CL2.2

The WMO World Weather Research Programme (WWRP) “promotes international and interdisciplinary research for more accurate and reliable forecasts from minutes to seasons, expanding the frontiers of weather science to enhance society’s resilience to high-impact weather and the value of weather information for users. In the 2016-2023 WWRP implementation plan, activities focus on 4 challenges: High-Impact Weather, Water, Urbanization, Evolving technologies. Furthermore, the WMO Global Atmosphere Watch Urban Research Meteorology and Environment (GURME) focus on the development of models and associated research activities to enhance the capabilities in providing urban-environmental forecasting and air quality services, illustrating the linkages between meteorology and air quality (https://public.wmo.int/en/programmes).

This talk presents an international Research Demonstration Project (RDP), that will focus on international research on scientific urban issues addressed by both WWRP and GURME. The strategic objective of this RDP is to focus on the Olympic Games of Paris in 2024 in order to advance research on the theme of the “future Meteorological Forecasting systems at 100m (or finer) resolution for urban areas”. Such systems would prefigure the numerical weather prediction at the horizon 2030. The focus will be on themes related to extreme weather events in summer which both are influenced by and impacts urbanization: thunderstorms and strong Urban Heat Islands, and their consequences.

There are 5 scientific questions that will be addressed during this Paris RDP:

• Nowcasting & Numerical Weather Prediction in cities at order 100m resolution
• High resolution thunderstorm nowcasting (probabilistic and deterministic) in the urban environment,  Urban heat islands, cool areas and air quality
• Nowcasting and forecast in coastal cities (for the Marseilles site)
• How to improve and better use observational networks in urban areas, including (big) non-conventional data
• Conception and Communication of tailored weather, climate, environmental information at infra-urban resolution.

Several High-Impact weather case studies were selected. Storm cases (starting with one the 10th July 2017) will allow to evaluate the role of the urban area on their enhancement. Extreme Heat wave aggravated by a strong Urban Heat Island are also studied (July 2019). Open urban data describing the agglomerations at very high resolution are provided. New innovative methods to produce maps of urban form characteristics (e.g. from street images) and meteorological data (from personal meteorological stations) will be explored.

This talk will describe these scientific questions, as well as the common methodology approach that is being discussed within the partners. A focus will be the international experimental campaign that will take place in 2022 over the Paris agglomeration, with an Intensive Observation Period in the summer 2022. Interactions between urban surface and the atmospheric boundary layer, the interactions between air quality and aerosols between city and biogenic plumes, and the local effect of urban trees on micro-climate and chemistry are some of the axes of the campaign. It will provide additional meteorological and air quality observations, to both help to improve the nowcasting and NWP systems at urban scale, and aim to define the required additional instrumentation that should be deployed during the Olympics games themselves.

How to cite: Masson, V., de Coning, E., Baklanov, A., Amorim, J., Augros, C., Bélair, S., Christen, A., Foret, G., Franklin, C., Gonzalez-Cruz, J., Grimmond, S., Haeffelin, M., Kotthaus, S., Lean, H., Lemonsu, A., Leroyer, S., Li, P., Middel, A., Rosso, A., and Swerdlin, S.: WMO Research Demonstration Project “Paris 2024 Olympic Games“ : An international initiative towards 100m-resolution meteorological and air quality forecasting in urban areas , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15389, https://doi.org/10.5194/egusphere-egu21-15389, 2021.

ABSTRACT:

    With the continuous spreading of global pandemic, environmental issues have aroused worldwide unprecedented attention. Airflow plays a crucial role in aerosol motions and pollutants removal in dense cities. Large-eddy simulation (LES) is conducted for a typical metropolitan, Hong Kong, to investigate the dynamics in the atmospheric boundary layer (ABL) over real urban surfaces. Full-scale building models (average building height h_m = 36 m) from Tsim Sha Tsui to Sham Shui Po, Kowloon Peninsula, are digitalized. Southerly wind with speed U_∞ (= 10 m sec^-1) in neutral stratification is prescribed at the domain inlet. The turbulence statistics extracted from three subdomains in Mong Kok neighborhood, each with size 800 m (streamwise) × 100 m (spanwise) × 500 m (vertical), are analyzed. Linear regression of the wind profile with the logarithmic law of the wall (log-law) show that the interface between inertial sublayer (ISL) and roughness sublayer (RSL) is in the range of 2.5h_m to 4.5h_m. In the RSL, the streamwise and vertical velocities are positively (S_u > 0) and negatively (S_w < 0) skewed, respectively. Their kurtosis K_u and K_w is less than 3. Conditional sampling of vertical momentum, flux u’’w’’ showed that ejection Q2 occurs more frequently than does sweep Q4. On the contrary, the contribution of Q4 exceeds that of Q2. These characteristics switch to the other way round in the ISL. Furthermore, the difference between Q4 and Q2, either in terms of occurrence or contribution, shows a local maximum around 50% of the total momentum flux, suggesting the major energy-carrying scales. Coherent structures depict elongated, (massive,) accelerating (decelerating) and descending (ascending) RSL (ISL) flows. Hence, the fresh (aged) air entrainment (detrainment) are signified by fast and extreme (slow and frequent) flows. These distinct features of RSL flows over real urban morphology provide an inspiration to improve the ground-level air quality by proper urban planning.

KEYWORDS: Large-eddy simulation (LES), real urban morphology, turbulent boundary layer (TBL), conditional sampling, hole filtering

How to cite: Yao, L. and Liu, C.-H.: Large-Eddy Simulation for the Roughness Sublayers over Real Urban Surfaces , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4575, https://doi.org/10.5194/egusphere-egu21-4575, 2021.

Surface (2 m) temperature and specific humidity data are measured at 5-minute intervals in a network comprising 33 stations distributed across the city of Berlin, Germany. These data are utilized in order to validate a LES (large eddy simulation) model designed to assess the local climate at a very high resolution of 10 m to 1 m. This model, was developed at the ​Institute of Meteorology and Climatology (IMUK) of the Leibniz Universität Hannover, Germany, and is developed into an application tool for city planners within the funding programme "[UC²] - Urban Climate under Change", of the German Federal Ministry of Education and Research (BMBF).

The evaluation distinguishes between the different Local climate zones (LCZ) in the city, which are defined following the concept of Stewart & Oke (2012). For Berlin, the following LCZ have been identified: 2 (compact midrise), 4 (open high-rise), 6 (open low-rise), 8 (large low-rise), A (dense trees), B (scattered trees), D (low Plants), G (water).

We analyzed one cold winter day during an intensive observation period from 06 UTC on 17^th January to 06 UTC on 18^th January, 2017. The minimum and maximum recorded temperatures were -8.1 °C and +2 °C, respectively, the sun shine duration was 6.5 hours. Daily and hourly mean absolute error, mean square error and root mean square error confirm that the deviation between measurements and the PALM-4U model differs between the LCZ for Berlin, with particularly large negative deviations of up to 5 K in forest areas, as they are not yet well represented in the model. Smallest deviations are found for the industrial zone. In all cases, the observed amplitude of the diurnal cycle is underestimated. The role of the driving model for the deviations found is addressed.

Stewart, I.D., Oke, T.R. (2012) Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc. 93 1879-1900. DOI: 10.1175/BAMS-D-11-00019.1.

How to cite: langer, I., Pasternack, A., Ulbrich, U., and Rust, H.: Comparison of urban climate measurements in Berlin and LES model output for a special observation period, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2194, https://doi.org/10.5194/egusphere-egu21-2194, 2021.

We implement and verify for the first time four Weather Research and Forecasting model urban configurations, focused on the coastal metropolitan area of Tel-Aviv (MTA) using updated land use and urban morphological maps. We analyze the mesoscale summertime flow and the urban canopy (UC) role in the occurrence of different hodograph dynamics observed within MTA at night. These events may be significant in air quality research. The four configurations – bulk (MM), single-layer (SLUCM), multi-layer (BEP), and BEP coupled with the building energy model (BEPBEM) – reproduce the observed diurnal temperature and wind cycles, with similar 10m wind direction bias and RMSE (15° and ~30°, respectively), with preference for MM and SLUCM at night. However, the SLUCM shows the lowest skill for the 10m wind speed (WS) (bias and RMSE 1ms^-1), and the BEP shows the largest underestimation of the 2m temperature, ~-2.5°C. In the SLUCM, the WS increases over an UC and with increasing building heights. The simulations show that at night, a convergence line (CL) builds up with the urban heat island, downstream of the NW flow. West of the CL, the wind continues flowing from the sea, and rotates anti-clockwise to form a non-elliptical sea-breeze hodograph. Removing MTA UC restores an elliptical hodograph. East of the CL, the UC supports an elliptical hodograph with a clockwise rotation through the NE sector, previously reported as dynamically unstable. We expect such wind hodograph dynamics within similar coastal metropolitan areas.

How to cite: Avisar, D., Pelta, R., Chudnovsky, A., and Rostkier-Edelstein, D.: The urban fingerprint in the sea-breeze hodograph reveled by high resolution WRF simulations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1715, https://doi.org/10.5194/egusphere-egu21-1715, 2021.

Studies concerning the effects of urbanization on heavy precipitation events mostly focused on the summertime convective precipitation events. In these studies, the Urban Heat Island (UHI) effect was prominent over the urbanized region before the event, changing the spatial and temporal distribution of the precipitation. We aim to reveal the impact of urbanization over Ankara on the springtime frontal precipitation event of 5 May 2014, when the ground heating and UHI effects are not as strong as those in the summertime. We performed two different simulations based on the land-use scenarios with urban (URBAN) and without urban areas (NOURBAN) over Ankara, integrating the CORINE Land Use dataset into the Weather Research and Forecasting Model (WRF v3.8) and replacing the urban areas with the dominant land use category over the region. Four sub-regions with the identical area coverages corresponding to the upwind, central, and downwind parts of the city center are defined to have a lucid spatial and temporal representation of the event. The two simulation results agreed reasonably with the observations. In the simulation (URBAN) with the urban land use included, the spatial average of the daily rainfall amounts over the predefined sub-regions slightly decreased, especially the sub-regions to the upwind and downwind of the highly urbanized area. However, the difference in precipitation amount in the vicinity of the urbanized area between the two different simulations is not of significance in comparison to what was observed in other summertime precipitation studies. On the other hand, the UHI effect might be crucial in determining the impact of urban land use on the distribution and magnitude of the heavy springtime rainfall. To support this idea, we performed a similar analysis for a summertime convective precipitation event over Ankara and compared the results.

How to cite: Dönmez, B., Dönmez, K., Diren-Üstün, D., and Ünal, Y.: The Impact of Urban Land Use On the Springtime Frontal Precipitation Event in Ankara: A Case Study of 5 May 2014, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3056, https://doi.org/10.5194/egusphere-egu21-3056, 2021.

Cities house over 50% of the population, despite covering only 2% of the earth’s surface area. With the increased urbanization, the impact of climate change in urban areas is seen as a major problem. In the case of the Mediterranean region, the increase in frequency, intensity and duration of extreme heat wave events supposes a significant risk for the population. These factors have raised the focus on understanding and modelling the impact of extreme heat events on cities and to improve the simulation of these events to investigate possible heat adaptation/mitigation measures to ameliorate urban temperatures. This study investigates the sensitivity of high-resolution mesoscale simulations of the Metropolitan Area of Barcelona (AMB) to different urban physical parametrizations for a heat wave event in order to improve urban atmospheric modelling of Mediterranean coastal cities and to reduce uncertainties. The simulations are conducted using the WRF model coupled to the Building Effect Parameterization and the Building Energy Model (BEP+BEM) at 1 km resolution. The physical aspects in WRF that are analysed are: 1) the refinement of urban morphological parameters; and 2) planetary boundary layer (PBL) scheme. The results show that the inclusion of more specific urban morphology does not suppose a better performance of the WRF simulation in comparison to the use of 11 urban land-use classes with averaged urban morphological parameters, although it reduces systematic errors on night-time near-surface temperatures, especially in urban green areas. The comparison between PBL schemes shows that this aspect has a significative influence in the simulation of potential temperature inside the PBL and on near-surface temperature and wind. Moreover, the impact of urbanization on the urban boundary layer (UBL) is determined for the AMB simulating a scenario with no urbanization inside the AMB (all urban areas are changed to croplands). Results show that urbanization not only changes near-surface temperatures, but it has a considerable reducing impact on sea and land-breezes, and an intensifying effect on the PBL height.

How to cite: Segura, R., Gilabert, J., Ventura, S., Badia, A., Martilli, A., and Villalba, G.: Sensitivity study of PBL schemes and urban morphology parameters using the WRF-BEP+BEM model over a Mediterranean coastal city, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1121, https://doi.org/10.5194/egusphere-egu21-1121, 2021.

In Great Britain (GB) 5.8% of the total land area is considered urban, yet the wider impact of Urban Heat Islands (UHIs) beyond city scales has not been fully explored. Through scaling data from a high-resolution urban monitoring network we estimate the current (2014) spatial daily-mean urban warming across GB to be 0.04°C [0.02 °C – 0.06°C]. Despite this GB-wide contribution appearing small (94% of the land cover is still rural), half of GB's population currently live in areas with average daily-mean UHIs of 0.4°C. GB is also experiencing rapid urbanisation, with urban land cover expanding from 4.3 to 5.8% between 1975 and 2014. Purely due to urbanisation in this period, we estimate GB as a whole is warming at a rate that is both equivalent and in addition to ~3% of the background surface-level climate change (i.e. natural and greenhouse gas induced). In areas with the greatest urban expansion, we find UHI-induced warming rates are up to three times this average. Although our study only applies to GB, the simplicity of our method means that it can be equally applied to other countries. Urbanisation is undeniably a global phenomenon with urban expansion in many countries far exceeding that found in GB.

