Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5609-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-13-5609-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
18 Nov 2020
Development and technical paper |
| 18 Nov 2020
| 18 Nov 2020
Multi-layer coupling between SURFEX-TEB-v9.0 and Meso-NH-v5.3 for modelling the urban climate of high-rise cities
Robert Schoetter
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, 42 avenue Gaspard Coriolis, 31057, CEDEX 1, Toulouse, France
Yu Ting Kwok
School of Architecture, The Chinese University of Hong Kong, Hong Kong, China
Cécile de Munck
CNRM, Université de Toulouse, Météo-France, CNRS, 42 avenue Gaspard Coriolis, 31057, CEDEX 1, Toulouse, France
Kevin Ka Lun Lau
Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong, China
Wai Kin Wong
Hong Kong Observatory, Hong Kong, China
Valéry Masson
CNRM, Université de Toulouse, Météo-France, CNRS, 42 avenue Gaspard Coriolis, 31057, CEDEX 1, Toulouse, France
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Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Robert Schoetter, Valéry Masson, Alexis Bourgeois, Margot Pellegrino, and Jean-Pierre Lévy
Geosci. Model Dev., 10, 2801–2831, https://doi.org/10.5194/gmd-10-2801-2017, https://doi.org/10.5194/gmd-10-2801-2017, 2017
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We enhance the urban climate model TEB to take into account for the variety of building use and human behaviour related to building energy consumption. This can improve urban climate simulations and is crucial for quantification of the impact of climate change mitigation and adaptation measures in urban areas (e.g. white roofs, insulation of buildings). An evaluation for Toulouse shows that the enhanced version of TEB captures well the spatio-temporal variability of building energy consumption.
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Wind Energ. Sci., 9, 97–117, https://doi.org/10.5194/wes-9-97-2024, https://doi.org/10.5194/wes-9-97-2024, 2024
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Erwan Jézéquel, Frédéric Blondel, and Valéry Masson
Wind Energ. Sci., 9, 119–139, https://doi.org/10.5194/wes-9-119-2024, https://doi.org/10.5194/wes-9-119-2024, 2024
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Analytical models allow us to quickly compute the decreased power output and lifetime induced by wakes in a wind farm. This is achieved by evaluating the modified velocity and turbulence in the wake. In this work, we present a new model based on the velocity and turbulence breakdowns presented in Part 1. This new model is physically based, allows us to compute the whole turbulence profile (rather than the maximum value) and is built to take atmospheric stability into account.
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EGUsphere, https://doi.org/10.5194/egusphere-2023-928, https://doi.org/10.5194/egusphere-2023-928, 2023
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Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
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We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Jérémy Bernard, Erwan Bocher, Elisabeth Le Saux Wiederhold, François Leconte, and Valéry Masson
Geosci. Model Dev., 15, 7505–7532, https://doi.org/10.5194/gmd-15-7505-2022, https://doi.org/10.5194/gmd-15-7505-2022, 2022
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OpenStreetMap is a collaborative project aimed at creaing a free dataset containing topographical information. Since these data are available worldwide, they can be used as standard data for geoscience studies. However, most buildings miss the height information that constitutes key data for numerous fields (urban climate, noise propagation, air pollution). In this work, the building height is estimated using statistical modeling using indicators that characterize the building's environment.
Emilie Redon, Aude Lemonsu, and Valéry Masson
Geosci. Model Dev., 13, 385–399, https://doi.org/10.5194/gmd-13-385-2020, https://doi.org/10.5194/gmd-13-385-2020, 2020
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The TEB urban climate model simulates micrometeorological conditions from the neighborhood scale to the entire city. It has recently been improved to more realistically address the radiative effects of trees within the urban canopy. This article presents additional developments that have been made to better represent the effect of trees on heat and moisture exchange, as well as on air flow in the streets, and on thermal comfort.
Franck Auguste, Géraldine Réa, Roberto Paoli, Christine Lac, Valery Masson, and Daniel Cariolle
Geosci. Model Dev., 12, 2607–2633, https://doi.org/10.5194/gmd-12-2607-2019, https://doi.org/10.5194/gmd-12-2607-2019, 2019
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The numerical implementation of an immersed boundary method in the atmospheric solver Meso-NH is presented. This technique models fluid–solid interaction and allows for the simulation of urban flows by considering buildings to be part of the resolved scales. This study constitutes a first robust step towards a better understanding of the interactions between weather and cities and better predictions of such interactions.
