2001-2010, and 3.84 in 2011-2020. 2022, with 7.11 DHW per station, is the year with the highest number of diurnal heat waves in the entire series. Regarding nocturnal heat waves (NHW) they have increased from 0.47 per station per year in the decade 1971-1980, to 1.53 (1981-1990), 1.57 (1991-2000), 3.55 (2001-2010), and 4.63 (2011-2020). Again 2022 is the year with the highest number of NHW, with 7.61 per weather station.

2022 appears, therefore, as the warmest year since records have been kept, and the one in which a greater number of NHW has been experienced.

How to cite: Roca, J., Arellano, B., and Zhang, X.: Global Warming in Spanish Cities (1971-2022), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16349, https://doi.org/10.5194/egusphere-egu23-16349, 2023.

Poli-HE, a coupled hydrological-energy budget model was developed to simulate the surface water, and energy fluxes between soil and shallow atmospheric boundary for the city of Milano, Northern Italy. So doing, we describe the urban heat island effect, i.e. differences in land surface temperature (LST) between paved/urban, and green/natural areas, i.e. parks, and suburban agricultural patches.

Energy and water balance equations are linked through soil water content (W), and latent heat flux (LE), calculated as a function of the LST. W in turn drives (actual) evapotranspiration, thus driving (water) mass balance. Input variables were used from i) meteorological stations, air temperature (Ta), net radiation (Rn), rainfall (R), and ii) satellite images, giving leaf area index (LAI) and land surface temperature were used for model tuning.

The results show large differences in LST between urban/green areas, high during summer, viz 3-4 °C, lower in winter, viz 0.3°C. During 2010-2021 max surface temperature in Milano was +37.3°C in urban areas, and to +33.6°C in the green areas.

The model was then used for future projections of LST, using outputs of the Global Circulation Model EC-Earth3.0, constrained to shared socio-economic pathways SSP1-2.6 and SSP5-8.5 of the CMIP6. We analysed near (2030-2041), medium (2050-2061) and long-term (2080-2091). On average in the city of Milano, LST is projected between +0.14°C (SSP 2.6 in the medium-term), and +6.35°C (SSP 8.5 in the long-term). The jump of LST between urban/green areas would reduce against average increase of air temperature, and LST, i.e. large increase of air temperature will be less and less dampened by the present green area cover.

How to cite: Casale, F., Zhang, W., and Bocchiola, D.: Urban heat island under climate change. The case study of Milano, Italy., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12896, https://doi.org/10.5194/egusphere-egu23-12896, 2023.

In this study, land use/land cover changes were examined to investigate their impact on the urban heat load of the City of Dubrovnik in the present and future climate. Dubrovnik is situated in the Mediterranean, which has been referenced as one of the most responsive regions to climate change. Therefore, it is crucial to investigate the effects of different substrates on the heat load and its possible mitigation. Firstly, urban heat load, in the current morphology of the city, is investigated in the present and future climate conditions by using data observed at the local meteorological station and data obtained from regional climate models of the EURO-CORDEX initiative. Also, the urban climate model MUKLIMO_3 is utilized to obtain the spatial distribution of the heat load. Climate indices based on measured data (summer days and tropical nights) show that the heat load has been increasing in the last 50 years. The spatial distribution of the heat load in the City of Dubrovnik in the present climate indicates that the highest heat load is in the public and residential parts of the city. Furthermore, during the nighttime, heat load decreases with a reduction in the density of buildings. Climate indices obtained by simulations of the model MUKLIMO_3 for future climate scenarios (rcp4.5 and rcp8.5) show that the heat load will increase in the entire city domain, with the strongest increase in its urbanized parts. In this study, the impact of modifications in land use/land cover (like changes in the fraction of buildings, impervious surfaces, vegetation and albedo of the roofs) on the heat load are examined. It is demonstrated that these changes will decrease the heat load to some extent. However, the impact is locally limited and significantly smaller than the contribution of global warming. Therefore, land use/land cover changes can mitigate the urban heat load. However, even more comprehensive interventions cannot eliminate the overall increase in the urban heat load due to global warming.   

How to cite: Boras, M., Žgela, M., and Herceg Bulić, I.: Impact of land use/land cover changes on the urban heat load - a case study for the city of Dubrovnik, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5207, https://doi.org/10.5194/egusphere-egu23-5207, 2023.

Territories are complex environments with many issues at stake. The issues of human health and energy consumption for instance are linked to local weather and climate change. Despite the scientific and societal developments of the last decades, some of the physical and social processes of territorial climate change are still not well understood, and the implementation of mitigation and adaptation is slow. The following studies address these aspects of processes, mitigation, and adaptation, based on different methods in climate and social sciences.