How to cite: Bassett, R., Young, P., Blair, G., Cai, X., and Chapman, L.: Urbanisation-induced climate warming in Great Britain, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2331, https://doi.org/10.5194/egusphere-egu21-2331, 2021.

The study of urban heat island (UHI) is of great importance in the context of climate change (CC). The literature on urban climate has highlighted the singular importance of night UHI phenomenon. It is during the night that the effects of UHI become most evident due to the low cooling capacity of urban construction materials and it is during nighttime that the accumulated heat and high temperatures can generate greater risks to health, leading to aggravate the negative impacts on people's health and comfort, especially in extreme events such as heat waves.

Traditional methods for obtaining nocturnal UHI have been directed either to extrapolation of data from weather stations. The lack of weather stations in urban landscapes makes it extremely difficult to obtain data to extrapolate and propose models at a detailed resolution scale.

The low spatial resolution of the air temperature information contrasts with the higher resolution of the thermal data of the land covers supplied by the satellite sensors. There is a high consensus that the temperature of the earth's surface (LST) plays a fundamental role in the generation of UHI, representing a determinant of surface radiation and energy exchange, as well as the control of the heat distribution between surface and atmosphere. However, the study of the nocturnal LST is still poorly developed due to structural problems related to the availability of detailed data on the LST at night. Most of the satellite sensors (Landsat, Aster, ...) allow to obtain daytime thermal images, but in a much more limited way nighttime thermal data. Only MODIS or Sentinel 3 provide abundant thermal night images, but the low resolution of these images (1 km / pixel) does not allow the construction of detailed models of the nocturnal UHI. For these reasons, estimating the nocturnal UHI remains a pending challenge.

This paper aims to develop a new methodology to determine nighttime LST using data from Landsat thermal bands and contrasting Landsat's very limited nighttime images with daytime ones. The contrast between the daytime and nighttime LST allows the construction of “cooling” models of the LST based on geographic characteristics and urban-spatial parameters, which could be extrapolated to different periods of time (during the same season).

However, the estimation of the LST from nighttime Landsat thermal bands is not a trivial question. The most used methodology to determine daytime LST is based on estimating the emissivity of the land from its degree of vegetation (NDVI threshold). But this method shows significant limitations at night. The NDVI overvalues vegetation when considering the canopy of trees. This overestimation may be correct during the day, when the shade of the trees limits the radiation incident on the ground. But it is critical at night.

For this reason, this paper seeks to develop a new methodology to estimate the degree of vegetation and soil moisture, and, based on it, determine the emissivity and, consequently, the nocturnal LST.

The case study is the Metropolitan Area of Barcelona (636 km², 3.3 million inhabitants).

How to cite: Arellano, B. and Roca, J.: Towards a new methodology to determine nighttime Urban Heat Island, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1483, https://doi.org/10.5194/egusphere-egu21-1483, 2021.

We develop a discrete-time coastal urban adaptation model where the ‘present’ and ‘future’ time periods are distinguished. In the model, the city anticipates sea level rise and related coastal hazards with adverse impacts on urban economy in the future period. However, the magnitude of future sea level rise and induced climate damages are known with uncertainty. The urban planning agent has to make at present a decision on how much to invest in climate adaptation (in the form of construction of coastal protection). We explore three complementary models of decision making. They include the intertemporal maximization of time-discounted expected utility of consumption and two versions of the VIABLE modelling framework with an optimizing and a satisficing urban planning agent, respectively. It is shown that in certain model setups, investment decisions depend discontinuously on the value of key model parameters. In particular, when these parameters are varied, the urban planner can discontinuously switch from the ‘business-as-usual’ (BaU) strategy, when no adaptation investment is taken, to a proactive adaptation.

How to cite: Kovalevsky, D. and Scheffran, J.: A coastal urban adaptation model with time-discounting, optimizing and satisficing decision making, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12228, https://doi.org/10.5194/egusphere-egu21-12228, 2021.

In recent years, the use of remote sensed NDVI has become recurrent in urban studies regarding the adaptation of cities to climate change. However, due to the physical diversity within cities and the different resolution offered by the sensors, the territorial interpretation of what the NDVI values really mean becomes difficult. Where the larger the size of the cells of the image, the greater the number of elements of the built environment within it, and the more complex the interpretation becomes.

In this work, the relationship between the NDVI of three sensors with different cell resolution for the same location and date is studied. In particular, the city of Granollers in the Metropolitan Area of Barcelona is analyzed. First, the NDVI images were obtained from Landsat-8 with 30m resolution, Sentinel-2 with 10m and from the Ministry of Agriculture, Livestock, Fisheries and Food of Catalonia (DARP) with 0.125m resolution. Then, the comparison was performed with a sample of five different typologies of the territory: dense urban core, suburban, industrial, area of highway and rural.

As first results, a supervised classification of the DARP image allowed the definition of 0.30 as the precise minimum value of NDVI that indicates the actual presence of vegetation. On the other hand, the comparison indicates that, in the urban context, the larger the cell size, the presence of vegetation quality is overestimated, where the higher percentage of cells is concentrated in higher NDVI values than in those with lower resolution. However, this behavior is not appreciated in rural areas, where higher percentages of cells of different resolutions were concentrated in the same NDVI ranges.

In such a way, it is corroborated that it is in the urban context where this indicator has a greater difficulty of territorial interpretation. Statements that are analyzed in greater depth in this study, where its implications in the use of NDVI in urban studies for the adaptation of cities to climate change are discussed.

How to cite: García-Haro, A. and Roca, J.: Comparative analysis of three NDVI resolutions in different urban typologies. The case of Granollers in the Metropolitan Area of Barcelona., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14785, https://doi.org/10.5194/egusphere-egu21-14785, 2021.

The rate at which global climate change is happening is arguably the most pressing environmental challenge of the century and it affects our cities. Temperature is one of the most important parameters in climate monitoring and Earth Observation (EO) systems and the advances in remote sensing science increase the opportunities for monitoring the surface temperature from space. The EO4UTEMP project examines the exploitation of EO data for monitoring the urban surface temperature (UST). Large variations in surface temperatures can be observed within a couple of hours, particularly when referring to urban surfaces. The geometric, radiative, thermal, and aerodynamic properties of the urban surface are unique and exert particularly strong control on the surface temperature. EO satellites provide excellent means for mapping the land surface temperature, but the particular properties of the urban surface and the unique urban geometry in combination with the trade-off between temporal and spatial resolution of the current satellite missions impose the development of new sophisticated surface temperature retrieval methods particularly designed for urban areas. EO4TEMP develops a novel UST algorithm exploiting multi-temporal, multi-sensor, multi-resolution EO data, to be validated with in-situ measurements in urban sites and to be applied to Sentinel-3 and Sentinel-2 data. Therefore, EO4UTEMP will provide an advanced methodology for deriving frequent UST estimations at local scale (100 m), capable of resolving the diurnal variation of UST and contribute to the study of the urban energy balance.

How to cite: Mitraka, Z. and Chrysoulakis, N.: Large Scale Exploitation of Satellite Data for the Assessment of Urban Surface Temperatures, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9372, https://doi.org/10.5194/egusphere-egu21-9372, 2021.

The conversion of natural land to built-up surfaces has been widely documented as the main determinant of warming across urban areas. However, uncertainties remain regarding which primary land cover variables control urban heat in different climatic conditions at a global scale. While there is a very little understanding of how the cooling effects of vegetation cover vary over different cities, there is a deep knowledge gap in realizing how other land covers (such as soil, water, and built-up areas) are associated with urban warming and how this relationship is varied in different background climates. Accordingly, using a high spatial resolution dataset, a global synthetic investigation is needed to find the underlying factors influencing intra-urban temperature variability in various climates. To address this shortcoming, this study focuses on exploring the relationship between land surface temperature and land cover in different cities (using Landsat 8 imagery) and aims to investigate the effects of these land cover types on thermal environments in different climatic backgrounds. Preliminary analysis shows that different land cover types have different roles in different climate classes due to their various surface characteristics and in particular, the performance of green spaces to reduce LST is highly dependent on its background climate. For example, the efficiency of vegetation cover to reduce urban surface warming in temperate and tropical climates is more than that in arid and semi-arid areas. In this climate class, since baren soil is the main contributor to the intensity of LST, increasing the area of a green space presents an effective method to mitigate the adverse effects of local warming. Our findings provide helpful information for future urban climate-sensitive planning oriented at mitigating local climate warming in cities.

How to cite: Naserikia, M., Hart, M., and Nazarian, N.: Impact of Urban Land Cover Types on Surface Temperature, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10521, https://doi.org/10.5194/egusphere-egu21-10521, 2021.

In light of climate change as well as challenges associated with urban liveability, many cities are now focusing on outdoor spaces as an extension of living spaces.  Aligned with this, the Glasgow city development plan aims to achieve a healthy and high-quality compact city that supports sustainable development in times of climate change.  However, overheating associated with climate change as well as urban heat island requires planners to identify the thermal comfort consequences of decisions to enhance outdoor living in urban neighbourhoods. Yet, the lack of performance data often hinders planners’ ability to propose guidelines for the health and wellbeing of city dwellers.  In particular, the relationship between compact urban form and heat stress needs to explored.

In this paper, we explore the thermal performance of neighbourhoods based on vertical and horizontal density parameters that are amenable with planning control. We develop graphic tools for the analysis of neighbourhood thermal performance at street level.  We demonstrate mechanisms to integrate the tool into the planning process of City Centre development in Glasgow by way of thermal comfort guidelines to enhance the liveability of an existing streetscape as well as proposed new developments within pre-determined neighbourhood forms.

How to cite: Maharoof, N., Emmanuel, R., and Thomson, C.: Form-based recommendations for pedestrian level thermal comfort in compact neighbourhoods – A case study in Glasgow, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2184, https://doi.org/10.5194/egusphere-egu21-2184, 2021.

Many cities are facing urban overheating issues where the reduction of urban ventilation is one of the key drivers. To address the urban overheating problems, this study concentrates on the analysis of local-scale urban ventilation and its impacts of urban heat islands and outdoor thermal comfort, in order to support wind-sensitive urban planning and design. To achieve this, this study develops a framework for analysing local ventilation, urban heat islands and outdoor thermal comfort with the consideration of local morphological characteristics, external meteorological conditions, local ventilation performance, urban heat islands and outdoor thermal comfort. In particular, the consideration of local morphological characteristics is supported by the development of precinct morphology classification scheme based on three-component protocol of building height, street structure and compactness. Based on the three-component protocol, 20 types of the local ventilation zones were identified in the context of Greater Sydney, Australia.

Field measurement was conducted in three typical local ventilation zones, including open low-rise gridiron, open midrise gridiron and compact high-rise gridiron among the 20, to examine the local ventilation performance, urban heat islands and outdoor thermal comfort in summer 2019. The results indicate that the open midrise gridiron precinct underwent the best precinct ventilation performance, followed by the low-rise gridiron precinct and then the compact high-rise gridiron precinct. The local ventilation created by the sea breeze can help alleviate urban heat islands in the open low-rise gridiron and compact high-rise gridiron precincts with every 0.1 increase in relative wind velocity ratio leading to a 0.09-0.12 °C reduction in UHI intensity. However, in the open midrise gridiron precinct, the local ventilation created by the sea breeze made no difference for urban heat islands. However, the precinct ventilation of the open midrise gridiron precinct still partially exhibited UHI alleviation potential with every 0.1 increase in relative wind velocity ratio leading to a 0.06-0.1 °C reduction in UHI intensity depending on the approaching wind temperature and shading conditions.

Only the precinct ventilation of the open low-rise gridiron precinct leads to outdoor thermal comfort improvement with every 0.1 increase in relative wind velocity ratio leading to 0.29 °C and 0.50 °C physiological equivalent temperature reductions under sea breeze and varying wind conditions, respectively. The results also indicate that within ‘gridiron’ precincts, street orientation is not critical to precinct ventilation performance and its impact on urban heat islands and outdoor thermal comfort. Under wind conditions, trees do not always alleviate urban heat islands and improve outdoor thermal comfort as trees can block sea breeze penetration and inhibit wind cooling potential. These key findings will serve to inform urban heat island mitigation strategies and future planning and design decisions in the built environment.

How to cite: He, B.-J.: Local ventilation and its impacts on urban heat islands and outdoor thermal comfort, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13622, https://doi.org/10.5194/egusphere-egu21-13622, 2021.

Wind observations collected at citizen science wind stations (CWS) could be an invaluable resource in climate and meteorology studies, yet these observations are underutilised because scientists do not have confidence in their quality. While a few studies have considered the quality of CWS wind speed observations, none have addressed the biases, likely caused by instrumentation biases and station placement errors. These systematic biases introduce spatial inconsistencies that prevent comparison of these stations spatially and limit the possible usage of the data. In this paper, we address these issues by improving and developing new methods for identifying suspect observations and calibrating systematic biases in the wind speed observations collected at CWS.

Our complete quality control system consists of four steps: (1) performing within-station quality controls to check the plausible range and the temporal consistency of observations; (2) correcting the bias, mainly caused by low sensor heights, using empirical quantile mapping; (3) implementing between-station quality control that compares observations from neighbouring stations to identify spatially inconsistent observations; (4) providing estimates of the true wind when CWS falsely report zero wind speeds, as a complement to bias correction.

We apply these methods to CWS from the Weather Observation Website (WOW) in the Netherlands, comparing the citizen science data with official data, and statistically assessing the improvements in data quality after each step. The results demonstrate that the citizen science wind data are comparable with official data after quality control checks and bias corrections. Our quality assessment methods therefore give confidence to CWS, converting their observations into a usable data product and an invaluable resource for applications in need of additional wind observations.

