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Interfacing the Urban Land–Atmosphere System Through Coupled Urban Canopy and Atmospheric Models

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Abstract

We couple a single column model (SCM) to a cutting-edge single-layer urban canopy model (SLUCM) with realistic representation of urban hydrological processes. The land-surface transport of energy and moisture parametrized by the SLUCM provides lower boundary conditions to the overlying atmosphere. The coupled SLUCM–SCM model is tested against field measurements of sensible and latent heat fluxes in the surface layer, as well as vertical profiles of temperature and humidity in the mixed layer under convective conditions. The model is then used to simulate urban land–atmosphere interactions by changing urban geometry, surface albedo, vegetation fraction and aerodynamic roughness. Results show that changes of landscape characteristics have a significant impact on the growth of the boundary layer as well as on the distributions of temperature and humidity in the mixed layer. Overall, the proposed numerical framework provides a useful stand-alone modelling tool, with which the impact of urban land-surface conditions on the local hydrometeorology can be assessed via land–atmosphere interactions.

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References

  • Akbari H, Matthews HD, Seto D (2012) The long-term effect of increasing the albedo of urban areas. Environ Res Lett 7(2):024004

    Article  Google Scholar 

  • Arnfield AJ (2003) Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol 23(1):1–26

    Article  Google Scholar 

  • Atmospheric Radiation Measurement (ARM) Program (2011) Balloon-borne sounding system (SONDE), sondewnpn b1 data stream. ARM Archive, Oak Ridge, TN, USA. Data subset: Oct 2010–Mar 2011, \(36^{\circ }\) 36’18.0”N, \(97^{\circ }\)29’6.0”W

  • Bonan GB, Oleson KW, Vertenstein M, Levis S, Zeng XB, Dai YJ, Dickinson RE, Yang ZL (2002) The land surface climatology of the community land model coupled to the NCAR community climate model. J Clim 15(22):3123–3149

    Article  Google Scholar 

  • Brutsaert W (2005) Hydrology—an introduction. Cambridge University Press, New York 605 pp

    Book  Google Scholar 

  • Businger JA, Wyngaard JC, Bradley EF (1971) Flux–profile relationships in the atmospheric surface layer. J Atmos Sci 28:181–189

    Article  Google Scholar 

  • Chen F, Avissar R (1994) Impact of land-surface moisture variability on local shallow convective cumulus and precipitation in large-scale models. J Appl Meteorol 33(12):1382–1401

    Article  Google Scholar 

  • Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon Weather Rev 129(4):569–585

    Article  Google Scholar 

  • Chen F, Kusaka H, Bornstein R, Ching J, Grimmond CSB, Grossman-Clarke S, Loridan T, Manning KW, Martilli A, Miao S, Sailor D, Salamanca FP, Taha H, Tewari M, Wang X, Wyszogrodzki AA, Zhang C (2011) The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems. Int J Climatol 31(2):273–288

    Article  Google Scholar 

  • Chow WTL, Volo TJ, Vivoni ER, Jenerette GD, Ruddell BL (2014) Seasonal dynamics of a suburban energy balance in Phoenix, Arizona. Int J Climatol. doi:10.1002/joc.3947

  • Clarke RH, Dyer AJ, Brook RR, Reid DC, Troup AJ (1971) The Wangara Experiment: boundary layer data. Tech. Paper No. 19, Div Met Phys. CSIRO, Australia, p 316

  • Collier CG (2006) The impact of urban areas on weather. Q J R Meteorol Soc 132(614):1–25

    Article  Google Scholar 

  • Deardorff JW (1980) Stratocumulus-capped mixed layers derived from a three-dimensional model. Boundary-Layer Meteorol 18:495–527

    Article  Google Scholar 

  • Dupont S, Otte TL, Ching JKS (2004) Simulation of meteorological fields within and above urban and rural canopies with a mesoscale model (mm5). Boundary-Layer Meteorol 113(1):111–158

    Article  Google Scholar 

  • Dvorak B, Volder A (2010) Green roof vegetation for north American ecoregions: a literature review. Landsc Urban Plan 96(4):197–213