The first study investigates the seasonality of weather conditions in Europe by using classification approaches (weather types, local analogues) on climate observations, simulations and projections. Simulations are close on average to the observed variability, winter conditions decrease while summer conditions increase, and Mediterranean seasonality expands Northwest while Scandinavian seasonality declines. 

The second study investigates the social perception of climate change and the acceptability of territorial options (mitigation, adaptation) by inhabitants and decision-makers, based on field interviews and foresight activities in the Gulf of Morbihan (France). A strong territorial seasonality (climate, socio-economy) and a complex role of climate change are found, as well as general agreement between local experiences and scientific knowledge. Despite divergent visions among inhabitants, two long-term scenarios and about twenty short-term actions emerged from foresight activities.

A third study investigates the effect of urban parameters on city temperature, and how urban planning options can optimize thermal comfort and reduce energy consumption and GHG emissions, based on urban climate observations and simulations. The city size drives urban warming, followed by urban fraction but building heights can cool the city depending on the season. Model adjustment and sensitivity simulations are presented for the urban planning approach.

How to cite: Breton, F.: Territorial climate change: understanding, mitigating and adapting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14056, https://doi.org/10.5194/egusphere-egu23-14056, 2023.

The population growth and its concentration within cities, on the one hand lead to an increment of water demand and on the other hand affect the urban water cycle with frequent urban flood events associated to rain extreme events. New approaches to the water management are currently being developed where a role is assigned to rain water harvesting (RWH). RWH provides water for non-potable uses (private and public, indoor and outdoor), reducing water consumption. Moreover, RWH allows to partially retain water on site, reducing the probability of failures of the sewerage system during heavy rain events.

These positive effects are easily evaluable at a building scale when well-known behavioral models are used, while the evaluation becomes often more complex at an urban scale, due to the lack of characteristics and demographic data about all the buildings in the city. In our work, we consider RWH impact at the urban scale, by means of the representative building concept.

We focus on several hypothetical retrofitting scenarios for the residential buildings of Turin (Italy): 1) domestic use of rainwater (e.g., toilet flushing and the washing machine), where buildings are independent of each other, and 2) two public uses of rainwater (the irrigation of public green areas and street washing), for which we have hypothesized that the rainwater collection takes place at a district scale. We estimate a reduction of 42% in the non-potable water consumption for domestic use (values vary across the municipal districts from 29% to 62%, according to the characteristics of the buildings), while for irrigation and street washing, that require a lower amount of water, about 80% of the water can be provided by RWH. The highest reduction of the flow peak conveyed to the sewerage system during extreme storms is reached in the domestic use scenario (about 60%, quite constant across the city), while for public uses the retention capacity is very low.

Finally, our estimations based on historical rainfall series are examined against different climate change scenarios.

How to cite: Carollo, M., Butera, I., and Revelli, R.: Rainwater harvesting potential: the Turin case for an analysis at the urban scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-848, https://doi.org/10.5194/egusphere-egu23-848, 2023.

The dual forcing of climate change and rapidly urban development on heat waves over the Greater Bay Area (GBA), China and Lagos, Nigeria are investigated by multi-scale numerical simulation with the Weather Research and Forecasting (WRF) model coupled with single-layer urban canopy model. Heat stress cases are dynamical downscaled for the GBA and Lagos, under different scenarios. Three experiments are designed: For the first one, historical climate background derived from ERA5 reanalysis data will be utilized as boundary conditions for WRF, and present urban information is used. For the second experiment, future projected climate forcing using CMIP6 is incorporated into ERA5, with present urban information used. For the third experiment, both future climate and future urban landuse data (2050) will be utilized. Model outputs will then serve as boundary conditions for the ENVI-met model, which simulates microclimate conditions and provides details about heat stress at the street scale in two megacities. Based on our previous work, both urbanization and climate change lead to near-future temperature rise over the GBA, with the intensity of extreme heat events greatly enhanced due to their joint effects. This study is envisaged to provide invaluable urban climate information for climate change risk identification, prediction, mitigation and adaptation, by assessing how global warming, future urbanization, and their dual forcing affect heat stress at the city scale with model. Results related to future heat waves will provide useful information to policy maker about climate-sensitive urban planning, nature-based mitigation strategies and public policies making in the future.

How to cite: Tam, C.-Y. F., Morakinyo, T. E., Mills, G., Wang, Z., Hu, C., Cheng, G. M., and Wu, R.: Investigating global warming and future urbanization impacts on heat stress inmegacities- a multi-scalemodeling approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12500, https://doi.org/10.5194/egusphere-egu23-12500, 2023.