How to cite: Chen, J., Whan, K., and Saunders, K.: Quality Control and Bias Correction of Citizen Science Wind Observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2419, https://doi.org/10.5194/egusphere-egu21-2419, 2021.

The worldwide restrictions imposed to contain the spread of Coronavirus (COVID-19) disease markedly affected social and economic systems, undeniably disrupting people’s habits. At the same time, the reduction of industrial and commercial activities and limitation of movements led to significant decline in most greenhouse gas (GHG) emissions, improving urban air quality. Nevertheless, worldwide CO₂ emission reduction was not accompanied by detectable CO₂ concentration decreasing, that continued to grow at a global scale.                 

The relationship between emission rate and urban atmospheric GHG concentrations represents a fundamental tool for monitoring activities aimed at indicating strategies to reduce and buffer GHG concentrations in the urban atmosphere. Generally, the occurrence of many different GHG sources (e.g. industry activities, domestic heating) in urban areas does not allow to evaluate the efficiency of short-term interventions on a specific source of contamination to mitigate urban air pollution (i.e. traffic restriction or reduction of energy use). The COVID-19 lockdown has provided a unique opportunity to empirically evaluate the effect on CO₂ urban plume of both total and sector-specific anthropogenic emission cutting related to traffic dramatic decrease, followed by the stop of the domestic heating and the progressive resumption of urban normal functions at the end of the lockdown period.

In Italy, the first country in Europe to adopt stringent restrictions, the lockdown (mainly consisting of movement limitation of all people and restrictions involving commercial and industrial sectors) was established from March 9, 2020, during and until the end of the heating season, to May 4, 2020, when vehicular traffic and economic activity progressively resumed. In this study, real-time data of concentration and carbon isotopic composition of CO₂ at ground level (2 m height) and of eddy covariance (EC) CO₂ flux at ~33 m above the ground level were measured in the historical center of Florence (Italy), from April 2 to June 4, 2020 and from February 1 to June 4, 2020, respectively. As expected, a clear stepwise decrease in CO₂ fluxes occurred, evidencing a rapid response of the EC measurements to drop in the urban emissions related to COVID-19-containment measures and domestic heating switch-off. Accordingly, during the observation period a relatively small decrease (i.e. few ppm) in the CO₂ concentrations at both ground level and 33 m height was recorded. Moreover, an overall increasing trend of ¹³C/¹²C ratios of CO₂ and daily CO₂-enhancement was observed concomitantly with the gradual easing of severe COVID-19 restrictions.

These trends highlighted that the COVID-19-related short-term (few months) drastic reduction of anthropogenic emission caused, at a local scale, a rapid response of CO₂ urban plume. Hence, the COVID-19 crisis made us aware of the importance of our actions to fight the CO₂-related climate change, although a worldwide CO₂ atmospheric concentration reduction requires a radical and long-lasting CO₂ emission cutting and lifestyle changes from each of us.

How to cite: Randazzo, A., Venturi, S., Tassi, F., Buccianti, A., Gioli, B., Gualtieri, G., Capecchiacci, F., Cabassi, J., Brilli, L., Carotenuto, F., Zaldei, A., and Vaselli, O.: The first Coronavirus (COVID-19) lockdown (March-May 2020): temporary drop in anthropogenic emissions reveals the dynamic of CO2 fluxes and concentrations in urban areas, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8473, https://doi.org/10.5194/egusphere-egu21-8473, 2021.

The amount and dynamics of urban water storage play an important role in mitigating urban flooding and heat. Assessment of the capacity of cities to store water remains challenging due to the extreme heterogeneity of the urban surface. Evapotranspiration (ET) recession after rainfall events during the period without precipitation, over which the amount of stored water gradually decreases, can provide insight on the water storage capacity of urban surfaces. Assuming ET is the only outgoing flux, the water storage capacity can be estimated based on the timescale and intercept of its recession. In this paper, we test the proposed approach to estimate the water storage capacity at neighborhood scale with latent heat flux data collected by eddy covariance flux towers in eleven contrasting urban sites with different local climate zones, vegetation cover and characteristics and background climates (Amsterdam, Arnhem, Basel, Berlin, Helsinki, Łódź, Melbourne, Mexico City, Seoul, Singapore, Vancouver). Water storage capacities ranging between 1 and 12 mm were found. These values correspond to e-folding timescales lasting from 2 to 10 days, which translate to half-lives of 1.5 to 7 days. We find ET at the start of a drydown to be positively related to vegetation fraction, and long timescales and large storage capacities to be associated with higher vegetation fractions. According to our results, urban water storage capacity is at least one order of magnitude smaller than the known water storage capacity in natural forests and grassland.

How to cite: Jongen, H., Steeneveld, G.-J., Beringer, J., Fortuniak, K., Hong, J., Hong, J.-W., Jacobs, C., Järvi, L., Meier, F., Roth, M., Theeuwes, N., Velasco, E., and Teuling, R.: Urban water storage capacity inferred from observed evapotranspiration recession , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2765, https://doi.org/10.5194/egusphere-egu21-2765, 2021.

We present initial results of the Urban-PLUMBER international model evaluation project. This project assesses the performance of land surface models used in meteorological simulations of urban areas. Phase 1 included 24 models of varying complexity, from simple slab models through to multi-layer urban canopy models.

54 model output variables are requested, including primary surface energy fluxes, anthropogenic heat and moisture fluxes, soil variables, albedo, canopy and building air temperatures. This rich dataset is used to both compare model outputs with observations and to understand factors contributing to model performance.

The project involved a number of other innovations including:

• An online portal (modelevaluation.org) is used to distribute site data and accept submissions.
• Upon submission to the portal participants are provided with variable near-instant compliance checks and analyses allowing participants to make corrections if required.
• A ten-year ERA5-derived spin up which overcomes the typically short period of urban flux tower observations and allows the entire observed period to be used in analyses.
• Testing models alongside simple empirical benchmarks (e.g. out-of-sample linear regression of turbulent fluxes on shortwave radiation) to assess if input information is used effectively.

We also discuss the initial stages of Phase 2 which involves testing models at many urban sites. From the known global urban flux tower observations, following assessment, 25 are selected to capture a range of urban characteristics and climates. Surface characteristics are gathered, observations quality controlled and prepended with ten years of bias corrected ERA5 meteorological data for spinup. This new standardised urban flux tower dataset will become a valuable tool in future urban modelling projects.

How to cite: Lipson, M., Grimmond, S., and Best, M. and the Urban-PLUMBER team: Urban-PLUMBER model evaluation project: initial results, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15230, https://doi.org/10.5194/egusphere-egu21-15230, 2021.

Urbanisation locally modifies the regional climate: an urban climate develops. For example, the average wind speed in cities is reduced, while the gustiness is increased. Buildings induce vertical winds, which influence the falling of rain. All these processes lead to heterogeneous patterns of rain at ground and on building surfaces. The small-scale spatial rain heterogeneities may cause discomfort for people. Moreover, non-uniform wetting of buildings affects their hydrothermal performance and durability of their facades.

Measuring rain heterogeneities between buildings is, however, nearly impossible. Building induced wind gusts negatively influence the representativeness of in-situ measurements, especially in densely urbanised areas. Weather radars are usually too coarse and, more importantly, require an unobstructed view over the domain and thus do not measure ground precipitation in urban areas. Consequently, researchers turn to numerical modelling in order to investigate small-scale precipitation heterogeneities between buildings.

In building science, numerical models are used to investigate rain heterogeneities typically focussing on single buildings and vertical facades. Only few studies were performed for more than a single building or with inclusion of atmospheric processes such as radiation or condensation. In meteorology, increasing computational power now allows the use of small-scale obstacle-resolving models resolving atmospheric processes while covering neighbourhoods.

In order to assess rain heterogeneities between buildings we extended the micro-scale and obstacle-resolving transport- and stream model MITRAS (Salim et al. 2019). The same cloud microphysics parameterisation as in its mesoscale sister model METRAS (Schlünzen et al., 2018) was applied and boundary conditions for cloud and rain water content at obstacle surfaces were introduced. MITRAS results are checked for plausibility using radar and in-situ measurements (Ferner et al., 2021). To our knowledge MITRAS is the first numerical urban climate model that includes rain and simulates corresponding processes.

Model simulations were initialised for various wind speeds and mesoscale rain rates to assess their influence on the heterogeneity of falling rain in a domain of 1.9 x 1.7 km² around Hamburg City Hall. We investigated how wind speed or mesoscale rain rate influence the precipitation patterns at ground and at roof level. Based on these results we assessed the height dependence of precipitation. First analyses show that higher buildings receive more rain on their roofs than lower buildings; the results will be presented in detail in our talk.

Ferner, K.S., Boettcher, M., Schlünzen, K.H. (2021): Modelling the heterogeneity of rain in an urban neighbourhood. Publication in preparation

Salim, M.H., Schlünzen, K.H., Grawe, D., Boettcher, M., Gierisch, A.M.U., Fock B.H. (2018): The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory. Geosci. Model Dev., 11, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018.

Schlünzen, K.H., Boettcher, M., Fock, B.H., Gierisch, A.M.U., Grawe, D., and Salim, M. (2018): Scientific Documentation of the Multiscale Model System M-SYS. Meteorological Institute, Universität Hamburg. MEMI Technical Report 4

How to cite: Ferner, K. S., Schlünzen, K. H., and Boettcher, M.: Modelling rain heterogeneities within an urban neighbourhood, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7806, https://doi.org/10.5194/egusphere-egu21-7806, 2021.

Cities have undergone a substantial increase in urbanization over the past decades. Whether the change in land-use type and the consequent Urban Heat Island (UHI) affects the extreme precipitation was of interest and has been under investigation for various developing cities. This study pursued a similar purpose and investigated the impact of urbanization on a heavy precipitation incident that took place in Istanbul on 18 July 2017. Two particular land-use scenarios were used to simulate the event by Weather Research and Forecasting Model (WRF). First, the control simulation (WRF-urban) was performed using the default CORINE 2018 land-use dataset. Subsequently, the test simulation (WRF-nourban) was implemented by replacing the urbanized land-use type of Istanbul with the most dominant land use category of arid cultivated area. Comparison of the WRF-urban simulation with station observations and satellite data reveal that the WRF captured the heavy precipitation event reasonably well over Istanbul.  Results showed that urbanization has a notable impact on both the magnitude and timing of heavy rainfall. Event day total precipitation amount decreased considerably over urbanized regions of Istanbul on the control run. Although the start time and location of the incident reasonably matched for both runs, the control run with urbanization advanced the rainfall quicker over Istanbul, and the heavy precipitation event took place about 1 hour earlier than the test run without urbanization. Another pronounced distinction between the simulations with and without urbanization is detected over the north of Istanbul as the maximum daily total precipitation line slightly shifted northwest on the WRF-urban run compared to the WRF-nourban run. This result indicates that urban-areas may have a substantial effect on the direction of the airflow. Analysis of both vertical cross-sections and sensible heat fluxes on the city revealed that urbanized areas increased the atmospheric instability, thus caused heavier precipitation.

How to cite: Dönmez, K., Dönmez, B., Diren-Üstün, D., and Ünal, Y.: Assessment of Urbanization Impact On Heavy Precipitation in Istanbul, Turkey, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3057, https://doi.org/10.5194/egusphere-egu21-3057, 2021.

In order to build resilient cities in face of climate change in Sub-Saharan Africa, much is to be done to understand the impact of rapid and uncontrolled urbanization on the local climate in the region. Recent efforts by Brousse et al. (2019, 2020) demonstrated that using generic urban parameter information  derived out of Local Climate Zones (LCZ ; Stewart and Oke, 2012) maps created through the World Urban Database and Access Portal Tool framework (Ching et al. 2018) may be used to model the impact of Sub-Saharan African cities on their local climate – using the case of Kampala, the capital city of Uganda. These studies showed that despite the characteristic data scarcity on urban typologies that is present in Sub-Saharan Africa, LCZ could be used as a solution for modelling and studying the urban climates in the region.

Yet these conclusions were only obtained through the use of the bulk-level urban canopy model TERRA_URB, embedded in the COSMO-CLM regional climate model. We therefore test the applicability of a more complex urban canopy models – the Building Effect Parameterization coupled to the Building Energy Model (BEP-BEM) – over the region. To do so, we focus on short periods with specific meteorological conditions during the dry season spanning from December 2017 to February 2018. These are obtained through a k-means clustering over hourly weather measurements given by the automatic weather station located at the Makerere University, in the city-center of Kampala. Wind direction and speed, 2-meter air temperature, incoming short-wave radiation, precipitation, daily temperature range, 2-meter air relative humidity and near-surface pressure are used to depict 5 weather typologies (ie. clusters) during the dry season. We chose to keep only periods with 5 consecutive days of one weather typology, which results in three 5-day periods of distinct typology. We then run the model for these periods and evaluate its outputs against the state-of-the-art simulation by Brousse et al. (2020) as well as in-situ and satellite observations for certain meteorological variables. After that, we show the effect of the recent urbanization on the local climate for each of those three periods and relate it to the variability in urban heat.

This study is the first to model a tropical African city at 1 km horizontal resolution using the BEP-BEM model embedded in WRF. The latter could have major implications as more complex urban canopy models coupled to building energy models could shed light on the impact of the built environment on the livability of indoor and outdoor environments in these cities. Furthermore, insights could indeed be gained on the contribution of air conditioning heat fluxes to outdoor temperatures and the energetic consumption needed to keep indoor environments at an optimal temperature. Additionally, by resolving the urban environment in three dimensions, BEP-BEM could help increase our understanding of how specific urban planning and architectural adaptation strategies (like green or cool roofs, roof top solar panel, new building materials, urban greening etc.) may increase the citizens’ thermal comfort and reduce negative health impacts under specific weather conditions.

