Journal articles: 'Urban climate model'

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Mills, G. "An urban canopy-layer climate model." Theoretical and Applied Climatology 57, no. 3-4 (1997): 229–44. http://dx.doi.org/10.1007/bf00863615.

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HARAYAMA, Kazuya, Ryozo OOKA, Shuzo MURAKAMI, Shinji YOSHIDA, Masahiro SETOJIMA, and Hiroaki KONDO. "STUDY ON URBAN CLIMATE ANALYSIS BASED ON MESO-SCALE CLIMATE MODEL INCORPORATED WITH THE URBAN CANOPY MODEL." Journal of Environmental Engineering (Transactions of AIJ) 70, no. 592 (2005): 75–82. http://dx.doi.org/10.3130/aije.70.75_3.

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Yilmaz, Didem Gunes. "Model Cities for Resilience: Climate-led Initiatives." Journal of Contemporary Urban Affairs 5, no. 1 (January 1, 2020): 47–58. http://dx.doi.org/10.25034/ijcua.2021.v5n1-4.

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Paris Agreement of December 2015 was the last official initiative led by the United Nations (UN) as the driver of climate change mitigation. Climate change was hence linked with an increase in the occurrence of natural hazards. A variety of initiatives were consequently adopted under different themes such as sustainable cities, climate-friendly development and low-carbon cities. However, most of the initiatives targeted by global cities with urban areas being the focus in terms of taking action against global warming issues. This is due to the structural and environmental features of cities characterized by being populated, as such, they not only generate a large number of carbon emissions but also happens to be the biggest consumer of natural resources. In turn, they create a microclimate, which contributes to climate change. Masdar City, for example, was designed as the first fully sustainable urban area, which replaced fuel-based energy with the electric-based energy. China, as another example, introduced the Sponge Cities action, a method of urban water management to mitigate against flooding. Consequently, architects and urban planners are urged to conform to the proposals that would mitigate global warming. This paper, as a result, examines some of the models that have been internationally adopted and thereafter provide the recommendations that can be implemented in large urban areas in Turkey, primarily in Istanbul.

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Früh, Barbara, Paul Becker, Thomas Deutschländer, Johann-Dirk Hessel, Meinolf Kossmann, Ingrid Mieskes, Joachim Namyslo, et al. "Estimation of Climate-Change Impacts on the Urban Heat Load Using an Urban Climate Model and Regional Climate Projections." Journal of Applied Meteorology and Climatology 50, no. 1 (January 1, 2011): 167–84. http://dx.doi.org/10.1175/2010jamc2377.1.

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Abstract A pragmatic approach to estimate the impact of climate change on the urban environment, here called the cuboid method, is presented. This method allows one to simulate the urban heat load and the frequency of air temperature threshold exceedances using only eight microscale urban climate simulations for each relevant wind direction and time series of daily meteorological parameters either from observations or regional climate projections. Eight representative simulations are designed to encompass all major potential urban heat-stress conditions. From these representative simulations, the urban-heat-load conditions in any weather situation are derived by interpolation. The presented approach is applied to study possible future heat load in Frankfurt, Germany, using the high-resolution Microscale Urban Climate Model in three dimensions (MUKLIMO_3). To estimate future changes in heat-load-related climate indices in Frankfurt, climate projections from the regional climate models Max Planck Institute Regional Model (REMO), Climate Limited-Area Model (CLM), Wetterlagen-basierte Regionalisierungsmethode (WETTREG), and Statistical Regional Model (STAR) are used. These regional climate models are driven by the “ECHAM5” general circulation model and Intergovernmental Panel on Climate Change emission scenario A1B. For the mean annual number of days with a maximum daily temperature exceeding 25°C, a comparison between the cuboid method results from observed and projected regional climate time series of the period 1971–2000 shows good agreement, except for CLM for which a clear underestimation is found. On the basis of the 90% significance level of all four regional climate models, the mean annual number of days with a maximum daily temperature exceeding 25°C in Frankfurt is expected to increase by 5–32 days for 2021–50 as compared with 1971–2000.

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Kubilay, Aytaç, Jonas Allegrini, Dominik Strebel, Yongling Zhao, Dominique Derome, and Jan Carmeliet. "Advancement in Urban Climate Modelling at Local Scale: Urban Heat Island Mitigation and Building Cooling Demand." Atmosphere 11, no. 12 (December 4, 2020): 1313. http://dx.doi.org/10.3390/atmos11121313.

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As cities and their population are subjected to climate change and urban heat islands, it is paramount to have the means to understand the local urban climate and propose mitigation measures, especially at neighbourhood, local and building scales. A framework is presented, where the urban climate is studied by coupling a meteorological model to a building-resolved local urban climate model, and where an urban climate model is coupled to a building energy simulation model. The urban climate model allows for studies at local scale, combining modelling of wind and buoyancy with computational fluid dynamics, radiative exchange and heat and mass transport in porous materials including evaporative cooling at street canyon and neighbourhood scale. This coupled model takes into account the hygrothermal behaviour of porous materials and vegetation subjected to variations of wetting, sun, wind, humidity and temperature. The model is driven by climate predictions from a mesoscale meteorological model including urban parametrisation. Building energy demand, such as cooling demand during heat waves, can be evaluated. This integrated approach not only allows for the design of adapted buildings, but also urban environments that can mitigate the negative effects of future climate change and increased urban heat islands. Mitigation solutions for urban heat island effect and heat waves, including vegetation, evaporative cooling pavements and neighbourhood morphology, are assessed in terms of pedestrian comfort and building (cooling) energy consumption.

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Chatzinikolaou, E., C. Chalkias, and E. Dimopoulou. "URBAN MICROCLIMATE IMPROVEMENT USING ENVI-MET CLIMATE MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 69–76. http://dx.doi.org/10.5194/isprs-archives-xlii-4-69-2018.

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<p><strong>Abstract.</strong> The aim of this paper is the modelling of urban microclimate, based on the limits imposed by the complexity of the three-dimensional space of cities. To this purpose, different Bioclimatic Scenarios were investigated through the microclimatic simulations using the micro-scale numerical model, ENVI-met 4v, applied in a case study of a Block in a highly residential neighbourhood of Athens. The study compares the bioclimatic scenarios of the roof top and road side vegetation plan in the current conditions, in order to evaluate how the existence of vegetation can affect the local air temperature and the thermal comfort condition of urban environment. This study also highlights the need to manage those microclimate data, through a geodatabase and provides a GIS approach of data organization and visualization. Creating building facades of the distributed temperature has showed that urban morphology parameters have an obvious impact on temperature distribution in the 3D space. On the other hand, the proposed roadside vegetation scenario has proved to be the most suitable way to improve the thermal comfort conditions of urban environment, as it can eliminate the Urban Heat Island (UHI) effects.</p>

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Cremades, Roger, and Philipp S. Sommer. "Computing climate-smart urban land use with the Integrated Urban Complexity model (IUCm 1.0)." Geoscientific Model Development 12, no. 1 (February 1, 2019): 525–39. http://dx.doi.org/10.5194/gmd-12-525-2019.

