Large-Eddy Simulations of the Tropical Cyclone Boundary Layer at Landfall in an Idealized Urban Environment

Christopher M. Rozoff aResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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David S. Nolan bDepartment of Atmospheric Sciences, University of Miami, Florida

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George H. Bryan aResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Eric A. Hendricks aResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Jason C. Knievel aResearch Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Abstract

Populated urban areas along many coastal regions are vulnerable to landfalling tropical cyclones (TCs). To the detriment of surface parameterizations in mesoscale models, the complexities of turbulence at high TC wind speeds in urban canopies are presently poorly understood. Thus, this study explores the impacts of urban morphology on TC-strength winds and boundary layer turbulence in landfalling TCs. To better quantify how urban structures interact with TC winds, large-eddy simulations (LESs) are conducted with the Cloud Model 1 (CM1). This implementation of CM1 includes immersed boundary conditions (IBCs) to represent buildings and eddy recycling to maintain realistic turbulent flow perturbations. Within the IBCs, an idealized coastal city with varying scales is introduced. TC winds impinge perpendicularly to the urbanized coastline. Numerical experiments show that buildings generate distinct, intricate flow patterns that vary significantly as the city structure is varied. Urban IBCs produce much stronger turbulent kinetic energy than is produced by conventional surface parameterizations. Strong effective eddy viscosity due to resolved eddy mixing is displayed in the wake of buildings within the urban canopy, while deep and enhanced effective eddy viscosity is present downstream. Such effects are not seen in a comparison LES using a simple surface parameterization with high roughness values. Wind tunneling effects in streamwise canyons enhance pedestrian-level winds well beyond what is possible without buildings. In the arena of regional mesoscale modeling, this type of LES framework with IBCs can be used to improve parameters in surface and boundary layer schemes to more accurately represent the drag coefficient and the eddy viscosity in landfalling TC boundary layers.

Significance Statement

This is among the first large-eddy simulation model studies to examine the impacts of tropical cyclone–like winds around explicitly resolved buildings. This work is a step forward in bridging the gap between engineering studies that use computational fluid dynamics models or laboratory experiments for flow through cities and mesoscale model simulations of landfalling tropical cyclones that use surface parameterizations specialized for urban land use.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Christopher M. Rozoff, rozoff@ucar.edu

Abstract

Populated urban areas along many coastal regions are vulnerable to landfalling tropical cyclones (TCs). To the detriment of surface parameterizations in mesoscale models, the complexities of turbulence at high TC wind speeds in urban canopies are presently poorly understood. Thus, this study explores the impacts of urban morphology on TC-strength winds and boundary layer turbulence in landfalling TCs. To better quantify how urban structures interact with TC winds, large-eddy simulations (LESs) are conducted with the Cloud Model 1 (CM1). This implementation of CM1 includes immersed boundary conditions (IBCs) to represent buildings and eddy recycling to maintain realistic turbulent flow perturbations. Within the IBCs, an idealized coastal city with varying scales is introduced. TC winds impinge perpendicularly to the urbanized coastline. Numerical experiments show that buildings generate distinct, intricate flow patterns that vary significantly as the city structure is varied. Urban IBCs produce much stronger turbulent kinetic energy than is produced by conventional surface parameterizations. Strong effective eddy viscosity due to resolved eddy mixing is displayed in the wake of buildings within the urban canopy, while deep and enhanced effective eddy viscosity is present downstream. Such effects are not seen in a comparison LES using a simple surface parameterization with high roughness values. Wind tunneling effects in streamwise canyons enhance pedestrian-level winds well beyond what is possible without buildings. In the arena of regional mesoscale modeling, this type of LES framework with IBCs can be used to improve parameters in surface and boundary layer schemes to more accurately represent the drag coefficient and the eddy viscosity in landfalling TC boundary layers.

Significance Statement

This is among the first large-eddy simulation model studies to examine the impacts of tropical cyclone–like winds around explicitly resolved buildings. This work is a step forward in bridging the gap between engineering studies that use computational fluid dynamics models or laboratory experiments for flow through cities and mesoscale model simulations of landfalling tropical cyclones that use surface parameterizations specialized for urban land use.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Christopher M. Rozoff, rozoff@ucar.edu
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  • Alford, A. A., J. A. Zhang, M. I. Biggerstaff, P. Dodge, F. D. Marks, and D. J. Bodine, 2020: Transition of the hurricane boundary layer during the landfall of Hurricane Irene (2011). J. Atmos. Sci., 77, 35093531, https://doi.org/10.1175/JAS-D-19-0290.1.

    • Search Google Scholar
    • Export Citation
  • Atzori, M., P. Torres, A. Vidal, S. Le Clainche, S. Hoyas, and R. Vinuesa, 2023: High-resolution simulations of a turbulent boundary layer impacting two obstacles in tandem. Phys. Rev. Fluids, 8, 063801, https://doi.org/10.1103/PhysRevFluids.8.063801.

