• Allen, L., , F. Lindberg, , and C. Grimmond, 2011: Global to city scale urban anthropogenic heat flux: Model and variability. Int. J. Climatol., 31, 19902005, doi:10.1002/joc.2210.

    • Search Google Scholar
    • Export Citation
  • Andrejczuk, M., , W. Grabowski, , S. Malinowski, , and P. Smolarkiewicz, 2004: Numerical simulation of cloud-clear air interfacial mixing. J. Atmos. Sci., 61, 17261739, doi:10.1175/1520-0469(2004)061<1726:NSOCAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Anquetin, S., , C. Guilbaud, , and J. Chollet, 1998: The formation and destruction of inversion layers within a deep valley. J. Appl. Meteor., 37, 15471560, doi:10.1175/1520-0450(1998)037<1547:TFADOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Anquetin, S., , C. Guilbaud, , and J. Chollet, 1999: Thermal valley inversion impact on the dispersion of a passive pollutant in a complex mountainous area. Atmos. Environ., 33, 39533959, doi:10.1016/S1352-2310(99)00137-5.

    • Search Google Scholar
    • Export Citation
  • Argentini, S., , G. Mastrantonio, , and F. Lena, 1999: Case studies of the wintertime convective boundary-layer structure in the urban area of Milan, Italy. Bound.-Layer Meteor., 93, 253267, doi:10.1023/A:1002057414039.

    • Search Google Scholar
    • Export Citation
  • Arnfield, A., 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, 126, doi:10.1002/joc.859.

    • Search Google Scholar
    • Export Citation
  • Bader, D. C., , and T. B. McKee, 1985: Effects of shear, stability and valley characteristics on the destruction of temperature inversions. J. Climate Appl. Meteor., 24, 822832, doi:10.1175/1520-0450(1985)024<0822:EOSSAV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Baklanov, A., 2002: The mixing height in urban areas—A review. Proc. Workshop on Mixing Height and Inversions in Urban Areas, Toulouse, France, European Cooperation in Science and Technology Action 715, 9–28.

  • Berge, E., , A. Karppinen, , J. Kukkonen, , M. Køltzow, , and L. Slørdal, 2002: Simulations of wintertime inversions in northern European cities by use of NWP-models. Proc. Workshop on Mixing Height and Inversions in Urban Areas, Toulouse, France, European Cooperation in Science and Technology Action 715, 75–88.

  • Bonan, G., 2008: Forest and climate change: Forcings, feedbacks, and the climate benefits of forests. Science, 320, 14441449, doi:10.1126/science.1155121.

    • Search Google Scholar
    • Export Citation
  • Chen, X.-L., , H.-M. Zhao, , P.-X. Li, , and Z.-Y. Yin, 2006: Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens. Environ., 104, 133146, doi:10.1016/j.rse.2005.11.016.

    • Search Google Scholar
    • Export Citation
  • Chu, P. C., , Y. Chen, , S. Lu, , Z. Li, , and Y. Lu, 2008: Particulate air pollution in Lanzhou China. Environ. Int., 34 (5), 698713, doi:10.1016/j.envint.2007.12.013.

    • Search Google Scholar
    • Export Citation
  • Colette, A., , F. Chow, , and R. Street, 2003: A numerical study of inversion-layer breakup and the effects of topographic shading in idealized valleys. J. Appl. Meteor., 42, 12551272, doi:10.1175/1520-0450(2003)042<1255:ANSOIB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Colvile, R., , E. Hutchinson, , J. Mindell, , and R. Warren, 2001: The transport sector as a source of air pollution. Atmos. Environ., 35, 15371565, doi:10.1016/S1352-2310(00)00551-3.

    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1980: Stratocumulus-capped mixed layers derived from a three-dimensional model. Bound.-Layer Meteor., 18, 495527, doi:10.1007/BF00119502.

    • Search Google Scholar
    • Export Citation
  • Edgerton, S. A., and et al. , 1999: Particulate air pollution in Mexico City: A collaborative research project. J. Air Waste Manage. Assoc., 49, 12211229, doi:10.1080/10473289.1999.10463915.

    • Search Google Scholar
    • Export Citation
  • Fan, H., , and D. Sailor, 2005: Modeling the impacts of anthropogenic heating on the urban climate of Philadelphia: A comparison of implementations in two PBL schemes. Atmos. Environ., 39, 7384, doi:10.1016/j.atmosenv.2004.09.031.

    • Search Google Scholar
    • Export Citation
  • Foley, J., and et al. , 2005: Global consequences of land use. Science, 309, 570, doi:10.1126/science.1111772.

  • Grimmond, C., , and T. Oke, 2002: Turbulent heat fluxes in urban areas: Observations and a local-scale urban meteorological parameterization scheme (LUMPS). J. Appl. Meteor., 41, 792810, doi:10.1175/1520-0450(2002)041<0792:THFIUA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Grimmond, S., 2007: Urbanization and global environmental change: Local effects of urban warming. Geogr. J., 173, 8388, doi:10.1111/j.1475-4959.2007.232_3.x.

    • Search Google Scholar
    • Export Citation
  • Haeger-Eugensson, M., , and B. Holmer, 1999: Advection caused by the urban heat island circulation as a regulating factor on the nocturnal urban heat island. Int. J. Climatol., 19, 975988, doi:10.1002/(SICI)1097-0088(199907)19:9<975::AID-JOC399>3.0.CO;2-J.

    • Search Google Scholar
    • Export Citation
  • Jacobson, M., 2005: Fundamentals of Atmospheric Modeling. 2nd ed. Cambridge University Press, 813 pp.

  • Janhall, S., , K. Olofson, , P. Andersson, , J. Pettersson, , and M. Hallquist, 2006: Evolution of the urban aerosol during winter temperature inversion episodes. Atmos. Environ., 40, 53555366, doi:10.1016/j.atmosenv.2006.04.051.

    • Search Google Scholar
    • Export Citation
  • Jung, M., and et al. , 2011: Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res., 116, G00J07, doi:10.1029/2010JG001566.

    • Search Google Scholar
    • Export Citation
  • Kalthoff, N., , H. Binder, , M. Kossmann, , R. Vögtlin, , U. Corsmeier, , F. Fiedler, , and H. Schlager, 1998: Temporal evolution and spatial variation of the boundary layer over complex terrain. Atmos. Environ., 32, 11791194, doi:10.1016/S1352-2310(97)00193-3.

    • Search Google Scholar
    • Export Citation
  • Kanda, M., 2007: Progress in urban meteorology: A review. J. Meteor. Soc. Japan, 85B, 363383, doi:10.2151/jmsj.85B.363.

  • Lee, S.-H., , and H.-D. Kim, 2008: Effects of regional warming due to urbanization on daytime local circulations in a complex basin of the Daegu metropolitan area, Korea. J. Appl. Meteor. Climatol., 47, 14271441, doi:10.1175/JAMC1504.1.

    • Search Google Scholar
    • Export Citation
  • Lehner, M., , and A. Gohm, 2010: Idealised simulations of daytime pollution transport in a steep valley and its sensitivity to thermal stratification and surface albedo. Bound.-Layer Meteor., 134, 327351, doi:10.1007/s10546-009-9442-y.

    • Search Google Scholar
    • Export Citation
  • Li, Y., , R. Smith, , and V. Grubišic, 2009: Using surface pressure variations to categorize diurnal valley circulations: Experiments in Owens Valley. Mon. Wea. Rev., 137, 17531769, doi:10.1175/2008MWR2495.1.

    • Search Google Scholar
    • Export Citation
  • Malek, E., , T. Davis, , R. S. Martin, , and P. J. Silva, 2006: Meteorological and environmental aspects of one of the worst national air pollution episodes (January, 2004) in Logan, Cache Valley, Utah, USA. Atmos. Res., 79, 108122, doi:10.1016/j.atmosres.2005.05.003.

    • Search Google Scholar
    • Export Citation
  • Masson, V., 2006: Urban surface modeling and the meso-scale impact of cities. Theor. Appl. Climatol., 84, 3545, doi:10.1007/s00704-005-0142-3.

    • Search Google Scholar
    • Export Citation
  • Matzinger, N., , M. Andretta, , E. Gorsel, , R. Vogt, , A. Ohmura, , and M. Rotach, 2003: Surface radiation budget in an alpine valley. Quart. J. Roy. Meteor. Soc., 129, 877895, doi:10.1256/qj.02.44.

    • Search Google Scholar
    • Export Citation
  • Nadeau, D., and et al. , 2009: Estimation of urban sensible heat flux using a dense wireless network of observations. Environ. Fluid Mech., 9, 635653, doi:10.1007/s10652-009-9150-7.

    • Search Google Scholar
    • Export Citation
  • Offerle, B., , C. Grimmond, , K. Fortuniak, , and W. Pawlak, 2006: Intraurban differences of surface energy fluxes in a central European city. J. Appl. Meteor. Climatol., 45, 125136, doi:10.1175/JAM2319.1.

    • Search Google Scholar
    • Export Citation
  • Ogura, Y., , and N. Phillips, 1962: Scale analysis of deep and shallow convection in the atmosphere. J. Atmos. Sci., 19, 173179, doi:10.1175/1520-0469(1962)019<0173:SAODAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Oke, T., 1995: The heat island of the urban boundary layer: Characteristics, causes and effects. Wind Climate in Cities, J. E. Cermak et al., Eds., Kluwer Academic, 81–107.

  • Olofson, K., , P. Andersson, , M. Hallquist, , E. Ljungström, , L. Tang, , D. Chen, , and J. Pettersson, 2009: Urban aerosol evolution and particle formation during wintertime temperature inversions. Atmos. Environ., 43, 340346, doi:10.1016/j.atmosenv.2008.09.080.

    • Search Google Scholar
    • Export Citation
  • Panday, A. K., , and R. G. Prinn, 2009: Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: Observations. J. Geophys. Res.,114, doi:10.1029/2008JD009777.

  • Piotrowski, Z. P., , M. J. Kurowski, , B. Rosa, , and M. Z. Ziemianski, 2010: EULAG model for multiscale flows—Towards the petascale generation of mesoscale numerical weather prediction. Parallel Processing and Applied Mathematics, Lecture Notes in Computer Sciences, R. Wyrzykowski et al., Eds., Springer, 380–387.

  • Prusa, J., , P. Smolarkiewicz, , and A. Wyszogrodzki, 2008: EULAG, a computational model for multiscale flows. Comput. Fluids, 37, 11931207, doi:10.1016/j.compfluid.2007.12.001.

    • Search Google Scholar
    • Export Citation
  • Rampanelli, G., , D. Zardi, , and R. Rotunno, 2004: Mechanisms of up-valley winds. J. Atmos. Sci., 61, 30973111, doi:10.1175/JAS-3354.1.

  • Reuten, C., , D. Steyn, , K. Strawbridge, , and P. Bovis, 2005: Observations of the relation between upslope flows and the convective boundary layer in steep terrain. Bound.-Layer Meteor., 116, 3761, doi:10.1007/s10546-004-7299-7.

    • Search Google Scholar
    • Export Citation
  • Rizwan, A., , L. Dennis, , and C. Liu, 2008: A review on the generation, determination and mitigation of urban heat island. J. Environ. Sci. (China), 20, 120128, doi:10.1016/S1001-0742(08)60019-4.

