Articles | Volume 15, issue 13
https://doi.org/10.5194/gmd-15-5309-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-5309-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
13 Jul 2022
Development and technical paper |
| 13 Jul 2022
| 13 Jul 2022
uDALES 1.0: a large-eddy simulation model for urban environments
Ivo Suter
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
Tom Grylls
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Birgit S. Sützl
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Chair of Building Physics, ETH, Zürich, Switzerland
Sam O. Owens
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Chris E. Wilson
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Maarten van Reeuwijk
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Imperial College London, London, UK
Related authors
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Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Alexei Koldunov, Tobias Kölling, Josh Kousal, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Domokos Sármány, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
EGUsphere, https://doi.org/10.5194/egusphere-2024-913, https://doi.org/10.5194/egusphere-2024-913, 2024
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale"), and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
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AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
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Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2024-1713, https://doi.org/10.5194/egusphere-2024-1713, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols, and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-52, https://doi.org/10.5194/gmd-2024-52, 2024
Preprint under review for GMD
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This work describe how we linked meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction in a global scale. This new model scales well on high performance computing environment and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Álvaro González-Cervera and Luis Durán
EGUsphere, https://doi.org/10.5194/egusphere-2024-958, https://doi.org/10.5194/egusphere-2024-958, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the Analog Method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities of broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Cited articles
Ambirajan, A. and Venkateshan, S. P.: Accurate determination of diffuse view
factors between planar surfaces, Int. J. Heat Mass Transf., 36, 2203–2208,
https://doi.org/10.1016/S0017-9310(05)80151-6, 1993. a
American Society of Civil Engineers Task Committee on Outdoor Human Comfort ASCE: Outdoor human comfort and its assessment: state of the art, American Society of Civil Engineers (ASCE), Reston, VA, 68 pp., ISBN 0784406847, 2004. a
American Society of Civil Engineers Task Committee on Urban Aerodynamics ASCE: Urban aerodynamics: wind engineering for urban planners and designers, American Society of Civil Engineers (ASCE), Reston, VA, 63 pp., ISBN 9780784411797, 2011. a
American Society of Heating Refrigerating and Air-Conditioning Engineers Inc. (ASHRAE): 2011 ASHRAE Handbook: Heating, Ventilating, and Air-Conditioning Applications, chapter 35, Solar energy use, American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., 1108 pp., ISBN 978-1-936504-07-7, 2011. a
Aoyagi, T. and Takahashi, S.: Development of an Urban Multilayer Radiation
Scheme and Its Application to the Urban Surface Warming Potential,
Bound.-Lay. Meteorol., 142, 305–328, https://doi.org/10.1007/s10546-011-9679-0,
2012. a
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical
processes of the UCLA general circulation model, in: Methods Comput. Phys.,
edited by: Chang, J., vol. 17, Academic Press, New York, NY,
USA, pp. 173–265, https://doi.org/10.1016/B978-0-12-460817-7.50009-4, 1977. a
Arnfield, A. J.: Two decades of urban climate research: A review of
turbulence, exchanges of energy and water, and the urban heat island, Int.
