UP2.1

Nudging is a simple method that aims to dynamically adjust the model toward the observations by including an additional feedback term in the model governing equation. This method is widely applied in data assimilation due to its simple implementation and reasonable model results. The basic concept of nudging is similar to that of urban canopy parameterization, in which additional terms are usually added in the conservation equations of momentum and energy aiming to simulate the canopy effects. However, few studies have investigated the implementation of nudging methods in urban canopy parameterizations. In this study we developed a multi-layer urban canopy parameterization (UCP) by using a nudging approach to represent the impacts of vegetated urban canopies on temperatures and winds in mesoscale models.

The difficulty of developing UCP by using a nudging method lies in defining appropriate values for the nudging coefficients and the forcing fields (e.g. indoor temperature fields for temperature nudging). To determine nudging coefficients, we use three major urban canopy morphological parameters: building height, frontal area density and building density. The ranges of these parameters are taken from the values for the Local Climate Zones datasets, in our case for the city of Hamburg. The UCP is employed in the three -dimensional atmospheric mesoscale model METRAS. Results show that this UCP can well simulate wind-blocking effects induced from obstacles as buildings and trees and urban heat island phenomenon for cities. Thus, nudging is an efficient and effective method that can be used for urban canopy parameterizations. However, as well known for nudging, it is not conserving energy. Therefore, we investigated the energy loss by tracking the reduced kinetic energy and internal energy. The UCP and model results will be presented.

How to cite: Cheng, G., Grawe, D., and Schlünzen, K. H.: Parameterizing the impact of vegetated urban canopies on wind and temperature fields by using a simple nudging method, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-394, https://doi.org/10.5194/ems2021-394, 2021.

Anthropogenic heat is one of the key factors that causes intensive urban heat island due to its direct impact on ambient temperature in urban areas. Stagnated airflow due to closely packed tall buildings causes weak dilution and removal of anthropogenic heat. Consequently, research is critically needed to investigate the effect of urban morphology on anthropogenic heat dispersion and provide effective planning strategies to reduce UHI intensity, especially at the extreme scenario, such as with very low wind speed and high heat emission. This study provides scientific understanding and develops a GIS-based modelling tool to support decision-making in urban planning practice. We start from a computational parametric study at the neighbourhood scale to investigate the impact of urban morphology on heat dispersion. Site coverage ratio ( ), and frontal area density ( ) are two urban morphological parameters. Ten parametric cases with two heat emission scenarios are designed to study representative urban areas. Furthermore, based on the energy conservation within the urban canopy layer, we develop a semi-empirical model to estimate spatially-averaged in-canopy air temperature increment, in which the exchange velocity between the street canyon and overlying atmosphere is estimated by the Bentham and Britter model. The performance of the new model is validated by cross-comparing with CFD results from the parametric study. By applying this new model, the impact of anthropogenic heat on air temperature is mapped in residential areas of Singapore for both long-term annually averaged and short-term extreme low wind speed to improve urban climate sustainability and resilience.

How to cite: Yuan, C., Mei, S., He, W., Adelia, A. S., and Zhang, L.: Mitigating Intensity of Urban Heat Island by Better Understanding on Urban Morphology and Anthropogenic Heat Dispersion, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-1, https://doi.org/10.5194/ems2021-1, 2021.

Wind speed is one of the key parameter affecting human thermal comfort: high wind speed during winter and low wind speed during summer may exacerbate respectively cold and heat stress. In urban areas, where more than 50% of the world population is currently living, the wind field is strongly affected by the size and the organization of the obstacles (mainly buildings and trees). Simple and quick estimation of the wind speed and direction in an urban setting could then be an interesting information for urban planning purpose. To calculate a high resolution three-dimensional wind field in an urban setting, Computational Fluid Dynamic (CFD) models are mostly used. They usually solve advection and turbulence equations by an iterative process which is too long for most of the urban planning applications. To reduce this time, Röckle (1990) proposed:

• to decrease the number of iteration by initializing the wind field around buildings: this is done by modeling empirically the wind speed and direction using results from wind tunnel observations,
• to solve only the advection equation from this initial wind field since the turbulence is supposed roughly “solved” by the initialization.

At our knowledge, at least two models have been developed using this approach: QUIC-URB (Brown et al. 2018) and the second is part of the SkyHelios software (Fröhlich and Matzarakis, 2018). However: (i) none of these softwares are open-source (i.e. source code is not freely available), it is then rather complicated to propose scientific improvements and (ii) none of them are integrated in a commonly used GIS-based urban planning tool which would popularize their use by urban planners.