    • Search Google Scholar
    • Export Citation
  • Romero, H., , M. Ihl, , A. Rivera, , P. Zalazar, , and P. Azocar, 1999: Rapid urban growth, land-use changes and air pollution in Santiago, Chile. Atmos. Environ., 33, 40394047, doi:10.1016/S1352-2310(99)00145-4.

    • Search Google Scholar
    • Export Citation
  • Rosenzweig, C., , W. Solecki, , S. Hammer, , and S. Mehrotra, 2010: Cities lead the way in climate-change action. Nature, 467, 909911, doi:10.1038/467909a.

    • Search Google Scholar
    • Export Citation
  • Rutllant, J., , and R. Garreaud, 1995: Meteorological air pollution potential for Santiago, Chile: Towards an objective episode forecasting. Environ. Monit. Assess., 34, 223244, doi:10.1007/BF00554796.

    • Search Google Scholar
    • Export Citation
  • Savijärvi, H., , and J. Liya, 2001: Local winds in a valley city. Bound.-Layer Meteor., 100, 301319, doi:10.1023/A:1019215031007.

  • Savov, P., , T. Skakalova, , I. Kolev, , and F. Ludwig, 2002: Lidar investigation of the temporal and spatial distribution of atmospheric aerosols in mountain valleys. J. Appl. Meteor., 41, 528541, doi:10.1175/1520-0450(2002)041<0528:LIOTTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schmidli, J., and et al. , 2011: Intercomparison of mesoscale model simulations of the daytime valley wind system. Mon. Wea. Rev., 139, 13891409, doi:10.1175/2010MWR3523.1.

    • Search Google Scholar
    • Export Citation
  • Schmidt, H., , and U. Schumann, 1989: Coherent structure of the convective boundary layer derived from large-eddy simulations. J. Fluid Mech., 200, 511562, doi:10.1017/S0022112089000753.

    • Search Google Scholar
    • Export Citation
  • Serafin, S., , and D. Zardi, 2010a: Daytime heat transfer processes related to slope flows and turbulent convection in an idealized mountain valley. J. Atmos. Sci., 67, 37393756, doi:10.1175/2010JAS3428.1.

    • Search Google Scholar
    • Export Citation
  • Serafin, S., , and D. Zardi, 2010b: Structure of the atmospheric boundary layer in the vicinity of a developing upslope flow system: A numerical model study. J. Atmos. Sci., 67, 11711185, doi:10.1175/2009JAS3231.1.

    • Search Google Scholar
    • Export Citation
  • Smolarkiewicz, P. K., , and J. M. Prusa, 2004: Forward-in-time differencing for fluids: Simulation of geophysical turbulence. Turbulent Flow Computation, D. Drikakas and B. J. Geurts, Eds., Springer, 279–312.

  • Smolarkiewicz, P. K., , L. Margolin, , and A. Wyszogrodzki, 2001: A class of nonhydrostatic global models. J. Atmos. Sci., 58, 349364, doi:10.1175/1520-0469(2001)058<0349:ACONGM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Smolarkiewicz, P. K., , R. Sharman, , J. Weil, , S. Perry, , D. Heist, , and G. Bowker, 2007: Building resolving large-eddy simulations and comparison with wind tunnel experiments. J. Comput. Phys., 227, 633653, doi:10.1016/j.jcp.2007.08.005.

    • Search Google Scholar
    • Export Citation
  • Taha, H., , S. Chang, , and H. Akbari, 2010: Meteorological and air quality impacts of heat island mitigation measures in three US cities. Lawrence Berkeley National Laboratory Rep. LBL-44222, 51 pp.

  • Toro, M. V., , J. J. Ramírez, , R. A. Quiceno, , and C. A. Zuluaga, 2001: Cálculo de la emisión vehicular de contaminantes atmosféricos en la ciudad de Medellín mediante factores de emisión Corinair. Rev. Acodal, 191, 4249.

    • Search Google Scholar
    • Export Citation
  • Wallace, J., , D. Corr, , and P. Kanaroglou, 2010: Topographic and spatial impacts of temperature inversions on air quality using mobile air pollution surveys. Sci. Total Environ., 408, 50865096, doi:10.1016/j.scitotenv.2010.06.020.

    • Search Google Scholar
    • Export Citation
  • Warner, T., 2011: Numerical Weather and Climate Prediction. Cambridge University Press, 526 pp.

  • Welch, T., , P. Smolarkiewicz, , R. Rotunno, , and B. Boville, 2001: The large-scale effects of flow over periodic mesoscale topography. J. Atmos. Sci., 58, 14771492, doi:10.1175/1520-0469(2001)058<1477:TLSEOF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wesson, G., , K. Gabriel, , and L. Chun-Ta, 2001: Sensible heat flux estimation by flux variance and half-order time derivative methods. Water Resour. Res., 37, 23332343, doi:10.1029/2001WR900021.

    • Search Google Scholar
    • Export Citation
  • Whiteman, C., 1982: Breakup of temperature inversions in deep mountain valleys: Part I. Observations. J. Appl. Meteor., 21, 270289, doi:10.1175/1520-0450(1982)021<0270:BOTIID>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Whiteman, C., 2000: Mountain Meteorology: Fundamentals and Applications. Oxford University Press, 355 pp.

  • Whiteman, C., , and T. McKee, 1982: Breakup of temperature inversions in deep mountain valleys: Part II. Thermodynamic model. J. Appl. Meteor., 21, 290302, doi:10.1175/1520-0450(1982)021<0290:BOTIID>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Whiteman, C., , B. Pospichal, , S. Eisenbach, , P. Weihs, , C. Clements, , R. Steinacker, , E. Mursch-Radlgruber, , and M. Dorninger, 2004: Inversion breakup in small Rocky Mountain and Alpine basins. J. Appl. Meteor., 43, 10691082, doi:10.1175/1520-0450(2004)043<1069:IBISRM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wilson, J. G., , S. Kingham, , J. Pearce, , and A. P. Sturman, 2005: A review of intraurban variations in particulate air pollution: Implications for epidemiological research. Atmos. Environ., 39, 64446462, doi:10.1016/j.atmosenv.2005.07.030.

    • Search Google Scholar
    • Export Citation
  • Yao, W., , and S. Zhong, 2009: Nocturnal temperature inversions in a small, enclosed basin and their relationship to ambient atmospheric conditions. Meteor. Atmos. Phys., 103, 195210, doi:10.1007/s00703-008-0341-4.

    • Search Google Scholar
    • Export Citation
  • Zhong, S., , C. Whiteman, , and X. Bian, 2004: Diurnal evolution of three-dimensional wind and temperature structure in California’s Central Valley. J. Appl. Meteor., 43, 16791699, doi:10.1175/JAM2154.1.

    • Search Google Scholar
    • Export Citation
  • Zoumakis, N., , and G. Efstathiou, 2006: Parameterization of inversion breakup in idealized valleys. Part II: Thermodynamic model. J. Appl. Meteor. Climatol., 45, 609623, doi:10.1175/JAM2354.1.

    • Search Google Scholar
    • Export Citation
  • View in gallery

    Vertical θ profiles taken every hour from 0600 to 1800 LST in the center of the valley. Each panel corresponds to a different urban area fraction (ranging from 0% to 100%) and shows the evolution in time from the initial inversion profile on the left to the final profile on the right. The arrow indicates the profile corresponding to 1200 LST, and the horizontal dotted line indicates the altitude of the top of the valley.

  • View in gallery

    Consecutive longitudinal mean fields of the cross-valley w in the (left) rural, (center) 40% urbanized, and (right) 80% urbanized valleys. Isentropes are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

  • View in gallery

    As in Fig. 2, but for u.

  • View in gallery

    As in Fig. 2, but for resolved TKE.

  • View in gallery

    Passive tracer mixing ratio (mg kg−1) in the (left) 40% urbanized and (right) 80% urbanized valleys (see text for details). Isentropes are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

  • View in gallery

    Heights of the bottom (dotted line) and top (solid line) of the inversion layer in the center of the valley for different urban area fractions (ranging from 0% to 100%).

  • View in gallery

    Idealized sketch of the evolution in time of the BTI process and the mean cross-valley circulation depicting the inversion layer (dashed lines), the main wind flows (black arrows), and the resolved TKE field (shading), for the (left) rural, (center) 40% urbanized, and (right) 80% urbanized valleys. Isentropes (solid lines) are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

  • View in gallery

    Consecutive longitudinal mean fields of the (left) cross-valley w and (center) u wind speed components, and (right) the passive tracer mixing ratio (mg kg−1) in the 20% urbanized valley. Isentropes are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 402 402 95
PDF Downloads 300 300 71

Effects of Urbanization on the Temperature Inversion Breakup in a Mountain Valley with Implications for Air Quality

View More View Less
  • 1 El Grupo de Ingeniería y Gestión Ambiental, Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia, Medellín, Colombia
  • | 2 Institute for Atmospheric Physics, Johannes Gutenberg-University Mainz, Mainz, Germany
© Get Permissions
Full access

Abstract

Many cities located in valleys with limited ventilation experience serious air pollution problems. The ventilation of an urban valley can be limited not only by orographic barriers, but also by urban heat island–induced circulations and/or the capping effect of temperature inversions. Furthermore, land-use/-cover changes caused by urbanization alter the dynamics of temperature inversions and urban heat islands, thereby affecting air quality in an urban valley. By means of idealized numerical simulations, it is shown that in a mountain valley subject to temperature inversions urbanization can have an important influence on air quality through effects on the inversion breakup. Depending on the urban area fraction in the simulations, the breakup time changes, the cross-valley wind system can evolve from a confined to an open system during the daytime, the slope winds can be reversed by the interplay between the urban heat island and the temperature inversion, and the breakup pattern can migrate from one dominated by the growth of the convective boundary layer to one also involving the removal of mass from the valley floor by the upslope winds. The analysis suggests that the influence of urbanization on the air quality of an urban valley may lead to contrasting and possibly counterintuitive effects when considering temperature inversions. More urban land does not necessarily imply worse air quality, even when considering that the amount of pollutants emitted grows with increased urbanization.

Corresponding author address: Angela M. Rendón, GIGA, Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia (UdeA), Calle 70, No. 52-21, Of. 20-414, Medellín, Colombia. E-mail: angela.rendon@udea.edu.co

Abstract

Many cities located in valleys with limited ventilation experience serious air pollution problems. The ventilation of an urban valley can be limited not only by orographic barriers, but also by urban heat island–induced circulations and/or the capping effect of temperature inversions. Furthermore, land-use/-cover changes caused by urbanization alter the dynamics of temperature inversions and urban heat islands, thereby affecting air quality in an urban valley. By means of idealized numerical simulations, it is shown that in a mountain valley subject to temperature inversions urbanization can have an important influence on air quality through effects on the inversion breakup. Depending on the urban area fraction in the simulations, the breakup time changes, the cross-valley wind system can evolve from a confined to an open system during the daytime, the slope winds can be reversed by the interplay between the urban heat island and the temperature inversion, and the breakup pattern can migrate from one dominated by the growth of the convective boundary layer to one also involving the removal of mass from the valley floor by the upslope winds. The analysis suggests that the influence of urbanization on the air quality of an urban valley may lead to contrasting and possibly counterintuitive effects when considering temperature inversions. More urban land does not necessarily imply worse air quality, even when considering that the amount of pollutants emitted grows with increased urbanization.