How to cite: Brousse, O., Van de Walle, J., Demuzere, M., Martilli, A., van Lipzig, N., Zonato, A., and Heaviside, C.: Modelling the impact of a Sub-Saharan metropolis (Kampala) on the local climate during specific meteorological conditions of a dry season, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11145, https://doi.org/10.5194/egusphere-egu21-11145, 2021.

The interdisciplinary research project Abc (Augsburg bleibt cool – Augsburg stays cool) – funded by the German Federal Ministry for Environment, Nature Conservation and Nuclear Safety – deals with different aspects of heat-stress exposure and adaptation to heat-stress in indoor and outdoor urban environments in the urban area of Augsburg (Bavaria, SE Germany).

As one essential research approach this includes the estimation of the thermal effects of vegetation enhancements in different urban environments via numerical simulations performed with the ENVI-met V4 numerical model.

For several model domains – each of them covering 300 m x 300 m with a 2 m x 2 m horizontal resolution - model runs have been performed utilizing observational data for a heat wave end of July 2019 as meteorological forcing, thus serving as a climate analogue for thermal conditions expected to appear more frequently under future climate change conditions. For each domain model runs for the current-state and several adaptation scenarios have been performed. Adaptation scenarios thereby comprise varying measures for enhancing urban green (street and facade greening) and blue infrastructure.

In this contribution we present and discuss selected model settings and scenarios.

Model results indicate the general capability of vegetation enhancements to counteract heat-stress exposure in urban environments. However, partly also contrary effects emerge pointing to the complex interdependencies within the urban climate system which have to be taken into account when projecting urban heat island adaptation strategies.

How to cite: Beck, C., Buse, K., Fritsch, M., and Irber, P.: Numerical simulation of thermal effects of urban green enhancements in different urban environments in the city of Augsburg (Bavaria, SE Germany), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3562, https://doi.org/10.5194/egusphere-egu21-3562, 2021.

Large spatial differences in canopy-layer air temperature are found across the city as a consequence of distinct urban morphologies and anthropogenic activities throughout the urban landscape. Model-based studies investigating the spatial and temporal variability of air temperature are commonly employed to assess heat mitigation strategies in cities. It is therefore important that models are capable to accurately predict air temperature variability across the city to account for the local climate context. This study explores the sensitivity of the Weather Research and Forecasting (WRF) model coupled with a multi-layer urban scheme (BEP-BEM) to simulate intra-urban variations of 2-m air temperature during different synoptic conditions in a tropical city, Singapore. An accurate representation of the real heterogeneous urban morphology of Singapore is implemented in the model. Two one-month long simulations are conducted for distinct synoptic weather conditions: (a) a relatively wet period during the SW monsoon and (b) a very dry period during the NE monsoon. The performance of the model is firstly evaluated against micrometeorological data collected by a tall eddy covariance flux tower in a representative low-rise residential neighbourhood. Overall good performance is obtained for wind speed and direction, turbulence parameters and surface energy balance components, in particular during dry conditions. Some difficulties are found in predicting intermittent cloud cover, which results in an overestimation of net radiation increasing model errors during the wetter period. Hence the comparison of 2-m air temperatures against observations results in slightly higher errors during the latter period (RMSE<2.3°C) compared to the dry period (RMSE<1.6°C) using data from nine locations with different urban morphologies. Notable underestimation (overestimation) is obtained for the nighttime temperature at the most densely built-up (rural) area. A significant logarithmic relation between minimum nocturnal temperature and average aspect ratio is nevertheless obtained for both observations and simulations. Further analysis during clear sky conditions in both periods reveals that the spatial distribution of the diurnal temperature range computed at the urban locations varies according to synoptic conditions. The present research demonstrates the capability of the model to predict the intra-urban variability across distinct urban morphologies, however, it fails to accurately capture absolute differences in air temperature.

How to cite: Sanchez, B., Roth, M., Simón-Moral, A., Martilli, A., and Velasco, E.: Assessment of a meteorological mesoscale model’s capability to simulate intra-urban thermal variability in a tropical city, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4336, https://doi.org/10.5194/egusphere-egu21-4336, 2021.

The European Union-funded research project 'BigData@Geo ­­­­­­­­- Advanced Environmental Technologies using AI on the Web' is dedicated to researching connections and interactions in the natural regional environmental system. This includes the development of a high-resolution regional earth system model for modelling climate change in Northern Bavaria, Germany.

This research aims to run an urban climate model based on the Parallelized Large-Eddy Simulation Model for Urban Applications (PALM-4U) for Lower Franconia and thus to simulate the Main Valley with a focus on Wuerzburg in a high resolution of up to one meter. As part of this, PALM-4U is coupled to the regional climate model REMO to use generated dynamic input data in addition to static data, for example relating to buildings, roads, waterways, bridges, roof greening etc. in the simulation. The effects of variable development and the influence of green spaces and vegetation – especially also of street trees – on the urban climate are thereby considered, taking into account climate change in the 21st century. Furthermore, changes in the boundary conditions, topography and land use are also part of the research and compared using historical, current and future scenarios.

First results of the coupled model, its urban climate components and of applied approaches such as nesting will be shown. Besides possibilities for their evaluation, possible further steps are also presented.

How to cite: Baumann, M. and Paeth, H.: Adaptation of the urban climate model PALM-4U for Wuerzburg, Germany, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3293, https://doi.org/10.5194/egusphere-egu21-3293, 2021.

The urban heat island effect (UHI), defined as the temperature difference between urban areas and their surroundings, has been widely observed in many cities worldwide, impacting urban energy demand, citizen’s comfort and health. UHI intensities have been found to depend on background climate, and the urban fabric, including built (building thermal properties, heights, reflectance) and natural characteristics (vegetation cover, species composition, vegetation management). In this study, we focus on developing a global scale mechanistic understanding of how each of those properties alters the urban energy budget and leads to UHI development. To achieve this goal, we use the state-of-art urban ecohydrological and land-surface model (urban Tethys-Chloris) to perform a set of detailed UHI simulations for multiple large urban clusters across America, Europe and China in a 10-year time period (2009-2019), spanning a gradient of aridity, vegetation amount, and different compositions of the urban fabric. Model simulations were set up using the latest generation remote sensing data and climate reanalysis (ERA5). Using the simulations, we develop a paradigm of how UHIs develop worldwide, and propose viable solutions for sustainable UHI mitigation.

How to cite: Zhang, Z., Paschalis, A., Mijic, A., Meili, N., and Fatichi, S.: Investigating vegetation role on UHI with mechanistic modelling worldwide, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4198, https://doi.org/10.5194/egusphere-egu21-4198, 2021.

Cities around the world are under constant change. Population growth is leading to an increasing demand for residential, commercial and traffic areas and thus leading to progressive surface sealing and urban densification. Adding on the existing and growing challenging situation, the Earth’s climate is undergoing dramatical changes. Globally affecting cities by altering local temperature patterns, enhancing the occurrence of dry periods and increasing the frequency of Excessive Heat Events (EHE) as well as tropical nights per year, urban planning is becoming increasingly demanding. These consequences put cities (citizens and infrastructure) at risk, amplifying urban heat and the Urban Heat Island (UHI) effect. To ensure anticipatory and holistic planning approaches to counteract the consequences of climate change, specific tools must be developed enabling consideration of different aspects and boundary conditions as well as analysis of crucial processes and complex relationships within the urban environments. Therefore, we introduce a simple and fast spatial GIS-based modelling approach to carry out fine-scale simulations for land surface temperature (LST), mean radiant temperature (MRT) and Universal Thermal Climate Index (UTCI) in a 2D urban environment. This modelling approach combines a fine-scale surface classification, comprised of eight different surface classes, thermal characteristics (global radiation, direct radiation and diffuse radiation), surface characteristics (Emissivity and Bowen-Ratio values) and meteorological input data. Based on this combined dataset and well-established physical relations in the model set-up, the model uses an adapted approach to first evaluate LST, followed by the MRT and finally the UTCI. A DEM (Digital Elevation Model), a CIR-Image (Coloured Infrared Image) and a vector layer depicting building geometry are required as model input datasets. The accuracy of the input datasets determines the accuracy of the output datasets including the three main indicators. To improve this modelling approach and to consider the effects of climate change, we combine this spatial GIS-approach with the capabilities of computational fluid dynamics (CFD). We use CFD software to simulate wind velocities as well as air temperatures based on certain input parameters. Simulation time strongly depends on the complexity of the urban form within the area of interest. Therefore, a specific urban area was selected and the building structure, as well as the tree structure, was approximated by a self-designed 3D model. An additional input data set containing LST is provided by the modelling approach described above. Temperature data of the building envelope was conducted using a thermal infrared camera, with on-site measurements in the study area carried out during the summer of 2020. Among other settings, an initial wind speed and air temperature define the boundary conditions. Transferring calculated wind speed and air temperature datasets for different heights across the study area using CFD into the GIS based approach, leads to improved spatial LST, MRT and UTCI calculations and results and thus enhanced urban micro- and bioclimatic modelling.

How to cite: Back, Y., Kumar, P., Bach, P. M., Jasper-Tönnies, A., Rauch, W., and Kleidorfer, M.: Combining CFD and GIS software capabilities to enhance rapid fine-scale urban micro- and bioclimatic modelling , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11867, https://doi.org/10.5194/egusphere-egu21-11867, 2021.

Heatwaves (HWs) are extreme weather conditions characterized by persistent high temperatures with considerable impacts on society in terms of mortality, thermal stress and energy demand of the population. One of the most interesting aspects of HWs concerns the interaction with the phenomenon of urban heat island (UHI). The UHI is the tendency of urbanized areas to have warmer temperatures than the surrounding rural areas, mainly due to the thermal properties of materials forming urban environment and the heat produced by human activities. Some studies analyzed the behavior of UHI during periods of extreme heat, showing an amplification of the gradient of temperature between urban and rural areas in HW conditions, but the results are often limited to case studies with a single HW and/or a specific city. Other papers dealt with the same topic by examining events on various cities using outputs of global models, but with resolution insufficient to include in detail urban-scale processes and therefore to take into account specific properties of the cities investigated. The approach of this work consisted in providing observational evidence and extending the aforementioned results, studying the effect of HWs on UHI in about ten European cities with different characteristics (geography, topography, urban planning) through the analysis of daily maximum/minimum temperatures data measured by meteorological stations for the summers of period 2006-2019. In particular, the intensity of UHI was assessed through the computation of a Composite UHI Index (UHII), defined as the difference between averaged urban and non-urban values. The different behavior of UHII during HWs compared to "normal" summer days (NO) in selected European cities was investigated, detecting an intensification of index values regarding periods of extreme heat for the majority of examined locations. More specifically, the analysis of temporal evolution of UHII was conducted, revealing an average increase of this index during the occurrence of HW events. Moreover, a correlation between UHI index and maximum temperature anomalies was examined, and HW days appeared to exhibit a larger percentage of positive UHII with respect to NO days, showing also higher absolute values. This work provides an indication of how European urban areas respond to severe hot periods and could be useful to validate numerical model simulations for more detailed analysis, for example regarding mitigation strategies. Finally, the emergence of some outliers, namely cities whose UHI manifested a different reaction to HWs, may deserve dedicated studies in the future.

How to cite: Possega, M., Aragão, L., Ruggieri, P., Santo, M. A., and Di Sabatino, S.: Observational evidence of urban heat island intensification during heatwaves in European cities, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12369, https://doi.org/10.5194/egusphere-egu21-12369, 2021.

Both heat and cold waves cause extreme human thermal discomfort and a clear excess in mortality. This shows the importance of knowing the prevailing thermal comfort conditions and how thermal comfort conditions vary in various environments so measures can be taken. Microclimatic and outdoor human thermal comfort conditions are investigated in various built-up and green areas in the city of Ghent (Belgium) using meteorological measurements of six weather stations of the MOCCA (Monitoring the Cities Climate and Atmosphere) network in combination with calculations done by RayMan.

Normal to extreme summer heat wave periods show that dangerous strong heat stress prevails during the daytime periods at all locations. Comparison of thermal comfort during normal and extreme summer heat wave periods showed that heat stress is more extreme when a heat wave is more intense. Overall the urban park in Ghent was the most comfortable location during heat waves since it effectively mitigates heat stress in the city. These results should be taken into account in urban planning and design to keep mid-latitude cities livable.

Further, a one year data series revealed that outdoor cold stress was more apparent during 2017 in the mid-latitude city of Ghent that experiences a mild maritime climate. During spring and summer, both heat stress and cold stress occurred due to the larger diurnal temperature range compared to the other seasons. Even though high Physiological Equivalent Temperatures (PET) were obtained during a heat wave in summer, heat stress did not occur as intensely and as frequently compared to cold stress on annual level. It could thus be stated that outdoors, cold stress is a bigger threat than heat stress. However, one should keep in mind that the study was executed for outdoor thermal heat comfort and that people will take shelter or take measures when feeling uncomfortable. The question is thus rather, how are citizens protected against heat and cold stress? Currently, the Belgian society is better adapted to cold stress since most buildings contain central heating, while air conditioning is not standard. Future projections predict an increase in temperature, causing more occurrence of extreme heat stress, while extreme cold stress will be reduced. Additionally, the urban heat island effect currently has mainly a positive effect on the average annual outdoor thermal comfort conditions, while it will become a negative effect in the warmer future. Measures should thus be taken to reduce the threat of future heat stress.