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Abstract. Cities are fundamental to climate change mitigation, and although there is increasing understanding about the relationship between emissions and urban form, this relationship has not been used to provide planning advice for urban land use so far. Here we present the Integrated Urban Complexity model (IUCm 1.0) that computes “climate-smart urban forms”, which are able to cut emissions related to energy consumption from urban mobility in half. Furthermore, we show the complex features that go beyond the normal debates about urban sprawl vs. compactness. Our results show how to reinforce fractal hierarchies and population density clusters within climate risk constraints to significantly decrease the energy consumption of urban mobility. The new model that we present aims to produce new advice about how cities can combat climate change.

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Salim, Mohamed Hefny, Sebastian Schubert, Bjorn Maronga, Christoph Schneider, and Mohamed Fathy Cidek. "Introducing the Urban Climate Model PALM System 6.0." International Journal of Applied Energy Systems 2, no. 1 (January 1, 2020): 15–18. http://dx.doi.org/10.21608/ijaes.2020.169937.

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De Ridder, Koen, Dirk Lauwaet, and Bino Maiheu. "UrbClim – A fast urban boundary layer climate model." Urban Climate 12 (June 2015): 21–48. http://dx.doi.org/10.1016/j.uclim.2015.01.001.

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Li, Zhiqiang, Yulun Zhou, Bingcheng Wan, Hopun Chung, Bo Huang, and Biao Liu. "Model evaluation of high-resolution urban climate simulations: using the WRF/Noah LSM/SLUCM model (Version 3.7.1) as a case study." Geoscientific Model Development 12, no. 11 (November 5, 2019): 4571–84. http://dx.doi.org/10.5194/gmd-12-4571-2019.

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Abstract. The veracity of urban climate simulation models should be systematically evaluated to demonstrate the trustworthiness of these models against possible model uncertainties. However, existing studies paid insufficient attention to model evaluation; most studies only provided some simple comparison lines between modelled variables and their corresponding observed ones on the temporal dimension. Challenges remain since such simple comparisons cannot concretely prove that the simulation of urban climate behaviours is reliable. Studies without systematic model evaluations, being ambiguous or arbitrary to some extent, may lead to some seemingly new but scientifically misleading findings. To tackle these challenges, this article proposes a methodological framework for the model evaluation of high-resolution urban climate simulations and demonstrates its effectiveness with a case study in the area of Shenzhen and Hong Kong SAR, China. It is intended to (again) remind urban climate modellers of the necessity of conducting systematic model evaluations with urban-scale climatology modelling and reduce these ambiguous or arbitrary modelling practices.

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Ferreira, Cássia De Castro Martins, Franciele De Oliveira Pimentel, and Yan Carlos Gomes Vianna. "Proposta Metodológica Aplicada ao Estudo de Clima Urbano." Revista Brasileira de Geografia Física 12, no. 6 (December 16, 2019): 2023. http://dx.doi.org/10.26848/rbgf.v12.6.p2023-2040.

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Este artigo mostra uma metodologia analítica aplicada ao estudo de clima urbano, inspirada no Urban Climate Map (UC-Map). Foram utilizados uma série de camadas de informação espacial, medições climáticas e conhecimento do clima urbano para avaliar e mapear o potencial térmico e dinâmico em área urbana, visando identificar diferentes campos térmicos. As informações foram agrupadas em quatro eixos principais, a saber densidade construtiva, albedo, cobertura vegetal e altimetria. A proposta metodológica foi aplicada para a cidade de Juiz de Fora-MG, uma área urbana de médio porte, localizada em uma região de mares de morros, na qual fatores como declividade e altitude são importantes no potencial térmico e dinâmico. O resultado da aplicação desta metodologia converge com os dados experimentais e evidencia os efeitos do uso do solo, dos materiais construtivos e do fluxo de pessoas e mercadorias na definição de diferentes campos térmicos. Evidencia que a distribuição e o tamanho da cobertura vegetal, além da amplitude da ventilação, interferem e proporcionam ambientes mais frescos e, portanto, reduzem o armazenamento de calor. A metodologia apresentada é simples de aplicar e pode ser adaptada para outras áreas urbanas com características semelhantes às de Juiz de Fora-MG. Methodological Propose Applied to The Urban Climate Study A B S T R A C TThis article shows an analytical methodology applied to the urban climate study, inspired by the Urban Climate Map (UC-Map). A series of layers of spatial information, climate measurements and knowledge of the urban climate were used to evaluate and map the thermal and dynamic potential in an urban area, in order to identify different thermal fields. The information was grouped into four main axes, namely constructive density, albedo, vegetation cover and altimetry. The methodological proposal was applied to the city of Juiz de Fora-MG, a medium-sized urban area, located in a region of sea of hills, in which factors such as slope and altitude are important in the thermal and dynamic potential. The result of the application of this methodology converges with the experimental data and evidences the effects of the use of the soil, constructive materials and the flow of people and merchandise in the definition of different thermal fields. It shows that the distribution and size of the vegetation cover, besides the amplitude of the ventilation interfere and provide fresher environments and therefore reduce the storage of heat. The methodology presented is simple to apply and can be adapted to other urban areas with characteristics similar to those of Juiz de Fora-MG.Keywords: Thermal fields, urban climate, spatial model, urban climate map, dynamic potential.

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Chou, Jieming, Mingyang Sun, Wenjie Dong, Weixing Zhao, Jiangnan Li, Yuanmeng Li, and Jianyin Zhou. "Assessment and Prediction of Climate Risks in Three Major Urban Agglomerations of Eastern China." Sustainability 13, no. 23 (November 25, 2021): 13037. http://dx.doi.org/10.3390/su132313037.

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In the context of global climate change and urban expansion, extreme urban weather events occur frequently and cause significant social problems and economic losses. To study the climate risks associated with rapid urbanization in the global context of climate change, the vulnerability degree of urban agglomeration is constructed by the Grey Model (GM (1, 1)). Based on the sixth phase of the Coupled Model Intercomparison Project (CMIP6) data sets SSP1-2.6, SSP2-4.5, and SSP5-8.5, drought, heat wave, and flood hazards under different emission scenarios are calculated. The vulnerability degree of the urban agglomeration and the climate change hazard were input into the climate change risk assessment model to evaluate future climate change risk. The analysis results show regional differences, with the Beijing–Tianjin–Hebei urban agglomeration having good urban resilience, the Yangtze River Delta urban agglomeration having slightly higher overall risk, and the Pearl River Delta urban agglomeration having the highest relative risk overall. On the whole, the higher the emission intensity is, the greater the risk of climate change to each urban agglomeration under different emission scenarios.