Xenia Stavropulos-Laffaille, Katia Chancibault, Jean-Marc Brun, Aude Lemonsu, Valéry Masson, Aaron Boone, and Hervé Andrieu
Geosci. Model Dev., 11, 4175–4194, https://doi.org/10.5194/gmd-11-4175-2018, https://doi.org/10.5194/gmd-11-4175-2018, 2018
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Integrating vegetation in urban planning is promoted to counter steer potential impacts of climate and demographic changes. Assessing the multiple benefits of such strategies on the urban microclimate requires a detailed coupling of both the water and energy transfers in numerical tools. In this respect, the representation of water-related processes in the urban subsoil of the existing model TEB-Veg has been improved. The new model thus allows a better evaluation of urban adaptation strategies.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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Jeanne Colin, Christine Lac, Valéry Massion, and Alexandre Paci
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-226, https://doi.org/10.5194/gmd-2017-226, 2017
Preprint withdrawn
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The meteorological model Meso-NH is adapted in order to be run in DNS mode (Direct Numerical Simulation) to represent atmospheric flows generated in laboratory. The implementations we performed are validated against exact solutions and experimental data. Thus, Meso-NH can now be used as a complement to laboratory experiments, to complete and/or extend the data. The ability to run it in DNS also brings new prospects as it offers a new framework to test parametrizations of fine-scale processes.
Marie Mazoyer, Christine Lac, Odile Thouron, Thierry Bergot, Valery Masson, and Luc Musson-Genon
Atmos. Chem. Phys., 17, 13017–13035, https://doi.org/10.5194/acp-17-13017-2017, https://doi.org/10.5194/acp-17-13017-2017, 2017
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Large eddy simulations of a radiation fog event occurring during the ParisFog experiment have been studied to analyze the impact of the dynamics on the fog life cycle. They included a sophisticated microphysical scheme, the drag effect of a trees barrier and deposition on vegetation. The blocking effect of the trees induces elevated fog formation and limits cooling and cloud water production. The deposition process was found to exert the most significant impact on the fog prediction.
Robert Schoetter, Valéry Masson, Alexis Bourgeois, Margot Pellegrino, and Jean-Pierre Lévy
Geosci. Model Dev., 10, 2801–2831, https://doi.org/10.5194/gmd-10-2801-2017, https://doi.org/10.5194/gmd-10-2801-2017, 2017
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We enhance the urban climate model TEB to take into account for the variety of building use and human behaviour related to building energy consumption. This can improve urban climate simulations and is crucial for quantification of the impact of climate change mitigation and adaptation measures in urban areas (e.g. white roofs, insulation of buildings). An evaluation for Toulouse shows that the enhanced version of TEB captures well the spatio-temporal variability of building energy consumption.
Emilie C. Redon, Aude Lemonsu, Valéry Masson, Benjamin Morille, and Marjorie Musy
Geosci. Model Dev., 10, 385–411, https://doi.org/10.5194/gmd-10-385-2017, https://doi.org/10.5194/gmd-10-385-2017, 2017
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In order to assess the potential of cooling of urban vegetation in cities, we need to refine some processes in the microclimate models running on cities as the TEB model. The shading effects of trees on roads, low vegetation (grass), or walls are key processes impacting both air and surface temperatures in the streets by reducing them and improving the thermal comfort of inhabitants. They have been implemented into the TEB model and simulations have been evaluated by a fine-scale model, SOLENE.