How to cite: Top, S., Milošević, D., Caluwaerts, S., and Savić, S.: What is the most threatening for citizens of a mid-latitude city: cold stress or heat stress?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6320, https://doi.org/10.5194/egusphere-egu21-6320, 2021.

In our research we describe the micro-climatological influences of two heat-waves around and the air temperature development in a certain old people’s home in Helsinki, Finland. The stand-alone six-storey concrete building was erected in the late 1970’s and represents the prevailing construction type of this area. The building is located on a slightly southwards declining slope.

The first simulation used real meteorological forcing-data from the heat-wave event in summer 2018, which lasted from July, 13^th until August, 5^th. In this period the daily maximum air temperature reached almost every day 25 °C and more, sometimes even more than 30 °C. All air temperature, wind, humidity, and solar radiation (cloudiness) measurements were conducted at a near-by synoptical weather station.

The second simulation used fourteen-day constructed meteorological forcing-data, based on a clear-sky, slowly increasing air temperature, higher than normal humidity, and low wind conditions assumption starting on July, 13^th (day 194 of the year).

We used the holistic ENVI-met simulation soft-ware to simulate the physical environment around the old people’s home and especially the energy fluxes inside the concrete walls to explain the needs for cooling demands.

The research is part of the HEATCLIM-project financed by the Academy of Finland Science Program CLIHE (2020-2023).

How to cite: Drebs, A., Sinsel, T., and Jylhä, K.: Micro-climatological influences on temperature condition in an old people’s home in Helsinki, Finland, caused by extended heat-waves , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10897, https://doi.org/10.5194/egusphere-egu21-10897, 2021.

With progressive climate change, weather extremes are very likely to become more frequent. While rural regions may suffer from more intense and longer drought periods, urban spaces are going to be particularly affected by severe heat waves. This urban temperature anomaly, also known as “urban heat island” (UHI), can be traced back to different factors, the most prominent being soil sealing, lower albedo and lack of effective ventilation.

City planners have started developing mitigation strategies to reduce future forecasted heat stress in urban regions. While some heat reduction strategies are currently intensely scrutinized and applied within pilot projects, the efficiency of latter mitigation actions can be overseen due to the low density of reference in situ air temperature measurements in urban environments. The same problem applies when trying to benchmark modeling studies of UHI as the amount of benchmarking data may be insufficient.

To overcome this lack of data, over the last two years, a dense air temperature measurement network has been installed in the Swiss cities of Basel and Zurich, counting more than 450 sensors. The low-cost air temperature sensors are installed on street lamps and traffic signs in different local climate zones of the city with an emphasis on street canyons, where air temperatures are expected to be the largest and most of the city’s population lives and works. These low-cost sensors add valuable meteorological information in cities and complement the WMO reference stations.

Air temperature measurements from the low-cost sensor network were controlled for accuracy, reliability and robustness and homogenized in order to minimize radiation errors, although 40% of the stations were equipped with self-built radiation shields, allowing an efficient passive ventilation of the installed sensors.

We demonstrate the strength of our network by presenting first results of two exemplary heat waves that occurred in July 2019 and August 2020 and show that a) the radiation-error corrected datasets correlate well with different high-quality reference WMO stations, and b) the existence of urban heat islands in Zurich and Basel can be well confirmed, showing significant air temperature differences of several degrees between rural and urban areas.

The results demonstrate the advantages of a high-density low-cost air temperature network as a benchmark for future urban heat islands modelling studies.

How to cite: Anet, J. G., Schlögl, S., Spirig, C., Frey, M. P., Renold, M., and Gutbrod, K. G.: Building a new high-density air temperature measurement network in two Swiss cities, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9102, https://doi.org/10.5194/egusphere-egu21-9102, 2021.

With more and more people residing in cities globally, urban areas are particularly vulnerable to climate change. It is therefore important, that the principles of climate-resilient city planning are reflected in the planning phase already. A discussion of adaptation measures requires a holistic understanding of the complex urban environment, and necessarily has to involve cross-scale interactions, both spatially and temporally. This work examines the term “Smart City” with regard to its suitability for the definition of sustainable urban planning based on urban climate studies over the past decade and own modelling work. Existing literature is assessed from a meteorological perspective in order to answer the question how results from these studies can be linked to architectural design of future urban areas. It has been long understood that measures such as urban greening, or so-called "Nature Based Solutions", are able to dampen excess heat and help reducing energetic costs. As numerous studies show however, integrating vegetation in the urban landscape shares a double role in regional adaptation to climate change due to both cooling effect and air pollution control. Using the state-of-the-art chemical transport model MECO(n) coupled to the urban canopy parametrisation TERRA_URB, we simulated a case study for the Rhine-Main metropolitan region in Germany, highlighting mutual unwanted relationships in modern city planning. Hence, we oppose the so-called compact city approach to an urban greening scenario with regard to the potential for both heat island mitigation and air quality.

How to cite: Fallmann, J., Schipper, H., Emeis, S., Barra, M., and Tost, H.: Re-thinking “Smart City” – transferring urban climate research into city planning processes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9727, https://doi.org/10.5194/egusphere-egu21-9727, 2021.

Urban areas around the globe are growing rapidly and as a consequence the anthropogenic effects on the environment are ever-increasing. Understanding the dynamics, procedures and mechanics behind urban greenhouse gas emissions is a challenge for the scientific community. This study investigates the variability of urban CO₂ emissions in the city centre of Heraklion, a typical Mediterranean city in Greece, during a four-year period with gradual changes in the traffic regulations and changes in traffic patterns due to the recent restriction measures imposed to limit the spread of the COVID-19 pandemic. The CO₂ flux (Fc) was measured using the Eddy Covariance (EC) method with a single tower-based system, permanently installed in the centre of the city. Fc was calculated at a 30-min time step and the time-series were quality-controlled and gap-filled using a moving look-up table (mLUT) technique. Fc time series were then aggregated to monthly and yearly emissions totals. Annual flux source area was estimated with the Flux Footprint Prediction (FFP) model, parameterized using measured atmospheric parameters and urban morphological parameters extracted from a Digital Surface Model. The source area was characterized by complex urban morphology and land use types. Specifically, at North of the tower a commercial zone is located, where significantly higher Fc patterns were detected, compared to South, where a residential area dominates. A gradual reduction to CO₂ emissions has been observed since 2016, due to urban planning interventions related to pedestalization of extended areas in the city centre and traffic regulation. During the COVID-19 lockdown period in the Spring of 2020, the diurnal Fc patterns and the monthly aggregated Fc showed significant reductions in the order of 70 % compared to the previous years. Fc values returned to the previous years’ levels with the end of the lock-down in the summer 2020, as it was expected. Finally, during the second lock-down, started in Greece in November 2020, the CO₂ emissions were higher compared to the first lock-down, reflecting a higher level of mobility in Heraklion centre.

How to cite: Politakos, K., Stagakis, S., and Chrysoulakis, N.: Carbon dioxide emissions variability monitoring, based on four years of Eddy Covariance measurements in a typical Mediterranean city, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7723, https://doi.org/10.5194/egusphere-egu21-7723, 2021.

This study was carried out within the framework of the Improving Air Quality in West Africa (IAQWA) project funded by the Make Our Planet Great Again (MOPGA) program. In recent years, West African countries have experienced an economic upturn driven by GDP growth of nearly 3.7% in 2019 (AfDB, 2020). This economic boom is mainly felt in the cities where it promotes the construction of highway infrastructure, real estate development, and industry. All these activities are sources of air pollution. Unfortunately, there is almost no air quality monitoring in these cities partly due to the high cost of monitoring instruments. Low-cost air quality monitoring instruments can help improve the spatial and temporal resolution of measurements at relatively lower cost. However, the installation of these instruments in West African environments characterized by high relative humidity requires their calibration through collocation with reference instruments. The IAQWA project aims to improve our understanding of air pollutants such as fine particulate matter mass (PM_2.5), ozone (O₃), nitrogen oxides (NOx), sulfur dioxide (SO₂), and carbon monoxide (CO) in Abidjan and Accra, two major West African capitals, through the deployment of Real-time Affordable Multi-Pollutant (RAMP) monitors.

Since February 2020, five RAMPs have been installed and are operating continuously at various sites in Abidjan and Lamto in Cote d'Ivoire, and four RAMPs have been operating in Accra, Ghana. Some of the RAMPs have been collocated with PM and/or NOx reference instruments. At other sites the RAMPs have been collocated with INDAAF passive samplers and passive aerosol collectors. These collocations have allowed for the development of calibration models for these low-cost sensors. The performance of these calibration models is presented here along with the diurnal and seasonal variations of air pollution at the different sites in Abidjan and Accra. These results will eventually be used to improve our understanding of the drivers of air pollution in these major West African cities, which is essential to choosing sustainable development pathways in the future.

How to cite: Bahino, J., Giordano, M., Yoboué, V., Ochou, A., Galy-Lacaux, C., Liousse, C., Amegah, K., Hugues, A., Nimo, J., Beekmann, M., and Subramanian, R.: MOPGA/Improving Air Quality in West Africa: Low-cost sensors as a solution to improve the understanding of spatial and temporal variability in urban air pollution, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8210, https://doi.org/10.5194/egusphere-egu21-8210, 2021.

Present study explores pre-lockdown (1^st January-24^th March, 2020) and during lockdown (25^th March-20^th June, 2020) air quality changes in PM_2.5 along with meteorological effects at megacity- Delhi (28.7041°N, 77.1025°E). Alipur (Rural), Okhla (Industrial) and Pusa Road (Traffic dominant area) experienced mean concentrations (S.D.) of PM_2.5 as 87.56(±54.06), 124.45(±73.49) and 62.14(±58.64) µg/m³ before lockdown(BL; 1^st January-24^th March, 2020), while for Lockdown1(L1; 25^th March-14^th April, 2020), PM_2.5 decreased drastically as 39.26(±16.31), 38.01(±15.16) and 31.03(±12.79) µg/m³ and gradually increased during Lockdown2(L2; 15^th April-3^rd May, 2020), Lockdown3(L3; : 4^th May-17^th May, 2020), Lockdown4(L4; 18^th May-31^st May, 2020), respectively. Percentage decrease in PM_2.5 (-69.46%) correlated with outdoor activities of percentage decrease (-70 to -80%) in L1, from BL phase. Exposure assessment study showed, mean Respiratory Deposition Dose-RDD (S.D.) (µg/hr) for fine particles [Particle diameter (Dp) =0.5 µm] for walk and sit mode during BL, as 27.22(±13.53) and 9.90(±4.91) for Alipur, 30.55(±18.04) and 11.11(±6.56) for Okhla, and 28.67(±14.39) and 10.43(±5.23) for Pusa road, and decreased during L1 as 9.64(±4.00) and 3.50(±1.46) for Alipur, 9.33(±3.72) and 3.39(±1.35) for Okhla, and 7.62(±3.14) and 2.77(±1.14) for Pusa road, respectively. Delhiites were exposed to more fine RDD(walk/sit) before lockdown than during lockdown phases. People in sit mode found less exposed to fine RDD, in comparison to walk condition. The people living indoors were affected by outdoor RDD exposure with windows open condition, while exposed to different indoor pollution sources with windows closed condition during lockdown. Authors suggest avoid use of closed conditioned indoors and ACs; frequent opening of windows to lower the RDD and to minimize the COVID-19 virus transmission via particulates.

Keywords: PM_2.5, RDD, COVID-19.

How to cite: Fatima, S., Ahlawat, A., Mishra, S., Soni, V., and Guleria, R.: Spatio-temporal variations of PM2.5 and Respiratory Deposition Dose (RDD) before and during different COVID-19 lockdown phases at Delhi, India, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15349, https://doi.org/10.5194/egusphere-egu21-15349, 2021.

The climatic or meteorological characteristics over a city is significantly influenced by the city dynamics resulting in evolution of a typical micro-climatic condition enveloping the city and peripheral region. The shrinkage and expansion of the urban boundary layer depends on the dimension, design and functioning of a city and its physiographic setup. The lockdown that was enforced for varying durations globally to restrict the Covid-19 pandemic gave an extraordinary opportunity to understand the urban micro-climatic systems with substantially reduced urban operations. Therefore, the present study aims to evaluate the nature of temperature and precipitation conditions for 6 major cities in India, primarily accentuated by the urban fabric and design; during the strict as well as phased lockdown period in India (April – June, 2020). The principal objective of the study is to determine if moderation in transportation as well as commercial and industrial activities which are considered as the backbone of a metropolitan, can regulate the micro-climatic system it emanates. A comparative analysis has been attempted between the three coastal (Mumbai, Chennai, Kolkata) and three inland (Delhi, Hyderabad, Bangalore) cities to gather an understanding of the impact-magnitude, the sea has on urban meteorology. Meteorological reanalysis, satellite as well as in-situ Automatic Weather Station data products have been used for the analysis and validation of results. During the month of April when the lockdown was most stringent, there was an evident improvement in air quality with decrease in the concentration of PM2.5, PM10 and AOD (Aerosol Optical Depth) for all the cities in a range of 30 – 60 percent. To examine the direct and indirect impact of the decreased levels of air pollution on the shortwave as well as longwave radiation responsible for creating the UHI effect as well as abnormal rainfall intensity; the air temperature, land surface temperature (LST) and total amount of rainfall received by the individual cities on a daily as well as hourly basis have been considered. The study reveals that there is notable difference in LST and air temperature in the inland cities during the said period in comparison to the previous years, with relative decrease in both minimum and maximum temperature and significant increase in the number of days with lower temperatures. The pattern of high intensity rain events which is typical to intensive urbanization also experienced definite transformation in Bangalore and Delhi even during the phased lockdown period. However, the modification in all these meteorological parameters were observed to be relatively less significant in case of the coastal cities which solidifies the prominence of coastal influence in such metropolis. Therefore, the study concludes that the rapid strengthening of urban micro-climate and its consequences can be mitigated by implementing strategic reduction in core urban activities, especially for cities without external physiographic influence.