Our presentation will focus on the development of our tool called URock, an open-source application of the Röckle methodology. If the results produced by this tool are consistent with observation, it should be included in QGIS (a commonly used urban planning GIS) through the plug-in UMEP (Lindberg et al. 2017).

References

Brown, Michael John. Quick Urban and Industrial Complex (QUIC) CBR Plume Modeling System: Validation-Study Document. No. LA-UR-18-29993. Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2018.

Fröhlich, Dominik, and Andreas Matzarakis. "Spatial estimation of  thermal indices in Urban Areas—Basics of the SkyHelios Model." Atmosphere 9.6 (2018): 209.

Lindberg F, Grimmond CSB, Gabey A, Huang B, Kent CW, Sun T, Theeuwes N, Järvi L, Ward H, Capel-Timms I, Chang YY, Jonsson P, Krave N, Liu D, Meyer D, Olofson F, Tan JG, Wästberg D, Xue L, Zhang Z (2018) Urban Multi-scale Environmental Predictor (UMEP) - An integrated tool for city-based climate services. Environmen tal Modelling and Software.99, 70-87 https://doi.org/10.1016/j.envsoft.2017.09.020

Röckle, R., 1990: Bestimmung der Strömungsverhältnisse im Bereich komplexer Bebauungsstruk-turen. PhD thesis Fachbereich Mechanik der Technischen Hochschule Darmstadt Darmstadt.

How to cite: Bernard, J., Lindberg, F., and Oswald, S.: Urban wind field calculation through the Röckle based method: the basics for a GIS implementation, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-27, https://doi.org/10.5194/ems2021-27, 2021.

In the context of climate change, more frequent and intensive exposure to heat stress is observed and predicted for many cities worldwide. Urban climatological studies in recent decades have shown significant positive trends in the number of hot days. As heat stress poses a considerable health risk, adaptation measures need to be developed. Against this background, the research study aims to measure and model the urban microclimate of a 15 ha study area in Cologne. A network of IButtons and Netatmo weather stations with ultrasonic anemometers is used to measure temperature, humidity and wind speed/direction for assessing the climate character of the study area. The low cost sensors are calibrated against built up research grade meteorological stations. Utilizing low cost sensors also provides opportunities to activate citizens in microclimate research and to foster participation in mitigating climate change effects. The measurement network is set up as transects along street corridors and is used to a) identify the local climatic impacts of different surface types, vegetation areas and building structures, and b) to later calibrate and validate the ENVI-met model. Processes affecting the urban energy balance and microclimate are identified focussing particularly on source areas of excessive heat. Effects of urban green infrastructures are analysed with regard to their mitigation potential for heat stress, water demand for evapotranspiration, and their potential to modify the partitioning of the radiation balance into sensible heat and latent heat flux. We will use the validated ENVI-met model to simulate various adaptation scenarios and climate change scenarios. Adaptation measures will comprise changes in surface (e.g. urban water bodies and vegetation areas), facade/roof greenings or cooling materials. Climate projections until 2099 will be used with ENVI-met by downscaling meteorological data using the Statistical DownScaling Model (SDSM) and assuming the HadCM3 future emission scenarios.

How to cite: Eingrüber, N., Korres, W., and Schneider, K.: Pathways for climate change adaptation in urban areas - first results from field measurements and ENVI-met modeling, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-374, https://doi.org/10.5194/ems2021-374, 2021.

Today, every second person lives in a city, and urbanization is continuously increasing. For 2050, it is to be expected that 2 out of 3 people will live in a city and thus the vast majority of the world's population will be affected not only by global climate change but also by locally induced climatic changes. The canopy layer urban heat island (CL-UHI) is one of the most well-known meteorological characteristics of urban areas found in cities small and large around the world. Its characteristics differ between cities, across a city and with time. The climate change induced warming cities experience is additionally impacted by the CL-UHI.

Despite the city-scale importance of CL-UHI, the WMO has not had any specific guidance on this. In response to the request of the 18th World Meteorological Congress (Resolutions 32 and 61) experts from WMO GAW (Global Atmosphere Watch) Urban Research Meteorology and Environment (GURME) initiated in 2020 preparation of a guidance on measuring, modelling and monitoring the CL-UHI. The guidance is a community-based development with 30 contributors providing expertise in all different aspects of CL-UHI. This includes a clear definition of what a CL-UHI is and clarifications of what it is not, how it develops (e.g. meteorological and morphological influences), methods to assess CL-UHI intensities (measurements,  modelling approaches) as well as when its assessment  (applications) is needed and how it can be reduced (or when it is beneficial).

The presentation will specifically focus on the key questions addressed in the guidance: what a CL-UHI is and what it is not, where CL-UHI values are relevant for and the many challenges that exist in simulating the CL-UHI with different models.