C. S. de Munck, A. Lemonsu, R. Bouzouidja, V. Masson, and R. Claverie
Geosci. Model Dev., 6, 1941–1960, https://doi.org/10.5194/gmd-6-1941-2013, https://doi.org/10.5194/gmd-6-1941-2013, 2013
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, 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.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 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 emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Cited articles
Aflaki, A., Mirnezhad, M., Ghaffarianhoseini, A., Ghaffarianhoseini, A.,
Omrany, H., Wang, Z.-H., and Akbari, H.: Urban heat island mitigation
strategies: A state-of-the-art review on Kuala Lumpur, Singapore and Hong
Kong, Cities, 62, 13–145,
https://doi.org/10.1016/j.cities.2016.09.003, 2017. a
AOD: TERRA/MODIS Aerosol Optical Thickness, available at:
https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_AER_OD,
last access: 4 September 2020. 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
Aumond, P., Masson, V., Lac, C., Gauvreau, B., Dupont, S., and Berengier, M.:
Including the Drag Effects of Canopies: Real Case Large-Eddy Simulation
Studies, Bound.-Lay. Meteorol., 146, 65–80,
https://doi.org/10.1007/s10546-012-9758-x, 2013. a
Barlow, J., Best, M., Bohnenstengel, S. I., Clark, P., Grimmond, S., Lean, H.,
Christen, A., Emeis, S., Haeffelin, M., Harman, I. N., Lemonsu, A., Martilli,
A., Pardyjak, E., Rotach, M. W., Ballard, S., Boutle, I., Brown, A., Cai, X.,
Carpentieri, M., Coceal, O., Crawford, B., Di Sabatino, S., Dou, J., Drew,
D. R., Edwards, J. M., Fallmann, J., Fortuniak, K., Gornall, J., Gronemeier,
T., Halios, C. H., Hertwig, D., Hirano, K., Holtslag, A. A. M., Luo, Z.,
Mills, G., Nakayoshi, M., Pain, K., Schlünzen, K. H., Smith, S., Soulhac,
L., Steeneveld, G.-J., Sun, T., Theeuwes, N. E., Thomson, D., Voogt, J. A.,
Ward, H. C., Xie, Z.-T., and Zhong, J.: Developing a Research Strategy to
Better Understand, Observe, and Simulate Urban Atmospheric Processes at
Kilometer to Subkilometer Scales, B. Am. Meteorol. Soc., 98, ES261–ES264, https://doi.org/10.1175/BAMS-D-17-0106.1, 2017. a
Best, M. J., Beljaars, A., Polcher, J., and Viterbo, P.: A Proposed Structure
for Coupling Tiled Surfaces with the Planetary Boundary Layer, J.
Hydrometeorol., 5, 1271–1278, https://doi.org/10.1175/JHM-382.1, 2004. a
Bougeault, P. and Lacarrère, P.: Parameterization of orographic
induced turbulence in a mesobeta scale model, Mon. Weather Rev., 117,
1872–1890, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2, 1989. a, b, c
Bueno, B., Pigeon, G., Norford, L. K., Zibouche, K., and Marchadier, C.: Development and evaluation of a building energy model integrated in the TEB scheme, Geosci. Model Dev., 5, 433–448, https://doi.org/10.5194/gmd-5-433-2012, 2012. a
Champeaux, J. L., Masson, V., and Chauvin, F.: ECOCLIMAP: a global database
of land surface parameters at 1 km resolution, Meteorol. Appl.,
12, 29–32, https://doi.org/10.1017/S1350482705001519, 2005. a
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface–Hydrology Model
with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation
and Sensitivity, Mon. Weather Rev., 129, 569–585,
https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a, b
Chen, F., Kusaka, H., Bornstein, R., Ching, J., Grimmond, C. S. B.,
Grossman-Clarke, S., Loridan, T., Manning, K. W., Martilli, A., Miao, S.,
Sailor, D., Salamanca, F. P., Taha, H., Tewari, M., Wang, X., Wyszogrodzki,
A. A., and Zhang, C.: The integrated WRF/urban modelling system: development,
evaluation, and applications to urban environmental problems, Int.
J. Climatol., 31, 273–288, https://doi.org/10.1002/joc.2158, 2011. a, b
Chin, H.-N. S., Leach, M. J., Sugiyama, G. A., Leone, J. M., Walker, H.,
Nasstrom, J. S., and Brown, M. J.: Evaluation of an Urban Canopy
Parameterization in a Mesoscale Model Using VTMX and URBAN 2000 Data, Mon.
Weather Rev., 133, 2043–2068, https://doi.org/10.1175/MWR2962.1, 2005. a
Ching, J., Mills, G., Bechtel, B., See, L., Feddema, J., Wang, X., Ren, C.,
Brousse, O., Martilli, A., Neophytou, M., Mouzourides, P., Stewart, I.,
Hanna, A., Ng, E., Foley, M., Alexander, P., Aliaga, D., Niyogi, D.,
Shreevastava, A., Bhalachandran, P., Masson, V., Hidalgo, J., Fung, J.,
Andrade, M., Baklanov, A., Dai, W., Milcinski, G., Demuzere, M., Brunsell,
N., Pesaresi, M., Miao, S., Mu, Q., Chen, F., and Theeuwes, N.: WUDAPT: An
Urban Weather, Climate, and Environmental Modeling Infrastructure for the
Anthropocene, B. Am. Meteorol. Soc., 99,
1907–1924, https://doi.org/10.1175/BAMS-D-16-0236.1, 2018. a
Deardorff, J. W.: Stratocumulus-capped mixed layers derived from a
three-dimensional model, Bound.-Lay. Meteorol, 18, 495–527,
https://doi.org/10.1007/BF00119502, 1980. a, b
Garuma, G. F.: Review of urban surface parameterizations for numerical climate models, Urban Climate, 24, 830–851,
https://doi.org/10.1016/j.uclim.2017.10.006, 2018. a
Giorgi, F. and Avissar, R.: Representation of heterogeneity effects in Earth
system modeling: Experience from land surface modeling, Rev.