Urban green areas have multiple benefits extending from heat mitigation and carbon sinks to human well-being. Due to their multi-benefits, they are an attractive natural solution to aid climate change adaptation and mitigation. In cities of Helsinki and Tampere located in Finland, intensive observations and modelling of urban water and carbon dioxide (CO₂) fluxes have taken place to improve our understanding of the functioning and carbon sequestration potential of different urban green areas and provide science-based evidence for decision-makers on how urban green areas should be planned and constructed to maximize their climate benefits.

Extensive eco-physiological observations were collected from different vegetation types (urban forest, park, garden, and street vegetation) in Helsinki during summers 2020-2022. The observations were made in the vicinity of the ICOS Associated Ecosystem Station FI-Kmp where eddy covariance (EC) measurements presenting the ecosystem level are conducted. The measurements included photosynthesis, sap flow, soil respiration, phenology, fine root growth, meteorology and soil properties. FI-Kmp represents mixed land use and vegetation, and to get more information of the behavior of lawns, additional EC measurements were conducted over urban lawn in the city of Espoo in 2021-2022. The observations are complemented by ecosystem modelling using SUEWS (Surface Urban Energy and Water balance Scheme). SUEWS is used to examine the impact of different urban green area planning options on carbon sinks and storages with focus on the city of Tampere. 

This work will highlight some of the findings made so far and provide examples on the carbon and water fluxes in different urban green areas. We also demonstrate how science-based knowledge can aid decision-making concerning urban green areas.

How to cite: Järvi, L., Ahongshangbam, J., Havu, M., Lee, H. S., Soininen, J., Karvinen, E., Karvonen, A., and Kulmala, L.: Observations and modelling of urban carbon and water fluxes to aid cities in climate mitigation and adaptation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6042, https://doi.org/10.5194/egusphere-egu23-6042, 2023.

The Urban Multi-scale Environmental Predictor (UMEP) is a city based climate service tool that facilitate user-friendly open source capabilities to combine models and tools essential for climate simulations. The tool is designed for a broad range of users, both within academia as well as practitioners and non-expert users. UMEP is available as a plugin in QGIS, a free and open source geographic information system (GIS) available on all common platforms. One main purpose with UMEP is to include pre-processing of geo- and weather data, process calculations as well as post-processing and visualisation in the same tool.

Recent developments in UMEP enables creation of all essential input variables required to generate high-resolution raster grid of common human thermal comfort indices such as Physiological Equivalent Temperate (PET), Universal Thermal Comfort Index (UTCI), Comfort Formula (COMFA) etc. This work presents initial results and methodology used to compute these indices within UMEP. Examples of workflow throughout the process, all the way to the final result, will be presented and discussed.

Acknowledgement
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 896069.

How to cite: Lindberg, F., Bernard, J., Wallenberg, N., Bäcklin, O., Lönn, J., Thorsson, S., and Kalori, K.: Modelling spatial variation of thermal comfort indices in urban settings performed within an open source GIS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7111, https://doi.org/10.5194/egusphere-egu23-7111, 2023.

In recent years it has become increasingly evident that the solutions to climate changes, both mitigation
and adaptation, must pay greater attention to the places where most people on the planet live. Moreover,
the demand for weather services at urban scales is increasing in line with the ability to model
atmospheric processes at these finer scales; these advances could herald more resilient cities with the
evidence to support planning and design at appropriate time scales. In this context, the lack of
information on urban landscapes and the dearth of urban observations represent a major obstacle to
progress.
This work explores the possibility to create the scientific infrastructure needed to incorporate climate
knowledge into urban decision-making quickly. By combining globally available but locally appropriate
datasets (global map of LCZs, ERA5, Copernicus global land cover layers) and cloud computing (Google
Earth Engine), we created a seamless, holistic and user-friendly SUPY-based urban modelling framework
that can be applied anywhere at any time. Results are evaluated using the Urban Plumber flux tower
observations and a large unique database crowdsourced weather-station observations. The wider
purpose of the project is to develop a pathway to the creation of a universal ‘toolbox’ for baselining
climate-related data for use in any city.

How to cite: Demuzere, M., Kittner, J., Lipson, M., and Sun, T.: Urban climate modelling, anywhere, at any time, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1546, https://doi.org/10.5194/egusphere-egu23-1546, 2023.