    • Search Google Scholar
    • Export Citation
  • Avila, L. A., S. R. Stewart, R. Berg, and A. B. Hagen, 2020: Tropical cyclone report: Hurricane Dorian (AL052019): 24 August–7 September 2019. NHC Tech. Rep., 74 pp., https://www.nhc.noaa.gov/data/tcr/AL052019_Dorian.pdf.

  • Balderrama, J. A., and Coauthors, 2011: The Florida Coastal Monitoring Program (FCMP): A review. J. Wind Eng. Ind. Aerodyn., 99, 979995, https://doi.org/10.1016/j.jweia.2011.07.002.

    • Search Google Scholar
    • Export Citation
  • Basu, S., and A. Lacser, 2017: A cautionary note on the use of Monin-Obukhov similarity theory in very high-resolution large-eddy simulations. Bound.-Layer Meteor., 163, 351355, https://doi.org/10.1007/s10546-016-0225-y.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, https://doi.org/10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., and R. Rotunno, 2009: The maximum intensity of tropical cyclones in axisymmetric numerical model simulations. Mon. Wea. Rev., 137, 17701789, https://doi.org/10.1175/2008MWR2709.1.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., R. P. Worsnop, J. K. Lundquist, and J. A. Zhang, 2017: A simple method for simulating wind profiles in the boundary layer of tropical cyclones. Bound.-Layer Meteor., 162, 475502, https://doi.org/10.1007/s10546-016-0207-0.

    • Search Google Scholar
    • Export Citation
  • Chen, X., I. Ginis, and T. Hera, 2020: Impact of shoaling surface waves on wind stress and drag coefficient in coastal waters: 2. Tropical cyclones. J. Geophys. Res. Oceans, 125, e2020JC016223, https://doi.org/10.1029/2020JC016223.

    • Search Google Scholar
    • Export Citation
  • Chen, X., G. H. Bryan, J. A. Zhang, J. J. Cione, and F. D. Marks, 2021: A framework for simulating the tropical cyclone boundary layer using large-eddy simulation and its use in evaluating PBL parameterizations. J. Atmos. Sci., 78, 35593574, https://doi.org/10.1175/JAS-D-20-0227.1.

    • Search Google Scholar
    • Export Citation
  • Folkard, A. M., 2011: Vegetated flows in their environmental context: A review. Eng. Comput. Mech., 164, 324, https://doi.org/10.1680/eacm.8.00006.

    • Search Google Scholar
    • Export Citation
  • Foster, R., 2013: Signature of large aspect ratio roll vortices in synthetic aperture radar images of tropical cyclones. Oceanography, 26 (2), 5867, https://doi.org/10.5670/oceanog.2013.31.

    • Search Google Scholar
    • Export Citation
  • Grimmond, C. S. B., and T. R. Oke, 1999: Aerodynamic properties of urban areas derived from analysis of surface form. J. Appl. Meteor., 38, 12621292, https://doi.org/10.1175/1520-0450(1999)038<1262:APOUAD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hågbo, T.-O., and K. E. T. Giljarhus, 2022: Pedestrian wind comfort assessment using computational fluid dynamics simulations with varying number of wind directions. Front. Built Environ., 8, 858067, https://doi.org/10.3389/fbuil.2022.858067.

    • Search Google Scholar
    • Export Citation
  • Hendricks, E. A., J. C. Knievel, and D. S. Nolan, 2021: Evaluation of boundary layer and urban canopy parameterizations for simulating wind in Miami during Hurricane Irma (2017). Mon. Wea. Rev., 149, 23212349, https://doi.org/10.1175/MWR-D-20-0278.1.

    • Search Google Scholar
    • Export Citation
  • Hirth, B. D., J. L. Schroeder, C. C. Weiss, D. A. Smith, and M. I. Biggerstaff, 2012: Research radar analyses of the internal boundary layer over Cape Canaveral, Florida, during the landfall of Hurricane Frances (2004). Wea. Forecasting, 27, 13491372, https://doi.org/10.1175/WAF-D-12-00014.1.

    • Search Google Scholar
    • Export Citation
  • Hlywiak, J., and D. S. Nolan, 2022: The evolution of asymmetries in the tropical cyclone boundary layer wind field during landfall. Mon. Wea. Rev., 150, 529549, https://doi.org/10.1175/MWR-D-21-0191.1.

    • Search Google Scholar
    • Export Citation
  • Hoornweg, D., M. Freire, M. J. Lee, P. Bhada-Tata, and Y. Belinda, 2011: Cities and climate change: Responding to an urgent agenda. The World Bank, 328 pp., https://openknowledge.worldbank.org/handle/10986/2312.