Geophys., 35, 413–437, https://doi.org/10.1029/97RG01754, 1997. a
Guo, Z., Dirmeyer, P. A., Koster, R. D., Sud, Y. C., Bonan, G., Oleson, K. W.,
Chan, E., Verseghy, D., Cox, P., Gordon, C. T., McGregor, J. L., Kanae, S.,
Kowalczyk, E., Lawrence, D., Liu, P., Mocko, D., Lu, C.-H., Mitchell, K.,
Malyshev, S., McAvaney, B., Oki, T., Yamada, T., Pitman, A., Taylor, C. M.,
Vasic, R., and Xue, Y.: GLACE: The Global Land–Atmosphere Coupling
Experiment. Part II: Analysis, J. Hydrometeorol., 7, 611–625,
https://doi.org/10.1175/JHM511.1, 2006. a
Gutiérrez, E., Martilli, A., Santiago, J. L., and González, J. E.: A
Mechanical Drag Coefficient Formulation and Urban Canopy Parameter
Assimilation Technique for Complex Urban Environments, Bound.-Lay.
Meteorol., 157, 333–341, https://doi.org/10.1007/s10546-015-0051-7, 2015. a, b
HKCensus: https://www.censtatd.gov.hk/hkstat/sub/sp90.jsp (last access: 30 June 2020), 2018. a
HKO (Hong Kong Observatory): available at:
https://www.hko.gov.hk/en/Observatorys-Blog/101818/Will-2018-be-as-dry-as-1963
(last access: 30 June 2020), 2018. a
HKO (Hong Kong Observatory): available at: https://www.hko.gov.hk/en/cis/popup.htm (last access: 30 June 2020), 2020. a
Hogan, R. J.: An Exponential Model of Urban Geometry for Use in Radiative
Transfer Applications, Bound.-Lay. Meteorol., 170,
357–372, https://doi.org/10.1007/s10546-018-0409-8,
2019a. a, b
Hogan, R. J.: Flexible Treatment of Radiative Transfer in Complex Urban
Canopies for Use in Weather and Climate Models, Bound.-Lay. Meteorol.,
173, 1–26, https://doi.org/10.1007/s10546-019-00457-0, 2019b. a, b
Kain, J. S. and Fritsch, J. M.: A One-Dimensional Entraining/Detraining Plume
Model and Its Application in Convective Parameterization, J. Atmos. Sci., 47, 2784–2802,
https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2, 1990. a
Kondo, H. and Liu, F.: Study on the urban thermal environment obtained through one-dimensional urban canopy model, Taiki Kankyo Gakkaishi, 33, 179–192, https://doi.org/10.11298/taiki1995.33.3_179, 1998. a
Koster, R. D., Sud, Y. C., Guo, Z., Dirmeyer, P. A., Bonan, G., Oleson, K. W.,
Chan, E., Verseghy, D., Cox, P., Davies, H., Kowalczyk, E., Gordon, C. T.,
Kanae, S., Lawrence, D., Liu, P., Mocko, D., Lu, C.-H., Mitchell, K.,
Malyshev, S., McAvaney, B., Oki, T., Yamada, T., Pitman, A., Taylor, C. M.,
Vasic, R., and Xue, Y.: GLACE: The Global Land–Atmosphere Coupling
Experiment. Part I: Overview, J. Hydrometeorol., 7, 590–610,
https://doi.org/10.1175/JHM510.1, 2006. a
Krayenhoff, E. S., Jiang, T., Christen, A., Martilli, A., Oke, T. R., Bailey,
B. N., Nazarian, N., Voogt, J. A., Giometto, M. G., Stastny, A., and
Crawford, B. R.: A multi-layer urban canopy meteorological model with trees
(BEP-Tree): Street tree impacts on pedestrian-level climate, Urban Climate,
32, 100590, https://doi.org/10.1016/j.uclim.2020.100590, 2020 a
Kusaka, H., Kondo, H., Kikegawa, Y., and Kimura, F.: A Simple Single-Layer
Urban Canopy Model For Atmospheric Models: Comparison With Multi-Layer And
Slab Models, Bound.-Lay. Meteorol., 101, 329–358,
https://doi.org/10.1023/A:1019207923078, 2001. a, b
Kwok, Y. T., De Munck, C., Schoetter, R., Ren, C., and Lau, K. K.-L.: Refined
dataset to describe the complex urban environment of Hong Kong for urban
climate modelling studies at the mesoscale, Theor. Appl.