    Article  Google Scholar 

  • Grimmond CSB, Dandou A, Fortuniak K, Gouvea ML, Hamdi R, Hendry M, Kawai T, Kawamoto Y, Kondo H, Krayenhoff ES, Lee SH, Blackett M, Loridan T, Martilli A, Masson V, Miao S, Oleson K, Pigeon G, Porson A, Ryu YH, Salamanca F, Shashua-Bar L, Best MJ, Steeneveld GJ, Tombrou M, Voogt J, Young D, Zhang N, Barlow J, Baik JJ, Belcher SE, Bohnenstengel SI, Calmet I, Chen F (2010) The international urban energy balance models comparison project: first results from phase 1. J Appl Meteorol Climatol 49(6):1268–1292

    Article  Google Scholar 

  • Grimmond CSB, Coutts A, Dandou A, Fortuniak K, Gouvea ML, Hamdi R, Hendry M, Kanda M, Kawai T, Kawamoto Y, Kondo H, Blackett M, Krayenhoff ES, Lee SH, Loridan T, Martilli A, Masson V, Miao S, Oleson K, Ooka R, Pigeon G, Porson A, Best MJ, Ryu YH, Salamanca F, Steeneveld GJ, Tombrou M, Voogt JA, Young DT, Zhang N, Baik JJ, Belcher SE, Beringer J, Bohnenstengel SI, Calmet I, Chen F (2011) Initial results from phase 2 of the international urban energy balance model comparison. Int J Climatol 31(2):244–272

    Article  Google Scholar 

  • Holtslag AAM, Moeng CH (1991) Eddy diffusivity and countergradient transport in the convective atmospheric boundary-layer. J Atmos Sci 48(14):1690–1698

    Article  Google Scholar 

  • Hong SY, Yign N, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134(9):2318–2341

    Article  Google Scholar 

  • Jacobson MZ, Ten Hoeve JE (2012) Effects of urban surfaces and white roofs on global and regional climate. J Clim 25(3):1028–1044

    Article  Google Scholar 

  • Jeričević A, Grisogono B (2006) The critical bulk Richardson number in urban areas: verification and application in a numerical weather prediction model. Tellus 58(A):19–27

    Google Scholar 

  • Kim SW, Park SU, Pino D, Arellano JG (2006) Parameterization of entrainment in a sheared convective boundary layer using a first-order jump model. Boundary-Layer Meteorol 120(3):455–475

    Article  Google Scholar 

  • Kondo H, Genchi Y, Kikegawa Y, Ohashi Y, Yoshikado H, Komiyama H (2005) Development of a multi-layer urban canopy model for the analysis of energy consumption in a big city: structure of the urban canopy model and its basic performance. Boundary-Layer Meteorol 116(3):395–421

    Article  Google Scholar 

  • Kusaka H, Kondo H, Kikegawa Y, Kimura F (2001) A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Boundary-Layer Meteorol 101(3):329–358

    Article  Google Scholar 

  • Loridan T, Grimmond CSB, Grossman-Clarke S, Chen F, Tewari M, Manning K, Martilli A, Kusaka H, Best M (2010) Trade-offs and responsiveness of the single-layer urban canopy parametrization in WRF: an offline evaluation using the MOSCEM optimization algorithm and field observations. Q J R Meteorol Soc 136(649):997–1019

    Article  Google Scholar 

  • Martilli A, Clappier A, Rotach M (2002) An urban surface exchange parameterisation for mesoscale models. Boundary-Layer Meteorol 104(2):261–304

    Article  Google Scholar 

  • Mascart P, Noilhan J, Giordani H (1995) A modified parameterization of flux-profile relationships in the surface-layer using different roughness length values for heat and momentum. Boundary-Layer Meteorol 72(4):331–344

    Article  Google Scholar 

  • Masson V (2000) A physically-based scheme for the urban energy budget in atmospheric models. Boundary-Layer Meteorol 94(3):357–397

