Editorial Type:
Article
Article Type:
Research Article

Evaluation of Numerical Predictions of Boundary Layer Structure during the Lake Michigan Ozone Study

Perry C. Shafran Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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Nelson L. Seaman Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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George A. Gayno Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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Print Publication:
01 Mar 2000
DOI:
https://doi.org/10.1175/1520-0450(2000)039<0412:EONPOB>2.0.CO;2
Page(s):
412–426
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Abstract

The performance of two types of turbulence closures is compared in a 3D numerical investigation of an episode with poor air quality. The first is the Blackadar boundary layer scheme, which has a nonlocal closure for unstable conditions. The second is a 1.5-order scheme, known as Gayno–Seaman (GS), that predicts turbulent kinetic energy and is suitable for simulating foggy as well as dry conditions. In 3D mesoscale simulations of a 5-day air pollution episode over the Midwest, the GS turbulence scheme is found to be effective for reducing model errors in boundary layer depth and surface wind speeds, relative to the Blackadar nonlocal closure. In this case, wind direction and surface temperature simulations have comparable skill with both closures. The 1.5-order GS scheme also is shown to interact well with a four-dimensional data assimilation system that avoids assimilation of smooth analyses below 1500 m. Experiments that combined the 1.5-order boundary layer scheme and a multiscale data assimilation approach produced the lowest model errors overall while producing boundary layer trajectories that are consistent with the observed locations of ozone maxima. The efficiency of the two turbulence schemes was found to be nearly identical, each requiring about 25% of the overall central processing unit computation time.

Corresponding author address: Dr. Nelson L. Seaman, Dept. of Meteorology, The Pennsylvania State University, University Park, PA 16802.

Abstract

The performance of two types of turbulence closures is compared in a 3D numerical investigation of an episode with poor air quality. The first is the Blackadar boundary layer scheme, which has a nonlocal closure for unstable conditions. The second is a 1.5-order scheme, known as Gayno–Seaman (GS), that predicts turbulent kinetic energy and is suitable for simulating foggy as well as dry conditions. In 3D mesoscale simulations of a 5-day air pollution episode over the Midwest, the GS turbulence scheme is found to be effective for reducing model errors in boundary layer depth and surface wind speeds, relative to the Blackadar nonlocal closure. In this case, wind direction and surface temperature simulations have comparable skill with both closures. The 1.5-order GS scheme also is shown to interact well with a four-dimensional data assimilation system that avoids assimilation of smooth analyses below 1500 m. Experiments that combined the 1.5-order boundary layer scheme and a multiscale data assimilation approach produced the lowest model errors overall while producing boundary layer trajectories that are consistent with the observed locations of ozone maxima. The efficiency of the two turbulence schemes was found to be nearly identical, each requiring about 25% of the overall central processing unit computation time.

Corresponding author address: Dr. Nelson L. Seaman, Dept. of Meteorology, The Pennsylvania State University, University Park, PA 16802.

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Journal of Applied Meteorology and Climatology

  • Anthes, R. A., 1977: A cumulus parameterization scheme utilizing a one-dimensional cloud model. Mon. Wea. Rev.,105, 270–286.

  • Ballard, S. P., B. W. Golding, and R. N. B. Smith, 1991: Mesoscale model experimental forecasts of the Haar of northeast Scotland. Mon. Wea. Rev.,119, 2107–2123.

  • Betts, A. K., 1973: Non-precipitating cumulus convection and its parameterization. Quart. J. Roy. Meteor. Soc.,99, 178–196.

  • Blackadar, A. K., 1962: The vertical distribution of wind and turbulentexchange in a neutral atmosphere. J. Geophys. Res.,67, 3095–3102.

  • Blackadar, A. K., 1979: High resolution models of the planetary boundary layer. Advances in Environmental Science and Engineering, J. Pfafflin and E. Ziegler, Eds., Vol. 1, Gordon and Breach, 50–85.

  • Bougeault, Ph., 1981: Modeling the trade-wind cumulus boundary layer. Part I: Testing the ensemble cloud relations against numerical data. J. Atmos. Sci.,38, 2414–2428.

  • Bowne, N., and D. Shearer, 1991: Summary of LMOS 1991 field measurement program. Final Tech. Rep. ENSR Consulting and Engineering, Doc. 4133-001-300, 135 pp. [Available from ENSR Consulting and Engineering, 1220 Avenida Acaso, Camarillo, CA 93012.].

  • Deardorff, J. W., 1972: Parameterization of the planetary boundary layer for use in general circulation models. Mon. Wea. Rev.,100, 93–106.

  • Donaldson, C. du P., 1973: Construction of a dynamic model of the production of atmospheric turbulence and the dispersal of atmospheric pollutants. Workshop on Micrometeorology, D. A. Haugen, Ed., Amer. Meteor. Soc., 313–390.

  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci.,46, 3077–3107.

  • Dudhia, J., 1993: A nonhydrostatic version of the Penn State–NCAR Mesoscale Model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev.,121, 1493–1513.

  • Eastman, J. L., R. A. Pielke, and W. A. Lyons, 1995: Comparison of lake-breeze model solutions with tracer data. J. Appl. Meteor.,34, 1398–1418.

  • Gayno, G. A., 1994: Development of a higher-order, fog-producing boundary layer model suitable for use in numerical weather prediction. M. S. thesis, Dept. of Meteorology, The Pennsylvania State University, 104 pp. [Available from Dept. of Meteorology, The Pennsylvania State University, University Park, PA 16802.].

  • Gayno, G. A., N. L. Seaman, A. M. Lario, and D. R. Stauffer, 1994: Forecasting visibility using a 1.5-order closure boundary layer scheme in a 12-km non-hydrostatic model. Preprints, 10th Conf. on Numerical Weather Prediction, Portland, OR, Amer. Meteor. Soc., 18–20.