How to cite: Bhattacharjee, S. and Bharti, R.: The Impact of Covid-19 Lockdown on the Urban Micro-Climate of Major Coastal vs Inland Cities of India, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10790, https://doi.org/10.5194/egusphere-egu21-10790, 2021.

The flow in inertial sublayer (ISL) is horizontally homogeneous where the Monin–Obukhov similarity theory (MOST) well describes the flux-gradient relationship.  In contrast, roughness sublayer (RSL) flow is highly inhomogeneous. Its dynamics is influenced by the length scale of individual roughness elements. This study presents an analytical solution to the mean wind profile for both ISL and RSL by adding a new function in the flux-gradient relationship to handle the RSL dynamics. The mean wind speeds measured in the wind tunnel experiments over a range of idealized and real urban geometries are well predicted by the new analytical solution. The root-mean-square errors (RMSE) are reduced over an order of magnitude compared with the conventional logarithmic law of the wall (log-law). Its key parameter, the RSL constant converges asymptotically to μ = 1.7 for urban setting which is different from that (μ = 2.6) for vegetation canopy. The RSL turbulence intermittency is revealed by higher-order moments of velocities, probability density function (PDF), quadrant analysis, and conditional sampling. Ejection Q2 (-u’’, +w”) and sweep Q4 (+u’’, -w”) dominate in both RSL and ISL but with different share. Unlike the ISL, Q2 occurs more frequently (but contributes less to momentum flux) than Q4 in the RSL. It is thus suggested that RSL turbulent transport is driven by occasional, fast motions of accelerating downward flow (Q4) and bulk, slow decelerating upward flow (Q2).

How to cite: Mo, Z. and Liu, C.-H.: Wind Speed Parameterization and Turbulence Intermittency in the Roughness Sublayers over Urban Areas: a Wind Tunnel Study, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3992, https://doi.org/10.5194/egusphere-egu21-3992, 2021.

The low-level jet (LLJ) is an important phenomenon that can affect (and is affected by) the turbulence in the nocturnal urban boundary layer (UBL). We investigate the interaction of a regional LLJ with the UBL during a 2-day period over London. Observations from two Doppler Lidars and two numerical weather prediction models (Weather Research & Forecasting model and UKV Met Office Unified Model) are used to compared the LLJ characteristics (height, speed and fall-off) between a urban (London) and a rural (Chilbolton) site. We find that LLJs are elevated (70m) over London, due to the deeper UBL, an effect of the increased vertical mixing over the urban area and the difference in the topography between the two sites. Wind speed and fall-off are slightly reduced with respect to the rural LLJ. The effects of the urban area and the surrounding topography on the LLJ characteristics over London are isolated through idealized sensitivity experiments. We find that topography strongly affects the LLJ characteristics (height, falloff, and speed), but there is still a substantial urban influence.

How to cite: Tsiringakis, A., Theeuwes, N., Barlow, J., and Steeneveld, G.-J.: The impact of London on a low-level jet, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11307, https://doi.org/10.5194/egusphere-egu21-11307, 2021.

Since their introduction in 2012, Local Climate Zones (LCZs) emerged as a new standard for characterising urban landscapes, providing a holistic classification approach that takes into account micro-scale land-cover and associated physical properties. In 2015, as part of the community-based World Urban Database and Access Portal Tools (WUDAPT) project, a protocol was developed that enables the mapping of cities into LCZs, using freely available data and software packages, yet performed on local computing facilities. The ‘LCZ Generator’ described here further simplifies this process, providing an online platform that maps a city of interest into LCZs, solely expecting a valid training area file and some metadata as input. The tool integrates the state-of-the-art of LCZ mapping, and simultaneously provides an automated accuracy assessment, training data derivatives and a novel approach to identify suspicious training areas. In addition, this development will ease the dissemination of maps and metadata. We anticipate this development will significantly ease the accessibility and workflow of researchers and practitioners interested in using the LCZ framework for a variety of urban-induced human and environmental impacts.

How to cite: Demuzere, M., Kittner, J., and Bechtel, B.: LCZ Generator: online tool to create Local Climate Zone maps, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11385, https://doi.org/10.5194/egusphere-egu21-11385, 2021.

The heterogenous structure of cities impacts radiative exchanges (e.g. albedo and heat storage). Numerical weather prediction (NWP) models often characterise the urban structure with an infinite street canyon – but this does not capture the three-dimensional urban form. SPARTACUS-Urban (SU) - a fast, multi-layer radiative transfer model designed for NWP - is evaluated using the explicit Discrete Anisotropic Radiative Transfer (DART) model for shortwave fluxes across several model domains – from a regular array of cubes to real cities .

SU agrees with DART (errors < 5.5% for all variables) when the SU assumptions of building distribution are fulfilled (e.g. randomly distribution). For real-world areas with pitched roofs, SU underestimates the albedo (< 10%) and shortwave transmission to the surface (< 15%), and overestimates wall-plus-roof absorption (9-27%), with errors increasing with solar zenith angle. SU should be beneficial to weather and climate models, as it allows more realistic urban form (cf. most schemes) without large increases in computational cost.

How to cite: Stretton, M., Morrison, W., Hogan, R., and Grimmond, S.: Evaluation of shortwave radiation fluxes in the multi-layer SPARTACUS-Urban scheme using DART, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16076, https://doi.org/10.5194/egusphere-egu21-16076, 2021.

Worldwide, there has been an unusual epidemiological phenomenon with the SARS -COV2 virus, which has had important repercussions at the social and economic level and has left the country in a vulnerable situation. From the beginning, various epidemiological mathematical models have been presented that simulate the behavior of the contagion over time, however, these do not contemplate climatic and spatial variables. It is well known that respiratory problems are associated mainly with environmental pollution, sudden changes in temperature or low temperatures, and high humidity content in the environment. Therefore, it is necessary to carry out a quantitative projection of the behavior of the virus in environmental matrices of strategic importance for human health. For this project, a multicriteria analysis was carried out that consists of the conjugation of the different thematic maps related in a categorized way by the level of affectation, divided into five classes, from very low to very high, considering the repercussions and relationship of each of these factors. With respect to the mitigation or spread of respiratory diseases, respectively. For this, 3 scenarios were carried out from a weighted linear sum of the projected levels of affectation under 3 considerations: Climate susceptibility: minimum temperatures, average temperatures, height, and humidity; Environmental susceptibility: with urban mobility, industrial activity, and Social exposure: Population density and marginalization. The result will allow us to obtain a zoning map for the Probability of contagion due to environmental and social conditions at the national level that highlights the population that needs greater mitigation efforts and that can be used freely by the corresponding authorities.

How to cite: Morales, A., Yépez Rincón, F. D., Delgado Granados, H., Velasco Herrera, V. M. N., and Ramírez Serrato, N. L.: Zoning of probability of contagion of COVID 19 and common respiratory diseases aggravated by climatic, environmental and social factors., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14071, https://doi.org/10.5194/egusphere-egu21-14071, 2021.

During the COVID-19 pandemic lockdowns, human activities are strongly restricted, which results in a reduction in greenhouse gas (GHG) emissions associated with changes in energy consumptions. The Copernicus Atmosphere Monitoring Service (CAMS) reported a 10.3% decrease in CO₂ fossil fuel emissions during the first lockdown (February-July, 2020) of the COVID-19 pandemic throughout Europe. Using our WRF modeling framework built for the Munich area [1,3] and the column measurements from our automated Munich Urban Carbon Column network (MUCCnet, [2]), we aim to quantify the reduction of GHG emissions within Munich during the COVID-19 pandemic.

Our high-resolution modeling framework can simulate the sources, sinks, and emissions of CO₂ and CH₄ at a spatial resolution of up to 400m. The initial and boundary conditions for meteorological fields are taken from ERA5 and CAMS data is used for initializing the initial and lateral tracer boundary conditions. Anthropogenic emissions below ~1 km altitude above the ground level are obtained from TNO-GHGco v1.1 at a resolution of 1 km². Various tagged tracers are included to quantify the contribution from different emission categories (such as biogenic emissions from wetlands, emissions from road transport, industry, etc). By refining the vegetation classification using the Dynamic Land Cover map of the Copernicus Global Land Service at 100 m resolution (CGLS-LC100), the urban biogenic signals of CO₂ can be well captured using the diagnostic light-use-efficiency biosphere model VPRM (Vegetation Photosynthesis and Respiration Model), which is driven by MODIS indices. Moreover, we integrate urban canopy information derived from World Urban Database and Access Portal Tools (WUDAPT) classified by local climate zones (LCZs) [4] into our model infrastructure. Incorporating precise urban land use data in WRF helps to capture more urban transport features, improving the model behavior within urban areas.

We targeted the pandemic period from February to July 2020 and the same period in 2019 to make a comparison. Thanks to our nearly continuous column measurements during the COVID-19 pandemic, we are able to evaluate our simulated GHG concentrations by comparing them to the measurement results. Furthermore, an estimation of GHG emissions reduction in Munich during the targeted period will be obtained by performing a Bayesian inversion approach incorporating the simulated concentration enhancements from tagged tracers in WRF.

[1] Zhao, X., Chen, J., Marshall, J., Galkowski, M., Gerbig, C., Hachinger, S., Dietrich, F., Lan, L., Knote, C., and van der Gon, H.D., 2020. A semi-operational near-real-time Modelling Infrastructure for assessing GHG emissions in Munich using WRF-GHG. In EGU General Assembly 2020.

[2] Dietrich, F., Chen, J., Voggenreiter, B., Aigner, P., Nachtigall, N., and Reger, B.: Munich permanent urban greenhouse gas column observing network, Atmos. Meas. Tech. Discuss. https://doi.org/10.5194/amt-2020-300, in review, 2020.

[3] Zhao, X., Marshall, J., Hachinger, S., Gerbig, C., Frey, M., Hase, F., and Chen, J.: Analysis of total column CO₂ and CH₄ measurements in Berlin with WRF-GHG, Atmos. Chem. Phys., 19, 11279–11302, https://doi.org/10.5194/acp-19-11279-2019, 2019.

[4] Demuzere, M., Bechtel, B., Middel, A., & Mills, G. (2019). Mapping Europe into local climate zones. PLOS ONE, 14(4), e0214474. https://doi.org/10.1371/journal.pone.0214474.

How to cite: Zhao, X., Chen, J., Marshall, J., Galkowski, M., Gerbig, C., Hachinger, S., Gensheimer, J., Guo, X., Dietrich, F., Wenzel, A., and Klappenbach, F.: Quantifying the impact of urban greenhouse gas emissions for Munich during the COVID-19 pandemic using WRF V3.9.1.1, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13431, https://doi.org/10.5194/egusphere-egu21-13431, 2021.

Ambient air pollution caused by fine particulate matter (PM) and trace gases is a pressing topic as it affects the vast majority of the world's population, especially in densely populated urban environments. The main sources of ambient air pollution in cities are road traffic, industries and domestic heating. Alongside nitrogen oxides (NO_x) and PM, ammonia (NH₃) is also a relevant air pollutant due to its role as a precursor of particulate ammonium (NH₄⁺). To examine the temporal patterns and sources of air pollutants, this study used fast-response air quality measurements in combination with highly resolved traffic information in Münster, NW Germany. The temporal dynamics of NO_x and the particle number concentration (PN₁₀) were similar to the diurnal and weekly courses of the traffic density. On very short timescales, the real-world peak ratios of NO_x and PM ≤ 10 µm diameter (PM₁₀) exceeded the predicted pollutant emission ratios of the Handbook for Emission Factors for Road Transport (HBEFA) by a factor of 6.4 and 2.0, respectively. A relative importance model revealed that light-duty vehicles (LDVs) are the major relative contributor to PN₁₀ (38 %) despite their low abundance (4 %) in the local vehicle fleet.  Diesel and gasoline vehicles contributed similarly to the concentrations of PM₁₀ and PN₁₀, while the impact of gasoline vehicles on the PM₁ concentration was greater than that of diesel vehicles by a factor of 4.4. The most recent emission class Euro 6 had the highest influence on PM₁₀. Meteorological parameters explained a large portion of the variations in PM₁₀ and PM₁, while meteorology had only a minor influence on PN₁₀. We also studied the short-term temporal dynamics of urban NH₃ concentrations, the role of road traffic and agriculture as NH₃ sources and the importance of ammonia for secondary particle formation (SPF). The NH₃ mixing ratio was rather high (mean: 17 ppb) compared to other urban areas and showed distinct diurnal maxima around 10 a.m. and 9 p.m. The main source for ammonia in Münster was agriculture, but road traffic also contributed through local emissions from vehicle catalysts. NH₃ from surrounding agricultural areas accumulated in the nocturnal boundary layer and contributed to SPF in the city center. The size-resolved chemical composition of inorganic ions in PM₁₀ was dominated by NH₄⁺ (8.7 µg m^-3), followed by NO₃^- (3.9 µg m^-3), SO₄^2- (1.6 µg m^-3) and Cl^- (1.3 µg m^-3). Particles in the accumulation range (diameter: 0.1 – 1 µm) showed the highest inorganic ion concentrations. The ammonium neutralization index J (111 %) indicated an excess of NH₄⁺ leading to mostly alkaline PM. High ammonia emissions from surrounding agricultural areas combined with large amounts of NO_x from road traffic play a crucial role for SPF in Münster. Our results further indicate that replacing fossil-fuelled LDVs with electrical vehicles would greatly reduce the PN₁₀ concentrations at this urban site.