Corresponding author address: Angela M. Rendón, GIGA, Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia (UdeA), Calle 70, No. 52-21, Of. 20-414, Medellín, Colombia. E-mail: angela.rendon@udea.edu.co

1. Introduction

Many cities located in valleys with limited ventilation experience serious air pollution problems of concern for public health (Edgerton et al. 1999; Romero et al. 1999; Panday and Prinn 2009). The transport of pollutants out of an urban valley atmosphere can be limited not only by orographic barriers, but also by urban heat island–induced circulations (Haeger-Eugensson and Holmer 1999; Savijärvi and Liya 2001) and/or the presence of temperature inversions near the surface (Janhall et al. 2006; Yao and Zhong 2009). On a local scale, the characteristics of the urban land have a large influence on the heat and momentum transfer between the land surface and the atmosphere (Arnfield 2003; Grimmond 2007; Kanda 2007). Therefore, land-use/-cover changes induced by urbanization modify the dynamics of local winds (e.g., Lee and Kim 2008), the urban heat island (UHI) (e.g., Chen et al. 2006), and the local temperature inversions, with impacts on air quality and implications for urban planning (Romero et al. 1999; Janhall et al. 2006; Rizwan et al. 2008; Allen et al. 2011).

Although the term urbanization may refer to different processes of land-use/-cover change, here we use it only to refer to an expansion of a homogeneous urban area (further details are given below). Therefore, as a simplification, we are not considering processes such as population densification or any spatial heterogeneity within the urban area.

The temperature inversion is a common phenomenon in the lower atmosphere of urban areas and mountain valleys (Oke 1995; Whiteman 2000). Although the temperature inversion is sometimes defined in terms of absolute atmospheric temperature (e.g., Jacobson 2005, p. 54), here we consider that an inversion occurs when the potential temperature increases with height above the surface (i.e., when the potential temperature gradient is positive; Whiteman 1982). The atmospheric layer within which the potential temperature gradient is positive is termed an inversion layer.

The process of destruction of the inversion layer is defined as the breakup of the temperature inversion (BTI). Over flat, homogeneous terrain, inversions are destroyed predominantly by the upward growth of a convective boundary layer (CBL) from the ground. In a valley, however, inversions are destroyed not only by a CBL that develops over valley surfaces, but also as a result of the removal of air from the base of the inversion by the upslope flows that develop over heated sidewalls, thus inducing subsidence warming over the valley center (Whiteman 1982; Zoumakis and Efstathiou 2006). The interplay between the growth of a CBL and the removal of air from the base of the inversion leads to three different patterns of BTI in mountain valleys (Whiteman and McKee 1982; Whiteman 1982). These BTI patterns will be described and considered in section 4.

The dynamics of the temperature inversion (formation and breakup) is mainly driven by the heating of the surface, which is largely influenced by urbanization. These dynamics can exert strong effects on the air quality of urban areas, especially when they are located in complex terrain such as mountain valleys. A number of studies confirm the association between the occurrence and persistence of temperature inversions and the presence of high concentrations of air pollutants over urban areas. For instance, one of the worst national air pollution episodes in the United States took place in the city of Logan in the Cache Valley of Utah and was largely caused by the trapping of pollutants owing to a strong inversion (Malek et al. 2006). Also, heavy air pollution events experienced in Santiago, Chile (Rutllant and Garreaud 1995), and the Lanzhou urban valley, China (Chu et al. 2008), have been associated with low-level temperature inversions. In several Nordic urban sites, winter temperature inversions are a major cause for exceeding air-quality legislation thresholds for traffic-related pollutants. In such situations the BTI exerts a strong influence on air quality through the effects on the rates of vertical mixing and the consequent distribution of urban aerosols (Janhall et al. 2006; Olofson et al. 2009).

Previous studies have shown that the dynamics and effects of the temperature inversion vary depending on several factors, especially those associated with the topography of the terrain and the surface energy balance. For instance, in the city of Hamilton, Ontario, Canada, the air quality impacts of emissions from industry and traffic are exacerbated by temperature inversions and strongly controlled by the complex topography of the terrain (Wallace et al. 2010). The numerical simulations by Colette et al. (2003) show that the lifetime of the inversion layer is different in valleys with different widths and depths, and that the topographic shading can delay the BTI. According to the simulations by Anquetin et al. (1998), the BTI also varies with season, because in summer the more effective solar radiation speeds up the BTI. This seasonal variation may alternatively be interpreted, in a more general way, as a consequence of increasing the heating of the surface (as it is in summer), which could be a result of land-use/-cover changes (such as those caused by urbanization). This is consistent with the simulations of Bader and McKee (1985), which show that decreasing the surface heating rate in a valley delays the BTI, although the development of the structure of the boundary layer proceeds similarly. This latter study also shows that as the valley floor widens, the slope effects become increasingly less important until the valley atmosphere behaves similarly to boundary layers over flat terrain.

Given the dependence of the BTI on the topography of the terrain, the present study is limited in that we did not investigate different topographical settings. An analysis of this will be given in a forthcoming paper. However, studying the influence of urbanization on the temperature inversion dynamics through its effects on the surface heating is critical for understanding the interplay between land-cover change, local meteorology, and air quality. Cities obviously produce air pollution, but what has been less well studied is the impact of the boundary layer dynamics produced by the surface energy balance on this pollution (Masson 2006). In this regard, here we show that in an urban valley subject to temperature inversions, land-use/-cover changes resulting from urbanization, which include changes in the size of the UHI, have an important influence on air quality through effects on the BTI. To show this, we carried through and analyzed idealized simulations with an Eulerian–Lagrangian numerical model (EULAG) to study the BTI in a mountain valley with varying fractions of urban and rural land cover, as well as the transport of a passive tracer released from the urban surface. Although idealized, our model experiment is loosely based in a reference urban valley, the Aburrá valley in the Colombian Andes, where urbanization has been progressing rapidly and the urban area (Medellín and its neighboring cities) has expanded beyond the valley floor toward the sidewalls. Our analyses examine various effects resulting from the urban land expansion.

The remainder of the paper is organized as follows: the model and the experiment are described in section 2, results are presented in section 3 and discussed in section 4, and the conclusions are drawn in section 5.

2. Model description and experiment design

a. Model description

The numerical model employed in this study has been thoroughly documented in the literature, mainly in studies by P. K. Smolarkiewicz and others (Prusa et al. 2008 and references therein). EULAG is a nonhydrostatic model for simulating fluid flows across a wide range of scales and geophysical flows, whose name refers to its capability of solving the underlying anelastic equations within either an Eulerian (flux form) or a Lagrangian (advective form) framework. Different variants of EULAG have been applied to investigate orographic flows (Welch et al. 2001; Piotrowski et al. 2010), flows around urban buildings (Smolarkiewicz et al. 2007), turbulence (Smolarkiewicz and Prusa 2004), cloud dynamics (Andrejczuk et al. 2004), and global atmospheric circulation (Smolarkiewicz et al. 2001), among other topics generally related to the fluid dynamics of compressible or incompressible fluids. EULAG has been found to simulate the evolution of a daytime valley wind system, with results qualitatively similar to those of nine other mesoscale models [see the intercomparison study by Schmidli et al. (2011)].

EULAG admits several optional formulations of the equations of motion. Here, we are concerned with valley-scale thermal flows, so we use EULAG as a nonhydrostatic model that solves the anelastic equations of motion in terrain-following coordinates, under the Ogura and Phillips (1962) approximation of the atmosphere. The model employs an explicit predictive equation for turbulent kinetic energy (TKE hereinafter) and uses a local Deardorff-type TKE closure scheme derived for large eddy simulations for which the length scale is based on the grid spacing (Deardorff 1980). Surface drag is accounted for through the usual bulk formula with a drag coefficient (CD = 0.01). Furthermore, we modify the EULAG code to introduce a time- and space-varying forcing that represents the diurnal cycle of sensible heat flux over the mountain valley (see section 2b).

b. Experiment design

The model experiment performed in this study is based on the general idea that the comparison of paired simulations with different representations of land cover reveals the environmental effects of land-cover change (Bonan 2008). We performed simulations with different land-cover distributions involving two classes—urban and rural land—varying the urban area fraction in the valley every 20% between 0% and 100%, and then we compared the results between the six cases. In all cases, the urban area is homogeneous and grows symmetrically from the center of the valley toward the sloping sidewalls. It is important to bear in mind that a 40% or greater urban area fraction implies that urbanization spreads to the valley sidewalls (e.g., Fig. 2 in section 3, where the thick outline of the orography marks the urban area). All simulations started with a condition of temperature inversion and were performed during the daytime between 0600 local standard time (LST) and 1800 LST.

The urban and rural areas are distinguished only by differences in the specified heat flux. However, we tested the sensitivity of our results to the inclusion of roughness effects under the assumption that the urban areas are rougher than the rural ones, and found no significant differences. In these test runs the drag coefficients were 0.01 and 0.001 for the urban and rural land, respectively. We assume that the sensible heat flux from urban areas is higher than that from rural ones, which agrees with the idea that the urban energy balance is typically characterized by a high Bowen ratio owing to the thermal properties and impermeability of urban surfaces like concrete or asphalt (Offerle et al. 2006; Nadeau et al. 2009). For instance, Offerle et al. (2006) reported values of the Bowen ratio for an urban area ranging from ~0.5 to ~4.5 depending on the fraction of the vegetated surface. The idealized diurnal cycle of sensible heat flux was defined through the function
e1
where Qh(x, t) is the space–time varying flux of sensible heat (J m−2 s−1); Qr(x) is a maximum reference value depending on whether the surface at x is urban [Qr(x) = 300 J m−2 s−1] or rural [Qr(x) = 90 J m−2 s−1]; t is the time since the initial time (0600 LST), ranging from 0 to 12 h; and T is the total time of the simulation (T = 12 h). Note that the sensible heat flux peaks at noon.

There is no dependence of Qh(x, t) on y (the along-valley direction), because of the symmetry and orientation of the valley (topography is described below in section 2c). We assume that the valley is oriented east–west and located at 0° latitude, so that the sun follows a path along the valley, and there is no topographic shading. The Coriolis effect is neglected because of the spatial scale of our study and the location of the valley.

The sensible heat function [Eq. (1)] prescribes a symmetric sensible heat flux throughout the simulations. This is in good agreement with previous simulations of thermally driven valley winds by Serafin and Zardi (2010a), where the symmetry of the surface forcing is substantially maintained during the simulation time (see their Fig. 1), although they did not prescribe sensible heat but simulated it through a bulk relationship. Equation (1) involves the assumption that the shape of the diurnal cycle of sensible heat is similar to that of net solar radiation (see, e.g., Grimmond and Oke 2002; Matzinger et al. 2003). Values produced by Eq. (1) are on the same order of magnitude as those reported in the literature for different urban and rural areas (e.g., Wesson et al. 2001; Grimmond and Oke 2002; Jung et al. 2011) and can be considered as being representative of our reference urban valley (the Aburrá valley).

To obtain insights into the air quality impacts, we simulate the transport of a passive tracer released from the urban area, by assuming that this area acts as a uniform and continuous source, that is, there is no spatial or temporal heterogeneity of emissions. Urban areas can be considered one of the major sources of air pollution as a result of multiple factors such as the emission of gases by the industrial (Rosenzweig et al. 2010) or the transport sectors (Colvile et al. 2001). Hence, when the percentage of urban land cover increases, the amount of pollutants released to the atmosphere is also expected to increase.