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Maronga, Björn, Günter Gross, Siegfried Raasch, Sabine Banzhaf, Renate Forkel, Wieke Heldens, Farah Kanani-Sühring, et al. "Development of a new urban climate model based on the model PALM – Project overview, planned work, and first achievements." Meteorologische Zeitschrift 28, no. 2 (June 21, 2019): 105–19. http://dx.doi.org/10.1127/metz/2019/0909.

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Yuan, Chao. "Climate Modelling and Analytics for Urban Heat Risks Mitigation and Adaptation." IOP Conference Series: Earth and Environmental Science 1301, no. 1 (February 1, 2024): 012001. http://dx.doi.org/10.1088/1755-1315/1301/1/012001.

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Abstract This study highlights the need for climate-sensitive urban planning and design in the face of climate change, with a specific focus on Singapore. Rapid urbanization has led to significant warming trends, increased heat stress, and heightened electricity demand for cooling. The Urban Climate Design Lab (UCDL) at the National University of Singapore employs a multidisciplinary approach, merging urban planning, architecture, and urban climate science. The research introduces GIS-based tools to evaluate the microclimate impact of new developments, replacing time-consuming simulations and wind tunnel experiments. These tools encompass: 1) The Urban Wind Environment Model, assessing urban permeability for natural ventilation; 2) The Fine-Scale Wind Environment Model, providing high-resolution pedestrian-level wind speed data. 3) The Urban Tree-Airflow Model, aiding tree placement and species selection for optimal cooling. 4) The Anthropogenic Heat Dispersion Model, estimating the impact of human-generated heat emissions. These GIS tools are integrated into the open-access UCDL Microclimate Digital Platform, facilitating knowledge transfer and empowering stakeholders in climate-sensitive urban planning. The platform offers various climate models and visualization capabilities to enhance evidence-based decision-making for urban climate sustainability and resilience. In the future, the platform will expand its offerings, becoming a valuable resource for urban planners, engineers, health practitioners, environmental experts, and residents adapting to a changing climate.

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Oleson, Keith. "Contrasts between Urban and Rural Climate in CCSM4 CMIP5 Climate Change Scenarios." Journal of Climate 25, no. 5 (March 2012): 1390–412. http://dx.doi.org/10.1175/jcli-d-11-00098.1.

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A new parameterization of urban areas in the Community Climate System Model version 4 (CCSM4) allows for simulation of temperature in cities where most of the global population lives. CCSM4 Coupled Model Intercomparison Project phase 5 (CMIP5) simulations [Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5] are analyzed to examine how urban and rural areas might respond differently to changes in climate. The urban heat island (UHI), defined as the urban minus rural air temperature, is used as a metric. The average UHI at the end of the twenty-first century is similar to present day in RCP2.6 and RCP4.5, but decreases in RCP8.5. Both the daytime and nocturnal UHIs decrease in RCP8.5, but the decrease in the daytime UHI is larger and more uniform across regions and seasons than in the nocturnal UHI. This is caused by changes in evaporation that warm the rural surface more than the urban. There is significant spatial and seasonal variability in the response of the nocturnal UHI caused mainly by changes in the rural surface. In Europe, the response to climate change of rural leaf–stem area in summer and clouds and rural soil moisture in winter explains the majority of this variability. Climate change increases the number of warm nights in urban areas substantially more than in rural areas. These results provide evidence that urban and rural areas respond differently to climate change. Thus, the unique aspects of the urban environment should be considered when making climate change projections, particularly since the global population is becoming increasingly urbanized.

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Kjelgren, Roger, Yongyut Trisurat, Ladawan Puangchit, Nestor Baguinon, and Puay Tan Yok. "Tropical Street Trees and Climate Uncertainty in Southeast Asia." HortScience 46, no. 2 (February 2011): 167–72. http://dx.doi.org/10.21273/hortsci.46.2.167.

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Urban trees are a critical quality of life element in rapidly growing cities in tropical climates. Tropical trees are found in a wide variety of habitats governed largely by the presence and duration of monsoonal dry periods. Tropical cities can serve as a proxy for climate change impacts of elevated carbon dioxide (CO2), urban heat island, and drought-prone root zones on successful urban trees. Understanding the native habitats of species successful as tropical urban trees can yield insights into the potential climate impact on those habitats. Species from equatorial and montane wet forests where drought stress is not a limiting factor are not used as urban trees in cities with monsoonal dry climates such as Bangkok and Bangalore. Absence of trees from a wet habitat in tropical cities in monsoonal climates is consistent with model and empirical studies suggesting wet evergreen species are vulnerable to projected climates changes such as lower rainfall and increased temperatures. However, monsoonal dry forest species appear to have wider environmental tolerances and are successful urban trees in cities with equatorial wet climates such as Singapore as well as cities with monsoonal climates such as Bangkok and Bangalore. In cities with monsoonal dry climates, deciduous tree species are more common than dry evergreen species. Although dry deciduous species generally have better floral displays, their prevalence may in part be the result of greater tolerance of urban heat islands and drought in cities; this would be consistent with modeled habitat gains at the expense of dry evergreen species in native forest stands under projected higher temperatures from climate change. Ecological models may also point to selection of more heat- and drought-tolerant species for tropical cities under projected climate change.

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Resler, Jaroslav, Pavel Krč, Michal Belda, Pavel Juruš, Nina Benešová, Jan Lopata, Ondřej Vlček, et al. "PALM-USM v1.0: A new urban surface model integrated into the PALM large-eddy simulation model." Geoscientific Model Development 10, no. 10 (October 9, 2017): 3635–59. http://dx.doi.org/10.5194/gmd-10-3635-2017.

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Abstract. Urban areas are an important part of the climate system and many aspects of urban climate have direct effects on human health and living conditions. This implies that reliable tools for local urban climate studies supporting sustainable urban planning are needed. However, a realistic implementation of urban canopy processes still poses a serious challenge for weather and climate modelling for the current generation of numerical models. To address this demand, a new urban surface model (USM), describing the surface energy processes for urban environments, was developed and integrated as a module into the PALM large-eddy simulation model. The development of the presented first version of the USM originated from modelling the urban heat island during summer heat wave episodes and thus implements primarily processes important in such conditions. The USM contains a multi-reflection radiation model for shortwave and longwave radiation with an integrated model of absorption of radiation by resolved plant canopy (i.e. trees, shrubs). Furthermore, it consists of an energy balance solver for horizontal and vertical impervious surfaces, and thermal diffusion in ground, wall, and roof materials, and it includes a simple model for the consideration of anthropogenic heat sources. The USM was parallelized using the standard Message Passing Interface and performance testing demonstrates that the computational costs of the USM are reasonable on typical clusters for the tested configurations. The module was fully integrated into PALM and is available via its online repository under the GNU General Public License (GPL). The USM was tested on a summer heat-wave episode for a selected Prague crossroads. The general representation of the urban boundary layer and patterns of surface temperatures of various surface types (walls, pavement) are in good agreement with in situ observations made in Prague. Additional simulations were performed in order to assess the sensitivity of the results to uncertainties in the material parameters, the domain size, and the general effect of the USM itself. The first version of the USM is limited to the processes most relevant to the study of summer heat waves and serves as a basis for ongoing development which will address additional processes of the urban environment and lead to improvements to extend the utilization of the USM to other environments and conditions.