Climatol., 142, 129–150,
https://doi.org/10.1007/s00704-020-03298-x, 2020. a, b
Lac, C., Chaboureau, J.-P., Masson, V., Pinty, J.-P., Tulet, P., Escobar, J., Leriche, M., Barthe, C., Aouizerats, B., Augros, C., Aumond, P., Auguste, F., Bechtold, P., Berthet, S., Bielli, S., Bosseur, F., Caumont, O., Cohard, J.-M., Colin, J., Couvreux, F., Cuxart, J., Delautier, G., Dauhut, T., Ducrocq, V., Filippi, J.-B., Gazen, D., Geoffroy, O., Gheusi, F., Honnert, R., Lafore, J.-P., Lebeaupin Brossier, C., Libois, Q., Lunet, T., Mari, C., Maric, T., Mascart, P., Mogé, M., Molinié, G., Nuissier, O., Pantillon, F., Peyrillé, P., Pergaud, J., Perraud, E., Pianezze, J., Redelsperger, J.-L., Ricard, D., Richard, E., Riette, S., Rodier, Q., Schoetter, R., Seyfried, L., Stein, J., Suhre, K., Taufour, M., Thouron, O., Turner, S., Verrelle, A., Vié, B., Visentin, F., Vionnet, V., and Wautelet, P.: Overview of the Meso-NH model version 5.4 and its applications, Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, 2018. a, b
Lafore, J. P., Stein, J., Asencio, N., Bougeault, P., Ducrocq, V., Duron, J., Fischer, C., Héreil, P., Mascart, P., Masson, V., Pinty, J. P., Redelsperger, J. L., Richard, E., and Vilà-Guerau de Arellano, J.: The Meso-NH Atmospheric Simulation System. Part I: adiabatic formulation and control simulations, Ann. Geophys., 16, 90–109, https://doi.org/10.1007/s00585-997-0090-6, 1998. a, b
Lam, J., Lau, A., and Fung, J.: Application of Refined Land-Use Categories for
High Resolution Mesoscale Atmospheric Modelling, Bound.-Lay. Meteorol.,
119, 263–288, https://doi.org/10.1007/s10546-005-9027-3, 2006. a, b, c
Lemonsu, A., Masson, V., Shashua-Bar, L., Erell, E., and Pearlmutter, D.: Inclusion of vegetation in the Town Energy Balance model for modelling urban green areas, Geosci. Model Dev., 5, 1377–1393, https://doi.org/10.5194/gmd-5-1377-2012, 2012. a, b
Lin, W., Sui, C.-H., Yang, L., Wang, X., Deng, R., Fan, S., Wu, C., Wang, A.,
Fong, S., and Lin, H.: A numerical study of the influence of urban expansion
on monthly climate in dry autumn over the Pearl River Delta, China,
Theor. Appl. Climatol., 89, 63–72,
https://doi.org/10.1007/s00704-006-0244-6, 2007. a
Lin, W., Zhang, L., Du, D., Yang, L., Lin, H., Zhang, Y., and Li, J.:
Quantification of land use/land cover changes in Pearl River Delta and its
impact on regional climate in summer using numerical modeling, Reg.
