• Ackerman, B., 1987: Climatology of Chicago area urban-rural differences in humidity. J. Climate Appl. Meteor., 26, 427430, https://doi.org/10.1175/1520-0450(1987)026<0427:COCAUR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arya, S. P., 2001: Introduction to Micrometeorology. Academic Press, 402 pp.

  • Barlage, M., S. Miao, and F. Chen, 2016: Impact of physics parameterizations on high-resolution weather prediction over two Chinese megacities. J. Geophys. Res. Atmos., 121, 44874498, https://doi.org/10.1002/2015JD024450.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauer, T. J., 2020: Interaction of urban heat island effects and land–sea breezes during a New York City heat event. J. Appl. Meteor. Climatol., 59, 477495, https://doi.org/10.1175/JAMC-D-19-0061.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauweraerts, P., and J. Meyers, 2019: On the feasibility of using large-eddy simulations for real-time turbulent-flow forecasting in the atmospheric boundary layer. Bound.-Layer Meteor., 171, 213235, https://doi.org/10.1007/s10546-019-00428-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bougeault, P., and P. Lacarrere, 1989: Parameterization of orography-induced turbulence in a mesobeta-scale model. Mon. Wea. Rev., 117, 18721890, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, F., and Coauthors, 2011: The integrated WRF/urban modeling system: Development, evaluation, and applications to the urban environmental problems. Int. J. Climatol., 31, 273288, https://doi.org/10.1002/joc.2158.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ching, J., and Coauthors, 2009: National Urban Database and Access Portal Tool. Bull. Amer. Meteor. Soc., 90, 11571168, https://doi.org/10.1175/2009BAMS2675.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ching, J., and Coauthors, 2018: WUDAPT: An urban weather, climate, and environmental modeling infrastructure for the Anthropocene. Bull. Amer. Meteor. Soc., 99, 19071924, https://doi.org/10.1175/BAMS-D-16-0236.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chow, W. T. L., F. Salamanca, M. Georgescu, A. Mahalov, J. M. Milne, and B. L. Ruddell, 2014: A multi-method and multi-scale approach for estimating city-wide anthropogenic heat fluxes. Atmos. Environ., 99, 6476, https://doi.org/10.1016/j.atmosenv.2014.09.053.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, A. E., S. M. Cavallo, M. C. Coniglio, and H. E. Brooks, 2015: A review of planetary boundary layer parameterization schemes and their sensitivity in simulating southeastern U.S. cold season severe weather environments. Wea. Forecasting, 30, 591612, https://doi.org/10.1175/WAF-D-14-00105.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1972: Theoretical expression for the countergradient vertical heat-flux. J. Geophys. Res., 77, 59005904, https://doi.org/10.1029/JC077i030p05900.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grummann, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, https://doi.org/10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation
  • Gutiérrez, E., J. E. González, A. Martilli, R. Bornstein, and M. Arend, 2015: Simulations of a heat-wave event in New York City using a multilayer urban parameterization. J. Appl. Meteor. Climatol., 54, 283301, https://doi.org/10.1175/JAMC-D-14-0028.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hage, K. D., 1975: Urban–rural humidity differences. J. Appl. Meteor., 14, 12771283, https://doi.org/10.1175/1520-0450(1975)014<1277:URHD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hammerberg, K., O. Brousse, A. Martilli, and A. Mahdavi, 2018: Implications of employing detailed urban canopy parameters for mesoscale climate modelling: A comparison between WUDAPT and GIS databases over Vienna, Austria. Int. J. Climatol., 38, e1241e1257, https://doi.org/10.1002/joc.5447.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a Medium Range Forecast model. Mon. Wea. Rev., 124, 23222339, https://doi.org/10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and J.-O. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129151.