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Kovalevsky, Dmitry V., and Jürgen Scheffran. "A Two-Period Model of Coastal Urban Adaptation Supported by Climate Services." Urban Science 6, no. 4 (September 23, 2022): 65. http://dx.doi.org/10.3390/urbansci6040065.

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Coastal zones are experiencing rapid urbanization at unprecedented rates. At the same time, coastal cities are the most prone to climate-related vulnerability, including impacts of sea-level rise and climate-related coastal hazards under the present and projected future climate. Decision making about coastal urban climate adaptation can be informed by coastal climate services based on modeling tools. We develop a two-period coastal urban adaptation model in which two periods—the present and the future—are distinguished. In the model, a city agent anticipates sea-level rise and related coastal flood hazards with adverse impacts in the future period that, through damages, will reduce the urban income. However, the magnitude of future sea-level rise and induced damages are characterized by uncertainty. The urban planning agent has to make an investment decision under uncertainty: whether to invest in climate adaptation (in the form of construction of coastal protection) or not, and if so, how much. The decision making of the urban agent is derived from intertemporal maximization of expected time-discounted consumption. An exact solution in the closed form is derived for an analytically tractable particular case, for which it is shown that investment decisions depend discontinuously on the value of a single non-dimensional model indicator. When this indicator exceeds a certain threshold value, the urban agent discontinuously switches from the ‘business-as-usual’ (BaU) strategy when no adaptation investment is taken to a proactive adaptation. The role of coastal climate services in informing the decision making on adaptation strategies is discussed.

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Chapman, David, and Agneta Larsson. "Toward an Integrated Model for Soft-Mobility." International Journal of Environmental Research and Public Health 16, no. 19 (September 29, 2019): 3669. http://dx.doi.org/10.3390/ijerph16193669.

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A key urban design challenge is to create built environments that encourage outdoor activity all year round. This study explores a new model for soft-mobility that places the interaction between the urban form, the seasonal climate and climate change, and the individual at the center of people’s soft-mobility choices, or in more general, their modal choice. The research methods used were comparative studies of documents, surveys, mental mapping, and photo elicitation. These studies were undertaken to research people’s outdoor activity in the built environment during the winter season of a cold climate settlement. The results were analyzed against the three-dimensions of the model. In the discussion it is argued that in places with significant climate variation, the interaction between the urban form, the season, and the individual together influence soft-mobility choices. In turn, these interactions influence people’s level of outdoor activity and the individual health benefits such activity can afford. In conclusion, it is highlighted that all three dimensions of the model are in a constant state of change and evolution, especially in relation to planning and development processes and climate change.

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Chen, Ning, Xiaolin Tang, and Weihui Liu. "Urban Disaster Risk Prevention and Mitigation Strategies from the Perspective of Climate Resilience." Wireless Communications and Mobile Computing 2022 (August 21, 2022): 1–13. http://dx.doi.org/10.1155/2022/4907084.

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Enhancing urban climate resilience and innovating urban risk governance model are of great significance to promote the security development of cities. This paper discusses urban disaster risk prevention and mitigation strategies from the perspective of climate resilience. The urban climate resilience index system is constructed through text mining. The entropy weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method and obstacle degree model are used to measure the climate resilience index and identify the main obstacle factors that affect the improvement of urban climate resilience. This provides a quantitative representation method for the analysis of urban climate resilience and clarifies the contribution of climate resilience to urban disaster risk prevention and mitigation, as well as the key and difficult points of urban disaster risk prevention and mitigation. Therefore, based on the quantitative analysis of climate resilience, this paper puts forward disaster risk prevention and mitigation strategies from five aspects: collaborative governance, urban planning, early warning system, scientific and technological empowerment, and disaster education. It is expected to provide a reference for the urban system to maintain green, low-carbon, and high-quality development under climate change.

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Gautier, J., S. Christophe, and M. Brédif. "VISUALIZING 3D CLIMATE DATA IN URBAN 3D MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 781–89. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-781-2020.

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Abstract. In order to understand and explain urban climate, the visual analysis of urban climate data and their relationships with the urban morphology is at stake. This involves partly to co-visualize 3D field climate data, obtained from simulation, with urban 3D models. We propose two ways to visualize and navigate into simulated climate data in urban 3D models, using series of horizontal 2D planes and 3D point clouds. We then explore different parameters regarding transparency, 3D semiologic rules, filtering and animation functions in order to improve the visual analysis of climate data 3D distribution. To achieve this, we apply our propositions to the co-visualization of air temperature data with a 3D urban city model.

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Grum, M., A. T. Jørgensen, R. M. Johansen, and J. J. Linde. "The effect of climate change on urban drainage: an evaluation based on regional climate model simulations." Water Science and Technology 54, no. 6-7 (September 1, 2006): 9–15. http://dx.doi.org/10.2166/wst.2006.592.

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That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 × 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at time-scales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.

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Craninx, Michel, Koen Hilgersom, Jef Dams, Guido Vaes, Thomas Danckaert, and Jan Bronders. "Flood4castRTF: A Real-Time Urban Flood Forecasting Model." Sustainability 13, no. 10 (May 18, 2021): 5651. http://dx.doi.org/10.3390/su13105651.

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Worldwide, climate change increases the frequency and intensity of heavy rainstorms. The increasing severity of consequent floods has major socio-economic impacts, especially in urban environments. Urban flood modelling supports the assessment of these impacts, both in current climate conditions and for forecasted climate change scenarios. Over the past decade, model frameworks that allow flood modelling in real-time have been gaining widespread popularity. Flood4castRTF is a novel urban flood model that applies a grid-based approach at a modelling scale coarser than most recent detailed physically based models. Automatic model set-up based on commonly available GIS data facilitates quick model building in contrast with detailed physically based models. The coarser grid scale applied in Flood4castRTF pursues a better agreement with the resolution of the forcing rainfall data and allows speeding up of the calculations. The modelling approach conceptualises cell-to-cell interactions while at the same time maintaining relevant and interpretable physical descriptions of flow drivers and resistances. A case study comparison of Flood4castRTF results with flood results from two detailed models shows that detailed models do not necessarily outperform the accuracy of Flood4castRTF with flooded areas in-between the two detailed models. A successful model application for a high climate change scenario is demonstrated. The reduced data need, consisting mainly of widely available data, makes the presented modelling approach applicable in data scarce regions with no terrain inventories. Moreover, the method is cost effective for applications which do not require detailed physically based modelling.

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KAWAI, Toru. "Comprehensive Outdoor Scale Model Experiment for Urban Climate (COSMO)." JOURNAL OF JAPAN SOCIETY OF HYDROLOGY AND WATER RESOURCES 29, no. 2 (2016): 130–39. http://dx.doi.org/10.3178/jjshwr.29.130.

