• Banta, R. M., , L. D. Olivier, , P. H. Gudiksen, , and R. Lange, 1996: Implications of small-scale flow features to modeling dispersion over complex terrain. J. Appl. Meteor., 35 , 330342.

    • Search Google Scholar
    • Export Citation
  • Bloom, S. C., , L. L. Takacs, , A. M. Da Silva, , and D. Ledvina, 1996: Data assimilation using incremental analysis updates. Mon. Wea. Rev., 124 , 12561271.

    • Search Google Scholar
    • Export Citation
  • Brewster, K. A., 2003a: Phase-correcting data assimilation and application to storm-scale numerical weather prediction. Part I: Method description and simulation testing. Mon. Wea. Rev., 131 , 480492.

    • Search Google Scholar
    • Export Citation
  • Brewster, K. A., 2003b: Phase-correcting data assimilation and application to storm-scale numerical weather prediction. Part II: Application to a severe storm outbreak. Mon. Wea. Rev., 131 , 493507.

    • Search Google Scholar
    • Export Citation
  • Brulfert, G., , C. Chemel, , E. Chaxel, , and J. P. Chollet, 2005: Modelling photochemistry in alpine valleys. Atmos. Chem. Phys., 5 , 23412355.

    • Search Google Scholar
    • Export Citation
  • Chang, J. C., , and S. R. Hanna, 2004: Air quality model performance evaluation. Meteor. Atmos. Phys., 87 , 167196.

  • Chen, Y., , F. L. Ludwig, , and R. L. Street, 2004: Stably stratified flows near a notched transverse ridge across the Salt Lake valley. J. Appl. Meteor., 43 , 13081328.

    • Search Google Scholar
    • Export Citation
  • Chow, F. K., , A. P. Weigel, , R. L. Street, , M. W. Rotach, , and M. Xue, 2006: High-resolution large-eddy simulations of flow in a steep Alpine valley. Part I: Methodology, verification, and sensitivity experiments. J. Appl. Meteor. Climatol., 45 , 6386.

    • Search Google Scholar
    • Export Citation
  • Hanna, S. R., , D. G. Strimaitis, , and J. C. Chang, 1991: Hazard response modeling uncertainty (a quantitative model), vol. I: User’s guide for software for evaluating hazardous gas dispersion models. ESL-TR-91-28, Engineering and Services Laboratory, Air Force Engineering and Services Center, Tyndall Air Force Base, 353 pp.

  • Hanna, S. R., , J. C. Chang, , and D. G. Strimaitis, 1993: Hazardous gas model evaluation with field observations. Atmos. Environ., 27 , 22652285.

    • Search Google Scholar
    • Export Citation
  • Hayashi, T., , M. Chino, , H. Yamazawa, , S. Moriuchi, , H. Ishikawa, , T. Adachi, , and H. Kojima, 1999: Data of atmospheric diffusion experiments (Tsukuba, 1989). JAERI-Data/Code 99-036. Japan Atomic Energy Institute, 332 pp.

  • Kemp, J. R., , and D. J. Thomson, 1996: Dispersion in stable boundary layers using large-eddy simulation. Atmos. Environ., 30 , 29112923.

    • Search Google Scholar
    • Export Citation
  • Kim, S. W., , C. H. Moeng, , J. C. Weil, , and M. C. Barth, 2005: Lagrangian particle dispersion modeling of the fumigation process using large-eddy simulation. J. Atmos. Sci., 62 , 19321946.

    • Search Google Scholar
    • Export Citation
  • Koracin, D., , A. Panorska, , V. Isakov, , J. S. Touma, , and J. Swall, 2007: A statistical approach for estimating uncertainty in dispersion modeling: An example of application in southwestern USA. Atmos. Environ., 41 , 617628.

    • Search Google Scholar
    • Export Citation
  • Lafore, J. P., and Coauthors, 1998: The meso-NH atmospheric simulation system. Part I: Adiabatic formulation and control simulation. Ann. Geophys., 11 , 90109.

    • Search Google Scholar
    • Export Citation
  • Meeder, J. P., , and F. T. M. Nieuwstadt, 2000: Large-eddy simulation of the turbulent dispersion of a reactive plume from a point source into a neutral atmospheric boundary layer. Atmos. Environ., 34 , 35633573.

    • Search Google Scholar
    • Export Citation
  • Nguyen, K., , J. Noonan, , I. Galbally, , and W. Physick, 1997: Predictions of plume dispersion in complex terrain: Eulerian versus Lagrangian models. Atmos. Environ., 31 , 947958.

