Articles | Volume 18, issue 2
https://doi.org/10.5194/gmd-18-405-2025
© Author(s) 2025. 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-18-405-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
24 Jan 2025
Development and technical paper |
| 24 Jan 2025
| 24 Jan 2025
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Robert Schoetter
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, 42 avenue Gaspard Coriolis, Toulouse, France
Robin James Hogan
ECMWF, Reading, United Kingdom
Department of Meteorology, University of Reading, Reading, United Kingdom
Cyril Caliot
CNRS, UPPA, E2S, LMAP, 1 Allée du Parc Montaury, Anglet, France
Valéry Masson
CNRM, Université de Toulouse, Météo-France, CNRS, 42 avenue Gaspard Coriolis, Toulouse, France
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William Morrison, Dana Looschelders, Jonnathan Céspedes, Bernie Claxton, Marc-Antoine Drouin, Jean-Charles Dupont, Aurélien Faucheux, Martial Haeffelin, Christopher C. Holst, Simone Kotthaus, Valéry Masson, James McGregor, Jeremy Price, Matthias Zeeman, Sue Grimmond, and Andreas Christen
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EGUsphere, https://doi.org/10.5194/egusphere-2025-4829, https://doi.org/10.5194/egusphere-2025-4829, 2025
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Kaah P. Menang, Stefan A. Buehler, Lukas Kluft, Robin J. Hogan, and Florian E. Roemer
Atmos. Chem. Phys., 25, 11689–11701, https://doi.org/10.5194/acp-25-11689-2025, https://doi.org/10.5194/acp-25-11689-2025, 2025
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Geosci. Model Dev., 18, 5329–5349, https://doi.org/10.5194/gmd-18-5329-2025, https://doi.org/10.5194/gmd-18-5329-2025, 2025
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Paolo Andreozzi, Mark D. Fielding, Robin J. Hogan, Richard M. Forbes, Samuel Rémy, Birger Bohn, and Ulrich Löhnert
EGUsphere, https://doi.org/10.5194/egusphere-2025-3790, https://doi.org/10.5194/egusphere-2025-3790, 2025
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Howard W. Barker, Jason N. S. Cole, Najda Villefranque, Zhipeng Qu, Almudena Velázquez Blázquez, Carlos Domenech, Shannon L. Mason, and Robin J. Hogan
Atmos. Meas. Tech., 18, 3095–3107, https://doi.org/10.5194/amt-18-3095-2025, https://doi.org/10.5194/amt-18-3095-2025, 2025
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Measurements made by three instruments aboard EarthCARE are used to retrieve estimates of cloud and aerosol properties. A radiative closure assessment of these retrievals is performed by the ACMB-DF processor. Radiative transfer models acting on retrieved information produce broadband radiances commensurate with measurements made by EarthCARE’s broadband radiometer. Measured and modelled radiances for small domains are compared, and the likelihood of them differing by 10 W m2 defines the closure.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
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A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
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.
Erwan Jézéquel, Frédéric Blondel, and Valéry Masson
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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Wind turbine wakes affect the production and lifecycle of downstream turbines. They can be predicted with the dynamic wake meandering (DWM) method. In this paper, the authors break down the velocity and turbulence in the wake of a wind turbine into several terms. They show that it is implicitly assumed in the DWM that some of these terms are neglected. With high-fidelity simulations, it is shown that this can lead to some errors, in particular for the maximum turbulence added by the wake.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
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Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
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Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
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.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
David Meyer, Thomas Nagler, and Robin J. Hogan
Geosci. Model Dev., 14, 5205–5215, https://doi.org/10.5194/gmd-14-5205-2021, https://doi.org/10.5194/gmd-14-5205-2021, 2021
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A major limitation in training machine-learning emulators is often caused by the lack of data. This paper presents a cheap way to increase the size of training datasets using statistical techniques and thereby improve the performance of machine-learning emulators.