Environ. Change, 9, 75–82, https://doi.org/10.1007/s10113-008-0057-5, 2009. a
Lo, J. C. F., Lau, A. K. H., Chen, F., Fung, J. C. H., and Leung, K. K. M.:
Urban Modification in a Mesoscale Model and the Effects on the Local
Circulation in the Pearl River Delta Region, J. Appl. Meteorol. Clim., 46, 457–476, https://doi.org/10.1175/JAM2477.1, 2007. a, b, c, d
Luo, M. and Lau, N.-C.: Heat Waves in Southern China: Synoptic Behavior,
Long-Term Change, and Urbanization Effects, J. Climate, 30, 703–720, https://doi.org/10.1175/JCLI-D-16-0269.1, 2017. 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, b
Masson, V.: Urban surface modeling and the meso-scale impact of cities,
Theor. Appl. Climatol., 84, 35–45,
https://doi.org/10.1007/s00704-005-0142-3,2006. a, b
Masson, V. and Seity, Y.: Including Atmospheric Layers in Vegetation and Urban
Offline Surface Schemes, J. Appl. Meteorol. Clim., 48,
1377–1397, https://doi.org/10.1175/2009JAMC1866.1, 2009. a
Masson, V., Champeaux, J.-L., Chauvin, F., Meriguet, C., and Lacaze, R.: A
Global Database of Land Surface Parameters at 1-km Resolution in
Meteorological and Climate Models, J. Climate, 16, 1261–1282,
https://doi.org/10.1175/1520-0442-16.9.1261, 2003. a
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013. a, b
Masson, V., Heldens, W., Bocher, E., Bonhomme, M., Bucher, B., Burmeister, C.,
de Munck, C., Esch, T., Hidalgo, J., Kanani-Sühring, F., Kwok, Y.-T.,
Lemonsu, A., Lévy, J.-P., Maronga, B., Pavlik, D., Petit, G., See, L.,
Schoetter, R., Tornay, N., Votsis, A., and Zeidler, J.: City-descriptive
input data for urban climate models: Model requirements, data sources and
challenges, Urban Climate, 31, 100536, https://doi.org/10.1016/j.uclim.2019.100536,
2020. 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,
Frontiers of Architectural Research, 1, 197–228,
https://doi.org/10.1016/j.foar.2012.05.002, 2012. a
Ng, Y. Y., Wong, K. S., Ho, B., Yau, R., Tse, T., and Ren, C.: Final Report and
Appendices, Urban Climatic Map and Standards for Wind Environment –
Feasibility Study, Technical Report for Planning Department HKSAR, p. 1685,
2012. 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
Oleson, K. W., Bonan, G. B., Feddema, J., Vertenstein, M., and Grimmond, C.
S. B.: An Urban Parameterization for a Global Climate Model. Part I:
Formulation and Evaluation for Two Cities, J. Appl. Meteorol. Clim., 47, 1038–1060, https://doi.org/10.1175/2007JAMC1597.1, 2008. a
Oleson, K. W., Lawrence, D. M., B, G., Flanner, M. G., Kluzek, E., J, P.,
Levis, S., Swenson, S. C., Thornton, E., Feddema, J., Heald, C. L., Francois Lamarque, J., Yue Niu, G., Qian, T., Running, S., Sakaguchi, K., Yang, L.,
Zeng, X., Zeng, X., and Decker, M.: Technical Description of version 4.0 of
the Community Land Model (CLM), University Corporation for Atmospheric Research, 257 pp., https://doi.org/10.5065/D6FB50WZ,
2010. a
Pergaud, J., Masson, V., Malardel, S., and Couvreux, F.: A Parameterization of
Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction,
Bound.-Lay. Meteorol., 132, 83, https://doi.org/10.1007/s10546-009-9388-0, 2009. a, b, c
Pigeon, G., Zibouche, K., Bueno, B., Bras, J. L., and Masson, V.: Improving the
capabilities of the Town Energy Balance model with up-to-date building
energy simulation algorithms: an application to a set of representative
buildings in Paris, Energ. Buildings, 76, 1–14,
https://doi.org/10.1016/j.enbuild.2013.10.038, 2014. a
Raupach, R.: Drag and drag partition on rough surfaces, Bound.-Lay.
Meteorol., 60, 375–395, https://doi.org/10.1007/BF00155203, 1992. a, b
Redon, E., Lemonsu, A., and Masson, V.: An urban trees parameterization for modeling microclimatic variables and thermal comfort conditions at street level with the Town Energy Balance model (TEB-SURFEX v8.0), Geosci. Model Dev., 13, 385–399, https://doi.org/10.5194/gmd-13-385-2020, 2020. a
Roth, M.: Review of atmospheric turbulence over cities, Q. J. Roy. Meteor. Soc., 126, 941–990,
https://doi.org/10.1002/qj.49712656409, 2000. a
Sailor, D. J.: A review of methods for estimating anthropogenic heat and
moisture emissions in the urban environment, Int. J.
Climatol., 31, 189–199, https://doi.org/10.1002/joc.2106, 2011. a
Salamanca, F., Krpo, A., Martilli, A., and Clappier, A.: A new building energy
model coupled with an urban canopy parameterization for urban climate
simulations – part I. formulation, verification, and sensitivity analysis of
the model, Theor. Appl. Climatol., 99, 331,
https://doi.org/10.1007/s00704-009-0142-9, 2009 a
Salgado, R. and Le Moigne, P.: Coupling of the FLake model to the Surfex
externalized surface model, Boreal Environ. Res., 15, 231–244,
2010. a
Santiago, J. and Martilli, A.: A Dynamic Urban Canopy Parameterization for
Mesoscale Models Based on Computational Fluid Dynamics Reynolds-Averaged
Navier–Stokes Microscale Simulations, Bound.-Lay. Meteorol., 137,
417–439, https://doi.org/10.1007/s10546-010-9538-4, 2010. a, b, c, d, e, f, g, h, i, j
Santiago, J., Coceal, O., and Martilli, A.: How to Parametrize Urban-Canopy
Drag to Reproduce Wind-Direction Effects Within the Canopy, Bound.-Lay.