    • Search Google Scholar
    • Export Citation
  • Nutter, P., , M. Xue, , and D. Stensrud, 2004: Application of lateral boundary condition perturbations to help restore dispersion in limited-area ensemble forecasts. Mon. Wea. Rev., 132 , 23782390.

    • Search Google Scholar
    • Export Citation
  • Olesen, H. R., 2000: The model validation kit—status and outlook. Int. J. Environ. Pollut., 14 , 6576.

  • Onogi, K., and Coauthors, 2007: The JRA-25 reanalysis. J. Meteor. Soc. Japan, 85 , 369432.

  • Sada, K., , and A. Sato, 2002: Numerical calculation of flow and stack-gas concentration fluctuation around a cubical building. Atmos. Environ., 36 , 55275534.

    • Search Google Scholar
    • Export Citation
  • Sada, K., , T. Michioka, , and Y. Ichikawa, 2006: Numerical simulation of atmospheric flow and stack gas diffusion under building and complex terrain conditions (Estimations of effective stack height and comparisons with wind tunnel experiments). JSME Int. J. Ser. B, 49 , 4859.

    • Search Google Scholar
    • Export Citation
  • Sykes, R. I., , and D. S. Henn, 1992: Large-eddy simulation of concentration fluctuations in a dispersing plume. Atmos. Environ., 26 , 31273144.

    • Search Google Scholar
    • Export Citation
  • Sykes, R. I., , D. S. Henn, , S. F. Parker, , and W. S. Lewellen, 1992: Large-eddy simulation of a turbulent reacting plume. Atmos. Environ., 26 , 25652574.

    • Search Google Scholar
    • Export Citation
  • Trini Castelli, S., , T. Hara, , R. Ohba, , and C. J. Tremback, 2006: Validation studies of turbulence closure schemes for high resolutions in mesoscale meteorological models. Atmos. Environ., 40 , 25102523.

    • Search Google Scholar
    • Export Citation
  • Warner, T. T., , R. A. Peterson, , and R. E. Treadon, 1997: A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull. Amer. Meteor. Soc., 78 , 25992617.

    • Search Google Scholar
    • Export Citation
  • Weigel, A. P., , F. K. Chow, , M. W. Rotach, , R. L. Street, , and M. Xue, 2006: High-resolution large-eddy simulations of flow in a steep Alpine valley. Part II: Flow structure and heat budgets. J. Appl. Meteor. Climatol., 45 , 87107.

    • Search Google Scholar
    • Export Citation
  • Weigel, A. P., , F. K. Chow, , and M. W. Rotach, 2007: On the nature of turbulent kinetic energy in a steep and narrow Alpine valley. Bound.-Layer Meteor., 123 , 177199.

    • Search Google Scholar
    • Export Citation
  • Weil, J. C., , P. P. Sullivan, , and C. H. Moeng, 2004: The use of large-eddy simulations in Lagrangian particle dispersion models. J. Atmos. Sci., 61 , 28772887.

    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 2004: Toward numerical modeling in the “terra incognita”. J. Atmos. Sci., 61 , 18161826.

  • Xue, M., , K. K. Droegemeier, , V. Wong, , A. Shapiro, , and K. Brewster, 1995: ARPS version 4.0 user’s guide. Center for Analysis and Prediction of Storms, University of Oklahoma, 380 pp.

  • Xue, M., , K. K. Droegemeier, , and V. Wong, 2000: The Advanced Regional Prediction System (ARPS): A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part I: Model dynamics and verification. Meteor. Atmos. Phys., 75 , 161193.

    • Search Google Scholar
    • Export Citation
  • Xue, M., and Coauthors, 2001: The Advanced Regional Prediction System (ARPS): A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Phys., 76 , 143165.

    • Search Google Scholar
    • Export Citation
  • Xue, M., , D. Wang, , J. Gao, , K. Brewster, , and K. K. Droegemeier, 2003: The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation. Meteor. Atmos. Phys., 82 , 139170.

    • Search Google Scholar
    • Export Citation
  • Yamada, T., 2000: Numerical simulations of airflows and tracer transport in the southwestern United States. J. Appl. Meteor., 39 , 399411.

    • Search Google Scholar
    • Export Citation
  • Zängl, G., , B. Chimani, , and C. Häberli, 2004: Numerical simulations of the foehn in the Rhine Valley on 24 October 1999 (MAP IOP 10). Mon. Wea. Rev., 132 , 368389.