J. Climatol., 23, 1–26, https://doi.org/10.1002/joc.859, 2003. a
Arnold, S., ApSimon, H., Barlow, J. F., Belcher, S. E., Bell, M., Boddy, J.,
Britter, R., Cheng, H., Clark, R., and Colvile, R.: Introduction to the
DAPPLE Air Pollution Project, Sci. Total Environ., 332,
139–153, https://doi.org/10.1016/j.scitotenv.2004.04.020, 2004. a
Barlow, J. F.: Progress in observing and modelling the urban boundary layer,
Urban Clim., 10, 216–240, https://doi.org/10.1016/j.uclim.2014.03.011, 2014. a, b
Bartholomew, P., Deskos, G., Frantz, R. A., Schuch, F. N., Lamballais, E., and
Laizet, S.: Xcompact3D: An open-source framework for solving turbulence
problems on a Cartesian mesh, SoftwareX, 12, 100550,
https://doi.org/10.1016/j.softx.2020.100550, 2020. a
Blocken, B.: Computational Fluid Dynamics for urban physics: Importance,
scales, possibilities, limitations and ten tips and tricks towards accurate
and reliable simulations, Build. Environ., 91, 219–245,
https://doi.org/10.1016/j.buildenv.2015.02.015, 2015. a, b
Blocken, B., Roels, S., and Carmeliet, J.: A numerical study of wind nuisance
for a high-rise building group, in: Proceedings of the 2nd International
conference on Research in Building Physics, Leuven,
Belgium, 14–18 September 2003, edited by: Carmeliet, J., Hens, H., and Vermeir, G., pp. 981–990, https://doi.org/10.1201/9781003078852,
2003. a
Blocken, B., Stathopoulos, T., and van Beeck, J.: Pedestrian-level wind
conditions around buildings: Review of wind-tunnel and CFD techniques and
their accuracy for wind comfort assessment, Build. Environ., 100, 50–81, https://doi.org/10.1016/j.buildenv.2016.02.004, 2016. a
Bohnenstengel, S., Evans, S., Clark, P. A., and Belcher, S.: Simulations of the
London urban heat island, Q. J. Roy. Meteor.
Soc., 137, 1625–1640, 2011. a
Bolton, D.: The computation of equivalent potential temperature, Mon. Weather
Rev., 108, 1046–1053,
https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2, 1980. a
Borge, R., Santiago, J. L., de la Paz, D., Martín, F., Domingo, J., Valdés, C., Sánchez, B., Rivas, E., Rozas, M. T., Lázaro, S., Pérez, J., and Fernández, Á.: Application of a short term air quality action plan in Madrid (Spain) under a high-pollution episode-Part II: Assessment from multi-scale modelling, Sci. Total Environ., 635, 1574–1584, https://doi.org/10.1016/j.scitotenv.2018.04.323, 2018. a
Bozovic, R., Maksimovic, C., Mijic, A., Smith, K., Suter, I., and Van Reeuwijk,
M.: Blue Green Solutions. A Systems Approach to Sustainable and
Cost-effective Urban Development, Tech. Rep., Imperial College London,
https://doi.org/10.13140/RG.2.2.30628.07046, 2017. a
Cai, X.-M.: Effects of differential wall heating in street canyons on
dispersion and ventilation characteristics of a passive scalar, Atmos.
Environ., 51, 268–277, https://doi.org/10.1016/j.atmosenv.2012.01.010,
2012b. a
Carpentieri, M. and Robins, A. G.: Tracer Flux Balance at an Urban Canyon
Intersection, Bound.-Lay. Meteorol., 135, 229–242,
https://doi.org/10.1007/s10546-010-9471-6, 2010. a, b, c
Carpentieri, M., Robins, A. G., and Baldi, S.: Three-Dimensional Mapping of Air
Flow at an Urban Canyon Intersection, Bound.-Lay. Meteorol., 133,
277–296, https://doi.org/10.1007/s10546-009-9425-z, 2009. a, b
Carpentieri, M., Hayden, P., and Robins, A. G.: Wind tunnel measurements of
pollutant turbulent fluxes in urban intersections, Atmos. Environ.,
46, 669–674, https://doi.org/10.1016/j.atmosenv.2011.09.083, 2012. a, b
Castleton, H. F., Stovin, V., Beck, S. B. M., and Davison, J. B.: Green roofs;
building energy savings and the potential for retrofit, Energy Build., 42,