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Ashie, Yasunobu, Vu Thanh Ca, and Takashi Asaeda. "Building canopy model for the analysis of urban climate." Journal of Wind Engineering and Industrial Aerodynamics 81, no. 1-3 (May 1999): 237–48. http://dx.doi.org/10.1016/s0167-6105(99)00020-3.

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Bokwa, Anita, Petr Dobrovolný, Tamás Gál, Jan Geletič, Ágnes Gulyás, Monika J. Hajto, Juraj Holec, et al. "Urban climate in Central European cities and global climate change." Acta climatologica et chorologica 51-52, no. 1 (2018): 7–35. http://dx.doi.org/10.14232/acta.clim.2018.52.1.

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Urban areas are among those most endangered with the potential global climate changes. The studies concerning the impact of global changes on local climate of cities are of a high significance for the urban inhabitants' health and wellbeing. This paper is the final report of a project (Urban climate in Central European cities and global climate change) with the aim to raise the public awareness on those issues in five Central European cities: Szeged (Hungary), Brno (Czech Republic), Bratislava (Slovakia), Kraków (Poland) and Vienna (Austria). Within the project, complex data concerning local geomorphological features, land use and long-term climatological data were used to perform the climate modelling analyses using the model MUKLIMO_3 provided by the German Weather Service (DWD).

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Keat, William J., Elizabeth J. Kendon, and Sylvia I. Bohnenstengel. "Climate change over UK cities: the urban influence on extreme temperatures in the UK climate projections." Climate Dynamics 57, no. 11-12 (September 29, 2021): 3583–97. http://dx.doi.org/10.1007/s00382-021-05883-w.

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AbstractIncreasing summer temperatures in a warming climate will increase the exposure of the UK population to heat-stress and associated heat-related mortality. Urban inhabitants are particularly at risk, as urban areas are often significantly warmer than rural areas as a result of the urban heat island phenomenon. The latest UK Climate Projections include an ensemble of convection-permitting model (CPM) simulations which provide credible climate information at the city-scale, the first of their kind for national climate scenarios. Using a newly developed urban signal extraction technique, we quantify the urban influence on present-day (1981–2000) and future (2061–2080) temperature extremes in the CPM compared to the coarser resolution regional climate model (RCM) simulations over UK cities. We find that the urban influence in these models is markedly different, with the magnitude of night-time urban heat islands overestimated in the RCM, significantly for the warmest nights (up to $$4~^{\circ }$$ 4 ∘ C), while the CPM agrees much better with observations. This improvement is driven by the improved land-surface representation and more sophisticated urban scheme MORUSES employed by the CPM, which distinguishes street canyons and roofs. In future, there is a strong amplification of the urban influence in the RCM, whilst there is little change in the CPM. We find that future changes in soil moisture play an important role in the magnitude of the urban influence, highlighting the importance of the accurate representation of land-surface and hydrological processes for urban heat island studies. The results indicate that the CPM provides more reliable urban temperature projections, due at least in part to the improved urban scheme.

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Wang, Yiwen, Zhiming Zhang, Zhiyong Zhao, Thomas Sagris, and Yang Wang. "Prediction of Future Urban Rainfall and Waterlogging Scenarios Based on CMIP6: A Case Study of Beijing Urban Area." Water 15, no. 11 (May 28, 2023): 2045. http://dx.doi.org/10.3390/w15112045.

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Extreme weather events will become more frequent and severe as a result of climate change, necessitating an immediate need for cities to adapt to future climate change. Therefore, the prediction of future precipitation and waterlogging is of utmost importance. Using Beijing as an example, the simulation capability of different models was evaluated, and the optimal model for the study area was screened using Taylor diagrams and interannual variability scores, along with actual monthly precipitation data from Chinese weather stations from 1994 to 2014 and historical monthly precipitation data from 10 coupled models from Coupled Model Intercomparison Project Phase 6 (CMIP6). The SWMM model was then used to simulate future rainfall and waterlogging scenarios for the study area using precipitation forecast data for 2020–2050 from the best model to investigate the impact of climate change on future rainfall and waterlogging in urban areas. CMIP6 brings together the most recent simulation data from major climate models on a global scale, providing a broader and more diverse range of model results and thereby making future predictions more accurate and dependable, and its findings provide a theoretical foundation for the emergency management of and scientific responses to urban flooding events. The following major conclusions were reached: 1. The best-performing models are EC-Earth3, GFDL-ESM4, and MPI- ESM1-2-HR. EC-Earth3 is a modular Earth system model developed collaboratively by a European consortium. MPI-ESM1-2 is a climate precipitation prediction model developed in Germany and promoted for global application, whereas the GFDL-ESM4 model was developed in the United States and is currently employed for global climate precipitation simulations. 2. Under future climate circumstances, the total annual precipitation in the example region simulated by all three models increases by a maximum of 40%. 3. Under future climatic conditions, urban surface runoff and nodal overflow in the study area will be more significant. The node overflow will become more severe with the increase in climate scenario oppression, and the potential overflow nodes will account for 1.5%, 2.7%, and 2.9% of the total number of nodes under the SSP1–2.6, SSP2–4.5, and SSP5–8.5 scenarios, respectively. 4. In the future, the effectiveness of stormwater drainage systems may diminish. To increase climate change resilience, the impacts of climate change should be considered when planning the scope of stormwater optimization and the integrated improvement of gray–green–blue facilities.

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Hollósi, Brigitta, Maja Žuvela-Aloise, Sandro Oswald, Astrid Kainz, and Wolfgang Schöner. "Applying urban climate model in prediction mode—evaluation of MUKLIMO_3 model performance for Austrian cities based on the summer period of 2019." Theoretical and Applied Climatology 144, no. 3-4 (March 25, 2021): 1181–204. http://dx.doi.org/10.1007/s00704-021-03580-6.

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AbstractExtreme heat events are natural hazards affecting many regions of the world. This study uses an example of the six largest cities in Austria to demonstrate the potential of urban climate model simulations applied in prediction mode providing detailed information on thermal conditions. For this purpose, the urban climate model MUKLIMO_3 of the German Meteorological Service (DWD) coupled with the hydrostatic numerical weather prediction model, ALARO, is used to simulate the development of the urban heat island (UHI) in Austrian cities for the summer period of 2019 with a horizontal resolution of 100 m. In addition to the evaluation of UHI predicting skills, other relevant variables, such as humidity and wind characteristics on hourly basis, are also analysed in this paper. Model evaluation confirmed that the MUKLIMO_3 microscale model had the capacity to simulate the main thermal spatiotemporal patterns in urban areas; however, a strong dependence on the input data from the mesoscale model was found. Our results showed large benefit in prediction of maximum air temperatures in urban areas, while the relative humidity predictions of MUKLIMO_3 appear to be much less plausible and show large variety of model prediction skills. Urban climate model simulations using real atmospheric conditions can facilitate better quantification and understanding of day-to-day intra-urban variations in microclimate as well as provide a basis for evaluation of the microclimate prediction skills of mesoscale numerical models with urban extensions.