  • Huang, S., Q. S. Li, and S. Xu, 2007: Numerical evaluation of wind effects on a tall steel building by CFD. J. Constr. Steel Res., 63, 612627, https://doi.org/10.1016/j.jcsr.2006.06.033.

    • Search Google Scholar
    • Export Citation
  • Knutson, T., and Coauthors, 2020: Tropical cyclones and climate change assessment. Part II: Projected response to anthropogenic warming. Bull. Amer. Meteor. Soc., 101, E303E322, https://doi.org/10.1175/BAMS-D-18-0194.1.

    • Search Google Scholar
    • Export Citation
  • Kosiba, K. A., and J. Wurman, 2014: Finescale dual-Doppler analysis of hurricane boundary layer structures in Hurricane Frances (2004) at landfall. Mon. Wea. Rev., 142, 18741891, https://doi.org/10.1175/MWR-D-13-00178.1.

    • Search Google Scholar
    • Export Citation
  • Ma, Z., and Coauthors, 2020: Investigating the impact of high-resolution land–sea masks on hurricane forecasts in HWRF. Atmosphere, 11, 888, https://doi.org/10.3390/atmos11090888.

    • Search Google Scholar
    • Export Citation
  • Maronga, B., and Coauthors, 2015: The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: Model formulation, recent developments, and future perspectives. Geosci. Model Dev., 8, 25152551, https://doi.org/10.5194/gmd-8-2515-2015.

    • Search Google Scholar
    • Export Citation
  • Martilli, A., A. Clappier, and M. W. Rotach, 2002: An urban surface exchange parameterisation for mesoscale models. Bound.-Layer Meteor., 104, 261304, https://doi.org/10.1023/A:1016099921195.

    • Search Google Scholar
    • Export Citation
  • Masters, F. J., H. W. Tieleman, and J. A. Balderrama, 2010: Surface wind measurements in three Gulf Coast hurricanes of 2005. J. Wind Eng. Ind. Aerodyn., 98, 533547, https://doi.org/10.1016/j.jweia.2010.04.003.

    • Search Google Scholar
    • Export Citation
  • McGranahan, G., D. Balk, and B. Anderson, 2007: The rising tide: Assessing the risks of climate change and human settlements in low elevation coastal zones. Environ. Urbanization, 19, 1737, https://doi.org/10.1177/0956247807076960.

    • Search Google Scholar
    • Export Citation
  • Momen, M., M. B. Parlange, and M. G. Giometto, 2021: Scrambling and reorientation of classical atmospheric boundary layer turbulence in hurricane winds. Geophys. Res. Letts., 48, e2020GL091695, https://doi.org/10.1029/2020GL091695.

    • Search Google Scholar
    • Export Citation
  • Montazeri, H., and B. Blocken, 2013: CFD simulation of wind-induced pressure coefficients on buildings with and without balconies: Validation and sensitivity analysis. Build. Environ., 60, 137149, https://doi.org/10.1016/j.buildenv.2012.11.012.

    • Search Google Scholar
    • Export Citation
  • Muñoz-Esparza, D., B. Kosović, J. Mirocha, and J. van Beeck, 2014: Bridging the transition from mesoscale to microscale turbulence in numerical weather prediction models. Bound.-Layer Meteor., 153, 409440, https://doi.org/10.1007/s10546-014-9956-9.

    • Search Google Scholar
    • Export Citation
  • Muñoz-Esparza, D., and Coauthors, 2020: Inclusion of building-resolving capabilities into the FastEddy GPU-LES model using an immersed body force method. J. Adv. Model. Earth Syst., 12, e2020MS002141, https://doi.org/10.1029/2020MS002141.

    • Search Google Scholar
    • Export Citation
  • Muñoz-Esparza, D., and Coauthors, 2021: Efficient graphics processing unit modeling of street-scale weather effects in support of aerial operations in the urban environment. AGU Adv., 2, e2021QV000432, https://doi.org/10.1029/2021AV000432.

    • Search Google Scholar
    • Export Citation
  • Nolan, D. S., B. D. McNoldy, and J. Yunge, 2021a: Evaluation of the surface wind field over land in WRF simulations of Hurricane Wilma (2005). Part I: Model initialization and simulation validation. Mon. Wea. Rev., 149, 679695, https://doi.org/10.1175/MWR-D-20-0199.1.

    • Search Google Scholar
    • Export Citation
  • Nolan, D. S., B. D. McNoldy, J. Yunge, F. J. Masters, and I. M. Giammanco, 2021b: Evaluation of the surface wind field over land in WRF simulations of Hurricane Wilma (2005). Part II: Surface winds, inflow angles, and boundary layer profiles. Mon. Wea. Rev., 149, 697713, https://doi.org/10.1175/MWR-D-20-0201.1.