1582–1591, https://doi.org/10.1016/j.enbuild.2010.05.004, 2010. a
Caton, F., Britter, R. E., and Dalziel, S.: Dispersion mechanisms in a street
canyon, Atmos. Environ., 37, 693–702,
https://doi.org/10.1016/S1352-2310(02)00830-0, 2003. a, b
Cheng, H. and Robins, A. G.: Wind tunnel simulation of field tracer release in London, in: Fourth International Conference on Fluid Mechanics, Dalian, China, 28–31 July 2004, 2004. a
COST Action 732: Model evaluation guidance and protocol document, edited by: Britter, R. E. and Schatzmann, M., Tech. Rep.,
University of Hamburg, 28 pp., ISBN 3-00-018312-4, https://mi-pub.cen.uni-hamburg.de/fileadmin/files/forschung/techmet/cost/cost_732/pdf/GUIDANCE_AND_PROTOCOL_DOCUMENT_1-5-2007_www.pdf (last access: 8 June 2022), 2007. a
Ehrhard, J., Khatib, I. A., Winkler, C., Kunz, R., Moussiopoulos, N., and
Ernst, G.: The microscale model MIMO: development and assessment, J. Wind
Eng. Ind. Aerodyn., 85, 163–176, https://doi.org/10.1016/S0167-6105(99)00137-3, 2000. a
Emanuel, K. A.: Atmospheric convection, Oxford University Press on Demand, ISBN 9780195066302,
1994. a
Erdélyi, R., Wang, Y., Guo, W., Hanna, E., and Colantuono, G.:
Three-dimensional SOlar RAdiation Model (SORAM) and its application to 3-D
urban planning, Sol. Energy, 101, 63–73,
https://doi.org/10.1016/j.solener.2013.12.023, 2014. a
Erell, E., Pearlmutter, D., and Williamson, T.: Urban microclimate – Designing
the spaces between buildings, 1st edn., Routledge, ISBN 9781844074679, 2011. a
Garratt, J. R.: The atmospheric boundary layer, 1st edn., Cambridge Univeristy Press, 316 pp., ISBN 0521380529,
1992. a
Girard, P., Nadeau, D. F., Pardyjak, E. R., Overby, M., Willemsen, P., Stoll,
R., Bailey, B. N., and Parlange, M. B.: Evaluation of the QUIC-URB wind
solver and QESRadiant radiation-transfer model using a dense array of urban
meteorological observations, Urban Clim., 24, 657–674,
https://doi.org/10.1016/j.uclim.2017.08.006, 2017. a
Grimmond, C. S. B., Blackett, M., Best, M. J., Barlow, J., Baik, J. J.,
Belcher, S. E., and Bohnenstengel, S. I.: The International Urban Energy
Balance Models Comparison Project: First Results from Phase 1, J. Appl.
Meteor. Clim., 49, 1268–1292, https://doi.org/10.1175/2010JAMC2354.1, 2010. a, b
Grimmond, S.: Urbanization and global environmental change: local effects of
urban warming, Geogr. J., 173, 83–88,
https://doi.org/10.1111/j.1475-4959.2007.232_3.x, 2007. a
Grylls, T.: Simulating air pollution in the urban microclimate, PhD thesis,
Imperial College London, https://doi.org/10.25560/91884, 2020. a
Grylls, T. and van Reeuwijk, M.: Tree model with drag, transpiration, shading
and deposition: Identification of cooling regimes and large-eddy simulation,
Agr. Forest Meteorol., 298–299, 108288,
https://doi.org/10.1016/j.agrformet.2020.108288, 2021. a
Grylls, T., Le Cornec, C. M., Salizzoni, P., Soulhac, L., Stettler, M. E.,
and van Reeuwijk, M.: Evaluation of an operational air quality model using
large-eddy simulation, Atmos. Environ. X, 3, 100041,
https://doi.org/10.1016/j.aeaoa.2019.100041, 2019. a, b, c, d
Grylls, T., Suter, I., Sützl, B., Owens, S., Meyer, D., and van Reeuwijk, M.:
uDALES: large-eddy-simulation software for urban flow, dispersion, and
microclimate modelling, J. Open Source Softw., 6, 3055,
https://doi.org/10.21105/joss.03055, 2021a. a
Grylls, T., Suter, I., Sützl, B., Owens, S., Meyer, D., and van Reeuwijk, M.: uDALES: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.5111497, 2021b. a
Hanjalić, K. and Kenjereš, S.: Some developments in turbulence
modeling for wind and environmental engineering, J. Wind Eng.