Cited articles
Blazejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H., and Tinz, B.: Comparison of UTCI to selected thermal indices, Int. J. Biometeorol., 56, 515–535, https://doi.org/10.1007/s00484-011-0453-2, 2012. a
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
Caliot, C., Schoetter, R., Forest, V., Eymet, V., and Chung, T.-Y.: Model of Spectral and Directional Radiative Transfer in Complex Urban Canopies with Participating Atmospheres, Bound.-Lay. Meteorol., 186, 145–175, https://doi.org/10.1007/s10546-022-00750-5, 2023. a, b
Coddington, O., Lean, L. J., Doug, L., Pilewskie, P., Snow, M., and NOAA CDR Program: NOAA Climate Data Record (CDR) of Solar Spectral Irradiance (SSI), NRLSSI Version 2, NOAA National Centers for Environmental Information [data set], https://doi.org/10.7289/V51J97P6, 2015. a
Daniel, M., Lemonsu, A., Déqué, M., Somot, S., Alias, A., and Masson, V.: Benefits of explicit urban parameterization in regional climate modeling to study climate and city interactions, Clim. Dynam., 52, 2745–2764, https://doi.org/10.1007/s00382-018-4289-x, 2019. a
de Munck, C. S., Lemonsu, A., Bouzouidja, R., Masson, V., and Claverie, R.: The GREENROOF module (v7.3) for modelling green roof hydrological and energetic performances within TEB, Geosci. Model Dev., 6, 1941–1960, https://doi.org/10.5194/gmd-6-1941-2013, 2013. a, b
Di Napoli, C., Hogan, R. J., and Pappenberger, F.: Mean radiant temperature from global-scale numerical weather prediction models, Int. J. Biometeorol., 64, 1233–1245, https://doi.org/10.1007/s00484-020-01900-5, 2020. a, b
Dissegna, M. A., Yin, T., Wu, H., Lauret, N., Wei, S., Gastellu-Etchegorry, J.-P., and Grêt-Regamey, A.: Modeling Mean Radiant Temperature Distribution in Urban Landscapes Using DART, Remote Sens., 13, 1443, https://doi.org/10.3390/rs13081443, 2021. a
El Hafi, M., Blanco, S., Dauchet, J., Fournier, R., Galtier, M., Ibarrart, L., Tregan, J.-M., and Villefranque, N.: Three viewpoints on null-collision Monte Carlo algorithms, J. Quant. Spectrosc. Ra., 260, 107402, https://doi.org/10.1016/j.jqsrt.2020.107402, 2021. a
Frayssinet, L., Merlier, L., Kuznik, F., Hubert, J.-L., Milliez, M., and Roux, J.-J.: Modeling the heating and cooling energy demand of urban buildings at city scale, Renew. Sust. Energ. Rev., 81, 2318–2327, https://doi.org/10.1016/j.rser.2017.06.040, 2018. a
Fröhlich, D. and Matzarakis, A.: Calculating human thermal comfort and thermal stress in the PALM model system 6.0, Geosci. Model Dev., 13, 3055–3065, https://doi.org/10.5194/gmd-13-3055-2020, 2020. a
Galtier, M., Blanco, S., Caliot, C., Coustet, C., Dauchet, J., El Hafi, M., Eymet, V., Fournier, R., Gautrais, J., Khuong, A., Piaud, B., and Terrée, G.: Integral formulation of null-collision Monte Carlo algorithms, J. Quant. Spectrosc. Ra., 125, 57–68, https://doi.org/10.1016/j.jqsrt.2013.04.001, 2013. a
Gastellu-Etchegorry, J.-P.: 3D Modeling of satellite spectral images, radiation budget and energy budget of urban landscapes, Meteorol. Atmos. Phys., 102, 187–207, https://doi.org/10.1007/s00703-008-0344-1, 2008. a
Gastellu-Etchegorry, J.-P., Yin, T., Lauret, N., Cajgfinger, T., Gregoire, T., Grau, E., Feret, J.-B., Lopes, M., Guilleux, J., Dedieu, G., Malenovský, Z., Cook, B. D., Morton, D., Rubio, J., Durrieu, S., Cazanave, G., Martin, E., and Ristorcelli, T.: Discrete Anisotropic Radiative Transfer (DART 5) for Modeling Airborne and Satellite Spectroradiometer and LIDAR Acquisitions of Natural and Urban Landscapes, Remote Sens., 7, 1667–1701, https://doi.org/10.3390/rs70201667, 2015. a
Geletič, J., Lehnert, M., Resler, J., Krč, P., Middel, A., Krayenhoff, E., and Krüger, E.: High-fidelity simulation of the effects of street trees, green roofs and green walls on the distribution of thermal exposure in Prague-Dejvice, Build. Environ., 223, 109484, https://doi.org/10.1016/j.buildenv.2022.109484, 2022. a