  • Grell, G. A., J. Dudhia, and D. R. Stauffer, 1994: A description of the Fifth-Generation Penn State/NCAR mesoscale model (MM5). NCAR Tech. Note, NCAR/TN-398+STR, 122 pp. [Available from NCAR, P.O. Box 3000, Boulder, CO 80307.].

  • Holtslag, A. A. M., and B. A. Boville, 1993: Local versus nonlocal boundary-layer diffusion in a global climate model. J. Climate,6, 1825–1842.

  • Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci.,47, 2784–2802.

  • Kain, J. S., and J. M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165–170.

  • Kumar, N., and A. G. Russell, 1995: Comparing prognostic and diagnostic meteorological fields and their impacts on photochemical air quality modeling. Atmos. Environ.,29, 1989–2010.

  • Lumley, J. L, and B. Khajeh-Nouri, 1974: Computational modeling of turbulent transport. Advances in Geophysics, Vol. 18A, Academic Press, 169–192.

  • Lyons, W. A., C. J. Tremback, and R. A. Pielke, 1995: Applications of the Regional Atmospheric Modeling System (RAMS) to provide input to photochemical grid models for the Lake Michigan Ozone Study (LMOS). J. Appl. Meteor.,34, 1762–1786.

  • [bu797]Mellor, G. L., and T. Yamada, 1974: A hierarchy of turbulence closure models for planetary boundary layers. J. Atmos. Sci.,31, 1791–1806.

  • Michelson, S. A., and N. L. Seaman, 2000: Assimilation of NEXRAD-VAD winds in summertime meteorological simulations over the northeastern United States. J. Appl. Meteor.,39, 367–383.

  • Moeng, C.-H., and J. C. Wyngaard, 1989: Evaluation of turbulent transport and dissipation closures in second-order modeling. J. Atmos. Sci.,46, 2311–2330.

  • Musson-Genon, L., 1987: Numerical simulation of a fog event with a one-dimensional boundary layer model. Mon. Wea. Rev.,115, 592–607.

  • Seaman, N. L., 2000: Meteorological modeling for air-quality assessments. Atmos. Environ., in press.

  • Seaman, N. L., and P. C. Shafran, 1996: Investigation of low-level jets and a mesoscale convective system observed by the Lake Michigan Ozone Study special observing system. Preprints, Sixth PSU/NCAR Mesoscale Model Users’ Workshop, Boulder, CO, National Center for Atmospheric Research, 109–113.

  • Seaman, N. L., and S. A. Michelson, 2000: Mesoscale meteorological structure of a high-ozone episode during the 1995 NARSTO-Northeast study. J. Appl. Meteor.,39, 384–398.

  • Seaman, N. L., D. R. Stauffer, and A. L. Lario-Gibbs, 1995: A multiscale four-dimensional data assimilation system applied in the San Joaquin Valley during SARMAP. Part I: Modeling design and basic performance characteristics. J. Appl. Meteor.,34, 1739–1761.

  • Seaman, N. L., S. A. Michelson, P. C. Shafran, and D. R. Stauffer, 1998: Forecasts of a severe squall line development in MM5 using explicit moist physics at 4-km resolution. Preprints, 16th Conf. on Weather Analysis and Forecasting, Phoenix, AZ, Amer. Meteor. Soc., J83–J86.

  • Shafran, P. C., 1997: Summertime circulation patterns in the Lake Michigan area. M. S. thesis, Dept. of Meteorology, The Pennsylvania State University, 206 pp. [Available from Dept. of Meteorology, The Pennsylvania State University, University Park, PA 16802.].

  • Sommeria, G., and J. W. Deardorff, 1977: Subgrid-scale condensation in models of nonprecipitating clouds. J. Atmos. Sci.,34, 344–355.

  • Stauffer, D. R., and N. L. Seaman, 1990: Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I: Experiments with synoptic-scale data. Mon. Wea. Rev.,118, 1250–1277.

  • Stauffer, D. R., and N. L. Seaman, 1994: Multiscale four-dimensional data assimilation. J. Appl. Meteor.,33, 416–434.

  • Stauffer, D. R., N. L. Seaman, and F. S. Binkowski, 1991: Use of four-dimensional data assimilation in a limited-area mesoscale model part II: Effects of data assimilation within the planetary boundary layer. Mon. Wea. Rev.,119, 734–754.

  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, 666 pp.

  • Tennekes, H., and J. L. Lumley, 1972: A First Course in Turbulence. The MIT Press, 300 pp.

  • Therry, G., and P. Lacarrere, 1983: Improving the eddy kinetic energy model for planetary boundary layer description. Bound.-Layer Meteor.,25, 63–88.

  • Wang, W., and N. L. Seaman, 1997: A comparison study of convective parameterization schemes in a mesoscale model. Mon. Wea. Rev.,125, 252–278.

  • Xu, Q., and C. J. Qiu, 1994: Simple adjoint methods for single-Doppler wind analysis with a strong constraint of mass conservation. J. Atmos. Oceanic Technol.,11, 289–298.

  • Xu, Q., and C. J. Qiu, 1995: Adjoint-method retrievals of low-altitude wind fields from single-Doppler reflectivity and radial-wind data. J. Atmos. Oceanic Technol.,12, 1111–1119.

  • Yamada, T., 1977: A numerical experiment on pollutant dispersion in a horizontally homogenous atmospheric boundary layer. Atmos. Environ.,11, 1015–1024.

  • Zhang, D.-L., and R. A. Anthes, 1982: A high-resolution model of the planetary boundary layer—Sensitivity tests and comparisons with SESAME-79 data. J. Appl. Meteor.,21, 1594–1609.

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