Ind. Aerod., 96, 1537–1570, 2008. a
Heus, T., van Heerwaarden, C. C., Jonker, H. J. J., Pier Siebesma, A., Axelsen, S., van den Dries, K., Geoffroy, O., Moene, A. F., Pino, D., de Roode, S. R., and Vilà-Guerau de Arellano, J.: Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications, Geosci. Model Dev., 3, 415–444, https://doi.org/10.5194/gmd-3-415-2010, 2010. a, b, c, d, e, f
Hölling, M. and Herwig, H.: Asymptotic analysis of the near-wall region
of turbulent natural convection flows, J. Fluid Mech., 541, 383–397,
https://doi.org/10.1017/S0022112005006300, 2005. a
Hundsdorfer, W., Koren, B., vanLoon, M., and Verwer, J. G.: A positive finite-difference
advection scheme, J. Comput. Phys., 117, 35–46, https://doi.org/10.1006/jcph.1995.1042, 1995. a
Huttner, S.: Further development and application of the 3D microclimate
simulation ENVI-met, PhD thesis, Johannes Gutenberg-Universität
Mainz, https://doi.org/10.25358/openscience-2022, 2012. a
Isymov, N. and Davenport, A. G.: The ground level wind environment in built up
areas, in: Proceedings of the 4th International Conference on Wind Effects on
Buildings and Structures, edited by: Eaton, K. J., Heathrow, 1975, pp.
403–422, Cambridge University Press, ISBN 9780521208017, 1975. a
Järvi, L., Grimmond, C. S. B., and Christen, A.: The surface urban
energy and water balance scheme (SUEWS): Evaluation in Los Angeles and
Vancouver, J. Hydrol., 411, 219–237, https://doi.org/10.1016/j.jhydrol.2011.10.001,
2011. a
Jarvis, P. G.: The Interpretation of the Variations in Leaf Water Potential
and Stomatal Conductance Found in Canopies in the Field, Philos. Trans. R.
Soc. London B Biol. Sci., 273, 593–610, https://doi.org/10.1098/rstb.1976.0035, 1976. a
Kong, H., Choi, H., and Lee, J. S.: Direct numerical simulation of turbulent
thermal boundary layers, Phys. Fluids, 12, 2555–2568,
https://doi.org/10.1063/1.1287912, 2000. a
Kotthaus, S. and Grimmond, C. S. B.: Atmospheric boundary-layer characteristics
from ceilometer measurements. Part 2: Application to London's urban boundary
layer, Q. J. Roy. Meteorol. Soc., 144,
1511–1524, 2018. a
Krayenhoff, E. S. and Voogt, J.: A microscale three-dimensional urban energy
balance model for studying surface temperatures, Bound.-Lay. Meteorol.,
123, 433–461, https://doi.org/10.1007/s10546-006-9153-6, 2007. a, b
Krayenhoff, E. S., Christen, A., Martilli, A., and Oke, T. R.: A Multi-layer
Radiation Model for Urban Neighbourhoods with Trees, Bound.-Lay.
Meteorol., 151, 139–178, https://doi.org/10.1007/s10546-013-9883-1, 2014. a, b
Lawson, T. V. and Penwarden, A. D.: The effect of wind on people in the
vicinity of buildings, in: Proceedings of the 4th International Conference on
Wind Effects on Buildings and Structures, Heathrow, 1975, edited by: Eaton,
K. J., Cambridge University Press, ISBN 9780521208017, 1975. a
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The
contribution of outdoor air pollution sources to premature mortality on a
global scale, Nature, 525, 367–371,
https://doi.org/10.1038/nature15371, 2015. a, b
Li, N. and Laizet, S.: 2DECOMP&FFT – A Highly Scalable 2D Decomposition
Library and FFT Interface,
https://www.turbulencesimulation.com/uploads/5/8/7/2/58724623/2010_laizet_nag.pdf (last access: 8 June 2022), 2010. a
Lindberg, F., Holmer, B., and Thorsson, S.: SOLWEIG 1.0 – Modelling spatial
variations of 3D radiant fluxes and mean radiant temperature in complex urban
settings, Int. J. Biometeorol., 52, 697–713,
https://doi.org/10.1007/s00484-008-0162-7, 2008. a
Llaguno-Munitxa, M. and Bou-Zeid, E.: Shaping buildings to promote street