The aim of the project CityCLIM is the development of a suite of services for the urban environment interesting for citizens and city administrations. The core of the CityCLIM services consists of a model chain to provide an operational weather forecast with an outstanding cell size of 100m for an area covering a whole city for a time span of up to three days. Therefore, the already operational SuperHD model by Meteologix is used to drive the new UltraHD model, which is a fully compressible large eddy simulation model including a two-moment microphysics parameterization. The UltraHD model was designed to use GPUs as the computational platform and is implemented using OpenCL. Surface orography and mountains were implemented using an immersed boundary layer approach and the model uses three-dimensional boundary conditions from the 1km SuperHD model. During the CityCLIM project further extensions for the UltraHD will be the implementation of a soil model for heat and moisture fluxes, a canopy layer to better represent vegetation fluxes and urban surface characteristics and a three-dimensional radiative transport code using raytracing for the short and a longwave band.

The developed CityCLIM services target at two different groups, the citizens within a city and the city administrations.

Services focused on the citizens are the Heat Wave Information and Warning Service, the Climate Information Service, the Pollution Information Service and the Citizen Weather Sensation Service. Except the Climate Information Service, the services will be based on operational everyday forecasts using the SuperHD and the GPU based UltraHD LES model chain. The Climate Information Service will be an extensive collection of climate and weather related parameters from available reanalysis models and measurement data on the Meteologix web portal. The Pollution Information Service will include aerosol compounds (PM10, PM2.5) and atmospheric trace gases (NOx, O3). With the added equations the computational effort for the UltraHD is significantly higher.

The administrative services consist of identification services for heat islands, city air flow and pollution areas within the city and simulation and mitigation strategies services. For the identification services a collection of many operational UltraHD model runs are analyzed for hot spots within a city and areas which are more sensitive to extreme weather conditions can be identified. The simulation and mitigation strategies services use manipulated input fields like orography and land use for recalculations for selected days. Those will be performed on demand and can be compared to previous simulations. This will provide insight in the effects of certain climate mitigation strategies and can be used as a testbed for large scale city planning.

To verify the results and to improve the initial model fields, high resolution measurement data is necessary. Therefore, the CityCLIM consortium installs additional weather stations within the pilot city regions and additional citizen science data will be collected. Earth observation data is extensively used, to characterize the surface of the city area with respect to land use and vegetation state and to compare model results like land surface temperature and soil moisture.

How to cite: Horn, S. and Zimmer, J.: CityCLIM – From an operational city weather forecast to a suite of services addressing the urban environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12118, https://doi.org/10.5194/egusphere-egu23-12118, 2023.

A major challenge for the urban community is the exploitation of Earth Observation intelligence in managing in the multidimensional nature of urban sustainability towards enhancing urban resilience, particularly in relation to the challenges of climate change. This study presents the ways in which the H2020 funded project CURE (Copernicus for Urban Resilience in Europe) synergistically exploited Copernicus Core Services to develop cross-cutting applications supporting urban resilience. CURE provided the urban planning community with spatially disaggregated environmental intelligence at a local scale, as well as a proof-of-concept that urban planning and management strategies development enhancing the resilience of cities can be supported by Copernicus Core Services. Here, we demonstrate the technical operational feasibility of an umbrella cross-cutting system on urban resilience, consisting of 11 specific applications. These use Copernicus core products from at least two services each as main input information, reflect the main urban sustainability dimensions and are relevant to user needs, which were identified based on a strong stakeholders’ engagement. As a result, CURE is built on Data and Information Access Services (DIAS), as a system integrating these cross-cutting applications, capable of supporting downstream services across Europe, enabling its incorporation into operational Copernicus products portfolio in the future and also addressing its economic feasibility. For more information on CURE: http://cure-copernicus.eu

How to cite: Chrysoulakis, N., Ludlow, D., Mitraka, Z., Somarakis, G., Khan, Z., Lauwaet, D., Hooyberghs, H., Feliu, E., Navarro, D., Feigenwinter, C., Holsten, A., Soukup, T., Dohr, M., Marconcini, M., and Holt Andersen, B.: Copernicus for Urban Resilience in Europe: Final results from the CURE project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1976, https://doi.org/10.5194/egusphere-egu23-1976, 2023.