How to cite: Schluenzen, K. H., Grimmond, S., and Baklanov, A.: Guidance to Measuring, Modelling and Monitoring the Canopy Layer Urban Heat Island, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-301, https://doi.org/10.5194/ems2021-301, 2021.

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

Cities are becoming one of the most vulnerable environments under climate change. In 2013, the CORDEX community identified cities to be one of the prime scientific challenges. Therefore, we proposed this topic to become an activity at CORDEX platform, within the framework of so called flagship pilot studies, which was accepted and the FPS URB-RCC activity has been started in May this year.

Indeed, from the perspective of recent regional climate model developments with increasing resolution down to the city scale, proper parameterization of urban processes is starting to play an important role to understand local/regional climate change. The inclusion of the individual urban processes affecting energy balance and transport (i.e. heat, humidity, momentum fluxes) via special urban land-use parameterization of distinct local processes becomes vital to simulate the urban effects properly. This will enable improved assessment of climate change impacts in the cities and inform adaptation and/or mitigation options by urban decision-makers, as well as adequately prepare for climate related risks (e.g. heat waves, smog conditions etc.).

The main goal of this FPS is to understand the effect of urban areas on the regional climate, as well as the impact of regional climate change on cities, with the help of coordinated experiments with urbanized RCMs. While the urban climate with all the complex processes has been studied for decades, there is a significant gap to incorporate this knowledge into RCMs. This FPS aims to bridge this gap, leading the way to include urban parameterization schemes as a standard component in RCM simulations, especially at  high resolutions.

How to cite: Halenka, T. and Langendijk, G.: CORDEX FPS on Urbanization - URBan environments and Regional Climate Change (URB-RCC), EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-477, https://doi.org/10.5194/ems2021-477, 2021.

Numerical modeling makes it possible to represent complex processes in small-scale and complex areas like cities. For resolving obstacles, grid sizes in the order of meters are needed. Due to small grid sizes and numerical restrictions, such high-resolution investigations require a great deal of resources. Therefore, a re-use of the results by others would enhance the value of any of these model results. However, the subsequent use of model results is still poorly developed. Comparisons of model data, dissemination of results, or reproduction of simulations are hampered by inconsistent data structures, non-standardized variable names, and lack of information on model setup. In general, to ensure the reusability and accessibility of model data, data standards should be used. The most common data standard for atmospheric model output data are the CF conventions, a data standard for netCDF files, but this standard is currently not extended to cover the model output of obstacle resolving models (ORM).

The AtMoDat (Atmospheric Model Data) project developed a model data standard (ATMODAT standard) which ensure FAIR (Findability, Accessibility, Interoperability, and Reuse) and well documented data. We involved the micro-scale modelling community in this process with a web based survey (http://uhh.de/orm-survey) to find out which micro-scale ORMs are currently in use, their model specifics (e.g. used grid, coordinate system), and the handling of the model result data. Furthermore, the survey provides the opportunity to include suggestions and ideas, what we should consider in the development of the standard. We already identified typical variables used by ORMs (i.e. building structures, wall temperatures) and will propose them to be included in the CF convention.  The application of this standard is tested on the model output of the ORM MITRAS. The standard and experiences with its application will be presented.

How to cite: Voss, V., Grawe, D., and Schlünzen, K. H.: How to develop and apply a model data standard on microscale model data., EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-420, https://doi.org/10.5194/ems2021-420, 2021.

The urban heat island (UHI) effect is primarily related to the atmosphere, but may also refer to the surfaces. The atmospheric UHI (AUHI), determined using air temperature (Tair), and the surface UHI (SUHI), assessed using land surface temperature (LST), are distinguished. There is undoubtedly a relationship between SUHI and AUHI due to the modulation of Tair by LST. On hot days in the summer months, the SUHI/AUHI effect may increase the heat load, which is dangerous to the health and comfort of people staying in the city. Detailed characteristics of the spatial distribution of Tair and LST in urban areas are required to identify the parts of the city with the highest heat load. Spatially continuous Tair data, enabling better characterizing AUHI, can be obtained by modelling. Satellite thermal data (LST) can be used as input to the Tair spatial distribution model. Satellite data with 1 km spatial resolution, due to availability several times a day, are most useful in characterizing SUHI diurnal variability and the relationship of LST with Tair. The detailed knowledge of LST and Tair correlation should be helpful in the development of the Tair estimation algorithm based on the LST values. Better recognition of the relationship between LST and Tair, and thus improving the quality of modelling the spatial distribution of Tair in urban area, can possibly be achieved through downscaling of LST data to higher spatial resolution. In the study the method of LST downscaling from 1 km to 100 m was developed, using LST derived from AVHRR, Landsat, ASTER and ECOSTRESS data. The LST-Tair correlation in the diurnal course was examined and the influence of LST downscaling on the correlation was assessed. A Tair regression model was developed based on LST, depending on local climate zone (LCZ). LST and Tair maps for Kraków and its vicinities were prepared, and on the basis of them the intensities of AUHI and SUHI in the multi-year period (2010-2019) in the summer months (June, July, August) were determined, separately for day and night.