ventilation: A large-eddy simulation study, Urban Clim., 26, 76–94, 2018. a
Luc Int Panis, Steven Broekx, R. L.: Modelling instantaneous traffic emission
and the influence of traffic speed limits, Sci. Total Environ.,
371, 270–285, 2006. a
Macdonald, R. W., Griffiths, R. F., and Hall, D. J.: An improved method for the
estimation of surface roughness of obstacle arrays, Atmos. Environ.,
32, 1857–1864, https://doi.org/10.1016/S1352-2310(97)00403-2, 1998. a
Maronga, B., Banzhaf, S., Burmeister, C., Esch, T., Forkel, R., Fröhlich, D., Fuka, V., Gehrke, K. F., Geletič, J., Giersch, S., Gronemeier, T., Groß, G., Heldens, W., Hellsten, A., Hoffmann, F., Inagaki, A., Kadasch, E., Kanani-Sühring, F., Ketelsen, K., Khan, B. A., Knigge, C., Knoop, H., Krč, P., Kurppa, M., Maamari, H., Matzarakis, A., Mauder, M., Pallasch, M., Pavlik, D., Pfafferott, J., Resler, J., Rissmann, S., Russo, E., Salim, M., Schrempf, M., Schwenkel, J., Seckmeyer, G., Schubert, S., Sühring, M., von Tils, R., Vollmer, L., Ward, S., Witha, B., Wurps, H., Zeidler, J., and Raasch, S.: Overview of the PALM model system 6.0, Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, 2020. a
Masson, V.: A physically-based scheme for the urban energy budget in
atmospheric models, Bound.-Lay. Meteorol., 94, 357–397,
https://doi.org/10.1023/A:1002463829265, 2000. a
Matzarakis, A., Rutz, F., and Mayer, H.: Modelling radiation fluxes in simple
and complex environments: basics of the RayMan model, Int. J. Biometeorol.,
54, 131–139, https://doi.org/10.1007/s00484-006-0061-8, 2010. a
Mirzaei, P. A.: Recent challenges in modeling of urban heat island, Sustain.
Cities Soc., 19, 200–206, https://doi.org/10.1016/j.scs.2015.04.001, 2015. a
Mirzaei, P. A. and Haghighat, F.: Approaches to study urban heat island –
abilities and limitations, Build. Environ., 45, 2192–2201, 2010. a
Mittal, R. and Iaccarino, G.: Immersed Boundary Methods, Annu. Rev. Fluid
Mech., 37, 239–261, https://doi.org/10.1146/annurev.fluid.37.061903.175743, 2005. a
Monin, A. S. and Obukhov, A. M.: Basic laws of turbulent mixing in the surface
layer of the atmosphere, Contrib. Geophys. Inst. Acad. Sci. USSR, 24,
163–187, 1954. a
Moonen, P., Defraeye, T., Dorer, V., Blocken, B., and Carmeliet, J.: Urban
Physics: Effect of the micro-climate on comfort, health and energy demand,
Front. Archit. Res., 1, 197–228, https://doi.org/10.1016/j.foar.2012.05.002, 2012. a
Morris, C. W.: The anisotropy of diffuse solar radiation, PhD thesis,
Texas Tech University, http://hdl.handle.net/2346/9001 (last access: 8 June 2022), 1969. a
Murphy, D. M. and Koop, T.: Review of the vapour pressures of ice and
supercooled water for atmospheric applications, Q. J. Roy. Meteor. Soc.,
131, 1539–1565, https://doi.org/10.1256/qj.04.94, 2005. a
Musy, M., Malys, L., Morille, B., and Inard, C.: The use of SOLENE-microclimat
model to assess adaptation strategies at the district scale, Urban Clim.,
14, 213–223, https://doi.org/10.1016/j.uclim.2015.07.004, 2015. a
NOAA: Solar Position Calculator,
https://www.esrl.noaa.gov/gmd/grad/solcalc/azel.html (last access: 8 June 2022), 2018. a
Noilhan, J. and Planton, S.: A Simple Parameterization of Land Surface
Processes for Meteorological Models, Mon. Weather Rev., 117, 536–549,
https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989. a
Obukhov, A. M.: Turbulence in an atmosphere with inhomogeneous temperature,
Tr, Inst. Teor. Geofis. Akad. Nauk. SSSR, 1, 95–115, 1946. a
Oke, T. R.: The energetic basis of the urban heat island, Q. J. Roy. Meteor.