Grimmond, C. S. B., Blackett, M., Best, M. J., Barlow, J., Baik, J.-J., Belcher, S. E., Bohnenstengel, S. I., Calmet, I., Chen, F., Dandou, A., Fortuniak, K., Gouvea, M. L., Hamdi, R., Hendry, M., Kawai, T., Kawamoto, Y., Kondo, H., Krayenhoff, E. S., Lee, S.-H., Loridan, T., Martilli, A., Masson, V., Miao, S., Oleson, K., Pigeon, G., Porson, A., Ryu, Y.-H., Salamanca, F., Shashua-Bar, L., Steeneveld, G.-J., Tombrou, M., Voogt, J., Young, D., and Zhang, N.: The International Urban Energy Balance Models Comparison Project: First Results from Phase 1, J. Appl. Meteorol. Clim., 49, 1268–1292, https://doi.org/10.1175/2010JAMC2354.1, 2010. a
Grimmond, C. S. B., Blackett, M., Best, M. J., Baik, J.-J., Belcher, S. E., Beringer, J., Bohnenstengel, S. I., Calmet, I., Chen, F., Coutts, A., Dandou, A., Fortuniak, K., Gouvea, M. L., Hamdi, R., Hendry, M., Kanda, M., Kawai, T., Kawamoto, Y., Kondo, H., Krayenhoff, E. S., Lee, S.-H., Loridan, T., Martilli, A., Masson, V., Miao, S., Oleson, K., Ooka, R., Pigeon, G., Porson, A., Ryu, Y.-H., Salamanca, F., Steeneveld, G., Tombrou, M., Voogt, J. A., Young, D. T., and Zhang, N.: Initial results from Phase 2 of the International Urban Energy Balance Model Comparison, Int. J. Climatol., 31, 244–272, https://doi.org/10.1002/joc.2227, 2011. a
Hamdi, R. and Masson, V.: Inclusion of a Drag Approach in the Town Energy Balance (TEB) Scheme: Offline 1D Evaluation in a Street Canyon, J. Appl. Meteorol. Clim., 47, 2627–2644, https://doi.org/10.1175/2008JAMC1865.1, 2008. 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, 53–78, https://doi.org/10.1007/s10546-019-00457-0, 2019b. a, b, c
Hogan, R. J., Schäfer, S. A. K., Klinger, C., Chiu, J. C., and Mayer, B.: Representing 3-D cloud radiation effects in two-stream schemes: 2. Matrix formulation and broadband evaluation, J. Geophys. Res.-Atmos., 121, 8583–8599, https://doi.org/10.1002/2016JD024875, 2016. a
Kotthaus, S., Smith, T., Wooster, M., and Grimmond, S.: Spectral Library of Impervious Urban Materials, Version 1.0, Zenodo [code and data set], https://doi.org/10.5281/zenodo.4263842, 2013. a
Kotthaus, S., Smith, T. E., Wooster, M. J., and Grimmond, C.: Derivation of an urban materials spectral library through emittance and reflectance spectroscopy, ISPRS J. Photogramm. Remote Sens., 94, 194–212, https://doi.org/10.1016/j.isprsjprs.2014.05.005, 2014. a, b, c
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
Kwok, Y. T., Schoetter, R., Lau, K. K.-L., Hidalgo, J., Ren, C., Pigeon, G., and Masson, V.: How well does the local climate zone scheme discern the thermal environment of Toulouse (France)? An analysis using numerical simulation data, Int. J. Climatol., 39, 5292–5315, https://doi.org/10.1002/joc.6140, 2019. a
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
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
Lemonsu, A., Caillaud, C., Alias, A., Riette, S., Seity, Y., Le Roy, B., Michau, Y., and Lucas-Picher, P.: What added value of CNRM-AROME convection-permitting regional climate model compared to CNRM-ALADIN regional climate model for urban climate studies? Evaluation over Paris area (France), Clim. Dynam., 61, 1643–1661, https://doi.org/10.1007/s00382-022-06647-w, 2023. a
Lipson, M., Grimmond, S., Best, M., Chow, W. T. L., Christen, A., Chrysoulakis, N., Coutts, A., Crawford, B., Earl, S., Evans, J., Fortuniak, K., Heusinkveld, B. G., Hong, J.-W., Hong, J., Järvi, L., Jo, S., Kim, Y.-H., Kotthaus, S., Lee, K., Masson, V., McFadden, J. P., Michels, O., Pawlak, W., Roth, M., Sugawara, H., Tapper, N., Velasco, E., and Ward, H. C.: Harmonized gap-filled datasets from 20 urban flux tower sites, Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, 2022. a
Martilli, A., Clappier, A., and Rotach, M. W.: An Urban Surface Exchange Parameterisation for Mesoscale Models, Bound.-Lay. Meteorol., 104, 261–304, https://doi.org/10.1023/A:1016099921195, 2002. 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., 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 (code available at: http://www.umr-cnrm.fr/surfex/spip.php?article387, last access: 22 January 2025). a
Masson, V., Bonhomme, M., Salagnac, J.-L., Briottet, X., and Lemonsu, A.: Solar panels reduce both global warming and urban heat island, Front. Environ. Sci., 2, 1–10, https://doi.org/10.3389/fenvs.2014.00014, 2014. a