In summary, we assume that urbanization inherently leads to an areal expansion of both the UHI and the emission area, which is consistent with the idea that, for instance, as the urban land expands so does the number of cars in the city. Intraurban variations of pollution (Wilson et al. 2005) and surface energy fluxes (Offerle et al. 2006) are still very complex issues that are strongly dependent on the particularities of each city. Therefore, we regard our assumption of intraurban homogeneity as the simplest possibility, although other assumptions may be raised as well. Neither chemical reactions nor the radiative effects of pollutants in the atmosphere are considered, and we do not include moisture in our simulations at this stage, because our main concern is related to thermally driven winds on a dry atmosphere, and to the BTI, which is mainly driven by heating processes (Whiteman and McKee 1982). This approach is similar to that of Anquetin et al. (1998), Colette et al. (2003), and Serafin and Zardi (2010a). We will leave consideration of moist processes and the intraurban spatial heterogeneity to future work.

c. Model setup

1) Topography and simulation domain

The model experiments are carried out in a three-dimensional domain of 25 600 m in the x direction (across the valley) and 6400 m in the y direction (along the valley), extending from the surface to a height of 6400 m (z direction). Figure 2, described below in section 3, clarifies this geometry by showing the x and z directions in the cross section of the valley. The extension in the y direction (normal to the plane shown in Fig. 2) allows us to capture the dynamics of large convective eddies inside the valley, as well as to reduce the influence of the boundary effects in the mouths of the valley on the rest of the domain. The depth of the domain (z) permits us to represent the evolution of vertical motions and thermal plumes over the valley. The dimensions of the modeling domain are similar to that of Anquetin et al. (1998), Colette et al. (2003), and Serafin and Zardi (2010b), and they are representative of our reference valley.

Following Rampanelli et al. (2004), the idealized topography is represented by the function
e2
where z(x) is the height of the terrain above the valley floor (m), h is the maximum depth of the valley (h = 1000 m), x0 is the x coordinate of the center of the valley (x0 = 12 800 m), sx is the width of the sloping sidewalls (sx = 8000 m), and υx is the half-width of the valley floor (υx = 2000 m). Equation (2) represents a symmetrical cross section, constant along the y direction. In addition, two 2800-m-length plateaus are included in the modeling domain in order to have the lateral boundaries far from the top of the sidewalls. The average steepness of the sidewalls is 12.5%, and the transitions between them and the plateaus and the valley floor are smooth in order to prevent abrupt changes in wind direction. The vertical grid is set with terrain-following coordinates stretched with a minimum grid size of 25 m at the surface and a maximum grid size of 121 m at the top of the simulation domain.

2) Initial and boundary conditions

The simulations are initialized with a temperature inversion profile that is constant over the whole valley with a Brunt–Väisälä frequency of N2 = 0.019 s−1, corresponding to a vertical potential temperature gradient of 11 K km−1 in the lowest 800 m above the valley floor, which represents a strong temperature inversion. Above the top of the inversion we assume neutral stratification (∂θ/∂z = 0 for z > 800 m). We assume that the atmosphere is at rest at the beginning of the simulations. These initial conditions are similar to those used in previous studies of the temperature inversion in idealized mountain valleys by Anquetin et al. (1998) and Colette et al. (2003).

Since we are concerned with the local valley winds, we neglect the influence of synoptic winds, under the assumption of weak synoptic conditions. To represent this, all the lateral boundary conditions are defined as periodic. The bottom and the top of the domain are treated as impermeable boundaries. A Rayleigh damping layer of 2000 m is included below the top of the domain, to avoid unrealistic reflection of upward-propagating internal gravity waves aloft (Warner 2011). The model setup is summarized in Table 1.

Table 1.

Summary of the model setup.

Table 1.

3. Temperature inversion breakup and wind fields in the valley

In this section we present the simulations of the BTI process in the valley (see section 2 for details) under different urban and rural land distributions: recall that the urban area fraction in the valley varies from 0% to 100% every 20%. Our results show the time variation of the potential temperature θ profile in the center of the valley, the horizontal u and vertical w wind fields, and the resolved TKE in the valley cross section, during the daytime from 0600 to 1800 LST. Our analyses are focused on the dynamics of the atmosphere in the valley cross section (the x direction), so all of the results are averaged along the valley (the y direction). We numerically verify that this averaging procedure does not affect the qualitative behavior of our results; there are only minor quantitative changes with respect to a single cross section in the center of the valley. The plots do not show the entire simulation domain but only a part of it around the valley, which is the selected region of interest.

We first consider the BTI as described by consecutive vertical profiles of θ in the center of the valley (section 3a), then we consider several features of the cross-valley wind system and its relationship with BTI (section 3b), and finally we give insights into the impacts of the circulation on the transport of pollutants released from the urban surface (section 3c).

a. Temperature inversion breakup

The time variation of vertical θ profiles in the center of the valley for different percentages of urban land cover is depicted in Fig. 1, where the inversion layer is evident. This layer is destroyed faster (i.e., the BTI is accelerated) as the urban area fraction increases, which is in agreement with the simulations by Bader and McKee (1985), Anquetin et al. (1998), and Colette et al. (2003), showing that decreasing the surface heating rate in a valley delays the BTI. Note that the inversion layer is finally destroyed at a time when the height of the CBL grows to the height of the top of the inversion layer, thus producing a constant potential temperature atmosphere in the valley (see, e.g., Fig. 2 of Whiteman 1982).

Fig. 1.
Fig. 1.

Vertical θ profiles taken every hour from 0600 to 1800 LST in the center of the valley. Each panel corresponds to a different urban area fraction (ranging from 0% to 100%) and shows the evolution in time from the initial inversion profile on the left to the final profile on the right. The arrow indicates the profile corresponding to 1200 LST, and the horizontal dotted line indicates the altitude of the top of the valley.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

Interestingly, there are only small differences between the sequences of θ profiles corresponding to the highest percentages (80% and 100%) of urban land cover (Figs. 1e,f), thus suggesting that there is an upper percentage of urban land above which the BTI is not further accelerated by augmenting the urban area fraction. We attribute this to the location of the rural–urban fringe relative to the altitude of the top of the inversion layer: for the highest urban area fractions the former is above the latter, so in both cases all of the land below the top of the inversion layer is urban and, therefore, the heating of the surface is the same. Furthermore, any additional heat from the urban land above the inversion top is distributed over a very large volume and, therefore, it is hardly noticeable. We interpret this as a saturation effect in our model setup, which occurs when the heat released from the surface is distributed either in the atmospheric column above the inversion layer or in the entire atmospheric column after the BTI. This effect cannot be generalized to all situations because it may change if, for instance, the conditions above the inversion were not neutral.

For the lowest percentages of urban land (≤20%; Figs. 1a,b), although the depth of the inversion layer decreases throughout the daytime, a temperature inversion remains until the end of the simulations. This is in agreement with observations of the temperature inversion in mountain valleys subject to weak thermal forcing, where a temperature inversion can persist throughout the day and can even remain in the valley for several days (Savov et al. 2002).

b. Wind fields

The BTI is intrinsically related to the dynamics of thermal cross-valley winds. The components of the mean wind field in the valley cross section for different urban area fractions are depicted every 3 h in Fig. 2 (vertical wind component w) and Fig. 3 (horizontal wind component u). These wind fields are characterized by various features that are described below.

Fig. 2.
Fig. 2.

Consecutive longitudinal mean fields of the cross-valley w in the (left) rural, (center) 40% urbanized, and (right) 80% urbanized valleys. Isentropes are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

Fig. 3.
Fig. 3.

As in Fig. 2, but for u.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

In all simulations (rural and urban valleys), the flow field is initially symmetric owing to the symmetry of the topography and of the initial conditions. Symmetry is substantially maintained on the slopes throughout the daytime but not above the valley floor because of the development of randomly spaced thermals. The development of these thermals is in good agreement with the simulations of thermally driven winds in a wide valley by Serafin and Zardi (2010a).

Although the initial atmospheric conditions and the topography are the same in all valleys, the slope winds evolve differently depending on the urban area fraction. The rural valley produces relatively weak upslope winds prevailing during the daytime with a maximum speed around 0.5 m s−1. These upslope flows are compensated by horizontal winds below the top of the inversion layer, thus forming a closed circulation within the CBL. The persistence of upslope winds during the daytime is the typical condition in mountain valleys (Whiteman 2000, p. 187). These results are an example of a confined circulation system within a valley (e.g., Li et al. 2009), which can be caused by a temperature inversion (Yao and Zhong 2009). Closed circulations within a CBL have also been observed in regions with steep terrain (Reuten et al. 2005).

The atmosphere in the urban valleys is subject to stronger vertical mixing than that of the rural valley, as a result of the higher heating of the urban surface. This produces differences in the slope wind patterns. In the 40% urbanized valley, downslope winds appear close to the rural–urban fringe, as distinct from the prevailing upslope winds in the rural and more urbanized valleys (Figs. 2d–i and 3d–i). This difference can be explained by effects related to both the urban heat island and the temperature inversion. The urban heat island in the core of the 40% urbanized valley, resulting from the differential heating of the surface (urban or rural), creates buoyant thermals that induce air convergence from the surrounding rural areas. It is well known that the differential heating of the surface promotes the formation of rising thermals (Jacobson 2005, p. 22). Furthermore, thermal convection in the core of the valley, along with the presence of the inversion layer that restricts the vertical free convection, causes downslope compensating winds below the inversion layer and close to the rural–urban fringe. The heat island’s effect on creating downslope winds toward the city near the surface was also found in simulations of local winds in a valley city by Savijärvi and Liya (2001). As will be shown in section 4, downslope winds also appear in the 20% urbanized valley.

In contrast to the downslope winds found in the 20% and 40% urbanized valleys, upslope winds prevail throughout the daytime in the 80% urbanized valley. We attribute this difference to effects related to the extension of urban land along the sidewalls of the valley. Note that for 80% of urban land the outer edge of the urban area is close to the mountaintop, while for 20% or 40% of urban land this boundary is close to or within the valley floor. When the sidewalls are highly urbanized, the heating of the surface enhances thermal convection and upslope flows, in turn strengthening the transport of air from the bottom of the valley to the atmosphere above the inversion layer. As a consequence, the compensating flow responsible for the downslope winds in the 20% and 40% urbanized valleys does not appear in the 80% urbanized valley.

Upslope winds detach from the ridgetops and create thermal plumes in the rural and urban valleys. The intensity of the plumes is nearly the same at 0900 LST in all cases (Figs. 2a–c), but evident differences appear at noon: while the rural and the 40% urbanized valleys produce upward motions in the mountaintops with maximum speeds of around 0.3 m s−1 (Figs. 2d,e), in the more urbanized valley thermal plumes reach maximum updraft speeds of about 1.0 m s−1 (Fig. 2f). The difference between the more urbanized valley and the other two valleys suggests that the extra heat produced from the extended urban land is resulting in more energetic plumes. On the other hand, the similarity between the rural and the 40% urbanized valleys can be related to the downslope winds appearing in the second case. The higher heating of the surface in the 40% urbanized valley, in comparison to the rural one, does not result in more energetic thermal plumes because the extra energy is expended in the circulation involving the downslope winds, as a result of the interplay between the urban heat island and the temperature inversion. Moreover, such extra energy results in more and larger plumes within the CBL of the 40% urbanized valley than in the rural one.