Soc., 108, 1–24, https://doi.org/10.1002/qj.49710845502, 1982. a
Oke, T. R., Mills, G., Christen, A., and Voogt, J. A.: Urban Climates, 1st edn.,
Cambridge University Press, ISBN 9780521849500, https://doi.org/10.1017/9781139016476, 2017. a, b, c, d
Peyret, R. and Taylor, T. D.: Computational methods for fluid flow, 1st edn., Springer
Science & Business Media, 358 pp., ISBN 9783642859526, https://doi.org/10.1007/978-3-642-85952-6, 1983. a
Pourquie, M., Breugem, W. P., and Boersma, B. J.: Some Issues Related to the
Use of Immersed Boundary Methods to Represent Square Obstacles, Int. J.
Multiscale Comput. Eng., 7, 509–522, https://doi.org/10.1615/IntJMultCompEng.v7.i6.30,
2009. a
PTV AG: PTV VISSIM 9 User Manual, PTV AG, 1084 pp., https://www.myptv.com/en/mobility-software/ptv-vissim (last access: 8 June 2022), 2017. a
Pyrgou, A. and Santamouris, M.: Increasing Probability of Heat-Related
Mortality in a Mediterranean City Due to Urban Warming, Int. J. Environ. Res.
Public Health, 15, 1571, https://doi.org/10.3390/ijerph15081571, 2018. a
Rao, V. R. and Sastri, V. M. K.: Efficient evaluation of diffuse view factors
for radiation, Int. J. Heat Mass Transf., 39, 1281–1286,
https://doi.org/10.1016/0017-9310(95)00203-0, 1996. a, b
Resler, J., Krč, P., Belda, M., Juruš, P., Benešová, N., Lopata, J., Vlček, O., Damašková, D., Eben, K., Derbek, P., Maronga, B., and Kanani-Sühring, F.: PALM-USM v1.0: A new urban surface model integrated into the PALM large-eddy simulation model, Geosci. Model Dev., 10, 3635–3659, https://doi.org/10.5194/gmd-10-3635-2017, 2017. a
Resler, J., Eben, K., Geletič, J., Krč, P., Rosecký, M., Sühring, M., Belda, M., Fuka, V., Halenka, T., Huszár, P., Karlický, J., Benešová, N., Ďoubalová, J., Honzáková, K., Keder, J., Nápravníková, Š., and Vlček, O.: Validation of the PALM model system 6.0 in a real urban environment: a case study in Dejvice, Prague, the Czech Republic, Geosci. Model Dev., 14, 4797–4842, https://doi.org/10.5194/gmd-14-4797-2021, 2021. a
Rizwan, A. M., Dennis, L. Y. C., and Liu, C.: A review on the generation,
determination and mitigation of Urban Heat Island, J. Environ. Sci., 20,
120–128, https://doi.org/10.1016/S1001-0742(08)60019-4, 2008. a
Rosenzweig, C., Solecki, W., Romero-Lankao, P., Mehrotra, S., Dhakal, S.,
Bowman, T., and Ibrahim, S. A.: ARC3.2 Summary for City Leaders – Climate Change and Cities: Second
Assessment Report of the Urban Climate Change Research Network, Tech. Rep., Urban
Climate Change Research Network (UCCRN), https://pubs.giss.nasa.gov/abs/ro02510w.html (last access: 8 June 2022), 2015. a
Salim, M. H., Schlünzen, K. H., Grawe, D., Boettcher, M., Gierisch, A. M. U., and Fock, B. H.: The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory, Geosci. Model Dev., 11, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018, 2018. a
Santamouris, M.: Cooling the cities – A review of reflective and green roof