Today’s urban areas are excessive heat sources. The urbanization process has led to the development of positive temperature anomalies, called Urban Heat Islands (UHI). The future climate projections add an increasingly concern to the already heated and polluted urban environments, especially the increase in air temperature and in the frequency, intensity and duration of heat wave events. Hence, the degradation of the thermal conditions is already affecting human thermo-physiological comfort (TC) and health. In this investigation the UHI effect in Lisbon was detailed analyzed according to different thermal seasons (created based on the annual cycle of maximum and minimum air temperatures) and meteorological conditions, these later grouped into Local Weather Types (LWT). Over 60 000 hourly air temperature grids between 2008 and 2014 with a spatial resolution of 100m were extracted from the Copernicus Earth Observation Program. The UHI was calculated based on the widely used land use/land cover scheme, Local Climate Zones (LCZ). Furthermore, the UHI daily cycle by LWT and LCZ was also analyzed. Results show that on rainy conditions with higher cloud coverage the UHI effect is less pronounced (median intensity close to 0ºC), while on sunny conditions with weak to moderate winds and almost no clouds, especially very cold winter days and very hot summer days, median UHI reach 1.5ºC. The analysis of the UHI daily cycle proves that the UHI effect is mainly a nighttime phenomenon, while during the morning a slight Urban Cool Island (UCI) appears on most LWT. However, the analysis of UHI’s patterns and intensities only shows and compares the distribution of air temperature across different land uses, but the human body’s thermal sensation depends not only on air temperature, but also on wind, humidity, and radiation fluxes Therefore, the TC on 163 days between 2008 and 2014 from a particular LWT (the hottest summer days) was modeled in Lisbon. Thirteen microscale samples were selected according to the LCZ scheme, and 2 different TC indices based on the heat balance of the human body (Physiologically Equivalent Temperature (PET) and Universal Thermal Climate Index (UTCI)) and Mean Radiant Temperature (MRT) were modeled during the day (12:00 to 15:00h) and night (00:00 to 03:00h) on a freely available and user-friendly software (SkyHelios v. 1.5). Results depict a moderate heat stress on LCZ A during the day (average PET/UTCI/MRT of 34ºC, 32ºC and 45ºC respectively) while the  sun-exposed and poorly ventilated areas on the remaining samples registered higher PET, UTCI (strong to extreme heat stress) and MRT values. During the night, PET results present a slight cold stress in all samples, while UTCI simulations show no thermal stress. This investigation will ultimately help to identify critical areas in the city that need interventions on surface materials, urban morphology, urban greenery and anthropogenic heat emissions in order to mitigate extreme heat conditions and its health risks associated.

How to cite: Reis, C., Nouri, A., and Lopes, A.: Urban Heat Island and thermo-physiological stress by Local Weather Types in Lisbon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-197, https://doi.org/10.5194/egusphere-egu23-197, 2023.

Climate and climate-related hazards are growing threats to our cities, as a result of the twin challenges derived from the warming climate and urban expansion. Accountable development strategies must take into consideration the safety of the urban population, including its vulnerability and exposure to different hazards. The evaluation of risks related to heat hazards is a priority for urban municipalities, especially in big cities where the urban heat island intensity is significant. For example, the urban perimeter of Bucharest (Romania) is 2 - 3°C warmer than the 5 km buffer of the rural neighborhood, as an average of the land surface temperature (LST) over the summer months.

This research explores the risk associated with the heat hazard occurring over Bucharest due to vulnerabilities derived from different urban elements, such as population, land cover-land use, local climate zones, and characteristics of the buildings. The analysis covers the period 2013-2022, and the outputs are delivered at 100-m spatial resolution. The heat hazards were derived from LST retrieved from high-resolution imagery (i.e. Landsat 8) data using emissivity estimation, and the urban risk was calculated based on several variables related to demographics and built environment, considering their influence on the vulnerability to heat hazard. The Heat Hazard-Risk was computed using a risk matrix approach, as a product between the heat hazard and vulnerability, and the results inform the level of Census Administrative Units (CAU).

The results show that the heat hazard is more frequent during the warm season, and especially in June-July-August, when the average daily LST exceeds 40°C over the largest part of the city. The land cover characteristics and the LCZ have a significant influence on the LST values and generate adverse impacts on health, economic activities, and the environment.

As regards the demographic profile, this study examines the consequent risk derived from (a) population size (i.e. number of inhabitants and density), (b) age (i.e. younger and older people), and (c) density of people in the same dwelling.

This study has been partly funded by the project Synergies between Urban Heat Island and Heat Wave Risks in Romania: Climate Change Challenges and Adaptation Options (SynUHI) PN-III-P4-PCE-2021-1695.

How to cite: Cheval, S., Dumitrescu, A., Micu, D., Onțel, I., Paraschiv, M.-G., and Simion, G.: Heat hazard and risk assessment in urban areas. Case study of Bucharest (Romania), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7133, https://doi.org/10.5194/egusphere-egu23-7133, 2023.