    Article  Google Scholar 

  • Niyogi D, Mahmood R, Adegoke JO (2009) Land-use/land-cover change and its impacts on weather and climate. Boundary-Layer Meteorol 133(3):297–298

    Article  Google Scholar 

  • Noh Y, Cheon WG, Hong SY, Raasch S (2003) Improvement of the k-profile model for the planetary boundary layer based on large eddy simulation data. Boundary-Layer Meteorol 107(2):401–427

    Article  Google Scholar 

  • Nunez M, Oke TR (1977) The energy balance of an urban canyon. J Appl Meteorol 16:11–19

    Article  Google Scholar 

  • Ouwersloot HG, Vilà-Guerau de Arellano J (2013) Analytical solution for the convectively-mixed atmospheric boundary layer. Boundary-Layer Meteorol 148(3):557–583

    Article  Google Scholar 

  • Ramamurthy P, Bou-Zeid E, Smith JA, Wang Z, Baeck ML, Saliendra NZ, Hom JL, Welty C (2014) Influence of sub-facet heterogeneity and material properties on the urban surface energy budget. J Appl Meteorol Climatol 53(9):2114–2129

    Article  Google Scholar 

  • Sailor DJ, Elley TB, Gibson M (2012) Exploring the building energy impacts of green roof design decisions—a modeling study of buildings in four distinct climates. J Building Phys 35(4):372–391

    Article  Google Scholar 

  • Skamarock WC, Klemp JB (2008) A time-split non-hydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227(7):3465–3485

    Article  Google Scholar 

  • Stull RB (1988) An introduction to boundary layer meteorology. Kluwer, Dordrecht 666 pp

    Book  Google Scholar 

  • Sun T, Bou-Zeid E, Wang ZH, Zerba E, Ni GH (2013a) Hydrometeorological determinants of green roof performance via a vertically-resolved model for heat and water transport. Build Environ 60:211–224

    Article  Google Scholar 

  • Sun T, Wang ZH, Ni GH (2013b) Revisiting the hysteresis effect in surface energy budgets. Geophys Res Lett 40:1741–1747

    Article  Google Scholar 

  • Taha H (1997) Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat. Energy Buildings 25(2):99–103

    Article  Google Scholar 

  • Theeuwes NE, Steeneveld GJ, Ronda RJ, Heusinkveld BG, van Hove LWA, Holtslag AAM (2014) Seasonal dependence of the urban heat island on the street canyon aspect ratio. Q J R Meteorol Soc 140:2197–2210

  • Trier SB, LeMone MA, Chen F, Manning KW (2011) Effects of surface heat and moisture exchange on ARW-WRF warm-season precipitation forecasts over the central United States. Weather Forecast 26(1):3–25

    Article  Google Scholar 

  • Troen I, Mahrt L (1986) A simple-model of the atmospheric boundary-layer—sensitivity to surface evaporation. Boundary-Layer Meteorol 37(1–2):129–148

    Article  Google Scholar 

  • The United Nations (UN) (2012) World urbanization prospects: the 2011 revision, New York, 33 pp

  • Van Genuchten MT (1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44(5):892–898

    Article  Google Scholar 

  • Wang ZH (2010) Geometric effect of radiative heat exchange in concave structure with application to heating of steel I-sections in fire. Int J Heat Mass Transf 53(5–6):997–1003

    Article  Google Scholar 

  • Wang ZH, Bou-Zeid E, Smith JA (2011a) A spatially-analytical scheme for surface temperatures and conductive heat fluxes in urban canopy models. Boundary-Layer Meteorol 138(2):171–193

    Article  Google Scholar 

  • Wang ZH, Bou-Zeid E, Au SK, Smith JA (2011b) Analyzing the sensitivity of WRF’s single-layer urban canopy model to parameter uncertainty using advanced Monte Carlo simulation. J Appl Meteorol Climatol 50(9):1795–1814

    Article  Google Scholar 

  • Wang ZH, Bou-Zeid E, Smith JA (2013) A coupled energy transport and hydrological model for urban canopies evaluated using a wireless sensor network. Q J R Meteorol Soc 139(675):1643–1657