  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P., and J. Dudhia, 2012: Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF Model. J. Appl. Meteor. Climatol., 51, 300316, https://doi.org/10.1175/JAMC-D-11-084.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P., J. Dudhia, J. F. Gonzalez-Rouco, J. Navarro, J. P. Montavez, and E. Garcia-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898918, https://doi.org/10.1175/MWR-D-11-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Knievel, J. C., G. H. Bryan, and J. P. Hacker, 2007: Explicit numerical diffusion in the WRF Model. Mon. Wea. Rev., 135, 38083824, https://doi.org/10.1175/2007MWR2100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kusaka, H., and F. Kimura, 2004: Coupling a single-layer urban canopy model with a simple atmospheric model: Impact on urban heat island for and idealized case. J. Meteor. Soc. Japan, 82, 6780, https://doi.org/10.2151/jmsj.82.67.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kusaka, H., H. Kondo, Y. Kikegawa, and F. Kimura, 2001: A simple single-layer urban canopy model for atmospheric models: Comparison with multi-layer and slab models. Bound.-Layer Meteor., 101, 329358, https://doi.org/10.1023/A:1019207923078.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuttler, W., S. Weber, J. Schonnefeld, and A. Hesselschwerdt, 2007: Urban/rural atmospheric water vapour pressure differences and urban moisture excess in Krefeld, Germany. Int. J. Climatol., 27, 20052015, https://doi.org/10.1002/joc.1558.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lim, K.-S. S., and S.-Y. Hong, 2010: Development of an effective double moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon. Wea. Rev., 138, 15871612, https://doi.org/10.1175/2009MWR2968.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, X., X.-X. Li, S. Harshan, M. Roth, and E. Velasco, 2017: Evaluation of an urban canopy model in a tropical city: The role of tree evapotranspiration. Environ. Res. Lett., 12, 094008, https://doi.org/10.1088/1748-9326/AA7EE7.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Martilli, A., S. Grossman-Clarke, M. Tewari, and K. W. Manning, 2009: Description of the modifications made in WRF.3.1 and short user’s manual of BEP. NCAR RAL Tech. Note, 24 pp., https://ral.ucar.edu/sites/default/files/public/product-tool/Multi_layer_UCM.pdf.

  • Meier, F., D. Fenner, T. Grassmann, M. Otto, and D. Scherer, 2017: Crowdsourcing air temperature from citizen weather stations for urban climate research. Urban Climate, 19, 170191, https://doi.org/10.1016/j.uclim.2017.01.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys., 20, 851875, https://doi.org/10.1029/RG020i004p00851.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, A. H., B. G. Brown, and Y.-S. Chen, 1989: Diagnostic verification of temperature forecasts. Wea. Forecasting, 4, 485501, https://doi.org/10.1175/1520-0434(1989)004<0485:DVOTF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Noh, Y., W. G. Cheon, S.-Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401427, https://doi.org/10.1023/A:1022146015946.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oke, T., 1976: The distinction between canopy and boundary-layer urban heat islands. Atmosphere, 14, 268277, https://doi.org/10.1080/00046973.1976.9648422.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oke, T., 1982: The energetic basis of the urban heat island. Quart. J. Roy. Meteor. Soc., 108, 124, https://doi.org/10.1002/qj.49710845502.

    • Search Google Scholar
    • Export Citation
  • Sailor, D. J., M. Georgescu, J. M. Milne, and M. A. Hart, 2015: Development of a national anthropogenic heating database with an extrapolation for international cities. Atmos. Environ., 118, 718, https://doi.org/10.1016/j.atmosenv.2015.07.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salamanca, F., A. Krpo, A. Martilli, and A. Clappier, 2010: 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, 331344, https://doi.org/10.1007/s00704-009-0142-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salamanca, F., A. Martilli, M. Tewari, and F. Chen, 2011: A study of the urban boundary layer using different urban parameterizations and high-resolution urban canopy parameters in WRF. J. Appl. Meteor. Climatol., 50, 11071128, https://doi.org/10.1175/2010JAMC2538.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salamanca, F., M. Georgescu, A. Mahalov, M. Moustaoui, and M. Wang, 2014: Anthropogenic heating of the urban environment due to air conditioning. J. Geophys. Res. Atmos., 119, 59495965, https://doi.org/10.1002/2013JD021225.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salamanca, F., Y. Zhang, M. Barlage, F. Chen, A. Mahalov, and S. Miao, 2018: Evaluation of the WRF-urban modeling system coupled to Noah and Noah-MP land surface models over a semiarid urban environment. J. Geophys. Res. Atmos., 123, 23872408, https://doi.org/10.1002/2018JD02837.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shin, H. H., S.-Y. Hong, Y. Noh, and J. Dudhia, 2013: Derivation of turbulent kinetic energy from a first-order nonlocal planetary boundary layer parameterization. J. Atmos. Sci., 70, 17951805, https://doi.org/10.1175/JAS-D-12-0150.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the Advanced Research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp., https://doi.org/10.5065/D6DZ069T.