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Chen, Yu-Cheng, Fang-Yi Cheng, Cheng-Pei Yang, and Tzu-Ping Lin. "Explore the Accuracy of the Pedestrian Level Temperature Estimated by the Combination of LCZ with WRF Urban Canopy Model through the Microclimate Measurement Network." Environmental Sciences Proceedings 8, no. 1 (June 22, 2021): 14. http://dx.doi.org/10.3390/ecas2021-10349.

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Due to the urban heat island effect becoming more evident in the cities in Taiwan, the urban climate has become an essential factor in urban development. Taiwan is located on the border of tropical and subtropical climate zones, the climate condition is hot and humid, and the city shows high-density development. The dense urban development has increased the heat storage capacity of the ground and buildings. However, if only the climate stations set by the Central Meteorological Bureau to observe the climate data are applied, the predicted results differ from the actual urban climate conditions due to the small number of these stations and the too far distance between them. Therefore, this study employs the local climate zone (LCZ), which can classify the land features by considering both land use and land cover, and can be freely generated from satellite images. The LCZ classification method can view the type of the city through the height and density of obstacles. This study also combines the urban canopy model (UCM) of the mesoscale climate prediction model and weather research and forecasts (WRF). This approach can calculate vertical and horizontal planes of the city, such as building volume, road width, the influence of streets and roofs, roof heat capacity, building wall heat capacity, etc., to predict the climatic conditions in different lands in the study area. Simultaneously, to understand the actual distribution of urban climate more accurately, this study used the microclimate measurement network built in the research area to produce pedestrian-level temperature distribution and compared the estimated results with the actual measured values for urban climate assessment. This study can understand the cause of urban heat islands and assist urban planners more appropriately formulate heat island mitigation strategies in different regions.

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Karlický, Jan, Peter Huszár, Tereza Nováková, Michal Belda, Filip Švábik, Jana Ďoubalová, and Tomáš Halenka. "The “urban meteorology island”: a multi-model ensemble analysis." Atmospheric Chemistry and Physics 20, no. 23 (December 4, 2020): 15061–77. http://dx.doi.org/10.5194/acp-20-15061-2020.

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Abstract. Cities and urban areas are well-known for their impact on meteorological variables and thereby modification of the local climate. Our study aims to generalize the urban-induced changes in specific meteorological variables by introducing a single phenomenon – the urban meteorology island (UMI). A wide ensemble of 24 model simulations with the Weather Research and Forecasting (WRF) regional climate model and the Regional Climate Model (RegCM) on a European domain with 9 km horizontal resolution were performed to investigate various urban-induced modifications as individual components of the UMI. The results show that such an approach is meaningful, because in nearly all meteorological variables considered, statistically significant changes occur in cities. Besides previously documented urban-induced changes in temperature, wind speed and boundary-layer height, the study is also focused on changes in cloud cover, precipitation and humidity. An increase in cloud cover in cities, together with a higher amount of sub-grid-scale precipitation, is detected on summer afternoons. Specific humidity is significantly lower in cities. Further, the study shows that different models and parameterizations can have a strong impact on discussed components of the UMI. Multi-layer urban schemes with anthropogenic heat considered increase winter temperatures by more than 2 ∘C and reduce wind speed more strongly than other urban models. The selection of the planetary-boundary-layer scheme also influences the urban wind speed reduction, as well as the boundary-layer height, to the greatest extent. Finally, urban changes in cloud cover and precipitation are mostly sensitive to the parameterization of convection.

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Rahman, Moh Shadiqur, Novil Dedy Andriatmoko, Moh Saeri, Herman Subagio, Afrizal Malik, Joko Triastono, Renie Oelviani, et al. "Climate Disasters and Subjective Well-Being among Urban and Rural Residents in Indonesia." Sustainability 14, no. 6 (March 14, 2022): 3383. http://dx.doi.org/10.3390/su14063383.

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Climate disasters pose a risk to residents’ well-being globally. However, information about the impact of climate disasters among urban and rural residents remains lacking, especially in Indonesia. This study aims to fill the gap by investigating the impact of climate disaster on subjective well-being based on urban and rural typology model. The data were cross-sectional, involving 7110 Indonesian residents who had experienced climate disasters, 3813 from urban areas and 3297 from rural areas. An ordered probit model was employed to estimate the impact of climate disasters on subjective well-being (i.e., happiness and life satisfaction). In general, the empirical results show that climate disasters do not significantly affect the happiness of Indonesian residents, but they significantly and negatively impact their life satisfaction. Further analysis reveals that climate disasters impact urban and rural residents differently. The subjective well-being of rural residents is more severely affected than those living in urban areas. Further estimation also indicated that climate disaster significantly reduces residents’ subjective well-being at the lowest income level for both rural and urban residents. Our finding confirms that rural residents remain the most vulnerable to the impacts of climate change.

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Zsebeházi, Gabriella, and Gabriella Szépszó. "Modeling the urban climate of Budapest using the SURFEX land surface model driven by the ALADIN-Climate regional climate model results." Időjárás 124, no. 2 (2020): 191–207. http://dx.doi.org/10.28974/idojaras.2020.2.3.

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Zsebeházi, Gabriella, and Sándor István Mahó. "Assessment of the Urban Impact on Surface and Screen-Level Temperature in the ALADIN-Climate Driven SURFEX Land Surface Model for Budapest." Atmosphere 12, no. 6 (May 31, 2021): 709. http://dx.doi.org/10.3390/atmos12060709.

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Land surface models with detailed urban parameterization schemes provide adequate tools to estimate the impact of climate change in cities, because they rely on the results of the regional climate model, while operating on km scale at low cost. In this paper, the SURFEX land surface model driven by the evaluation and control runs of ALADIN-Climate regional climate model is validated over Budapest from the aspect of urban impact on temperature. First, surface temperature of SURFEX with forcings from ERA-Interim driven ALADIN-Climate was compared against the MODIS land surface temperature for a 3-year period. Second, the impact of the ARPEGE global climate model driven ALADIN-Climate was assessed on the 2 m temperature of SURFEX and was validated against measurements of a suburban station for 30 years. The spatial extent of surface urban heat island (SUHI) is exaggerated in SURFEX from spring to autumn, because the urbanized gridcells are generally warmer than their rural vicinity, while the observed SUHI extent is more variable. The model reasonably simulates the seasonal means and diurnal cycle of the 2 m temperature in the suburban gridpoint, except summer when strong positive bias occurs. However, comparing the two experiments from the aspect of nocturnal UHI, only minor differences arose. The thorough validation underpins the applicability of SURFEX driven by ALADIN-Climate for future urban climate projections.

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Jin, Lei, Xinpei Pan, Lin Liu, Liru Liu, Jing Liu, and Yunfei Gao. "Block-based local climate zone approach to urban climate maps using the UDC model." Building and Environment 186 (December 2020): 107334. http://dx.doi.org/10.1016/j.buildenv.2020.107334.