    • Search Google Scholar
    • Export Citation
  • Nystrom, R. G., X. Chen, F. Zhang, and C. A. Davis, 2020: Nonlinear impacts of surface exchange coefficient uncertainty on tropical cyclone intensity and air-sea interactions. Geophys. Res. Letts., 47, e2019GL085783, https://doi.org/10.1029/2019GL085783.

    • Search Google Scholar
    • Export Citation
  • Oke, T. R., 1988: Street design and urban canopy layer climate. Energy Build., 11, 103113, https://doi.org/10.1016/0378-7788(88)90026-6.

    • Search Google Scholar
    • Export Citation
  • Richter, D. H., C. Wainwright, D. P. Stern, G. H. Bryan, and D. Chavas, 2021: Potential low bias in high-wind drag coefficient inferred from dropsonde data in hurricanes. J. Atmos. Sci., 78, 23392352, https://doi.org/10.1175/JAS-D-20-0390.1.

    • Search Google Scholar
    • Export Citation
  • Shin, H. H., D. Muñoz-Esparza, J. A. Sauer, and M. Steiner, 2021: Large-eddy simulations of stability-varying atmospheric boundary layer flow over isolated buildings. J. Atmos. Sci., 78, 14871501, https://doi.org/10.1175/JAS-D-20-0160.1.

    • Search Google Scholar
    • Export Citation
  • Sparks, N., K. K. Hon, P. W. Chan, S. Wang, J. C. L. Chan, T. C. Lee, and R. Toumi, 2019: Aircraft observations of tropical cyclone boundary layer turbulence over the South China Sea. J. Atmos. Sci., 76, 37733783, https://doi.org/10.1175/JAS-D-19-0128.1.

    • Search Google Scholar
    • Export Citation
  • Sterzel, T., M. K. B. Lüdeke, C. Walther, M. T. Kok, D. Sietz, and P. L. Lucas, 2020: Typology of coastal urban vulnerability under rapid urbanization. PLOS ONE, 15, e0220936, https://doi.org/10.1371/journal.pone.0220936.

    • Search Google Scholar
    • Export Citation
  • Tamura, T., K. Nozawa, and K. Kondo, 2008: AIJ guide for numerical prediction of wind loads on buildings. J. Wind Eng. Ind. Aerodyn., 96, 19741984, https://doi.org/10.1016/j.jweia.2008.02.020.

    • Search Google Scholar
    • Export Citation
  • Thordal, M. S., J. C. Bennetsen, and H. H. H. Koss, 2019: Review for practical application of CFD for the determination of wind load on high-rise buildings. J. Wind Eng. Ind. Aerodyn., 186, 155168, https://doi.org/10.1016/j.jweia.2018.12.019.

    • Search Google Scholar
    • Export Citation
  • Zhang, J. A., F. D. Marks, M. T. Montgomery, and S. Lorsolo, 2011: An estimation of turbulent characteristics in the low-level region of intense Hurricanes Allen (1980) and Hugo (1989). Mon. Wea. Rev., 139, 14471462, https://doi.org/10.1175/2010MWR3435.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, W., G. Villarini, G. A. Vecchi, and J. A. Smith, 2018: Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston. Nature, 563, 384388, https://doi.org/10.1038/s41586-018-0676-z.

    • Search Google Scholar
    • Export Citation
  • Zhao, Z., P. W. Chan, N. Wu, J. A. Zhang, and K. K. Hon, 2020: Aircraft observations of turbulence characteristics in the tropical cyclone boundary layer. Bound.-Layer Meteor., 174, 493511, https://doi.org/10.1007/s10546-019-00487-8.

    • Search Google Scholar
    • Export Citation
  • Zhao, Z., R. Gao, J. A. Zhang, Y. Zhu, C. Liu, P. W. Chan, and Q. Wan, 2022: Observations of boundary layer wind and turbulence of a landfalling tropical cyclone. Sci. Rep., 12, 11056, https://doi.org/10.1038/s41598-022-14929-w.

    • Search Google Scholar
    • Export Citation
  • Zhou, X., T. Hara, I. Ginis, E. D’Asaro, J.-Y. Hsu, and B. G. Reichl, 2022: Drag coefficient and its sea state dependence under tropical cyclones. J. Phys. Oceanogr., 52, 14471470, https://doi.org/10.1175/JPO-D-21-0246.1.

    • Search Google Scholar
    • Export Citation
  • Zhu, P., 2008: Impact of land-surface roughness on surface winds during hurricane landfall. Quart. J. Roy. Meteor. Soc., 134, 10511057, https://doi.org/10.1002/qj.265.

    • Search Google Scholar
    • Export Citation
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