Thermal plumes detaching from the mountaintops are linked to compensating horizontal winds blowing toward the center of the valley with maximum intensities of about 2.0 m s−1, in a layer approximately 700 m above the mountaintop level (i.e., z ~1700 m). These winds advect warm air and thermal energy from the plumes toward the valley center, in turn producing air subsidence. This compensating flow is similar to that found by Serafin and Zardi (2010a), and it is in agreement with the fact that the ascending motions related to upslope flows and thermal plumes must be compensated by descending flows elsewhere, because of mass continuity. However, in contrast to that study, we also found that air subsidence does not reach the valley core since the descending winds deviate toward the mountaintops as a consequence of the inversion layer, which restricts the downward motions. Hence, we found horizontal winds diverging from the valley center just above the inversion layer, so that a circulation cell is evident above such a layer (Figs. 3d–f). The formation of this circulation cell results from the effect of the inversion layer in decoupling the wind field above and below it, as the temperature inversion restricts both the growth of the CBL and subsidence from the atmosphere aloft. A similar decoupling effect was observed over the urban area of Milan, Italy (see Fig. 2 of Argentini et al. 1999).

Figure 2 also shows the development of a CBL at the floor of all of the valleys, exhibiting a structure of convective circulations composed by updrafts (thermals) and downdrafts. This structure agrees well with the well-known structure of the CBL arising when turbulence generated by buoyancy due to upward heat flux from the surface dominates relative to turbulence generated by mean shear (Schmidt and Schumann 1989). Since the CBL is capped by the inversion layer, its growth is directly linked to the BTI. In the rural valley (Fig. 2, left) thermals never exceed a vertical extent of 500 m, while exhibiting maximum vertical wind speeds not greater than 0.4 m s−1. In contrast, thermals in the 40% urbanized valley (Fig. 2, center) reach a vertical extent between 700 m (at 1200 LST) and 1500 m (at 1500 LST), and maximum vertical wind speeds of around 1 m s−1, while the temperature inversion persists. In the 80% urbanized valley (Fig. 2, right), thermals reach maximum vertical wind speeds around 1 m s−1 and a vertical extent of 700 m before the BTI (at 1200 LST), and the development of the CBL at the valley floor continually elevates the bottom of the inversion layer until the breakup process is completed (at 1500 LST).

The mean field of the resolved TKE in the cross section of the valleys is depicted in Fig. 4. This figure confirms that the flow field in the valley floor is dominated by thermal turbulence driving the growth of the CBL, while in the slopes it is dominated by the slope flow. This is in agreement with simulations showing that turbulence is better developed above a valley floor than over the slopes (Serafin and Zardi 2010a), and also confirms that turbulence is enhanced over the urban areas. The TKE above the floor of the rural valley peaks at around 0.3 m2 s−2, while in the urban valleys such peak value is more than tripled (~1.0 m2 s−2). The weak turbulence in the rural valley can be explained by considering the interplay of two factors: the low heating of the rural surface that diminishes the available energy to promote buoyancy and thermal convection, and the persistent flow divergence at the slopes, which continually removes the TKE produced on the surface.

Fig. 4.
Fig. 4.

As in Fig. 2, but for resolved TKE.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

Turbulence is more efficiently generated by buoyancy above the urban areas, so it is better developed over the urban valleys that we studied than over the rural one. This is in good agreement with the well-known fact that cities increase the production of thermal turbulence compared to their surrounding rural areas, as a result of the increase in the surface heat flux and changes in stability accompanying the urban heat island (Oke 1995; Baklanov 2002). Better development of turbulence can enhance the BTI because of the effect of the CBL on the bottom of the inversion layer.

A comparison between Figs. 4h and 4i reveals an effect of temperature inversion on turbulence within the valley atmosphere. Turbulence remains substantially confined within the core of the less urbanized valley, while in the more urbanized example the TKE generated at the surface is continually removed by free convection after the BTI.

Figures 24 also show that the urban area fraction influences whether the diurnal valley circulation is a “confined” or an “open” system, that is, whether the circulation in the valley atmosphere is decoupled (confined system) or coupled (open system) to that in the overlying atmosphere. For instance, Fig. 3 shows that for low extents of urban land (Fig. 3, center), the valley circulation is confined to the valley during almost the entire daytime, while for high extents of urban land (Fig. 3, right) there is a transition from a confined to an open system during the afternoon (Figs. 3f–l). Decoupling is caused by the effect of the inversion layer in restricting vertical motions (see, e.g., Kalthoff et al. 1998; Zhong et al. 2004). The transition from a confined to an open system in a valley atmosphere is also expected to be dependent on some topographic features (Li et al. 2009); however, as mentioned in the introduction, in this study we did not consider different topographical settings.

c. Transport of pollutants

To consider the air quality implications, we simulate the transport of a passive tracer continuously emitted from the urban area, under the influence of the BTI (further details are given in section 2b). Figure 5 shows the mixing ratio of the tracer for different urban area fractions (40% and 80%). We assumed that the tracer is emitted only from the urban area, and in these areas the surface flux is given by 17 kg−1 h−1 km−2. At each time step, a corresponding amount of tracer is added to the lowest grid box. The resulting mixing ratio χ is then advected by the flow according to /Dt = 0, where D/Dt denotes the material derivative. The chosen surface flux is based on measurements of annual carbon emissions from an urban area of about 360 km2 in Colombia’s Aburrá river valley (Toro et al. 2001). Note that the amount of pollutant released to the atmosphere grows linearly both with time and with the size of the urban area. Note also that the rural valley is not included in Fig. 5 because the only source of pollution considered is the urban area.

Fig. 5.
Fig. 5.

Passive tracer mixing ratio (mg kg−1) in the (left) 40% urbanized and (right) 80% urbanized valleys (see text for details). Isentropes are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

Figure 5 confirms that the temperature inversion restricts the transport of pollutants out of the valley atmosphere, as previously reported in a number of experimental and modeling studies (e.g., Anquetin et al. 1999; Savijärvi and Liya 2001; Berge et al. 2002; Reuten et al. 2005). While a temperature inversion persists, the mixing ratio of pollutants in the valley atmosphere reaches higher values than those after the BTI. For instance, in the 80% urbanized valley, the mixing ratio reaches higher values during the morning (Figs. 5b,d) than those in the afternoon when the inversion layer has already been destroyed (Fig. 5f), and therefore the pollutant is distributed over a larger volume than that of the stable core (below the inversion top). This is analogous to the saturation effect that was discussed in section 3a when considering that the heat released from the surface tends to be distributed in the entire atmospheric column after the BTI. Note that in the 40% urbanized valley a temperature inversion persists throughout the daytime so the pollutant remains substantially trapped within the valley atmosphere (Fig. 5, left). This is consistent with the aforementioned difference between a confined and an open circulation in the valley, depending on the presence of the inversion layer (section 3b).

The maximum mixing ratios are found in the slopes of the 80% urbanized valley during the morning, before the BTI (Fig. 5b). The occurrence of such extreme values over the slopes can be related to three factors. First, as opposed to the less urbanized valley (Fig. 5, left) in the more urbanized one (Fig. 5, right), the sidewalls are mostly covered by urban land that releases pollutants to the atmosphere. Second, upslope winds advect polluted air from the valley floor to the sidewalls, and the presence of the inversion layer restricting the transport of mass out of the valley produces an accumulation of this polluted air over the slopes. Third, the atmospheric column below the inversion layer is shorter along the sidewalls than on the valley floor, so over the slopes the pollutant is mixed with relatively less air. Numerical simulations by Lehner and Gohm (2010; see their Fig. 3) show a similar process of accumulation of polluted air over the slope of a valley as a consequence of the upslope flow interacting with an inversion layer.

Finally, a comparison between Figs. 5c and 5d shows an effect of the slope wind patterns on the transport of the passive tracer. In the 40% urbanized valley a large amount of the pollutant is trapped near the rural–urban fringe (Fig. 5c), in the region where the downslope winds associated with a closed circulation below the inversion layer appear (recall Fig. 3e). This closed circulation can trap air pollutants within a relatively small volume (darker areas in Fig. 5c). This may be an example of a “smog trap” (i.e., a situation in which air pollutants tend to accumulate), which is likely to occur in a valley city as a result of the interplay between the slope flow, a temperature inversion, and an urban heat island, according to Savijärvi and Liya (2001). However, here it is worth noting that the same mechanisms causing the smog trap do not appear in our simulations when the sidewalls are highly urbanized. In the 80% urbanized valley (Fig. 5d), most of the tracer is removed from the valley floor and distributed along the slopes by the prevailing upslope winds (recall Fig. 3f), even before the complete destruction of the inversion layer.

4. Discussion

To better understand the likely effects of urbanization on the BTI in a valley and their implications on air quality, in this section we conceptually integrate the results presented above by considering changes in the BTI pattern as a result of changes in the urban area fraction (section 4a), and we discuss the possible air quality implications of such alterations (section 4b).

Before continuing, it is important to note two things. First, our simulations do not include different topographical settings, although the influence of the topography of the terrain on the BTI has been well recognized (see references in the introduction section). Second, our model runs use one uniform value of roughness length for the entire model domain. Obviously, in a more realistic model setup one would expect the roughness length to increase as one passes from the rural to the urban part of the domain. Correspondingly, we did some additional model runs where we accounted for increased surface friction over the urban area (no figure shown). It turned out that the sensitivity of our results (such as those shown in Figs. 2 and 3) to the treatment of the drag coefficient is very small. This is consistent with a recent scaling analysis by J. Schmidli and R. Rotunno (2013, personal communication) indicating that surface friction plays a secondary role in thermally driven valley wind systems.

a. Breakup patterns

The effects of urbanization on the BTI in a valley may be summarized and understood within the framework of the BTI patterns proposed by Whiteman (1982) and Whiteman and McKee (1982). They distinguish three different patterns depending on the relative magnitude of two processes whose interplay causes the breakup: (i) the rise of the bottom of the inversion layer resulting from the growth of the CBL and (ii) the descent of the top of the inversion layer caused by the removal of air from the bottom of the valley by the upslope winds, and the air subsidence from the upper atmosphere. In pattern 1, the BTI is dominated by the rise of the bottom of the inversion layer, while in pattern 2 the BTI is mainly caused by the descent of the top of the inversion layer. In pattern 3, the BTI is caused by the combined effect of both the ascent of the bottom of the inversion layer and the descent of its top.

We find that the BTI pattern is sensitive to the percentage of urban land. Figure 6 shows the temporal evolution of the heights of the bottom and top of the inversion layer obtained from the potential temperature profiles in the center of the valley showed in Fig. 1. In all cases the growth of the CBL continuously reduces the depth of the inversion layer, but it is not always completely destroyed. For low percentages of urban land (≤40%; Figs. 6a–c) the height of the top of the inversion layer does not substantially change, and the reduction of the inversion layer is dominated by the growth of the CBL, so this can be described as pattern 1. In contrast, for high percentages of urban land (≥60%; Figs. 6d–f), the breakup follows pattern 3, meaning that the inversion layer is reduced not only by the rise of its bottom, but also by the descent of its top.

Fig. 6.
Fig. 6.

Heights of the bottom (dotted line) and top (solid line) of the inversion layer in the center of the valley for different urban area fractions (ranging from 0% to 100%).