mitigation technologies to fight heat island and improve comfort in urban
environments, Sol. Energy, 103, 682–703,
https://doi.org/10.1016/j.solener.2012.07.003, 2014. a
Schlünzen, K. H., Hinneburg, D., Knoth, O., Lambrecht, M., Leitl, B.,
Lopez, S., Lüpkes, C., Panskus, H., Renner, E., and Schatzmann, M.:
Flow and transport in the obstacle layer: First results of the micro-scale
model MITRAS, J. Atmos. Chem., 44, 113–130, 2003. a
Seneviratne, S., Zhang, X., Adnan, M., Badi, W., Dereczynski, C., Di Luca, A.,
Ghosh, S., Iskandar, I., Kossin, J., Lewis, S., Otto, F., Pinto, I., Satoh,
M., Vicente-Serrano, S., Wehner, M., and Zhou, B.: 2021: Weather and Climate
Extreme Events in a Changing Climate, in: Climate Change 2021: The Physical
Science Basis, Contribution of Working Group I to the Sixth Assessment Report
of the Intergovernmental Panel on Climate Change, Tech. Rep.,
Intergovernmental Panel on Climate Change, https://www.ipcc.ch/report/ar6/wg1/downloads/ (last access: 8 June 2022), 2021. a
Siegel, R. and Howell, J. R.: Thermal radiation heat transfer, 4th edn.,
Taylor and Francis-Hemisphere, Washington, ISBN 1560328398, 2001. a
Sievers, U.: Das kleinskalige Strömungsmodell MUKLIMO_3. Teil 2:
Thermodynamische Erweiterungen, Deutscher Wetterdienst, 151 pp., ISBN 9783881484909, https://www.dwd.de/DE/leistungen/pbfb_verlag_berichte/pdf_einzelbaende/248_pdf.html (last access: 8 June 2022), 2016. a
Sikkema, J. K., Ong, S.-K., and Alleman, J. E.: Photocatalytic concrete
pavements: Laboratory investigation of NO oxidation rate under varied
environmental conditions, Constr. Build. Mater., 100, 305–314,
2015. a
Smagorinsky, J.: General circulation experiments with the primitive
equations, Mon. Weather Rev., 91, 99–164,
https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
Stewart, J. B.: Modelling surface conductance of pine forest, Agric. For.
Meteorol., 43, 19–35, https://doi.org/10.1016/0168-1923(88)90003-2, 1988. a
Suter, I.: Simulating the impact of blue-green infrastructure on the
microclimate of urban areas, PhD thesis, Imperial College London, https://doi.org/10.25560/78715, 2019. a, b, c, d
Suter, I.: uDALES 1.0: a large-eddy-simulation model for urban environments, Zenodo [data set], https://doi.org/10.5281/zenodo.5480826, 2021. a
Suter, I., Maksimović, Č., and van Reeuwijk, M.: A
neighbourhood-scale estimate for the cooling potential of green roofs, Urban
Clim., 20, 33–45, https://doi.org/10.1016/j.uclim.2017.02.007, 2017. a
Suter, I., Grylls, T., Sützl, B., Owens, S., Meyer, D., and van Reeuwijk, M.: uDALES, Github [code], https://github.com/uDALES/u-dales, last access: 8 June 2022. a
Sützl, B. S., Rooney, G. G., and van Reeuwijk, M.: Drag Distribution in
Idealized Heterogeneous Urban Environments, Bound.-Lay. Meteorol., 178,
225–248, https://doi.org/10.1007/s10546-020-00567-0, 2021b. a, b
Swinbank, W. C.: Long-wave radiation from clear skies, Q. J. Roy. Meteor.