How to cite: Hajto, M. J. and Bokwa, A.: Multi-annual variability of summertime atmospheric and surface urban heat island in Kraków, Poland, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-64, https://doi.org/10.5194/ems2021-64, 2021.

Heat waves (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 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 41 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 2000-2019. 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 due to higher urban than rural temperatures. 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, EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-160, https://doi.org/10.5194/ems2021-160, 2021.

Dry periods and heat waves are becoming more frequent and intense in changing climate. Effect and impact of such specific events on local climate and ecosystems may vary spatially. One of the critical spots regarding extreme warm events are urban areas due to increased heat load. Here, we examine impact of drought conditions on characteristics of summertime urban heat island (UHI) for Zagreb, Croatia. For these purposes daily air temperature, precipitation, relative humidity, wind speed and wind direction data from the station Zagreb-Maksimir in a period 1928–2019 are used in the analysis. To define dry and wet conditions, standardized precipitation evapotranspiration index (SPEI) is used. The effect of drought conditions on summer UHI is analyzed from the perspective of preceding (i.e. wintertime and springtime) as well as concurrent (i.e. summertime) drought conditions. To estimate urban heat load in the city, urban climate model MUKLIMO_3 combined with cuboid method is used. Urban heat load is here represented as a number of summer days, i.e. days with maximum air temperature above 25°C. Landsat-8 satellite data were employed to analyze land surface temperature for specific situations. Results indicated substantial increase in heat load for situations when dry summer was preceded by dry late winter-spring period. However, when late winter-spring period was wet and followed with dry summer, much weaker increase in heat load is obtained. On the other hand, decrease in heat load is found for wet summer preceded by wet late winter-spring season. It is also showed that intensity of UHI is affected with drought conditions.

How to cite: Nimac, I., Herceg-Bulić, I., Žuvela-Aloise, M., and Žgela, M.: Impact of drought conditions on urban climate of Zagreb (Croatia), EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-315, https://doi.org/10.5194/ems2021-315, 2021.

Historical changes, spanning 1971–2016, in the Athens Urban Heat Island (UHI) over summer were assessed by contrasting two air temperature records from established meteorological stations in urban and rural settings. When contrasting two 20-year historical periods (1976–1995 and 1996–2015), there is a significant difference in summer UHI regimes. The stronger UHI-intensity of the second period (1996–2015) is likely linked to increased pollution and heat input. Observations suggest that the Athens summer UHI characteristics even fluctuate on multi-annual basis. Specifically, the reduction in air pollution during the Greek Economic Recession (2008-2016) probable subtly changed the UHI regime, through lowering the frequencies of extremely hot days (T_max > 37 °C) and nights (T_min > 26 °C).

Subsequently, we examined the future temporal trends of two different UHIs in Athens (Greece) under three climate change scenarios. A five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11° (~12 × 12 km) simulated air temperature data, spanning the period 1976–2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5 and RCP8.5) were implanted in the simulations after 2005. The observed daily maximum and minimum air temperature data (T_max and T_min) from two historical UHI regimes (1976–1995 and 1996–2015, respectively) were used, separately, to bias-adjust the model simulations thus creating two sets of results.

This novel approach allowed us to assess future temperature developments in Athens under two different UHI intensity regimes. We found that the future frequency of days with T_max > 37 °C in Athens was only different from rural background values under the intense UHI regime. There is a large increase in the future frequency of nights with T_min > 26 °C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site.

This study shows a large urban amplification of the frequency of extremely hot days and nights which is likely forced by increasing air pollution and heat input. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be also effective in reducing urban temperatures during extreme heat events in Athens under all future climate change scenarios. Such policies therefore have multiple benefits, including: reducing electricity (energy) needs, improving living quality and decreasing heat- and pollution related illnesses/deaths.

How to cite: van der Schriek, T., Varotsos, K. V., Founda, D., and Giannakopoulos, C.: Historical and future temporal trends in the summer Urban Heat Island of Athens (Greece), EMS Annual Meeting 2021, online, 6–10 Sep 2021, EMS2021-318, https://doi.org/10.5194/ems2021-318, 2021.