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

BTI pattern 2 was not found in any of the studied cases; that is, the descent of the top of the inversion layer does not dominate the BTI in any case. This may be explained by two factors. First, the presence of the urban area in all valleys but the rural one increases the heating of the valley floor, thus enhancing the growth of a CBL, which is a process that does not substantially occur in pattern 2. Second, the occurrence of pattern 2 implies not only that the development of a CBL over the valley floor is weak, but also that the upslope winds are strong enough to substantially remove air from the base of the inversion. In our simulations, the upslope winds are not that strong in the rural valley due to the low heating of the surface, and the development of the CBL is not that weak in the urban valleys because of the high heating of the urban area.

The differences between the breakup pattern for low and high percentages of urban land can be explained by changes in the dynamics of the wind fields associated with the urban area fraction. To clarify and discuss such differences, we introduce Fig. 7, which shows a schematic representation of the BTI for different percentages of urban land, based on the results presented in section 3 and on our understanding of the BTI process. This scheme includes a sketch of the inversion layer (dashed lines), the isentropes (solid lines), the main wind flows (black arrows), and the resolved TKE (shading). Figures 2 and 3 do not always show the updraft region over the mountaintops as sketched in Fig. 7, simply because sometimes the associated thermals lie outside the plotted domain. Similarly, the convergence zone above the mountaintops is not completely shown in Fig. 3 but is present in our results and sketched in Fig. 7. It is worth noting that the dashed lines bounding the inversion layer have been sketched so as not to exactly match the isentropes, but only with the purpose of improving the visualization.

Fig. 7.
Fig. 7.

Idealized sketch of the evolution in time of the BTI process and the mean cross-valley circulation depicting the inversion layer (dashed lines), the main wind flows (black arrows), and the resolved TKE field (shading), for the (left) rural, (center) 40% urbanized, and (right) 80% urbanized valleys. Isentropes (solid lines) are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

In the rural valley the height of the top of the inversion layer remains approximately constant at ~800 m (above the valley floor), while that of the bottom rises from ~200 m (at 0900 LST) to ~450 m (at 1800 LST), as a result of the buoyant production of turbulence at the surface and the consequent development of a CBL. Pattern 1 implies that the removal of air from the valley floor, as well as the subsidence above the inversion layer, are weak. The airmass transport out of the rural valley atmosphere is weak because the low heating of the surface produces weak upslope flows, and the persistent inversion layer restricts vertical motions. The effect of the inversion layer in decoupling the circulation above and below it is evident. The lines (isentropes) limiting the inversion layer in the cross section of the valley are approximately horizontal, as proposed in the conceptual model of Whiteman (1982) and Whiteman and McKee (1982). At the end of the simulation, an inversion layer is still present and calm winds prevail.

In low urbanized valleys (20% and 40% percentages of urban land) the BTI also follows pattern 1, but the mechanisms driving this pattern differ from those in the rural valley. Figure 8 summarizes the results obtained for the 20% urban area fraction, which were not shown previously. In both valleys, the interplay between the urban heat island and the presence of the inversion layer produces downslope winds, thus restricting the removal of air from the valley floor. Recall from section 3 that the circulation associated with these downslope winds leads to an accumulation of air pollutants below the inversion layer (smog trap). Moreover, weak upslope flows along the upper half of the slopes (Figs. 2e,h and 3e,h; Figs. 8a,b,d,e) are linked to weak air subsidence from above the inversion layer, since the ascending motions related to the former are compensated by the descending motions related to the latter. Similarly to the case in the rural valley, in the low urbanized valleys a temperature inversion remains throughout the daytime. The presence of a shallow inversion layer between 1500 and 1800 LST in the 20% and 40% urbanized valleys is evidenced in Figs. 5e,g and 8f,i, where the tracer remains capped by such a layer.

Fig. 8.
Fig. 8.

Consecutive longitudinal mean fields of the (left) cross-valley w and (center) u wind speed components, and (right) the passive tracer mixing ratio (mg kg−1) in the 20% urbanized valley. Isentropes are shown every 1 K. The thick (thin) outline of the orography marks the urban (rural) area.

Citation: Journal of Applied Meteorology and Climatology 53, 4; 10.1175/JAMC-D-13-0165.1

In contrast to the rural valley, in low urbanized valleys turbulence is more efficiently produced over the urban areas, and the associated growth of the CBL substantially reduces the depth of the inversion layer. The surface heterogeneity in land cover (urban versus rural land) may lead to nonuniform elevation of the bottom of the inversion layer caused by the CBL, so that the isentropes that limit the inversion layer may differ from horizontal ones, as suggested in Fig. 7h. More significant variations of these isentropes from horizontal ones may arise when considering a south–north-oriented valley where the symmetry of the surface heating is lost, as a result of effects such as those of topographic shading. We are currently working on including topographic shading in our analyses and plan to report on it in a subsequent study.

In highly urbanized valleys (≥60% percentages of urban land) the BTI follows pattern 3, which implies that both the growth of the CBL and the removal of air from the valley floor exert significant effects on the breakup. Consequently, the top of the inversion layer descends while the bottom ascends. As a result of the high urban area fraction, most of the valley surface, including a significant part of the sidewalls, is highly heated, thus giving rise to an efficient buoyant production of turbulence on the valley floor, and inducing stronger upslope winds as compared to those in low urbanized valleys. Hence, a CBL develops above the valley surface, while air is continually removed from the valley floor by the upslope winds, in turn enhancing air subsidence from the upper atmosphere. The combined action of these processes leads to the complete destruction of the inversion layer between 1200 and 1500 LST. After that, most of the pollutant is transported out of the valley atmosphere and may be diluted at larger scale. Further implications on air quality are considered in the following section.

Our results regarding the dependence of the BTI pattern on the percentage of urban land are in reasonable agreement with the study by Whiteman et al. (2004) of valleys exhibiting different BTI patterns as a consequence of differences in factors affecting the sensible heat flux from the surface. These authors compared the BTI pattern in two valleys, one with moist conditions and the other with dry conditions, and they found that the breakup in the former follows pattern 2 while in the latter it follows pattern 3. They attributed this difference in the BTI pattern to the lower or higher heating of the surface in the moist or dry valley, respectively.

b. Air quality implications

The influence of urbanization on the air quality of an urban valley may exhibit contrasting effects when considering a temperature inversion. This influence does not appear to be as straightforward as it seems, meaning that keeping all properties of the urban land constant, the more urban land, the worse the air quality, even when considering that the amount of pollutants emitted grows with the size of the urban area. This is because of the strong effects that a temperature inversion can exert on the air quality of an urban valley, particularly through effects on the exchange of air between the atmosphere above and below the inversion layer. At this point it is important to remember that we have defined urbanization as the expansion of a homogeneous urban area with respect to both heating and emissions. Therefore, the situation described here could become even more complex if the intraurban variations of emissions were considered, but we did not address this issue in the present study.

A possibly counterintuitive effect of urbanization on the air quality of a valley city is apparent when comparing both columns in Fig. 5. Although peak mixing ratios occur for the higher percentages of urban land during the temperature inversion (Fig. 5d), higher urban area fractions do not necessarily imply higher mixing ratios during the whole day (cf. Figs. 5g and 5h), although the expansion of the urban area implies an increase in the emission of pollutants. This can be explained by the effects of the temperature inversion on the ventilation of the valley, which in turn is related to the urban area fraction. Under the assumption of homogeneity of the urban area, a temperature inversion may persist during the whole day in a less urbanized valley, so that air pollutants may remain trapped for longer periods of time than in a more urbanized valley, owing to the better ventilation of the latter after the destruction of the inversion layer. It would be interesting to examine this idea with empirical evidence from historical data of air quality covering different percentages of urban land in a mountain valley. We could not find such data, so we leave this as an open question.

Taha et al. (2010) performed a model study in three U.S. cities and found that UHI mitigation measures associated with lowering surface temperatures can lead to reductions in air pollution. Our findings are in striking contrast to this study, since, in our simulations, a weaker urban heat island associated with lower percentages of urban land or lower heating of the surface does not necessarily result in lower air pollution throughout the daytime. In the 40% urbanized valley we found an urban heat island effect concurrent with a temperature inversion and low air quality, while the absence of a temperature inversion after the BTI in the 80% urbanized valley is concurrent with better air quality (recall Fig. 5). This is due to the effects of the temperature inversion in restricting the valley ventilation and the consequent trapping of air pollutants, which are not considered in the simulations by Taha et al. (2010). The authors acknowledge that the extent to which urban areas can effectively improve local air quality through UHI mitigation depends on numerous factors, among which one could consider a temperature inversion. Furthermore, we study the transport of a passive tracer, without taking into account any chemical reaction or the possible effects of pollution on radiation (see e.g., Fan and Sailor 2005). However, we still consider that our findings with respect to the interplay between the transport of pollutants released to the atmosphere from a valley city, and the presence and eventual destruction of an inversion layer are plausible, and that they are in reasonable agreement with previous studies about the impacts of the temperature inversion on air quality over urban and/or complex terrain, as discussed above.

In sections 3 and 4a we described a circulation below the inversion layer that can lead to a smog trap situation associated with the appearance of downslope winds. We showed that such a downslope flow does not occur in our simulations when the sidewalls are highly urbanized, that is, for high percentages of urban land (≥60%). However, the interplay between the upslope flows, the temperature inversion, and the emissions from urban areas over highly urbanized valleys may lead to an accumulation of air pollutants over the sidewalls and below the inversion layer, which might be considered as another type of smog trap. While a temperature inversion remains, prevailing upslope flows tend to accumulate air pollutants over the slopes. This is why peak mixing ratios are found over the slopes in the highly urbanized valleys and before the complete destruction of the inversion layer (recall Fig. 5). This may be relevant to understanding the features of the spatial variability of air quality over highly urbanized valleys along the diurnal cycle.

An important aspect of our model experiment is that as the urban land expands beyond the valley floor, the sloping sidewalls are increasingly heated. Heating the sidewalls will generally enhance the BTI and the ventilation of the valley through strengthening of the upslope winds. A comparison between the valleys with 40% and 20% urban area fractions (left panels of Fig. 5 and right panels of Fig. 8) shows that the air quality is worse in the former valley throughout the daytime. This result, along with our previous observation that higher urban area fractions do not imply worse air quality during the whole day (recall the comparison between the 40% and 80% urbanized valleys, based on Fig. 5), suggest that the extent to which urbanization adversely affects air quality depends strongly on the possible expansion of the urban area beyond the valley floor toward the sidewalls. We think that this problem deserves further research.

We want to stress that in this paper we are not suggesting that urbanization is good for air quality, since land-use/-cover change (e.g., urbanization) has potentially detrimental, or at least uncertain, environmental effects at multiple spatial and temporal scales (Foley et al. 2005). Our concern is to investigate the local effects of urbanization at the valley scale and, particularly, those related to the temperature inversion and its influence on the transport of pollutants out of an urban valley. Further research on this topic is needed to provide better information for decision-making processes related to urban planning, which is of particular importance in several medium-sized and megacities in Latin America (Romero et al. 1999), many of which are located in the mountain terrain of the Andes (e.g., Medellín in the Aburrá river valley in Colombia).

5. Summary and conclusions

We have shown through idealized simulations that in an urban valley subject to temperature inversions, land-use/-cover changes resulting from urbanization, which include changes in the size of the UHI, can have an important influence on air quality through effects on the BTI. Despite the completely idealized framework adopted, the present study provides evidence about a series of physical processes that are likely to occur in nature and agrees well with previous studies. In summary, the main effects of urbanization on the BTI and the accompanying air quality implications are related to (i) changes in the breakup time, (ii) alterations of the thermal cross-valley winds and turbulence dynamics, (iii) modifications of the breakup pattern, and (iv) impacts on the ventilation of the urban valley.