Meteorol., 149, 43–63, https://doi.org/10.1007/s10546-013-9833-y, 2013. a
Santiago, J., Krayenhoff, E., and Martilli, A.: Flow simulations for simplified
urban configurations with microscale distributions of surface thermal
forcing, Urban Climate, 9, 115–133,
https://doi.org/10.1016/j.uclim.2014.07.008, 2014. a
Santiago, J.-L., Buccolieri, R., Rivas, E., Calvete-Sogo, H., Sanchez, B.,
Martilli, A., Alonso, R., Elustondo, D., Santamaría, J. M., and Martin, F.:
CFD modelling of vegetation barrier effects on the reduction of
traffic-related pollutant concentration in an avenue of Pamplona, Spain,
Sustain. Cities Soc., 48, 101559,
https://doi.org/10.1016/j.scs.2019.101559, 2019. a
Schoetter, R., Kwok, Y. T., de Munck, C., Lau, K. K. L., Wong, W. K., and Masson, V.: Overview of the source code modifications, numerical simulations, and postprocessing scripts described in the research article “Multi-layer coupling between SURFEX-TEB-v9.0 and Meso-NH-v5.3 for modelling the urban climate of high-rise cities”, Zenodo, available at: https://zenodo.org/record/3937222#.X64kiVDTWUk, 2020. a
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F.,
Lac, C., and Masson, V.: The AROME-France Convective-Scale Operational
Model, Mon. Weather Rev., 139, 976–991, https://doi.org/10.1175/2010MWR3425.1, 2011. a
Shepherd, J. M.: A Review of Current Investigations of Urban-Induced Rainfall
and Recommendations for the Future, Earth Interact., 9, 1–27,
https://doi.org/10.1175/EI156.1, 2005. a
Simón-Moral, A., Santiago, J., Krayenhoff, E., and Martilli, A.: Streamwise
Versus Spanwise Spacing of Obstacle Arrays: Parametrization of the Effects on
Drag and Turbulence, Bound.-Lay. Meteorol., 151, 579–596,
https://doi.org/10.1007/s10546-013-9901-3, 2014. a
Simón-Moral, A., Santiago, J., and Martilli, A.: Effects of Unstable Thermal
Stratification on Vertical Fluxes of Heat and Momentum in Urban Areas,
Bound.-Lay. Meteorol., 163, 103–121, https://doi.org/10.1007/s10546-016-0211-4, 2017. a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A Description of the
Advanced Research WRF Version 3, Tech. rep., National Center for Atmospheric
Research Boulder, Colorado, USA, 2008. a
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A., Colin,
J., Decharme, B., Delire, C., Berthet, S., Chevallier, M., Sénési, S.,
Franchisteguy, L., Vial, J., Mallet, M., Joetzjer, E., Geoffroy, O.,
Guérémy, J.-F., Moine, M.-P., Msadek, R., Ribes, A., Rocher, M., Roehrig,
R., Salas-y Mélia, D., Sanchez, E., Terray, L., Valcke, S., Waldman, R.,
Aumont, O., Bopp, L., Deshayes, J., Éthé, C., and Madec, G.: Evaluation of
CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in
Present-Day and Future Climate, J. Adv. Model. Earth
Sy., 11, 4182–4227, https://doi.org/10.1029/2019MS001791, 2019. a
Termonia, P., Fischer, C., Bazile, E., Bouyssel, F., Brožková, R., Bénard, P., Bochenek, B., Degrauwe, D., Derková, M., El Khatib, R., Hamdi, R., Mašek, J., Pottier, P., Pristov, N., Seity, Y., Smolíková, P., Španiel, O., Tudor, M., Wang, Y., Wittmann, C., and Joly, A.: The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1, Geosci. Model Dev., 11, 257–281, https://doi.org/10.5194/gmd-11-257-2018, 2018. a
Trusilova, K., Schubert, S., Wouters, H., Früh, B., Grossman-Clarke, S.,
Demuzere, M., and Becker, P.: The urban land use in the COSMO-CLM model: a
comparison of three parameterizations for Berlin, Meteorol.