Climate change is causing temperatures around the globe to rise, leading to an increase in hot days and nights and a rise in the frequency and intensity of heat waves. High temperatures represent one of the key factors causing heat stress, which is affecting human health. Examples include the mega heat wave in August 2003 that took more than 70,000 lives across Europe or the unprecedented heat in 2018 with more than 100,000 heat-related deaths in the EU. Spatial exposure to heat stress varies, with urban areas usually heating up much stronger than their rural surroundings (urban heat island effect). With progressing global warming, the importance of spatially monitoring and predicting urban heat stress over large areas to prevent heat-associated morbidity and mortality is thus rising. For this purpose, thermal data obtained by satellites may represent a valuable alternative or addition to in-situ observations and climate modelling, which both show several advantages, but also shortcomings in terms of spatial coverage (in-situ), data needs (climate modelling) and costs.

One of the main challenges for the use of satellite thermal data for urban heat stress monitoring is to convert the obtained land surface temperature (LST) into air temperature (AT), since satellites only provide information on the former whereas the latter is needed as input for most heat stress indicators. In our presentation, we will address this challenge with emphasis on urban regions. Two main strands of methods are used in the literature for converting LST into AT. First, data driven methods that use the empirical relationship between in-situ observations of AT from weather stations and LST data from satellites. These methods usually work well for individual stations, but the transferability of the relationship to different locations is typically limited. In addition, especially for methods based on machine learning techniques, a significant amount of data is needed for model calibration. The second type of methods comprises physical models. They typically make use of the energy balance to estimate AT from LST. These models show the advantage of better transferability but need additional input data besides LST. Moreover, physical methods are often designed for applications in rural areas, which may differ from the situation in cities. We apply different methods to derive AT from LST in urban regions and discuss their suitability to monitor and predict urban heat stress based on satellite thermal data.

How to cite: Kortschak, D., Damm, A., Gallaun, H., Kernitzkyi, M., Köberl, J., and Strohmaier, M.: Towards a satellite based long-term monitoring and prediction of urban heat stress, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6962, https://doi.org/10.5194/egusphere-egu23-6962, 2023.

Urban green infrastructures are considered useful tools to mitigate air pollution, increase the resistance of cities to climate change, optimize energy consumption expenses and promote the integral management of economic, social and cultural development, according to a "sustainable cooperation". However, there are few studies that quantitatively support this contribution and there is also a lack of knowledge about which species are the most suitable for an urban area in order to improve air quality.  

Therefore, the research project proposes to analyze the improvement of air quality and the contribution to reducing the effects of climate change by trees of an entire urban area. i-Tree Eco software and the inventory of the urban trees of the Madrid Municipality of Boadilla del Monte, with which the project has been developed, have been used. Results about air pollutants reduction have been compared with the Municipality's emissions in order to see how urban greenery helps to the improvement of air quality. Finally, an annual monetary estimation of the Ecosystem Services (ES) offered by the urban trees of the city has been made through the software, then compared with the annual costs (planting, maintenance, removal) agreed with the Municipality of Boadilla, reaching a Cost-Benefit Analysis representative of the contribution given by urban green areas to the surroundings. 

How to cite: Busca, F., Gómez-Villarino, M. T., and Revelli, R.: Influence of urban trees on the climate change adaptation in Boadilla del Monte (Spain), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14239, https://doi.org/10.5194/egusphere-egu23-14239, 2023.

The rapid expansion of impermeable surfaces in cities has a major impact on hydrology and meteorology. The infiltration of rainwater is reduced resulting in more overland flow with higher peak flows, but also reduced evapotranspiration and hence higher sensible heat flux. Urban trees are becoming more important as stormwater management or climate adaptation tools. The rainfall interception of trees already reduces overland flow generation and increases latent heat flux. An in-situ field experiment to measure throughfall on the common urban trees Acer platanoides (Norway maple) and Tilia cordata (small-leaved lime) was conducted to determine the interception of solitary trees on urban sites with different degrees of surface sealing and shading from surrounding buildings in the city of Freiburg, Germany. The influence of rainfall characteristics and tree morphological traits on interception behaviour was investigated with eight trees per species. 76 recorded rainfall events were evaluated from April to September 2021. The recorded interception rates were much higher compared to typical values in forests. Average interception rates were higher for T. cordata (70.29 ± 6.56%) than for A. platanoides (54.76 ± 10.29%). The average interception loss of the recorded events per tree was 2.58 ± 0.60 mm and 3.73 ± 0.29 mm for A. platanoides and T. cordata, respectively. For both tree species, significant linear correlations were found between the relative interception values and other factors like rainfall characteristics, the leaf area index (LAI), and the plant area index (PAI) (adj.R2 > 0.45). Compared to A. platanoides, T. cordata showed significant relationships between several tree morphological parameters (CR, CPA, CC, CV, LAD, PAD) and the relative interception values (adj.R2 > 0.43). The lowest LAI of both tree species were observed at sites with highest degree of surface sealing (tree pits), which also impacts the interception process. Our results provide a better understanding of the interception process of solitary trees for different urban settings. However, further field experiments with various tree species need to be conducted in order to obtain a larger database for simplified applications in modelling approaches and to support urban planners in managing stormwater runoff and adapt to climate change.

