Articles | Volume 14, issue 3
Geosci. Model Dev., 14, 1469–1492, 2021
https://doi.org/10.5194/gmd-14-1469-2021
Geosci. Model Dev., 14, 1469–1492, 2021
https://doi.org/10.5194/gmd-14-1469-2021

Model description paper 15 Mar 2021

Model description paper | 15 Mar 2021

An urban large-eddy-simulation-based dispersion model for marginal grid resolutions: CAIRDIO v1.0

Michael Weger et al.

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Cited articles

Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., and Young, J. O.: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, 2017. a
Baik, J.-J., Park, S.-B., and Kim, J.-J.: Urban flow and dispersion simulation using a CFD model coupled to a mesoscale model, J. Appl. Meteorol. Clim., 48, 1667–1681, https://doi.org/10.1175/2009JAMC2066.1, 2009. a
Baumann-Stanzer, K., Andronopoulos, S., Armand, P., Berbekar, E., Efthimiou, G., Fuka, V., Gariazzo, C., Gašparac, G., Harms, F., Hellsten, A., Jurcacova, K., Petrov, A., Rákai, A., Stenzel, S., Tavares, R., Tinarelli, G., and Trini Castelli, S.: COST ES1006 Model evaluation case studies: Approach and results, available at: http://www.elizas.eu/images/Documents/Model Evaluation Case Studies_web.pdf (last access: 2 March 2021), 2015. a
Benavides, J., Snyder, M., Guevara, M., Soret, A., Pérez García-Pando, C., Amato, F., Querol, X., and Jorba, O.: CALIOPE-Urban v1.0: coupling R-LINE with a mesoscale air quality modelling system for urban air quality forecasts over Barcelona city (Spain), Geosci. Model Dev., 12, 2811–2835, https://doi.org/10.5194/gmd-12-2811-2019, 2019. a
Birmili, W., Rehn, J., Vogel, A., Boehlke, C., Weber, K., and Rasch, F.: Micro-scale variability of urban particle number and mass concentrations in Leipzig, Germany, Meteorol. Z., 22, 155–165, https://doi.org/10.1127/0941-2948/2013/0394, 2013. a
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A new numerical air-quality transport model for cities is presented, in which buildings are described diffusively. The used diffusive-obstacles approach helps to reduce the computational costs for high-resolution simulations as the grid spacing can be more coarse than in traditional approaches. The research which led to this model development was primarily motivated by the need for a computationally feasible downscaling tool for urban wind and pollution fields from meteorological model output.