How to cite: Ehrnsperger, L. and Klemm, O.: Air pollution in an urban street canyon: Novel insights from highly resolved traffic information and meteorology, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15830, https://doi.org/10.5194/egusphere-egu21-15830, 2021.

Traditional Lagrangian particle dispersion models reflect particles at the zero-plane displacement height and therefore cannot properly take near-ground effects into account. In this study, we investigate whether including the urban canopy layer improves the performance of such a Lagrangian particle dispersion model. Here, spatially averaged flow and turbulence profiles throughout the urban canopy are constructed based on data from the literature (mostly from wind tunnel and numerical modeling studies).

We apply a first-order approach to test to what degree the explicit inclusion of the urban canopy changes the simulated concentration distributions. In a comprehensive sensitivity study, we show that most of the parameters introduced to describe the turbulence and flow profiles in the canopy have a relatively minor impact on the dispersion (and hence concentration distribution) – despite their inherent uncertainty. In particular, concentration fields are more sensitive to previously existing parameters of the model. One exception is a parameter describing the mean canopy wind speed profile, to which the model is sensitive.

When compared to data from the BUBBLE tracer experiment, the results show that the inclusion of the urban canopy layer slightly improves the modelled concentration values. The improvement is minor and might likely differ when comparing with other field experiments. However, the key point here is that the increased complexity and added capability of near-ground concentration simulation did not fundamentally change the model performance.

Ultimately, inclusion of the urban canopy layer will allow the model to be used as the dispersion core for an urban footprint model with footprint estimates near the ground.

How to cite: Stöckl, S., Rotach, M. W., and Kljun, N.: Integrating the Urban Canopy Layer in a Lagrangian Particle Dispersion Model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16119, https://doi.org/10.5194/egusphere-egu21-16119, 2021.

Urban environments in numerical weather prediction models are currently parameterised as part of the atmosphere-surface exchange at ground-level. The vertical structure of buildings is represented by the average height, which does not account for heterogeneous building forms at the subgrid-level. The use of city-scale models with sub-kilometre resolutions and growing number of high-rise buildings in cities call for a better vertical representation of urban environments.

We present the use of a newly developed, height-distributed urban drag parameterization with the London Model, a high-resolution version of the Met Office Unified Model over Greater London and surroundings at approximately 333 m resolution. The distributed drag parameterization requires vertical morphology profiles in form of height-distributed frontal area functions, which capture the full extent and variability of building-heights. These morphology profiles were calculated for Greater London and parameterised by an exponential distribution with the ratio of maximum to mean building-height as parameter.

A case study with the high-resolution London Model and the new drag parameterization appears to capture more realistic features of the urban boundary layer compared to the standard parameterization. The simulation showed increased horizontal spatial variability in total surface stress, identifying a broad range of morphology features (densely built-up areas, high-rise building clusters, parks and the river). Vertical effects include heterogeneous wind profiles, extended building wakes, and indicate the formation of internal boundary layers. This study demonstrates the potential of height-distributed urban parameterizations to improve urban weather forecasting, albeit research into distribution of heat- and moisture-exchange is necessary for a fully distributed parameterization of urban areas.

How to cite: Sützl, B., Rooney, G., Finnenkoetter, A., Bohnenstengel, S., Grimmond, S., and van Reeuwijk, M.: Distributed urban drag parameterization in the sub-kilometre scale London Model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15472, https://doi.org/10.5194/egusphere-egu21-15472, 2021.

The ratio of population living in cities is growing and this is especially true for the largest ones, megacities. However, even smaller cities like the City of Prague  (about 1.5 M) can suffer significantly and the night time temperature difference under summer heat wave can achieve more than 5°C. To assess the impact of cities and urban structures on weather, climate and air-quality, modelling approach is commonly used and the inclusion of urban parameterization in land-surface interactions is of primary importance to capture the urban effects properly. This is especially important when going to higher resolution, which is common trend in operational weather forecast, air-quality prediction as well as regional climate modeling. This represents the rapidly developing research, motivated by specific risks in urban environment, with strong impacts on vulnerable communities there, leading to the tools to assess properly impacts within the cities and the effectiveness of adaptation and mitigation options applied there by the city authorities. Under the action towards the Smart Cities and within the framework for developing adequate climate services, such supporting tools for decission making are inevitable. It is valid not only for extreme heat waves impact prediction, but as well in air-quality forecast and in long term perspective in connection to climate change impacts assessment. This provides the background for the project within Operational Program Prague - The Pole of Growth “Urbanization of weather forecast, air-quality prediction and climate scenarios for Prague”, shortly URBI PRAGENSI.

There are four main tasks within the project. First, urbanization of weather forecast, i.e. involving and testing the urban parameterization scheme in the weather prediction model can provide in very high resolution localized weather prediction and especially under the heat wave condition it can well capture the temperature differences in the city center with respect to the remote areas. There are applications, which can use such localized prediction for planning and decision making on e.g. public services for some specific groups of population in risks. Further, air-quality forecast based on such urbanized weather condition forecast can benefit from better estimates of temperature for chemical reactions, mixing height for dispersion conditions etc. Third, urbanized scenarios of climate change can provide better description of future conditions in the city for adaptation and mitigation options, moreover, in connection to urban heat island urbanized regional climate model in very high resolution is good tool for estimates of efficiency  of potential adaptation or mitigation measures which might be applied by the city administration. Last, but not least, microscale simulations using LES methods are supposed to be used for selected local hot-spots to solve them.

How to cite: Halenka, T., Belda, M., Huszar, P., Karlicky, J., and Novakova, T.: Urbanization of Weather Forecast, Air-Quality Prediction and Climate Scenarios - Project URBI PRAGENSI, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15657, https://doi.org/10.5194/egusphere-egu21-15657, 2021.

Cities modify the background climate through the surface-atmosphere interaction. This modification is function of urban design features, such as the configuration of buildings and the amount of vegetation. Compared to the undisturbed climate of the region, the climate of cities is characterized by higher temperature and lower wind speed. This modification is especially pronounce in dense urban areas. The climate modification of cities is not static, but varies in space and time. The spatial variations are governed by land use and built form differences, as well as by the presence or absence of green and blue infrastructures. Due to the spatial complexity of cities and the general lack of urban weather station networks in most places, the amount of available urban weather data is limited. As a consequence, planners, engineers and public health professionals can only approximate the climate impact of built environments in their respective fields.

Over the past years, several numerical simulation models have emerged that are able to model the influence of built areas on the atmosphere at the local scale and thus, deliver urban weather data for an area of interest. The aim of this study is to assess the performance of three numerical models with an ability to predict site-specific urban air temperature. The evaluated models are the Urban Weather Generator (UWG), the Vertical City Weather Generator (VCWG) and the Surface Urban Energy and Water Balance Scheme (SUEWS). Although the models differ in their scopes, modeling approaches and applications, they all derive the urban weather data from rural observations considering the land use and built form characteristics of the site.

The models are evaluated against air temperature measurements from the dense, 13^th District of Budapest (Hungary). The field measurement utilized simple air temperature and relative humidity loggers placed in non-aspirated solar radiation screens at four shaded sites. The two week measurement period encompassed a five-day-long anticyclonic period with clear sky and low wind speed. Preliminary results indicate a good general agreement between modeled and observed values with root mean square error below or at 2ºC and index of agreement between 0.92-0.96. During the anticyclonic period most models slightly overestimate the daily maximum and underestimated the daily minimum urban air temperature.

How to cite: Gal, C.: Urban weather generation: the intercomparison of three emerging models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16001, https://doi.org/10.5194/egusphere-egu21-16001, 2021.

Cities are particularly vulnerable to climate change. At the same time, cities change slowly. Accordingly, preparatory measures to adapt to climate change have to be taken urgently. High-performance urban climate models with various applications can form the basis for prospective planning decisions, however, as of today no such model exists that can be easily applied outside of the scientific community. Therefore, the funding program Urban Climate Under Change [UC]² aims to further develop the new urban climate model PALM-4U (Parallelized Large-Eddy Simulation Model for Urban Applications) into a practice-oriented and user-friendly product that meets the needs of municipalities and other practical users in addition to scientific research.

Specifically, the high-performance model PALM-4U allows simulation of entire large cities comprising the area over 1.000 km² with a grid size of down to few meters. One of our goals within the project ProPolis is to design and test the practical implementation of PALM-4U in standard and innovative application fields which include thermal comfort (indices like PT, PET, UTCI), cold air balance (source areas, reach and others), local wind comfort (indices derived from medium winds and gusts) as well as dispersion of pollutants.

In close cooperation with our practice partners, we explore the potential of PALM-4U to support the urban planning processes in each specific application setting. Additionally, with development of the fit for purpose graphic user interface, manuals and trainings we aim to enable practitioners to apply the model for their individual planning questions and adaptation measures.

In our presentation, we will show an application case of PALM-4U in a major German city. We will investigate the effect of a planned development area on the local climate and the impact of different climate change adaptation measures (such as extensive vs. intensive green roofs). The comparative simulations of the current state and planning scenarios with integrated green and blue infrastructure should provide arguments for the municipal decision making in consideration of climate change aspects in a densely built-up environment, e.g. urban heat stress.

How to cite: Kriuger, A., Reinbold, A., Schubert-Frisius, M., and Cortekar, J.: Innovative urban climate model PALM-4U as a support tool for municipal climate adaptation strategies., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12563, https://doi.org/10.5194/egusphere-egu21-12563, 2021.

The EU’s Green Deal has a goal of a climate-neutral Europe by 2050. Achieving this goal will require a comprehensive set of actions across all economic sectors, especially the building sector, which currently accounts for 40% of the energy consumed.  Residential energy use is a significant contributor, much of it due to the poorly insulated building stock. Making a ‘just transition’ to more energy-efficient cities requires a spatial approach that can address the correspondence of poor housing and people and the potential for energy innovation at a neighbourhood-scale. In this study, a geographic database of building archetypes is developed for use by the Urban Modelling Interface (Umi) to perform simulations of urban energy use intensity and test the efficacy of energy policies. Umi is applied to a neighbourhood of residential buildings in Dublin (Ireland), many of which perform poorly. Simulated annual energy use intensity is evaluated favourably using energy performance certificate data. Umi is used subsequently to design and test the efficacy of district-level energy policies; the results indicate that the most cost-effective mix of envelope retrofit and onsite energy production to achieve the Green Deal’s target of 60% reduction in greenhouse gas emissions by 2030 and 100% by 2050. The methodology shown here employs data and software that is publicly available for many EU countries.

How to cite: Buckley, N., Mill s, G., and Reinhart, C.: Using an Urban Building Energy Modelling Towards a Carbon-Neutral Neighbourhood: A case study of Dublin Ireland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13503, https://doi.org/10.5194/egusphere-egu21-13503, 2021.

Existence of more or less dense urban meteorological networks is nowadays relatively common, even if often heterogenous in scopes, hardware and management. Those networks are undoubtedly useful tools for a variety of practical purposes.  Nevertheless, they are generally unfit to climatological studies, and unable to describe Air Temperature in the Urban Canopy Layer (UCL) with sufficient spatial resolution: for example, as required by several professional activities and for local adaptation measures to climate change.

 On the other hand, remote sensing data from space has become more and more frequent and easily available, offering a higher spatial resolution (but a still very low frequency) of surface characteristics as the Land Surface Temperature (LST). Often used to describe Urban Heat Islands (UHI), LST has not a simple correlation with canopy layer Air Temperature, which on the contrary is the most required variable for planning and management purposes in cities.

 Using both high quality in situ measurements of Air Temperature at top of UCL obtained by a dedicated urban network as a primary variable, and satellite derived LSTs as the secondary one, a Co-Kriging based methodology has been developed and tested to obtain medium to high spatial resolution Air Temperature maps. Instantaneous as well as long period mean fields of fine spatially resolved Air Temperature find relevant application not only in monitoring and assessing activities of adaptation and mitigation measures in the urban environment, but also in urban climate studies.

 In this paper the methodology is shortly described, and results for the metropolitan area of Milan and the neighbourhoods, obtained in the framework of the first 2 years of ClimaMi Project (https://www.progettoclimami.it/), are presented and discussed together with error estimations.

How to cite: Frustaci, G., Montoli, E., Lavecchia, C., and Pilati, S.: High resolution air temperature maps for urban planning and management, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16430, https://doi.org/10.5194/egusphere-egu21-16430, 2021.

The urban heat island (UHI) is mostly due to urbanization and it is considered as a nocturnal phenomenon, but it also appears during the day in Mexico City. The UHI in concert with the high temperatures caused by global climate change (CC) may profoundly affect human thermal comfort, which can influence human productivity and morbidity in the spring/summer period. Obesity is a disease manifested by the accumulation of excess body fat with implications for the health of people, and Mexico ranks first in overweight and obesity, where 30% of the population has obesity and near 40% is overweight. The main objective of this investigation was to determine the changes in the degree of thermal comfort of Mexico City inhabitants according to their nutritional status, because of the increase in temperatures due UHI and CC. A series of microclimatological measurements to estimate the physiologically equivalent temperature (PET) were made. Concomitantly, a series of surveys of thermal perception were applied to 1300 passersby. The results show that PET has increased from 1990 to 2010 from 0.0372 °C/year to 0.0887 °C/year in the study sites, besides overestimating the degree of thermal comfort of people with normal weight but underestimating that of overweight and obese people according to the stablished categories or classes. It is concluded that it is imperative that people with overweight and obesity reduce their weight but also should be investigated that influences the unbalanced consumption of food. It is also imperative to mitigate UHI and CC through urban architectural techniques.