    • Search Google Scholar
    • Export Citation
  • Zhong, S. Y., , and J. Fast, 2003: An evaluation of the MM5, RAMS, and Meso-Eta models at subkilometer resolution using VTMX field campaign data in the Salt Lake Valley. Mon. Wea. Rev., 131 , 13011322.

    • Search Google Scholar
    • Export Citation
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High-Resolution Large-Eddy Simulations of Scalar Transport in Atmospheric Boundary Layer Flow over Complex Terrain

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  • 1 Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, Chiba, Japan
  • | 2 Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California
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Abstract

This paper presents high-resolution numerical simulations of the atmospheric flow and concentration fields accompanying scalar transport and diffusion from a point source in complex terrain. Scalar dispersion is affected not only by mean flow, but also by turbulent fluxes that affect scalar mixing, meaning that predictions of scalar transport require greater attention to the choice of numerical simulation parameters than is typically needed for mean wind field predictions. Large-eddy simulation is used in a mesoscale setting, providing modeling advantages through the use of robust turbulence models combined with the influence of synoptic flow forcing and heterogeneous land surface forcing. An Eulerian model for scalar transport and diffusion is implemented in the Advanced Regional Prediction System mesoscale code to compare scalar concentrations with data collected during field experiments conducted at Mount Tsukuba, Japan, in 1989. The simulations use horizontal grid resolution as fine as 25 m with up to eight grid nesting levels to incorporate time-dependent meteorological forcing. The results show that simulated ground concentration values contain significant errors relative to measured values because the mesoscale wind typically contains a wind direction bias of a few dozen degrees. Comparisons of simulation results with observations of arc maximum concentrations, however, lie within acceptable error bounds. In addition, this paper investigates the effects on scalar dispersion of computational mixing and lateral boundary conditions, which have received little attention in the literature—in particular, for high-resolution applications. The choice of lateral boundary condition update interval is found not to affect time-averaged quantities but to affect the scalar transport strongly. More frequent updates improve the simulated ground concentration values. In addition, results show that the computational mixing coefficient must be set to as small a value as possible to improve scalar dispersion predictions. The predicted concentration fields are compared as the horizontal grid resolution is increased from 190 m to as fine as 25 m. The difference observed in the results at these levels of grid refinement is found to be small relative to the effects of computational mixing and lateral boundary updates.

Corresponding author address: Takenobu Michioka, Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, 1646 Abiko, Abiko-shi, 270-1194 Chiba-ken, Japan. Email: michioka@criepi.denken.or.jp

Abstract

This paper presents high-resolution numerical simulations of the atmospheric flow and concentration fields accompanying scalar transport and diffusion from a point source in complex terrain. Scalar dispersion is affected not only by mean flow, but also by turbulent fluxes that affect scalar mixing, meaning that predictions of scalar transport require greater attention to the choice of numerical simulation parameters than is typically needed for mean wind field predictions. Large-eddy simulation is used in a mesoscale setting, providing modeling advantages through the use of robust turbulence models combined with the influence of synoptic flow forcing and heterogeneous land surface forcing. An Eulerian model for scalar transport and diffusion is implemented in the Advanced Regional Prediction System mesoscale code to compare scalar concentrations with data collected during field experiments conducted at Mount Tsukuba, Japan, in 1989. The simulations use horizontal grid resolution as fine as 25 m with up to eight grid nesting levels to incorporate time-dependent meteorological forcing. The results show that simulated ground concentration values contain significant errors relative to measured values because the mesoscale wind typically contains a wind direction bias of a few dozen degrees. Comparisons of simulation results with observations of arc maximum concentrations, however, lie within acceptable error bounds. In addition, this paper investigates the effects on scalar dispersion of computational mixing and lateral boundary conditions, which have received little attention in the literature—in particular, for high-resolution applications. The choice of lateral boundary condition update interval is found not to affect time-averaged quantities but to affect the scalar transport strongly. More frequent updates improve the simulated ground concentration values. In addition, results show that the computational mixing coefficient must be set to as small a value as possible to improve scalar dispersion predictions. The predicted concentration fields are compared as the horizontal grid resolution is increased from 190 m to as fine as 25 m. The difference observed in the results at these levels of grid refinement is found to be small relative to the effects of computational mixing and lateral boundary updates.

Corresponding author address: Takenobu Michioka, Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, 1646 Abiko, Abiko-shi, 270-1194 Chiba-ken, Japan. Email: michioka@criepi.denken.or.jp

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