Z., 25, 231–244, https://doi.org/10.1127/metz/2015/0587, 2016. a
Unger, J.: Urban-rural air humidity differences in Szeged, Hungary,
Int. J. Climatol., 19, 1509–1515, 1999. a
Uno, I., Ueda, H., and Wakamatsu, S.: Numerical modeling of the nocturnal urban
boundary layer, Bound.-Lay. Meteorol., 49, 77–98,
https://doi.org/10.1007/BF00116406, 1989. a
Voldoire, A., Decharme, B., Pianezze, J., Lebeaupin Brossier, C., Sevault, F., Seyfried, L., Garnier, V., Bielli, S., Valcke, S., Alias, A., Accensi, M., Ardhuin, F., Bouin, M.-N., Ducrocq, V., Faroux, S., Giordani, H., Léger, F., Marsaleix, P., Rainaud, R., Redelsperger, J.-L., Richard, E., and Riette, S.: SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales, Geosci. Model Dev., 10, 4207–4227, https://doi.org/10.5194/gmd-10-4207-2017, 2017. a
Vu, C. T., Asaeda, T., and Ashie, Y.: Development of a numerical model for the
evaluation of the urban thermal environment, J. Wind Eng. Ind. Aerod., 81, 181–196,
https://doi.org/10.1016/S0167-6105(99)00016-1, 1999. a
Vu, C. T., Asaeda, T., and Ashie, Y.: A k-*epsiv Turbulence Closure Model For
The Atmospheric Boundary Layer Including Urban Canopy, Bound.-Lay.
Meteorol., 102, 459–490, https://doi.org/10.1023/A:1013878907309, 2002. a
Wang, D., Lau, K. K.-L., Ren, C., Goggins, W. B. I., Shi, Y., Ho, H. C., Lee,
T.-C., Lee, L.-S., Woo, J., and Ng, E.: The impact of extremely hot weather
events on all-cause mortality in a highly urbanized and densely populated
subtropical city: A 10-year time-series study (2006–2015), Sci.
Total Environ., 690, 923–931,
https://doi.org/10.1016/j.scitotenv.2019.07.039, 2019. a
Wang, X., Liao, J., Zhang, J., Shen, C., Chen, W., Xia, B., and Wang, T.: A
Numeric Study of Regional Climate Change Induced by Urban Expansion in the
Pearl River Delta, China, J. Appl. Meteorol. Clim., 53,
346–362, https://doi.org/10.1175/JAMC-D-13-054.1, 2014. a, b, c, d
Wang, Y., Di Sabatino, S., Martilli, A., Li, Y., Wong, M. S., Gutiérrez, E.,
and Chan, P. W.: Impact of land surface heterogeneity on urban heat island
circulation and sea-land breeze circulation in Hong Kong, J.
Geophys. Res.-Atmos., 122, 4332–4352,
https://doi.org/10.1002/2017JD026702, 2017. a, b, c, d, e, f, g
Wang, Y., Li, Y., Sabatino, S. D., Martilli, A., and Chan, P. W.: Effects of
anthropogenic heat due to air-conditioning systems on an extreme high
temperature event in Hong Kong, Environ. Res. Lett., 13, 034015,
https://doi.org/10.1088/1748-9326/aaa848, 2018. a, b
Wong, M. M. F., Fung, J. C. H., Ching, J., Yeung, P. P. S., Tse, J. W. P., Ren,
C., Wang, R., and Cai, M.: Evaluation of uWRF performance and modeling
guidance based on WUDAPT and NUDAPT UCP datasets for Hong Kong, Urban
Climate, 28, 100460, https://doi.org/10.1016/j.uclim.2019.100460, 2019.
a, b, c, d, e
Wong, M. S., Yang, J., Nichol, J., Weng, Q., Menenti, M., and Chan,
P.: Modeling of Anthropogenic Heat Flux Using HJ-1B Chinese Small Satellite
Image: A Study of Heterogeneous Urbanized Areas in Hong Kong, IEEE Geosci.
Remote S., 12, 1466–1470, https://doi.org/10.1109/LGRS.2015.2409111,
2015. a
Short summary
Cities change the local meteorological conditions, e.g. by increasing air temperature, which can negatively impact humans and infrastructure. The urban climate model TEB is able to calculate the meteorological conditions in low- and mid-rise cities since it interacts with the lowest level of an atmospheric model. Here, a multi-layer coupling of TEB is introduced to enable modelling the urban climate of cities with many skyscrapers; the new version is tested for the high-rise city of Hong Kong.
Cities change the local meteorological conditions, e.g. by increasing air temperature, which can...
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