How to cite: Anys, M. and Weiler, M.: Urban influences on rainfall interception of different tree species, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5192, https://doi.org/10.5194/egusphere-egu23-5192, 2023.

Vegetations play an important role in the management of physical activities and the public health of urban residents. However, with the rapid urbanization in the world, vegetation regions are changing constantly. In order to prevent the decrease in vegetation areas, constant vegetation monitoring is required. In this study, we performed vegetation extraction and vegetation change monitoring in very high-resolution (VHR) satellite imagery through deep learning-based techniques. To this end, two deep learning networks (i.e., DeepLabV3-plus, and deeply supervised image fusion network (DSIFN)) were used for vegetation extraction and change detection, respectively. Firstly, the two networks were trained on the two datasets each for their respective purpose. Then, a DSIFN was tested to detect all the changes occurring in VHR bitemporal satellite images. Moreover, the binary vegetation maps from bitemporal images were independently generated by using DeepLabv3-plus. Later, the vegetation maps and the change detection result were combined to figure out the change tendency related to vegetation. To show the effectiveness of the proposed method, an accuracy assessment was carried out. The proposed method can be used to determine the amount of change occurring within a period in the vegetation of urban areas.

How to cite: Javed, A., Yun, Y., Hur, J., Yeom, J., and Han, Y.: Deep Learning-Based Vegetation Extraction and Vegetation Change Monitoring by using Very High-Resolution Satellite Imagery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2185, https://doi.org/10.5194/egusphere-egu23-2185, 2023.

The Mediterranean basin is expected to experience an increase in intensity and frequency of heat wave events. Additionally, heat peaks are exacerbated by the low albedo of urban materials and the heat island effect of urban areas. To reduce heat-related discomfort and health risks, urban planners aim to implement green infrastructures to regulate temperatures thanks to their transpiration cooling effect. For example, the Metropolitan Area of Barcelona (AMB) has created a metropolitan network of “climate shelters”, which are public spaces (both indoor and outdoor) where urban dwellers can find better climatic conditions. Urban parks can be considered “climate shelters” if two requirements are met: the NDVI of the vegetation is higher than 0.4 and the extension of the park is bigger than 0.5 ha. However, given the dense urban edification and space limitation, we wanted to explore the thermal regulation capacity of smaller urban parks which are easier to implement. In this study, we present the results of a micrometeorological measurement campaign to assess the temporal and spatial variations of thermal comfort in parks of different sizes in the AMB during a heatwave episode in July 2022. The goals of this study are to determine the impact on human biometeorology of urban design in the construction of urban parks for facing heatwave episodes and to check the classification requirements for the “climate shelters”.

Using a mobile human-biometeorological weather station (MaRTy cart), we registered the microclimatic factors affecting thermal exposure at different points inside and outside the parks. From the microclimatic measurements we derived the Universal Thermal Climate Index (UTCI). Additional characterization of the measurement points consisted in sky-view-factor estimations and 360^o vegetation and impervious view factors. Throughout the campaign period and measurement hours (14:00, 15:00 and 20:00 LT), the UTCI varied between 29.5 ^oC (moderate heat stress) and 41.9 ^oC (very strong heat stress). During the early afternoon, when air temperatures and heat stress are higher, the UTCI is lower inside of the parks, by a difference that ranges from 1.0 ^oC to 3.2 ^oC. The sky-view-factor is responsible for 43 to 58% of the observed variability in the UTCI, pointing out the importance of tree shadowing inside the parks. Air temperature has also a clear influence on thermal comfort, explaining between 17 and 50% of the UTCI variability. Although air temperature reductions in smaller parks are not as significant as in the “climate shelter” park, there are vegetation zones inside the smaller parks with comparable reductions in the UTCI. The results show that small parks can provide thermal comfort in similar capacity as bigger parks classified as “climate shelters”.

How to cite: Segura, R., Estruch, C., Badia, A., Ventura, S., Krayenhoff, E. S., and Villalba, G.: Evaluating the impact of urban parks on the thermal comfort during a heat wave episode in a Mediterranean city, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1367, https://doi.org/10.5194/egusphere-egu23-1367, 2023.