The percentage of urban land affects the breakup time, that is, the time that it takes for the inversion layer to be completely destroyed. We find that the larger the urban area fraction, the faster the BTI. However, there are no noticeable differences between the breakup times for high-percentage urban land cases (≥80% in our simulations), thus suggesting that there is an upper limit above which the BTI is not further accelerated by increasing the urban area fraction. This seems to be attributable to the location of the rural–urban fringe relative to the altitude of the top of the inversion layer, since it determines whether or not the atmosphere below the inversion layer is all urban and hence subject to a similar heating. This conclusion is only valid under conditions where the vertical transport of heat above the inversion is substantially unrestricted.

Several changes in the thermal cross-valley wind system, associated with changes in the dynamics of the temperature inversion, can occur depending on the percentage of urban land. We found that (i) changes in the urban area fraction may result in a confined or open diurnal cross-valley circulation, that is, cross-valley circulation cells decoupled (confined system) or coupled (open system) to the overlying atmosphere, due to a capping effect of the inversion layer; (ii) lower percentages of urban land (≤40% in our simulations) result in reversed cross-valley circulations producing downslope winds, as a consequence of the interplay between the UHI in the core of the valley and the presence of the inversion layer restricting vertical motions; (iii) upslope winds and thermal convective plumes rising off the top of the valley sidewalls may be intensified as the urban area fraction grows, thus strengthening the removal of air from below the inversion layer; and (iv) turbulence is more efficiently produced by buoyancy over the urban areas and, therefore, the expansion of urban land enlarges the area above which the CBL is substantially developed.

The BTI pattern in an urban valley is sensitive to the percentage of urban land. Under null (rural valley) or low percentages (≤40% in our simulations) of urban land, the reduction of the inversion layer is dominated by the rise of its bottom owing to the growth of the CBL (pattern 1), while when the percentage of urban land is high (≥60% in our simulations), the inversion layer is reduced by both the rise of its bottom and the descent of its top (pattern 3). Such descent is caused by the removal of air from the bottom of the valley by the upslope winds, as well as the air subsidence from the upper atmosphere. This process of the descent of the top of the inversion layer does not dominate the BTI (pattern 2) in any of the studied cases.

The influence of urbanization on the air quality of an urban valley may lead to contrasting and possibly counterintuitive effects when considering a temperature inversion. It does not seem to be necessarily true that, keeping all properties of the urban land constant (assuming that emissions expand uniformly with urban land cover), more urban land implies worse air quality, even when considering that the amount of pollutants emitted grows with the size of the urban area. The mixing ratio of pollutants in the valley atmosphere is sensitive to the percentage of urban land, not only because of changes in the amount of pollutant emitted, but also because of the effects that urbanization can exert on the dynamics of the temperature inversion, and the consequent effects on the exchange of air between the atmosphere above and below the inversion layer. In the simulations presented in this study, peak mixing ratios occur for the higher percentages of urban land when the temperature inversion is present, but higher percentages of urban land do not imply higher mixing ratios throughout the daytime and everywhere in the valley.

As a final remark, it is stressed that we are not suggesting that increasing the urban area fraction of a mountain valley would lead to better air quality but, rather, are pointing out that the urbanization processes of a mountain valley subject to temperature inversions may lead to nonevident, and possibly counterintuitive, impacts on air quality at the valley scale. Better understanding of these topics is of particular importance for urban planning in growing cities located in mountain terrains, such as several Latin American cities in the Andes. We acknowledge that urbanization has potentially detrimental, or at least uncertain, environmental effects on multiple spatial and temporal scales, and that further research into these topics is needed to support decision-making processes related to urban planning.

Acknowledgments

We thank S. Serafin for insightful comments during the early development of this study. We also thank Editor Joseph Charney and the anonymous reviewers for their constructive comments. The computations for this study were performed on the supercomputer Blizzard at the German Climate Computing Center (Deutsches Klimarechenzentrum). AMR thanks the German Academic Exchange Service, DAAD, for supporting her as a visiting doctoral student in Germany through Short-Term Scholarship A/10/77699, and the Colombian Administrative Department of Science, Technology and Innovation, COLCIENCIAS, for funding her doctoral studies through the research project “Caracterización de procesos físicos en la baja atmósfera del Valle de Aburrá” (Código 1115-48925515, Contrato 458-09) and grant “Francisco José de Caldas.”

REFERENCES

  • Allen, L., , F. Lindberg, , and C. Grimmond, 2011: Global to city scale urban anthropogenic heat flux: Model and variability. Int. J. Climatol., 31, 19902005, doi:10.1002/joc.2210.

    • Search Google Scholar
    • Export Citation
  • Andrejczuk, M., , W. Grabowski, , S. Malinowski, , and P. Smolarkiewicz, 2004: Numerical simulation of cloud-clear air interfacial mixing. J. Atmos. Sci., 61, 17261739, doi:10.1175/1520-0469(2004)061<1726:NSOCAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Anquetin, S., , C. Guilbaud, , and J. Chollet, 1998: The formation and destruction of inversion layers within a deep valley. J. Appl. Meteor., 37, 15471560, doi:10.1175/1520-0450(1998)037<1547:TFADOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Anquetin, S., , C. Guilbaud, , and J. Chollet, 1999: Thermal valley inversion impact on the dispersion of a passive pollutant in a complex mountainous area. Atmos. Environ., 33, 39533959, doi:10.1016/S1352-2310(99)00137-5.

    • Search Google Scholar
    • Export Citation
  • Argentini, S., , G. Mastrantonio, , and F. Lena, 1999: Case studies of the wintertime convective boundary-layer structure in the urban area of Milan, Italy. Bound.-Layer Meteor., 93, 253267, doi:10.1023/A:1002057414039.

    • Search Google Scholar
    • Export Citation
  • Arnfield, A., 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, 126, doi:10.1002/joc.859.

    • Search Google Scholar
    • Export Citation
  • Bader, D. C., , and T. B. McKee, 1985: Effects of shear, stability and valley characteristics on the destruction of temperature inversions. J. Climate Appl. Meteor., 24, 822832, doi:10.1175/1520-0450(1985)024<0822:EOSSAV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Baklanov, A., 2002: The mixing height in urban areas—A review. Proc. Workshop on Mixing Height and Inversions in Urban Areas, Toulouse, France, European Cooperation in Science and Technology Action 715, 9–28.

  • Berge, E., , A. Karppinen, , J. Kukkonen, , M. Køltzow, , and L. Slørdal, 2002: Simulations of wintertime inversions in northern European cities by use of NWP-models. Proc. Workshop on Mixing Height and Inversions in Urban Areas, Toulouse, France, European Cooperation in Science and Technology Action 715, 75–88.

  • Bonan, G., 2008: Forest and climate change: Forcings, feedbacks, and the climate benefits of forests. Science, 320, 14441449, doi:10.1126/science.1155121.

    • Search Google Scholar
    • Export Citation
  • Chen, X.-L., , H.-M. Zhao, , P.-X. Li, , and Z.-Y. Yin, 2006: Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens. Environ., 104, 133146, doi:10.1016/j.rse.2005.11.016.

    • Search Google Scholar
    • Export Citation
  • Chu, P. C., , Y. Chen, , S. Lu, , Z. Li, , and Y. Lu, 2008: Particulate air pollution in Lanzhou China. Environ. Int., 34 (5), 698713, doi:10.1016/j.envint.2007.12.013.

    • Search Google Scholar
    • Export Citation
  • Colette, A., , F. Chow, , and R. Street, 2003: A numerical study of inversion-layer breakup and the effects of topographic shading in idealized valleys. J. Appl. Meteor., 42, 12551272, doi:10.1175/1520-0450(2003)042<1255:ANSOIB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Colvile, R., , E. Hutchinson, , J. Mindell, , and R. Warren, 2001: The transport sector as a source of air pollution. Atmos. Environ., 35, 15371565, doi:10.1016/S1352-2310(00)00551-3.

    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1980: Stratocumulus-capped mixed layers derived from a three-dimensional model. Bound.-Layer Meteor., 18, 495527, doi:10.1007/BF00119502.

    • Search Google Scholar
    • Export Citation
  • Edgerton, S. A., and et al. , 1999: Particulate air pollution in Mexico City: A collaborative research project. J. Air Waste Manage. Assoc., 49, 12211229, doi:10.1080/10473289.1999.10463915.

    • Search Google Scholar
    • Export Citation
  • Fan, H., , and D. Sailor, 2005: Modeling the impacts of anthropogenic heating on the urban climate of Philadelphia: A comparison of implementations in two PBL schemes. Atmos. Environ., 39, 7384, doi:10.1016/j.atmosenv.2004.09.031.

    • Search Google Scholar
    • Export Citation
  • Foley, J., and et al. , 2005: Global consequences of land use. Science, 309, 570, doi:10.1126/science.1111772.

  • Grimmond, C., , and T. Oke, 2002: Turbulent heat fluxes in urban areas: Observations and a local-scale urban meteorological parameterization scheme (LUMPS). J. Appl. Meteor., 41, 792810, doi:10.1175/1520-0450(2002)041<0792:THFIUA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Grimmond, S., 2007: Urbanization and global environmental change: Local effects of urban warming. Geogr. J., 173, 8388, doi:10.1111/j.1475-4959.2007.232_3.x.

    • Search Google Scholar
    • Export Citation
  • Haeger-Eugensson, M., , and B. Holmer, 1999: Advection caused by the urban heat island circulation as a regulating factor on the nocturnal urban heat island. Int. J. Climatol., 19, 975988, doi:10.1002/(SICI)1097-0088(199907)19:9<975::AID-JOC399>3.0.CO;2-J.

    • Search Google Scholar
    • Export Citation
  • Jacobson, M., 2005: Fundamentals of Atmospheric Modeling. 2nd ed. Cambridge University Press, 813 pp.

  • Janhall, S., , K. Olofson, , P. Andersson, , J. Pettersson, , and M. Hallquist, 2006: Evolution of the urban aerosol during winter temperature inversion episodes. Atmos. Environ., 40, 53555366, doi:10.1016/j.atmosenv.2006.04.051.

    • Search Google Scholar
    • Export Citation
  • Jung, M., and et al. , 2011: Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res., 116, G00J07, doi:10.1029/2010JG001566.

    • Search Google Scholar
    • Export Citation
  • Kalthoff, N., , H. Binder, , M. Kossmann, , R. Vögtlin, , U. Corsmeier, , F. Fiedler, , and H. Schlager, 1998: Temporal evolution and spatial variation of the boundary layer over complex terrain. Atmos. Environ., 32, 11791194, doi:10.1016/S1352-2310(97)00193-3.

    • Search Google Scholar
    • Export Citation
  • Kanda, M., 2007: Progress in urban meteorology: A review. J. Meteor. Soc. Japan, 85B, 363383, doi:10.2151/jmsj.85B.363.

  • Lee, S.-H., , and H.-D. Kim, 2008: Effects of regional warming due to urbanization on daytime local circulations in a complex basin of the Daegu metropolitan area, Korea. J. Appl. Meteor. Climatol., 47, 14271441, doi:10.1175/JAMC1504.1.