Nagel, T., Schoetter, R., Bourgin, V., Masson, V., and Onofri, E.: Drag Coefficient and Turbulence Mixing Length of Local Climate Zone-Based Urban Morphologies Derived Using Obstacle-Resolving Modelling, Bound.-Lay. Meteorol., 186, 737–769, https://doi.org/10.1007/s10546-022-00780-z, 2023. 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
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
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
Redon, E. C., Lemonsu, A., Masson, V., Morille, B., and Musy, M.: Implementation of street trees within the solar radiative exchange parameterization of TEB in SURFEX v8.0, Geosci. Model Dev., 10, 385–411, https://doi.org/10.5194/gmd-10-385-2017, 2017. 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
Schäfer, S. A. K., Hogan, R. J., Klinger, C., Chiu, J. C., and Mayer, B.: Representing 3-D cloud radiation effects in two-stream schemes: 1. Longwave considerations and effective cloud edge length, J. Geophys. Res.-Atmos., 121, 8567–8582, https://doi.org/10.1002/2016JD024876, 2016. a
Schoetter, R., Grawe, D., Hoffmann, P., Kirschner, P., Grätz, A., and Schlünzen, K. H.: Impact of local adaptation measures and regional climate change on perceived temperature, Meteorol Z., 22, 117–130, https://doi.org/10.1127/0941-2948/2013/0381, 2013. a
Schoetter, R., Masson, V., Bourgeois, A., Pellegrino, M., and Lévy, J.-P.: Parametrisation of the variety of human behaviour related to building energy consumption in the Town Energy Balance (SURFEX-TEB v. 8.2), Geosci. Model Dev., 10, 2801–2831, https://doi.org/10.5194/gmd-10-2801-2017, 2017. a
Schoetter, R., Kwok, Y. T., de Munck, C., Lau, K. K. L., Wong, W. K., and Masson, V.: Multi-layer coupling between SURFEX-TEB-v9.0 and Meso-NH-v5.3 for modelling the urban climate of high-rise cities, Geosci. Model Dev., 13, 5609–5643, https://doi.org/10.5194/gmd-13-5609-2020, 2020. a
Schoetter, R., Hogan, R. J., Caliot, C., and Masson, V.: Source code, numerical simulations, and postprocessing scripts described in the research article ”Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation”, submitted to Geoscientific Model Development, Zenodo [code], https://doi.org/10.5281/zenodo.11244064, 2024. 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
Stewart, I. D. and Oke, T. R.: Local Climate Zones for Urban Temperature Studies, B. Am. Meteorol. Soc., 93, 1879–1900, https://doi.org/10.1175/BAMS-D-11-00019.1, 2012. a
Stretton, M. A., Morrison, W., Hogan, R., and Grimmond, S.: Evaluation of the SPARTACUS-Urban radiation model for vertically resolved shortwave radiation in urban areas, Bound.-Lay. Meteorol., 184, 301–331, https://doi.org/10.1007/s10546-022-00706-9, 2022. a, b, c
Stretton, M. A., Morrison, W., Hogan, R. J., and Grimmond, S.: Evaluation of vertically resolved longwave radiation in SPARTACUS-Urban 0.7.3 and the sensitivity to urban surface temperatures, Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, 2023. a
Strømann-Andersen, J. and Sattrup, P.: The urban canyon and building energy use: Urban density versus daylight and passive solar gains, Energ. Buildings, 43, 2011–2020, https://doi.org/10.1016/j.enbuild.2011.04.007, 2011. a
Thorsson, S., Lindberg, F., Eliasson, I., and Holmer, B.: Different methods for estimating the mean radiant temperature in an outdoor urban setting, Int. J. Climatol., 27, 1983–1993, https://doi.org/10.1002/joc.1537, 2007. a, b
Tornay, N., Schoetter, R., Bonhomme, M., Faraut, S., and Masson, V.: GENIUS: A methodology to define a detailed description of buildings for urban climate and building energy consumption simulations, Urban Clim., 20, 75–93, 2017. a
Villefranque, N., Fournier, R., Couvreux, F., Blanco, S., Cornet, C., Eymet, V., Forest, V., and Tregan, J.-M.: A Path-Tracing Monte Carlo Library for 3-D Radiative Transfer in Highly Resolved Cloudy Atmospheres, J. Adv. Model. Earth Sy., 11, 2449–2473, https://doi.org/10.1029/2018MS001602, 2019. a
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can...
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