    Article  Google Scholar 

  • Yang J, Wang ZH (2014) Parameterization and sensitivity of urban hydrological models: application to green roof systems. Build Environ 75:250–263

    Article  Google Scholar 

  • Yang ZL (1995) Investigating impacts of anomalous land-surface conditions on Australian climate with an advanced land-surface model coupled with the BMRC-GCM. Int J Climatol 15(2):137–174

    Article  Google Scholar 

  • Zilitinkevich S, Baklanov A (2002) Calculation of the height of the stable boundary layer in practical applications. Boundary-Layer Meteorol 105(3):389–409

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Science Foundation (NSF) under grant number CBET-1435881. The authors thank the Central Arizona-Phoenix Long-Term Ecological Research (CAP LTER) project under NSF grant CAP3: BCS-1026865, for partial financial support and sharing of field measurements in Phoenix. Field measurement by the Atmospheric Radiation Measurement (ARM) Program (2011) sponsored by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division is acknowledged.

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Correspondence to Zhi-Hua Wang.

Appendix 1: Calculation of Net Radiation in a Street Canyon

Appendix 1: Calculation of Net Radiation in a Street Canyon

The net shortwave and longwave radiative fluxes for walls and ground inside a street canyon can be computed using a two-reflection model (Kusaka et al. 2001; Wang et al. 2013) as,

$$\begin{aligned} S_\mathrm{W}&= (1-a_\mathrm{W})\left[ {\begin{array}{l} S_\mathrm{D} \frac{l_\mathrm{shadow} }{2h}+S_\mathrm{Q} F_{\mathrm{W}\rightarrow \mathrm{S}} +S_\mathrm{D} \left( {\frac{w-l_\mathrm{shadow} }{w}} \right) a_\mathrm{G} F_{\mathrm{W}\rightarrow \mathrm{G}} \\ +S_\mathrm{Q} F_{\mathrm{W}\rightarrow \mathrm{G}} +S_\mathrm{D} \frac{l_\mathrm{shadow} }{2h}a_\mathrm{W} F_{\mathrm{W}\rightarrow \mathrm{W}} +S_\mathrm{Q} a_\mathrm{W} F_{\mathrm{W}\rightarrow \mathrm{S}} F_{\mathrm{W}\rightarrow \mathrm{W}} \\ \end{array}} \right] , \end{aligned}$$
(34)
$$\begin{aligned} S_\mathrm{G}&= \left( {1-a_\mathrm{G} } \right) \left[ S_\mathrm{D} \left( {\frac{w-l_\mathrm{shadow} }{w}} \right) +S_\mathrm{Q} F_{\mathrm{G}\rightarrow \mathrm{S}} +S_\mathrm{D} \frac{l_\mathrm{shadow} }{2h}a_\mathrm{W} F_{\mathrm{G}\rightarrow \mathrm{W}}\right. \nonumber \\&\left. +\,S_\mathrm{Q} a_\mathrm{W} F_{\mathrm{W}\rightarrow \mathrm{S}} F_{\mathrm{G}\rightarrow \mathrm{W}} \right] , \end{aligned}$$
(35)
$$\begin{aligned} L_\mathrm{W}&= \varepsilon _\mathrm{W} \left( {F_{\mathrm{W}\rightarrow \mathrm{S}} L^{\downarrow }+\varepsilon _\mathrm{G} F_{\mathrm{W}\rightarrow \mathrm{G}} \sigma T_\mathrm{G}^4 +\varepsilon _\mathrm{W} F_{\mathrm{W}\rightarrow \mathrm{W}} \sigma T_\mathrm{W}^4 -\sigma T_\mathrm{W}^4 } \right) \nonumber \\&+\,\varepsilon _\mathrm{W} \left( {1-\varepsilon _\mathrm{G} } \right) L^{\downarrow }F_{\mathrm{G}\rightarrow \mathrm{S}} F_{\mathrm{W}\rightarrow \mathrm{G}} \nonumber \\&+\,2\left( {1-\varepsilon _\mathrm{G} } \right) \varepsilon _\mathrm{W} \sigma T_\mathrm{W}^4 F_{\mathrm{G}\rightarrow \mathrm{W}} F_{\mathrm{W}\rightarrow \mathrm{G}} +\varepsilon _\mathrm{W} \left( {1-\varepsilon _\mathrm{W} } \right) L^{\downarrow }F_{\mathrm{W}\rightarrow \mathrm{S}} F_{\mathrm{W}\rightarrow \mathrm{W}} \nonumber \\&+\,\left( {1-\varepsilon _\mathrm{W} } \right) \varepsilon _\mathrm{G} \sigma T_\mathrm{G}^4 F_{\mathrm{W}\rightarrow \mathrm{G}} F_{\mathrm{W}\rightarrow \mathrm{W}} +\varepsilon _\mathrm{W} \varepsilon _\mathrm{W} \left( {1-\varepsilon _\mathrm{W} } \right) \sigma T_\mathrm{W}^4 F_{\mathrm{W}\rightarrow \mathrm{W}} F_{\mathrm{W}\rightarrow \mathrm{W}}, \end{aligned}$$
(36)
$$\begin{aligned} L_\mathrm{G}&= \varepsilon _\mathrm{G} \left( {F_{\mathrm{G}\rightarrow \mathrm{S}} L^{\downarrow }+2\varepsilon _\mathrm{W} F_{\mathrm{G}\rightarrow \mathrm{W}} \sigma T_\mathrm{W}^4 -\sigma T_\mathrm{G}^4 } \right) +2\varepsilon _\mathrm{G} \left( {1-\varepsilon _\mathrm{W} } \right) F_{\mathrm{W}\rightarrow \mathrm{S}} F_{\mathrm{G}\rightarrow \mathrm{W}} L^{\downarrow } \nonumber \\&+\left( {1-\varepsilon _\mathrm{W} } \right) \varepsilon _\mathrm{G} F_{\mathrm{G}\rightarrow \mathrm{W}} F_{\mathrm{W}\rightarrow \mathrm{G}} \sigma T_\mathrm{G}^4 +2\varepsilon _\mathrm{G} \varepsilon _\mathrm{W} \left( {1-\varepsilon _\mathrm{W} } \right) F_{\mathrm{W}\rightarrow \mathrm{W}} F_{\mathrm{G}\rightarrow \mathrm{W}} \sigma T_\mathrm{W}^4, \end{aligned}$$
(37)

