Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 20
Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-5703-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5703-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 20
Model description paper
 | 
16 Oct 2023
Model description paper |  | 16 Oct 2023

URock 2023a: an open-source GIS-based wind model for complex urban settings

Jérémy Bernard, Fredrik Lindberg, and Sandro Oswald

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Cited articles

Bagal, N., Pardyjak, E., and Brown, M.: Improved upwind cavity parameterization for a fast response urban wind model, in: 84th Annual AMS Meeting, Seattle, WA, 10–16 January 2004. a, b, c, d, e, f, g, h
Bernard, J.: URock 2023a: Data and Code to use to reproduce the evaluation of the model (pre_submission), Zenodo [code, data set], https://doi.org/10.5281/zenodo.7681245, 2023. a, b, c
Bocher, E., Petit, G., Fortin, N., and Palominos, S.: H2GIS a spatial database to feed urban climate issues, in: 9th International Conference on Urban Climate (ICUC9), Toulouse, France, 20–24 July 2015, https://shs.hal.science/halshs-01179756/, 2015. a
Bozorgmehr, B., Willemsen, P., Gibbs, J. A., Stoll, R., Kim, J.-J., and Pardyjak, E. R.: Utilizing dynamic parallelism in CUDA to accelerate a 3D red-black successive over relaxation wind-field solver, Environ. Modell. Softw., 137, 104958, https://doi.org/10.1016/j.envsoft.2021.104958, 2021. a
Brown, M. J., Gowardhan, A., Nelson, M., Williams, M., and Pardyjak, E. R.: Evaluation of the QUIC wind and dispersion models using the Joint Urban 2003 field experiment dataset, in: AMS 8th Symp. Urban Env, Phoenix, USA, 10–16 January 2009, 2009a. a, b
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Short summary
The UMEP plug-in integrated in the free QGIS software can now calculate the spatial variation of the wind speed within urban settings. This paper shows that the new wind model, URock, generally fits observations well and highlights the main needed improvements. According to this work, pedestrian wind fields and outdoor thermal comfort can now simply be estimated by any QGIS user (researchers, students, and practitioners).
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