How to cite: Barradas, V. L. and Ballinas, M.: Implications of the urban heat island and global climate change and nutritional status on the human thermal comfort in Mexico City, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-965, https://doi.org/10.5194/egusphere-egu21-965, 2021.

This study is devoted to analysis of urban development effects on surface thermal characteristics for the case of Belarusian cities of Minsk and Mahiloŭ. Both cities being situated on the same latitude (53.90 N) and not far from each other (~180 km distance), while also sharing a number of similar features typical for cities in Belarus (and in some other former Eastern Bloc countries as well), Minsk and Mahiloŭ nevertheless differ significantly in terms of their population, size and structure. It is therefore of interest to perform urban climate studies for these two cities in parallel.

First, we use geoinformation systems (QGIS), centralized city planning databases and Open Street Maps (OSM) vector data to implement description of Minsk and Mahiloŭ urban territories in terms of functional zones, taking into account such features as buildings density and urban area category (industrial, residential, business, recreational and other types).

Furthermore, we perform analysis of surface temperature fields for both cities from satellite data (Landsat-8) and ground-based observations, the latter including both regular meteorological stations (in urban as well as surrounding rural areas) and a volunteer network of weather and air quality sensors distributed in both cities as part of the AirMQ project [1]. We analyze observations for several months in the 2019-2021 period (depending on data availability), paying special attention to days with specific weather conditions (e.g. blocking anticyclones).

Analysis demonstrates clear evidence of significant urban heat island effects in thermal regimes of both cities, with specific areas of increased temperature related to urban zoning, industrial and green areas, buildings heights and density. However, the selected method of surface urban heat island (SUHI) detection turns out to be somewhat limited for the purposes of studying the effects of blocking anticyclones on urban heat island phenomena development, thereby calling for application of atmospheric numerical modelling techniques.

[1] AirMQ project, URL: https://airmq.by/

How to cite: Burchanka, H., Prakopchyk, Y., Schlender, T., Baravik, A., and Barodka, S.: A comparative study of urban heat island effects in two Belarusian cities from satellite and ground-based observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16146, https://doi.org/10.5194/egusphere-egu21-16146, 2021.

Heat waves (HW) are expected to become more frequent and intense in urban areas, where currently 54% of the population resides (United Nations, 2018) and 60% are expected to do so by 2030. Urban policy makers are proposing various mitigation strategies, but currently lack the tools to determine how effective they will be in terms of the city´s geography climate and urban morphology. We use the Weather and Research Forecasting Model (WRF)  with the multi-layer Urban Scheme Building Effect Parametrization (BEP) and Building Energy Model (BEP+BEM) (Martilli et al., 2002), to simulate three scenarios proposed by the Urban Master Plan of the Metropolitan Area of Barcelona (AMB) for potential implementation. We include detailed input data using cartography at 10 m resolution and eleven urban classes.  We simulate a HW episode that occurred in July-August 2015 when temperatures reached 40°C during the day and did not go below 25°C at night, for more than five consecutive days. The three potential scenarios simulated are: 1) Increasing the albedo of rooftops to 0.85 for certain urban classes, 2) Increasing the urban green by an additional 255.64 ha according to the proposal of the Master Urban Plan for 2030 with two different irrigation schemes and 3) a combination of these two complementary mitigation strategies. We find that the cool roofs reduce temperatures best during the day (average reductions of 2.22°C), while the additional green areas help moderate temperatures evenly during the day and nighttime (average reductions of 0.15°C and 0.17°C, respectively). However, when irrigation is increased from 2 to 5L/m²day, the temperature reduction potential during the day is intensified due to the cooling effect of more evapotranspiration. The thermal regulation potential of the combined scenario is the most propagated over the AMB and has the highest impact with average daytime reductions of 1.26°C and maximum reduction of 4.73°C at 13:00 UTC.

How to cite: Ventura, S., Badia, A., Segura, R., Gilabert, J., Llasat, C., Martilli, A., and Villalba, G.: Assessing heat wave mitigation strategies in a Mediterranean coastal city: how effective are cool roofs and urban green? , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12682, https://doi.org/10.5194/egusphere-egu21-12682, 2021.

Today, more than half of the world’s population lives in urban areas and the proportion is projected to increase further in the near future. The increased number of heatwaves worldwide caused by the anthropogenic climate change may lead to heat stress and significant economic and ecological damages. Therefore, the growth of urban areas in combination with climate change can increase future mortality rates in cities, given that cities are more vulnerable to heatwaves due to the greater heat storage capacity of artificial surfaces towards higher longwave radiation fluxes.

To detect urban heat islands and resolve the micro-scale air temperature field in an urban environment, a low-cost air temperature network, including 450 sensors, was installed in the Swiss cities of Zurich and Basel in 2019 and 2020. These air temperature data, complemented with further official measurement stations, force a statistical air temperature downscaling model for urban environments, which is used operationally to calculate hourly micro-scale air temperatures in 10 m horizontal resolution. In addition to air temperature measurements from the low-cost sensor network, the model is further forced by albedo, NDVI, and NDBI values generated from the polar-orbiting satellite Sentinel-2, land surface temperatures estimated from Landsat-8, and high-resolution digital surface and elevation models.

Urban heat islands (UHI) are processed averaging hourly air temperatures over an entire year for each grid point, and comparing this average to the overall average in rural areas. UHI effects can then be correlated to high-resolution local climate zone maps and other local factors.

Between 60-80 % of the urban area is modeled with an accuracy below 1 K for an hourly time step indicating that the approach may work well in different cities. However, the outcome may depend on the complexity of the cities. The model error decreases rapidly by increasing the number of spatially distributed sensor data used to train the model, from 0 to 70 sensors, and then plateaus with further increases. An accuracy below 1 K can be expected for more than 50 air temperature measurements within the investigated cities and the surrounding rural areas. 

A strong statistical air temperature model coupled with atmospheric boundary layer models (e.g. PALM-4U, MUKLIMO, FITNAH) will aid to generate highly resolved urban heat island prediction maps that help decision-makers to identify local heat islands easier. This will ensure that financial resources will be invested as efficiently as possible in mitigation actions.

How to cite: Schlögl, S., Bader, N., Anet, J. G., Frey, M., Spirig, C., Renold, M., and Gutbrod, K.: Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network                                     , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14143, https://doi.org/10.5194/egusphere-egu21-14143, 2021.

Large cities and urban regions are highly sensitive to impacts caused by extreme events (e.g. heavy rainfall). As problems caused by hazardous atmospheric events are expected to intensify due to the Anthropogenic Climate Change, adequate adaptation planning of urban infrastructure is needed. Planning adaptations not only requires further research on potential impacts under changing climate conditions 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. Based on 10 years of data with a cross validation setup, both the occurrence model and the model for the number of operations significantly outperform the reference climatology for certain areas over Berlin.

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 2021, online, 19–30 Apr 2021, EGU21-14913, https://doi.org/10.5194/egusphere-egu21-14913, 2021.

Many cities in the northern hemisphere experience both extreme heat and extreme cold weather. Pedestrians are exposed to these thermal extremes, causing bodily stress. With a growing and ageing urban population, city design that contributes to the mitigation of summer heat exposure while also reducing winter cold exposure is of increasing importance. Pedestrian thermal exposure depends on several microclimatic factors in addition to air temperature, including wind speed, humidity, as well as shortwave and longwave radiation, which can be quantified by the mean radiant temperature (Tmrt). There has been little study of the impacts on pedestrian thermal exposure in climates with high humidity during summer and snow cover in the winter. We gathered seasonal radiation data from varied urban microclimates using the six-directional Tmrt method in a Canadian city. We deployed a mobile human-biometeorological weather station (MaRTy cart), which has previously been used primarily in hot, dry climates. Tmrt profiles are decomposed into their directional components, and they demonstrate substantial differences in the drivers of thermal exposure between seasons and locations within the city.

How to cite: Aiello, T., Krayenhoff, S., Middel, A., and Warland, J.: A seasonal assessment of urban outdoor thermal exposure in a humid continental climate using the MaRTy observational platform, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5993, https://doi.org/10.5194/egusphere-egu21-5993, 2021.

In face of climate change and urbanization, the need for thermally comfortable outdoor urban spaces is increasing. In the design of the thermally comfortable urban spaces and decision making about interventions that enhance thermal comfort, scientists and professionals that work for cities use meteorological measurements and models. These measurements can be done by professional and accurate meteorological sensors, but also by simpler mobile instruments such as the easy-to-use Kestrel weather meters. In using these simple type of sensors, it is important to know what the performance of these sensors is for outdoor thermal comfort assessments and how they can be used by scientists and professionals in decision making about urban designs that enhance thermal comfort.

To answer these questions, we carried out three experiments in the summer of 2020 in Amsterdam, in which we tested the 11 Kestrel 5400 heat stress sensors and assessed the performance of this equipment for thermal comfort studies. We concluded that Kestrel sensors can be used very well for assessing differences in air temperature and PET (Physiological Equivalent Temperature) between outdoor built environments. For both air temperature and PET, the RMSE between the 11 Kestrel sensors was 0.5 °C maximum when measuring the same conditions. However, Kestrel sensors that were placed in the sun without a wind vane mounted to the equipment showed large radiation errors. In this case, temperature differences up to 3.4 °C were observed compared to Kestrels that were shaded. The effect of a higher air temperature on the PET calculation is, however, surprisingly small. A sensitivity analysis showed that an increase of 3 °C in the air temperature results in a maximal PET reduction of 0.5 °C. We concluded that Kestrel sensors can very well be used for assessing differences between air temperatures and PET between two locations and assessing the thermal effects of urban designs, but care should be taken when air temperature measurements are carried out in the sun. We always recommend using the wind vanes to deviate from high radiant input orientations for the temperature sensor, and placing the stations next to each other at the beginning and at the end of the measurements to check whether the stations actually measure the same values. Any differences can be corrected afterwards.

How to cite: Klok, L., Caverzam Barbosa, E., van Zandbrink, L., and Kluck, J.: Application and performance of Kestrel sensors for assessing thermal comfort in outdoor built environments, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13237, https://doi.org/10.5194/egusphere-egu21-13237, 2021.

In this study (Morrison et al., 2021) ground based thermal cameras are used to observe urban surface temperatures (T_s) with an unprecedented combination of: temporal and spatial resolution (5 min and ~ 0.5 m → 2.5 m), spatial extent (3.9 ha), instrument number (6 static cameras) and surface heterogeneity (mixed high rise and vegetation). The camera images are classified by geometry and material properties (surface orientation, albedo, solar irradiance, and shadow history). Unlike previous methods, pixels are objectively classified using sensor view modelling and a detailed three-dimensional surface model (430 m × 430 m extent). From detailed source area analysis, the cameras are shown to observe 9.5% of the study area. Across all camera pixels, the 5th - 95th percentile T_s range is 37.5 K around midday. Roofs T_s has the greatest diurnal range (290.6 K → 329.0 K). T_s differences across sloped roofs with different sun-surface geomeetry reach 23.3 K. Walls of different cardinal orientations consistently differ by >10 K between 10:00 and 15:00. High temporal resolution (5 min) shadow tracking from the classified images is used to model cooling rates, where recently shaded (<30 min) ground can be 18.6 K warmer than equivalent unshaded T_s. West walls remain warm past sunset and are 1.2 K warmer than north walls at 23:00 (~4 h after sunset). Recently shaded walls cool exponentially to ambient T_s at a similar rate as the ground, but four times slower than roofs. The observaiton methods and observed T_s characteristics are anticipated to have a wide range of applications (e.g. informing future ground-based thermogragy campaign setups, evaluation of urban surface energy balance models, ground-truthing of satellite thermal remote sensing).

Morrison, W., Kotthaus, S. and Grimmond, S. (2021) ‘Urban surface temperature observations from ground-based thermography: intra- and inter-facet variability’, Urban Climate, 35, p. 100748. doi: 10.1016/j.uclim.2020.100748.

How to cite: Morrison, W., Kotthaus, S., and Grimmond, S.: Urban surface temperature observations from ground-based thermography: intra- and inter-facet variability, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15837, https://doi.org/10.5194/egusphere-egu21-15837, 2021.

A model for calculating sensible heat flux (Q_H) – a primary component of the urban surface energy budget - is presented here. Remote sensing data from the NOAA GOES-16 satellite and a high-resolution land cover dataset are used as inputs to calculate the spatio-temporal variability in urban sensible heat flux. The primary motivation for this model is to present a cost-effective approach to calculate Q_H independent of traditional flux observations and computational methods. The GOES-16 satellite data, which has a moderate spatial and high temporal resolution (2 km square at 5 minute intervals) enables the estimation of Q_H over highly heterogeneous urban areas. The model is constructed using an iterative algorithm that uses surface layer turbulence parameterization to solve for Q_H as a function of the enterprise GOES-16 Land Surface Temperature product, an urban air temperature model, publicly-accessible ground observations, and the National Land Cover Database (NLCD). Preliminary model validation was performed over a five-month period in 2019. Three (3) ground flux stations in the New York City metro area with varying degrees of urbanization were used for model validation. Statistics from validation found an RMSE of 42.9 W-m^-2, a mean bias of 12.9 W-m^-2, and an R² of 0.80. Validation results demonstrate that the algorithm shows good correlation with observed values, suggesting that satellite data can be used as an accessible and cost-effective option to estimate Q_H in urban areas.

How to cite: Rios, G. and Ramamurthy, P.: Estimating urban sensible heat flux using satellite-based data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6079, https://doi.org/10.5194/egusphere-egu21-6079, 2021.