Urbanization causes modifications in the urban climate of a city due to increase in impervious fraction and lack of evapotranspiration. The rise of extreme heatwave events due to climate change is causing concern for the cities effected by the urban heat island. Europe Union has recommended using Nature based solutions as a solution for multiple urban issues including the mitigation of urban heat. The UPSURGE project aims to use nature-based solutions for regenerative development in five demonstration cities. The five cities are based in different climate zones, consists of single to multiple demonstration sites, and are deploying various Nature based solutions based on the key city challenges.  The cities include Belfast, Breda, Budapest, Maribor, and Katowice. The demonstration sites are being Co-designed with multiple stakeholders to address the local concerns, diversity of voices to encompass perspectives and include citizens to address the longevity of Nature based solutions. The static and mobile sensors are being deployed to build a baseline and measure the effect of Nature based solutions. The cities have selected Nature based solutions varying from green roof, green wall, raingardens, Miyawaki forest, agroecology community gardens, rewilded zones, climate arboretum, meadows, water gardens. The work aims to model the effect of different Nature based solutions on the canopy urban heat island. The urban parameterization of the cities is done using local climate zone classification scheme. The advanced research Weather Research Forecast model is used to model the canopy urban heat island during the heatwave of July 2022. The WRF model is run for 7 days on three domains, 10 km, 5 km and 1 km horizontal resolution using six hourly data from ECMWF. The performance of the model has been assessed by analysing temperature, wind speed, relative humidity and surface level pressure considering their effect on local urban heat stress. The results showcase the importance of using actual urban morphology values in Weather Research Forecast to accurately simulate near-surface variables. The Weather Research Forecast simulations shows the presence of urban heat island and depicts the effect of deploying the various Nature based solutions across cities.

How to cite: Budhiraja, B. and McKinley, J.: Modelling the effect of Nature based solutions on urban heat island using the Local Climate Zone scheme in Weather Research Forecast model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11913, https://doi.org/10.5194/egusphere-egu23-11913, 2023.

Since almost half of the world’s population lives in cities and another third in settlements with similar characteristics, the current and future impacts of climate change in cities is of greatest importance. The characteristics of urban environments (reduced long-wave emissions towards the sky due to the blockage effect of the surrounding buildings, construction materials, anthropogenic heat production, lack of green and blue infrastructure) further increase ambient temperatures and cause urban heat islands. Nature-based solutions (NbS) have widely been investigated as a remedy to this challenge, which is quickly worsening due to the combined effects of climate change and the rapid densification of urban settlements. NbS cover a wide scope of measures such as planting roadside trees, greening facades or roofs, re-naturalizing rivers or unsealing of parking spaces to allow rainwater to penetrate and enable evapotranspiration. Yet, the widespread implementation of NbS often meets political, social, legal, financial or spatial barriers. 

In the presented study we combine interdisciplinary expertise from natural to social and economic sciences and a wide range of methods to evaluate and illustrate, exemplarily for the city of Vienna, how urban areas can implement NbS and overcome the aforementioned barriers. Therefore, (1) a list of possible NbS is compiled; (2), their performance is quantified through numerical micro-climate simulations, (3) their impact and potential trade-offs applying a socio-spatial analysis and survey, (4) individual preferences and willingness to pay are analyzed for a representative sample of 2,181 Viennese residents using a choice experiment, and finally, (5) a consolidated list of NbS is validated within policy workshops.

Using this approach we find that substantially transforming an existing quarter by implementing green and blue infrastructure, as well as technical solutions (e.g. sun blinds) may reduce the ambient air temperature by up to 2°C and the mean radiant temperature on some surfaces by up to 45°C, with natural measures being more effective than technical ones. Implementing these measures within the whole city of Vienna may yield a similar temperature effect. The socio-spatial vulnerability assessment identifies few areas where a strong overrepresentation of vulnerable age groups, low-income residents and housing vulnerabilities coincide.  In the city of Vienna, green gentrification owing to rising housing prices for already vulnerable groups thus seems to be very limited, especially as long-standing social housing policies and a rather strict regulation of the private housing markets lead to comparatively stable rent levels. The choice experiment shows a substantial willingness to pay for NbS, suggesting that Viennese citizens would financially support the implementation and maintenance of extensive greening measures. However, the politicians fear the conflicts with the citizens and other political parties as well as stakeholders. Stakeholders from the city authorities map potential physical and legal barriers for local implementation, such as building codes, administrative procedures for permits and inspections, or conflicts over scarce public space.

How to cite: Bügelmayer-Blaschek, M., Schneider, M., Tötzer, T., Friesenecker, M., Thaler, T., Schneider, A., Getzner, M., Seebauer, S., Hahn, C., and Zuvela-Aloise, M.: Climate resilience of the City of Vienna: social impact of Nature-based Solutions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9178, https://doi.org/10.5194/egusphere-egu23-9178, 2023.