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Zeleke, T. T., F. Giorgi, G. T. Diro, B. F. Zaitchik, G. Giuliani, D. Ayal, T. Kassahun, W. D. Sintayehu, and T. Demissie. "Effect of urbanization on East African climate as simulated by coupled urban-climate model." Climate Services 31 (August 2023): 100398. http://dx.doi.org/10.1016/j.cliser.2023.100398.

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Sanagar Darbani, Elham, and Danial Monsefi Parapari. "IDEAL MODEL FOR INVESTIGATING URBAN FORM EFFECTS ON URBAN HEAT ISLAND AND OUTDOOR THERMAL COMFORT: A REVIEW." International Journal of Engineering Science Technologies 6, no. 1 (February 16, 2022): 64–90. http://dx.doi.org/10.29121/ijoest.v6.i1.2022.275.

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In recent decades, urban planners have endeavoured to mitigate climate change, by adaptation programs in order to alleviate its adverse effects on human health and wellbeing. Outdoor thermal comfort as an environmental factor affects human health, as proven by various research studies conducted in different climates. The aim of this paper is to explore the components of urban heat island, outdoor thermal comfort, and urban form. The relationship between these keywords and variables that affect outdoor thermal comfort was also analysed. The research method is descriptive-analytical and besides that, the qualitative research method has been used. The components of each keyword have been extracted based on professional theories. Finally, the ideal model of outdoor thermal comfort is proposed. This paper gives a comprehensive view to urban heat islands, urban form and outdoor thermal comfort

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Wang, Cheng Xin, and Li Yuan Liu. "Empirical Research on the Impact to City Climate Caused by Urbanization – A Case of Jinan City." Applied Mechanics and Materials 295-298 (February 2013): 2669–74. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.2669.

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Over the past 10 years, the rapid urbanization in China has brought profound impact on China economy and society, and had certain influence on urban micro-climate. Taking Jinan city as an example, based on the model about the relation between the urban development and urban climate change, the trend of Jinan temperature and precipitation are analyzed, the relative impact between the urban climate and the urban development is studied. The results show that there are noticeable Heat Island Effect and Rain Island Effect in Jinan, the impact on the urban climate change caused by the urban development could not precisely match the Kuznets Curve in Jinan.

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Lu, Wei, and Xiaosheng Qin. "Integrated framework for assessing climate change impact on extreme rainfall and the urban drainage system." Hydrology Research 51, no. 1 (December 16, 2019): 77–89. http://dx.doi.org/10.2166/nh.2019.233.

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Abstract Urban areas are becoming increasingly vulnerable to extreme storms and flash floods, which could be more damaging under climate change. This study presented an integrated framework for assessing climate change impact on extreme rainfall and urban drainage systems by incorporating a number of statistical and modelling techniques. Starting from synthetic future climate data generated by the stochastic weather generator, the simple scaling method and the Huff rainfall design were adopted for rainfall disaggregation and rainfall design. After having obtained 3-min level designed rainfall information, the urban hydrological model (i.e., Storm Water Management Model) was used to carry out the runoff analysis. A case study in a tropical city was used to demonstrate the proposed framework. Particularly, the impact of selecting different general circulation models and Huff distributions on future 1-h extreme rainfall and the performance of the urban drainage system were investigated. It was revealed that the proposed framework is flexible and easy to implement in generating temporally high-resolution rainfall data under climate model projections and offers a parsimonious way of assessing urban flood risks considering the uncertainty arising from climate change model projections, downscaling and rainfall design.

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Burgstall, Annkatrin, Sven Kotlarski, Ana Casanueva, Elke Hertig, Erich Fischer, and Reto Knutti. "Urban multi-model climate projections of intense heat in Switzerland." Climate Services 22 (April 2021): 100228. http://dx.doi.org/10.1016/j.cliser.2021.100228.

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Nevat, Ido, Lea A. Ruefenacht, and Heiko Aydt. "Recommendation system for climate informed urban design under model uncertainty." Urban Climate 31 (March 2020): 100524. http://dx.doi.org/10.1016/j.uclim.2019.100524.

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Thatcher, Marcus, and Peter Hurley. "Simulating Australian Urban Climate in a Mesoscale Atmospheric Numerical Model." Boundary-Layer Meteorology 142, no. 1 (October 29, 2011): 149–75. http://dx.doi.org/10.1007/s10546-011-9663-8.

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Munsyi, Munsyi. "Urban Heat Island Spatial Model for Climate Village Program Planning." Journal of Applied Data Sciences 5, no. 2 (May 31, 2024): 546–58. http://dx.doi.org/10.47738/jads.v5i2.223.

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Oleson, K. W., G. B. Bonan, J. Feddema, and M. Vertenstein. "An Urban Parameterization for a Global Climate Model. Part II: Sensitivity to Input Parameters and the Simulated Urban Heat Island in Offline Simulations." Journal of Applied Meteorology and Climatology 47, no. 4 (April 1, 2008): 1061–76. http://dx.doi.org/10.1175/2007jamc1598.1.

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Abstract In a companion paper, the authors presented a formulation and evaluation of an urban parameterization designed to represent the urban energy balance in the Community Land Model. Here the robustness of the model is tested through sensitivity studies and the model’s ability to simulate urban heat islands in different environments is evaluated. Findings show that heat storage and sensible heat flux are most sensitive to uncertainties in the input parameters within the atmospheric and surface conditions considered here. The sensitivity studies suggest that attention should be paid not only to characterizing accurately the structure of the urban area (e.g., height-to-width ratio) but also to ensuring that the input data reflect the thermal admittance properties of each of the city surfaces. Simulations of the urban heat island show that the urban model is able to capture typical observed characteristics of urban climates qualitatively. In particular, the model produces a significant heat island that increases with height-to-width ratio. In urban areas, daily minimum temperatures increase more than daily maximum temperatures, resulting in a reduced diurnal temperature range relative to equivalent rural environments. The magnitude and timing of the heat island vary tremendously depending on the prevailing meteorological conditions and the characteristics of surrounding rural environments. The model also correctly increases the Bowen ratio and canopy air temperatures of urban systems as impervious fraction increases. In general, these findings are in agreement with those observed for real urban ecosystems. Thus, the model appears to be a useful tool for examining the nature of the urban climate within the framework of global climate models.

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Karlický, Jan, Peter Huszár, Tomáš Halenka, Michal Belda, Michal Žák, Petr Pišoft, and Jiří Mikšovský. "Multi-model comparison of urban heat island modelling approaches." Atmospheric Chemistry and Physics 18, no. 14 (July 26, 2018): 10655–74. http://dx.doi.org/10.5194/acp-18-10655-2018.