    • Search Google Scholar
    • Export Citation
  • Lehner, M., , and A. Gohm, 2010: Idealised simulations of daytime pollution transport in a steep valley and its sensitivity to thermal stratification and surface albedo. Bound.-Layer Meteor., 134, 327351, doi:10.1007/s10546-009-9442-y.

    • Search Google Scholar
    • Export Citation
  • Li, Y., , R. Smith, , and V. Grubišic, 2009: Using surface pressure variations to categorize diurnal valley circulations: Experiments in Owens Valley. Mon. Wea. Rev., 137, 17531769, doi:10.1175/2008MWR2495.1.

    • Search Google Scholar
    • Export Citation
  • Malek, E., , T. Davis, , R. S. Martin, , and P. J. Silva, 2006: Meteorological and environmental aspects of one of the worst national air pollution episodes (January, 2004) in Logan, Cache Valley, Utah, USA. Atmos. Res., 79, 108122, doi:10.1016/j.atmosres.2005.05.003.

    • Search Google Scholar
    • Export Citation
  • Masson, V., 2006: Urban surface modeling and the meso-scale impact of cities. Theor. Appl. Climatol., 84, 3545, doi:10.1007/s00704-005-0142-3.

    • Search Google Scholar
    • Export Citation
  • Matzinger, N., , M. Andretta, , E. Gorsel, , R. Vogt, , A. Ohmura, , and M. Rotach, 2003: Surface radiation budget in an alpine valley. Quart. J. Roy. Meteor. Soc., 129, 877895, doi:10.1256/qj.02.44.

    • Search Google Scholar
    • Export Citation
  • Nadeau, D., and et al. , 2009: Estimation of urban sensible heat flux using a dense wireless network of observations. Environ. Fluid Mech., 9, 635653, doi:10.1007/s10652-009-9150-7.

    • Search Google Scholar
    • Export Citation
  • Offerle, B., , C. Grimmond, , K. Fortuniak, , and W. Pawlak, 2006: Intraurban differences of surface energy fluxes in a central European city. J. Appl. Meteor. Climatol., 45, 125136, doi:10.1175/JAM2319.1.

    • Search Google Scholar
    • Export Citation
  • Ogura, Y., , and N. Phillips, 1962: Scale analysis of deep and shallow convection in the atmosphere. J. Atmos. Sci., 19, 173179, doi:10.1175/1520-0469(1962)019<0173:SAODAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Oke, T., 1995: The heat island of the urban boundary layer: Characteristics, causes and effects. Wind Climate in Cities, J. E. Cermak et al., Eds., Kluwer Academic, 81–107.

  • Olofson, K., , P. Andersson, , M. Hallquist, , E. Ljungström, , L. Tang, , D. Chen, , and J. Pettersson, 2009: Urban aerosol evolution and particle formation during wintertime temperature inversions. Atmos. Environ., 43, 340346, doi:10.1016/j.atmosenv.2008.09.080.

    • Search Google Scholar
    • Export Citation
  • Panday, A. K., , and R. G. Prinn, 2009: Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: Observations. J. Geophys. Res.,114, doi:10.1029/2008JD009777.

  • Piotrowski, Z. P., , M. J. Kurowski, , B. Rosa, , and M. Z. Ziemianski, 2010: EULAG model for multiscale flows—Towards the petascale generation of mesoscale numerical weather prediction. Parallel Processing and Applied Mathematics, Lecture Notes in Computer Sciences, R. Wyrzykowski et al., Eds., Springer, 380–387.

  • Prusa, J., , P. Smolarkiewicz, , and A. Wyszogrodzki, 2008: EULAG, a computational model for multiscale flows. Comput. Fluids, 37, 11931207, doi:10.1016/j.compfluid.2007.12.001.

    • Search Google Scholar
    • Export Citation
  • Rampanelli, G., , D. Zardi, , and R. Rotunno, 2004: Mechanisms of up-valley winds. J. Atmos. Sci., 61, 30973111, doi:10.1175/JAS-3354.1.

  • Reuten, C., , D. Steyn, , K. Strawbridge, , and P. Bovis, 2005: Observations of the relation between upslope flows and the convective boundary layer in steep terrain. Bound.-Layer Meteor., 116, 3761, doi:10.1007/s10546-004-7299-7.

    • Search Google Scholar
    • Export Citation
  • Rizwan, A., , L. Dennis, , and C. Liu, 2008: A review on the generation, determination and mitigation of urban heat island. J. Environ. Sci. (China), 20, 120128, doi:10.1016/S1001-0742(08)60019-4.

    • Search Google Scholar
    • Export Citation
  • Romero, H., , M. Ihl, , A. Rivera, , P. Zalazar, , and P. Azocar, 1999: Rapid urban growth, land-use changes and air pollution in Santiago, Chile. Atmos. Environ., 33, 40394047, doi:10.1016/S1352-2310(99)00145-4.

    • Search Google Scholar
    • Export Citation
  • Rosenzweig, C., , W. Solecki, , S. Hammer, , and S. Mehrotra, 2010: Cities lead the way in climate-change action. Nature, 467, 909911, doi:10.1038/467909a.

    • Search Google Scholar
    • Export Citation
  • Rutllant, J., , and R. Garreaud, 1995: Meteorological air pollution potential for Santiago, Chile: Towards an objective episode forecasting. Environ. Monit. Assess., 34, 223244, doi:10.1007/BF00554796.

    • Search Google Scholar
    • Export Citation
  • Savijärvi, H., , and J. Liya, 2001: Local winds in a valley city. Bound.-Layer Meteor., 100, 301319, doi:10.1023/A:1019215031007.

  • Savov, P., , T. Skakalova, , I. Kolev, , and F. Ludwig, 2002: Lidar investigation of the temporal and spatial distribution of atmospheric aerosols in mountain valleys. J. Appl. Meteor., 41, 528541, doi:10.1175/1520-0450(2002)041<0528:LIOTTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schmidli, J., and et al. , 2011: Intercomparison of mesoscale model simulations of the daytime valley wind system. Mon. Wea. Rev., 139, 13891409, doi:10.1175/2010MWR3523.1.

    • Search Google Scholar
    • Export Citation
  • Schmidt, H., , and U. Schumann, 1989: Coherent structure of the convective boundary layer derived from large-eddy simulations. J. Fluid Mech., 200, 511562, doi:10.1017/S0022112089000753.

    • Search Google Scholar
    • Export Citation
  • Serafin, S., , and D. Zardi, 2010a: Daytime heat transfer processes related to slope flows and turbulent convection in an idealized mountain valley. J. Atmos. Sci., 67, 37393756, doi:10.1175/2010JAS3428.1.

    • Search Google Scholar
    • Export Citation
  • Serafin, S., , and D. Zardi, 2010b: Structure of the atmospheric boundary layer in the vicinity of a developing upslope flow system: A numerical model study. J. Atmos. Sci., 67, 11711185, doi:10.1175/2009JAS3231.1.

    • Search Google Scholar
    • Export Citation
  • Smolarkiewicz, P. K., , and J. M. Prusa, 2004: Forward-in-time differencing for fluids: Simulation of geophysical turbulence. Turbulent Flow Computation, D. Drikakas and B. J. Geurts, Eds., Springer, 279–312.

  • Smolarkiewicz, P. K., , L. Margolin, , and A. Wyszogrodzki, 2001: A class of nonhydrostatic global models. J. Atmos. Sci., 58, 349364, doi:10.1175/1520-0469(2001)058<0349:ACONGM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Smolarkiewicz, P. K., , R. Sharman, , J. Weil, , S. Perry, , D. Heist, , and G. Bowker, 2007: Building resolving large-eddy simulations and comparison with wind tunnel experiments. J. Comput. Phys., 227, 633653, doi:10.1016/j.jcp.2007.08.005.

    • Search Google Scholar
    • Export Citation
  • Taha, H., , S. Chang, , and H. Akbari, 2010: Meteorological and air quality impacts of heat island mitigation measures in three US cities. Lawrence Berkeley National Laboratory Rep. LBL-44222, 51 pp.

  • Toro, M. V., , J. J. Ramírez, , R. A. Quiceno, , and C. A. Zuluaga, 2001: Cálculo de la emisión vehicular de contaminantes atmosféricos en la ciudad de Medellín mediante factores de emisión Corinair. Rev. Acodal, 191, 4249.

    • Search Google Scholar
    • Export Citation
  • Wallace, J., , D. Corr, , and P. Kanaroglou, 2010: Topographic and spatial impacts of temperature inversions on air quality using mobile air pollution surveys. Sci. Total Environ., 408, 50865096, doi:10.1016/j.scitotenv.2010.06.020.

    • Search Google Scholar
    • Export Citation
  • Warner, T., 2011: Numerical Weather and Climate Prediction. Cambridge University Press, 526 pp.

  • Welch, T., , P. Smolarkiewicz, , R. Rotunno, , and B. Boville, 2001: The large-scale effects of flow over periodic mesoscale topography. J. Atmos. Sci., 58, 14771492, doi:10.1175/1520-0469(2001)058<1477:TLSEOF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wesson, G., , K. Gabriel, , and L. Chun-Ta, 2001: Sensible heat flux estimation by flux variance and half-order time derivative methods. Water Resour. Res., 37, 23332343, doi:10.1029/2001WR900021.

    • Search Google Scholar
    • Export Citation
  • Whiteman, C., 1982: Breakup of temperature inversions in deep mountain valleys: Part I. Observations. J. Appl. Meteor., 21, 270289, doi:10.1175/1520-0450(1982)021<0270:BOTIID>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Whiteman, C., 2000: Mountain Meteorology: Fundamentals and Applications. Oxford University Press, 355 pp.

  • Whiteman, C., , and T. McKee, 1982: Breakup of temperature inversions in deep mountain valleys: Part II. Thermodynamic model. J. Appl. Meteor., 21, 290302, doi:10.1175/1520-0450(1982)021<0290:BOTIID>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Whiteman, C., , B. Pospichal, , S. Eisenbach, , P. Weihs, , C. Clements, , R. Steinacker, , E. Mursch-Radlgruber, , and M. Dorninger, 2004: Inversion breakup in small Rocky Mountain and Alpine basins. J. Appl. Meteor., 43, 10691082, doi:10.1175/1520-0450(2004)043<1069:IBISRM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wilson, J. G., , S. Kingham, , J. Pearce, , and A. P. Sturman, 2005: A review of intraurban variations in particulate air pollution: Implications for epidemiological research. Atmos. Environ., 39, 64446462, doi:10.1016/j.atmosenv.2005.07.030.

    • Search Google Scholar
    • Export Citation
  • Yao, W., , and S. Zhong, 2009: Nocturnal temperature inversions in a small, enclosed basin and their relationship to ambient atmospheric conditions. Meteor. Atmos. Phys., 103, 195210, doi:10.1007/s00703-008-0341-4.

    • Search Google Scholar
    • Export Citation
  • Zhong, S., , C. Whiteman, , and X. Bian, 2004: Diurnal evolution of three-dimensional wind and temperature structure in California’s Central Valley. J. Appl. Meteor., 43, 16791699, doi:10.1175/JAM2154.1.

    • Search Google Scholar
    • Export Citation
  • Zoumakis, N., , and G. Efstathiou, 2006: Parameterization of inversion breakup in idealized valleys. Part II: Thermodynamic model. J. Appl. Meteor. Climatol., 45, 609623, doi:10.1175/JAM2354.1.

    • Search Google Scholar
    • Export Citation
Save