Soc., 89, 339–348, https://doi.org/10.1002/qj.49708938105, 1963. a
Tomas, J. M.: Obstacle-resolving large-eddy simulation of dispersion in urban
environments Effects of stability and roughness geometry, PhD thesis, TU
Delft, https://doi.org/10.4233/uuid:5d93a697-be49-4f63-b871-b763bc327139, 2016. a
Tomas, J. M., Pourquie, M. J. B. M., and Jonker, H. J. J.: Stable
Stratification Effects on Flow and Pollutant Dispersion in Boundary Layers
Entering a Generic Urban Environment, Bound.-Lay. Meteorol., 159,
221–239, https://doi.org/10.1007/s10546-015-0124-7, 2016. a
United Nations Framework Convention on Climate Change (UNFCCC): Report of the Conference of the Parties on its twenty-fifth session, held in Madrid from 2 to 15 December 2019; Addendum Part two: Action taken by the Conference of the Parties at its twenty-fifth session, Tech. Rep.,
United Nations Framework Convention on Climate Change, https://unfccc.int/documents/210471 (last access: 8 June 2022), 2020. a
United Nations Population Fund (UNFPA): State of World Population 2012, Tech. Rep., United Nations Population
Fund, 128 pp., ISBN 978-1-61800-009-5, https://www.unfpa.org/publications/state-world-population-2012 (last access: 8 June 2022), 2012. a
Uno, I., Cai, X. M., Steyn, D. G., and Emori, S.: A simple extension of the
Louis method for rough surface layer modelling, Bound.-Lay. Meteorol.,
76, 395–409, https://doi.org/10.1007/BF00709241, 1995. a, b
Van den Hurk, B., Viterbo, P., Beljaars, A. C. M., and Betts, A. K.: Offline
validation of the ERA40 surface scheme, 295, Tech. Rep., ECMWF, https://www.ecmwf.int/node/12900 (last access: 8 June 2022), 2000. a
Van Reeuwijk, M.: Efficient simulation of non-hydrostatic free-surface flow,
Master's thesis, TU Delft, Delft, http://resolver.tudelft.nl/uuid:be73f057-804a-41bf-9170-c577e2f14d83 (last access: 8 June 2022), 2002. a
Vreman, A. W.: An eddy-viscosity subgrid-scale model for turbulent shear flow:
Algebraic theory and applications, Phys. Fluids, 16, 3670–3681,
https://doi.org/10.1063/1.1785131, 2004. a
Walker, T., Xue, S.-C., and Barton, G. W.: Numerical determination of
radiative view factors using ray tracing, J. Heat Transfer, 132, 72702,
https://doi.org/10.1115/1.4000974, 2010. a
Wallace, J. M. and Hobbs, P. V.: Chapter 5 – Atmospheric Chemistry, in:
Atmospheric Science: An Introductory Survey, second edn., edited by: Wallace, J. M. and Hobbs,
P. V., Academic Press, San Diego, pp. 153–207, ISBN 9780127329512, 2006. a
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic Models
Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097,
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002. a
World Heath Organization: WHO global air quality guidelines: particulate
matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon
monoxide, Tech. Rep., WHO, ISBN 9789240034228, https://apps.who.int/iris/handle/10665/345329 (last access: 8 June 2022), 2021. a
Wu, L.: URBAN4: An Urban Canopy Layer Surface Energy Balance Climate Model,
PhD thesis, University of California, Los Angeles, Dissertation Abstracts International, Section: B, 56–11, 6009, 1995. a
Xie, Z.-T. and Castro, I. P.: Efficient Generation of Inflow Conditions for Large Eddy Simulation of Street-Scale Flows, Flow Turbul. Combust., 81,
449–470, https://doi.org/10.1007/s10494-008-9151-5, 2008. a
Xie, Z.-T. and Castro, I. P.: Large-eddy simulation for flow and dispersion in
urban streets, Atmos. Environ., 43, 2174–2185,
https://doi.org/10.1016/j.atmosenv.2009.01.016, 2009. a, b
Yaghoobian, N. and Kleissl, J.: Effect of reflective pavements on building
energy use, Urban Clim., 2, 25–42, https://doi.org/10.1016/j.uclim.2012.09.002, 2012. a
Zhong, J., Cai, X.-M., and Bloss, W. J.: Large eddy simulation of reactive
pollutants in a deep urban street canyon: Coupling dynamics with O3-NOx-VOC
chemistry, Environ. Pollut., 224, 171–184, 2017. a
Short summary
Cities are increasingly moving to the fore of climate and air quality research due to their central role in the population’s health and well-being, while suitable models remain scarce. This article describes the development of a new urban LES model, which allows examining the effects of various processes, infrastructure and vegetation on the local climate and air quality. Possible applications are demonstrated and a comparison to an experiment is shown.
Cities are increasingly moving to the fore of climate and air quality research due to their...