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Abstract. Cities are characterized by different physical properties of surface compared to their rural counterparts, resulting in a specific regime of the meteorological phenomenon. Our study aims to evaluate the impact of typical urban surfaces on the central European urban climate in several model simulations, performed with the Weather Research and Forecasting (WRF) model and Regional Climate Model (RegCM). The specific processes occurring in the typical urban environment are described in the models by various types of urban parameterizations, greatly differing in complexity. Our results show that all models and urban parameterizations are able to reproduce the most typical urban effect, the summer evening and nocturnal urban heat island, with the average magnitude of 2–3 °C. The impact of cities on the wind is clearly dependent on the urban parameterization employed, with more simple ones unable to fully capture the wind speed reduction induced by the city. In the summer, a significant difference in the boundary-layer height (about 25 %) between models is detected. The urban-induced changes of temperature and wind speed are propagated into higher altitudes up to 2 km, with a decreasing tendency of their magnitudes. With the exception of the daytime in the summer, the urban environment improves the weather conditions a little with regard to the pollutant dispersion, which could lead to the partly decreased concentration of the primary pollutants.

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Dare, Robert. "A System Dynamics Model to Facilitate the Development of Policy for Urban Heat Island Mitigation." Urban Science 5, no. 1 (February 1, 2021): 19. http://dx.doi.org/10.3390/urbansci5010019.

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This article presents a customized system dynamics model to facilitate the informed development of policy for urban heat island mitigation within the context of future climate change, and with special emphasis on the reduction of heat-related mortality. The model incorporates a variety of components (incl.: the urban heat island effect; population dynamics; climate change impacts on temperature; and heat-related mortality) and is intended to provide urban planning and related professionals with: a facilitated means of understanding the risk of heat-related mortality within the urban heat island; and location-specific information to support the development of reasoned and targeted urban heat island mitigation policy.

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van der Linden, Lara, Patrick Hogan, Björn Maronga, Rowell Hagemann, and Benjamin Bechtel. "Crowdsourcing air temperature data for the evaluation of the urban microscale model PALM—A case study in central Europe." PLOS Climate 2, no. 8 (August 18, 2023): e0000197. http://dx.doi.org/10.1371/journal.pclm.0000197.

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In summertime and during heat events the urban heat island can negatively impact human health in urban areas. In the context of climate change, climate adaptation receives more attention in urban planning. Microscale urban climate modelling can identify risk areas and evaluate adaptation strategies. Concurrently, evaluating the model results with observational data is essential. So far, model evaluation is mostly limited to short-term field campaigns or a small number of stations. This study uses novel crowdsourcing data from Netatmo citizen weather stations (CWS) to evaluate the urban microscale model PALM for a hot day (Tmax ≥ 30°C) in Bochum in western Germany with anticyclonic atmospheric conditions. Urban-rural air temperature differences are represented by the model. A quality control procedure is applied to the crowdsourced data prior to evaluation. The comparison between the model and the crowdsourced air temperature data reveals a good model performance with a high coefficient of determination (R2) of 0.86 to 0.88 and a root mean squared error (RMSE) around 2 K. Model accuracy shows a temporal pattern and night-time air temperatures during the night are underestimated by the model, likely due to unresolved cloud cover. The crowdsourced air temperature data proved valuable for model evaluation due to the high number of stations within urban areas. Nevertheless, weaknesses related to data quality such as radiation errors must be considered during model evaluation and only the information derived from multiple stations is suitable for model evaluation. The procedure presented here can easily be transferred to planning processes as the model and the crowdsourced air temperature data are freely available. This can contribute to making informed decisions for climate adaptation in urban areas.

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Nevat, Ido, and Ayu Sukma Adelia. "Urban Wind Corridors Analysis via Network Theory." Atmosphere 14, no. 3 (March 16, 2023): 572. http://dx.doi.org/10.3390/atmos14030572.

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We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design.

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Silva, Humberto R., Rahul Bhardwaj, Patrick E. Phelan, Jay S. Golden, and Susanne Grossman-Clarke. "Development of a Zero-Dimensional Mesoscale Thermal Model for Urban Climate." Journal of Applied Meteorology and Climatology 48, no. 3 (March 1, 2009): 657–68. http://dx.doi.org/10.1175/2008jamc1962.1.

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Abstract A simple energy balance model is created for use in developing mitigation strategies for the urban heat island effect. The model is initially applied to the city of Phoenix, Arizona. There are six primary contributions to the overall energy balance: incident solar radiation, anthropogenic heat input, conduction heat loss, outgoing evapotranspiration, outgoing convection, and outgoing emitted radiation. Meteorological data are input to the model, which then computes an urban characteristic temperature at a calculated time step for a specified time range. The model temperature is shown to have the same periodic behavior as the experimentally measured air temperatures. Predicted temperature changes, caused by increasing the average urban albedo, agree within 0.1°C with comparable maximum surface temperature predictions from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). The present model, while maintaining valid energy-balance physics, allows users to quickly and easily predict the relative effects of urban heat island mitigation measures. Representative mitigation strategies, namely changes in average albedo and long-wavelength emissivity are presented here. Increasing the albedo leads to the greater reduction in daytime maximum temperatures; increasing the emissivity leads to a greater reduction in nighttime minimum temperatures.

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Sun, Qinke, Jiayi Fang, Xuewei Dang, Kepeng Xu, Yongqiang Fang, Xia Li, and Min Liu. "Multi-scenario urban flood risk assessment by integrating future land use change models and hydrodynamic models." Natural Hazards and Earth System Sciences 22, no. 11 (November 28, 2022): 3815–29. http://dx.doi.org/10.5194/nhess-22-3815-2022.

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Abstract. Urbanization and climate change are critical challenges in the 21st century. Flooding by extreme weather events and human activities can lead to catastrophic impacts in fast-urbanizing areas. However, high uncertainty in climate change and future urban growth limit the ability of cities to adapt to flood risk. This study presents a multi-scenario risk assessment method that couples a future land use simulation (FLUS) model and floodplain inundation model (LISFLOOD-FP) to simulate and evaluate the impacts of future urban growth scenarios with flooding under climate change (two representative concentration pathways (RCP2.6 and RCP8.5)). By taking the coastal city of Shanghai as an example, we then quantify the role of urban planning policies in future urban development to compare urban development under multiple policy scenarios (business as usual, growth as planned, growth as eco-constraints). Geospatial databases related to anthropogenic flood protection facilities, land subsidence and storm surge are developed and used as inputs to the LISFLOOD-FP model to estimate flood risk under various urbanization and climate change scenarios. The results show that urban growth under the three scenario models manifests significant differences in expansion trajectories, influenced by key factors such as infrastructure development and policy constraints. Comparing the urban inundation results for the RCP2.6 and RCP8.5 scenarios, the urban inundation area under the growth-as-eco-constraints scenario is less than that under the business-as-usual scenario but more than that under the growth-as-planned scenario. We also find that urbanization tends to expand more towards flood-prone areas under the restriction of ecological environment protection. The increasing flood risk information determined by model simulations helps us to understand the spatial distribution of future flood-prone urban areas and promote the re-formulation of urban planning in high-risk locations.

Journal articles on the topic 'Urban climate model'

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