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Examination of model predictions at different horizontal grid resolutions

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Abstract

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs and data requirements increase significantly with increasing grid resolution. Therefore, it is important to examine, for any given application, whether the expected benefit of increased grid resolution justifies the extra costs. In this study, we examine temperature and ozone observations and model predictions for three high ozone episodes that occurred over the northeastern United States during the summer of 1995. In the first set of simulations, the meteorological model RAMS4a was run with three two-way nested grids of 108/36/12 km grid spacing covering the United States and the photochemical model UAM-V was run with two grids of 36/12 km grid spacing covering the eastern United States. In the second set of simulations, RAMS4a was run with four two-way nested grids of 108/36/12/4 km grid spacing and UAM-V was run with three grids of 36/12/4 km grid spacing with the finest resolution covering the northeastern United States. Our analysis focuses on the comparison of model predictions for the finest grid domain of the simulations, namely, the region overlapping the 12 km and 4 km domains. A comparison of 12 km versus 4 km fields shows that the increased grid resolution leads to finer texture in the model predictions; however, comparisons of model predictions with observations do not reveal the expected improvement in the predictions. While high-resolution modeling has scientific merit and potential uses, the currently available monitoring networks, in conjunction with the scarceness of highly resolved spatial input data and the limitations of model formulation, do not allow confirmation of the expected superiority of the high-resolution model predictions.

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References

  1. Walko, R.L., Tremback, C.J. and Hertenstein, R.F.A.: 1995, RAMS — The Regional Atmospheric Modeling System, Version 3b, User’s Guide, ASTER Division, Mission Research Corporation, Fort Collins, CO.

    Google Scholar 

  2. Grell, G.A., Dudhia, J. and Stauffer, D.: 1994, A Description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5). NCAR Technical Note, NCAR/TN-398 + STR.

  3. Systems Applications International: 1995, Users Guide to the Variable Grid Urban Airshed Model (UAM-V), Systems Applications International, San Rafael, CA, 131 pp. [Available from Systems Applications International, 101 Lucas Valley Rd., San Rafael, CA 94903.]

    Google Scholar 

  4. ENVIRON: 1997, User’s Guide to the Comprehensive Air Quality Model with Extensions (CAMx). Available from ENVIRON International Corporation, 101 Rowland Way, Novato, CA 94945.

  5. Byun, D.W. and Ching, J.K.S. (eds.): 1999, Science algorithms of the EPA Models-3 Community Multiscale Air Quality Model (CMAQ) modeling system. EPA/600/R-99/030, U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC 20460.

    Google Scholar 

  6. Kunz, R. and Moussiopoulos, N.: 1997, Implementation and assessment of a one-way nesting technique for high resolution wind flow simulations, Atmos. Environ. 31, 3167–3176.

    Google Scholar 

  7. Mass, C., Ovens, D., Albright, M. and Westrick, K.: 2002, Does Increasing Horizontal Resolution Produce Better Forecasts? The Results of Two Years of Real-Time Numerical Weather Prediction in the Pacific Northwest, Bull. Amer. Meteorol. Soc. 83, 407–430.

    Google Scholar 

  8. Colle, B.A, Olson, J.B. and Tongue, J.S.: 2001, Verification of the Eta and Real-Time MM5 over the Eastern U.S., paper presented at Eleventh PSU/NCAR MM5 Users’ Workshop, Foothills Laboratory, NCAR, Boulder, Colorado, June 25–June 27 2001. (Available at http://www.mmm.ucar.edu/mm5/workshop/ws01/).

  9. Geron, C., Guenther, A. and Pierce, T.: 1994, An Improved Model for Estimating Emissions of Volatile Organic Compounds from Forests in the Eastern United States, J. Geophys. Res. 99, 12773–12791.

    Google Scholar 

  10. Sistla, G., Hao, W., Ku, J.-Y., Kallos, G., Zhang, K., Mao, H. and Rao, S.T.: 2001, An Operational Evaluation of Two Regional-Scale Ozone Air Quality Modeling Systems over the Eastern United States, Bull. Amer. Meteorol. Soc. 82, 945–964.

    Google Scholar 

  11. Biswas, J. and Rao, S.T.: 2001, Uncertainties in Episodic Ozone Modeling Stemming from Uncertainties in the Meteorological Fields. J. Appl. Meteorol. 40, 117–136.

    Google Scholar 

  12. Lagouvardos, K., Kallos, G. and Kotroni, V.: 1997a, Modeling and Analysis of Ozone and its Precursors in the Northeast U.S.A. (Atmospheric Model Simulations), Final report to Electric Power Research Institute, Palo Alto, CA, 46 pp. [Available from Office of Science and Technology, NYSDEC, 50 Wolf Rd., Albany, NY 12233-3259.

  13. Lagouvardos, K., Kotroni, V., Kallos, G. and Rao, S.T.: 1999, An Analysis of the Meteorological and Air Quality Conditions during an Extreme Ozone Episode over the Northeastern USA, Intern. J. Environ. Poll. 14, 581–587.

    Google Scholar 

  14. Willmott, C.J.: 1982, Some Comments on the Evaluation of Model Merformance, Bull. Amer. Meteorol. Soc. 63, 1309–1313.

    Google Scholar 

  15. Hanna, S.R.: 1994, Mesoscale Meteorological Model Evaluation Techniques with Emphasis on Needs of Air Quality Models. In: R.A. Pielke and R.P. Pearce (eds.), Mesoscale Modeling of the Atmosphere, pp. 47–58, Meteorological monographs 25, American Meteorological Society, 45 Beacon Str., Boston, MA 02108.

    Google Scholar 

  16. Olerud, D. and Wheeler, N.: 1997, Investigation of the Regional Atmospheric Modeling System (RAMS) for the Ozone Transport Assessment Group (OTAG), Report to the Southeast Modeling Center, MCNC Environmental Programs, Research Triangle Park, NC 27709.

    Google Scholar 

  17. McNally, D. and Tesche, T.W.: 1993, MAPS Sample Products, Alpine Geophysics, 16225 W. 74th Dr., Golden, CO 80403.

    Google Scholar 

  18. American Society for Testing and Materials D 6589: 2000, tandard Guide for Statistical Evaluation of Atmospheric Dispersion Model Performance (D 6589) (available at http://www.astm.org), 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428, 17 p.

  19. Sistla, G., Zhow, N., Hao, W., Ku, J.-Y., Rao, S.T., Bornstein, R., Freedman, F. and Thunis, P.: 1996, Effects of Uncertainties in Meteorological Inputs on Urban Airshed Model Predictions and Ozone Control Strategies, Atmos. Environ. 30, 2011–2025.

    Google Scholar 

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Correspondence to John S. Irwin.

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The U.S. Government’s right to retain a non-exclusive royalty-free licence in and to any copyright is acknowledged.

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Gego, E., Hogrefe, C., Kallos, G. et al. Examination of model predictions at different horizontal grid resolutions. Environ Fluid Mech 5, 63–85 (2005). https://doi.org/10.1007/s10652-005-0486-3

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  • DOI: https://doi.org/10.1007/s10652-005-0486-3

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