where \(S_\mathrm{W}\) and \(S_\mathrm{G}\) are the net shortwave radiative fluxes for wall and ground respectively, \(L_\mathrm{W}\) and \(L_\mathrm{G}\) are the net longwave radiative fluxes for wall and ground respectively, \(S_\mathrm{D}\) and \(S_\mathrm{Q}\) are the direct and diffuse solar radiative fluxes, \(a\) is the albedo (solar reflectivity), \(F_{i\rightarrow j}\) are the view factors for radiation emitted from a generic surface \(i\) and received by surface \(j\), and \(l_\mathrm{shadow}\) is the normalized shadow length. The shadow length is estimated by (Kusaka et al. 2001),

$$\begin{aligned} l_\mathrm{shadow} =\left\{ {\begin{array}{l@{\quad }l} h\tan \theta _z \sin \theta _\mathrm{n}, &{} l_\mathrm{shadow} < w \\ w,&{} l_\mathrm{shadow} \ge w \\ \end{array}} \right. , \end{aligned}$$
(38)

where \(\theta _{z}\) is the solar zenith angle, \(\theta _{n}\) is the difference between the solar azimuth angle and canyon orientation. All view factors for radiative exchange between canyon facets are directly related to the aspect ratio \(h/w\) (Wang 2010).

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Song, J., Wang, ZH. Interfacing the Urban Land–Atmosphere System Through Coupled Urban Canopy and Atmospheric Models. Boundary-Layer Meteorol 154, 427–448 (2015). https://doi.org/10.1007/s10546-014-9980-9

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