    • Crossref
    • Export Citation
  • Stewart, I. D., and T. R. Oke, 2012: Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc., 93, 18791900, https://doi.org/10.1175/BAMS-D-11-00019.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tewari, M., and Coauthors, 2004: Implementation and verification of the unified Noah land surface model in the WRF Model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 14.2A, https://ams.confex.com/ams/pdfpapers/69061.pdf.

  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Troen, I., and L. Marht, 1986: A simple model of the atmospheric boundary layer sensitivity to surface evaporation. Bound.-Layer Meteor., 37, 129148, https://doi.org/10.1007/BF00122760.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tucker, S. C., and Coauthors, 2006: Relationships of coastal nocturnal boundary layer winds and turbulence to Houston ozone concentrations during TexAQS 2006. J. Geophys. Res., 115, D10304, https://doi.org/10.1029/2009JD013169.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, B., J. C. H. Fung, A. Chan, and A. Lau, 2012: Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model. J. Geophys. Res., 117, D12103, https://doi.org/10.1029/2011JD017080.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., Y. Wang, and K. Hamilton, 2011: Improved representation of boundary layer clouds over the southeast Pacific in ARW-WRF using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev., 139, 34893513, https://doi.org/10.1175/MWR-D-10-05091.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Addition of Multilayer Urban Canopy Models to a Nonlocal Planetary Boundary Layer Parameterization and Evaluation Using Ideal and Real Cases

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  • 1 National Center for Atmospheric Research, Boulder, Colorado
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Abstract

The multilayer urban canopy models (UCMs) building effect parameterization (BEP) and BEP + building energy model (BEM; a building energy model integrated in BEP) are added to the Yonsei University (YSU) planetary boundary layer (PBL) parameterization in the Weather Research and Forecasting (WRF) Model. The additions allow for the first analysis of the detailed effects of buildings on the urban boundary layer in a nonlocal closure scheme. The modified YSU PBL parameterization is compared with the other 1.5-order local PBL parameterizations that predict turbulent kinetic energy (TKE), Mellor–Yamada–Janjić and Bougeault–Lacarerre, using both ideal and real cases. The ideal-case evaluation confirms that BEP and BEP+BEM produce the expected results in the YSU PBL parameterization because the simulations are qualitatively similar to the TKE-based PBL parameterizations in which the multilayer UCMs have long existed. The modified YSU PBL parameterization is further evaluated for a real case. Similar to the ideal case, there are larger differences among the different UCMs (simple bulk scheme, BEP, and BEP+BEM) than across the PBL parameterizations when the UCM is held fixed. Based on evaluation against urban near-surface wind and temperature observations for this case, the BEP and BEP+BEM simulations are superior to the simple bulk scheme for each PBL parameterization.

Corresponding author: Eric A. Hendricks, erichend@ucar.edu

Abstract

The multilayer urban canopy models (UCMs) building effect parameterization (BEP) and BEP + building energy model (BEM; a building energy model integrated in BEP) are added to the Yonsei University (YSU) planetary boundary layer (PBL) parameterization in the Weather Research and Forecasting (WRF) Model. The additions allow for the first analysis of the detailed effects of buildings on the urban boundary layer in a nonlocal closure scheme. The modified YSU PBL parameterization is compared with the other 1.5-order local PBL parameterizations that predict turbulent kinetic energy (TKE), Mellor–Yamada–Janjić and Bougeault–Lacarerre, using both ideal and real cases. The ideal-case evaluation confirms that BEP and BEP+BEM produce the expected results in the YSU PBL parameterization because the simulations are qualitatively similar to the TKE-based PBL parameterizations in which the multilayer UCMs have long existed. The modified YSU PBL parameterization is further evaluated for a real case. Similar to the ideal case, there are larger differences among the different UCMs (simple bulk scheme, BEP, and BEP+BEM) than across the PBL parameterizations when the UCM is held fixed. Based on evaluation against urban near-surface wind and temperature observations for this case, the BEP and BEP+BEM simulations are superior to the simple bulk scheme for each PBL parameterization.

Corresponding author: Eric A. Hendricks, erichend@ucar.edu
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