Diagnosing the Surface Layer Parameters for Dispersion Models within the Meteorological-to-Dispersion Modeling Interface

M. Sofiev Finnish Meteorological Institute, Helsinki, Finland

Search for other papers by M. Sofiev in
Current site
Google Scholar
PubMed
Close
,
E. Genikhovich Main Geophysical Observatory, St. Petersburg, Russia

Search for other papers by E. Genikhovich in
Current site
Google Scholar
PubMed
Close
,
P. Keronen University of Helsinki, Helsinki, Finland

Search for other papers by P. Keronen in
Current site
Google Scholar
PubMed
Close
, and
T. Vesala University of Helsinki, Helsinki, Finland

Search for other papers by T. Vesala in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The problem of providing dispersion models with meteorological information from general atmospheric models used, for example, for weather forecasting is considered. As part of a generalized meteorological-to-dispersion model interface, a noniterative scheme diagnosing the surface layer characteristics from wind, temperature, and humidity profiles was developed. The scheme verification included long-term comparison with data of meteorological masts at Cabauw, the Netherlands, and Hyytiälä, Finland. The algorithm compatibility and consistency with the High-Resolution Limited-Area Model (HIRLAM) was also checked, as this model is routinely used as a meteorological driver for the Air Quality and Emergency Modeling System (SILAM). The comparison with Cabauw mast data showed a good quantitative agreement between observed and diagnosed heat and momentum fluxes: the temporal correlation coefficient was ∼0.8, bias was less than 10% of the absolute flux levels, regression slope deviated from unity for less than 20% with the intercept being less than 10% of the absolute flux values, and so on. In the case of complex surface features (Hyytiälä mast in forest) the scheme proved to be robust with large deviations appearing only if the input profile data were taken outside the constant-flux layer. Comparison with the HIRLAM model showed qualitatively good agreement but also highlighted several differences between the goals, standards, and methodologies of meteorological and dispersion models. The scheme was implemented in SILAM, which served as the development platform.

Corresponding author address: M. Sofiev, Finnish Meteorological Institute, Erik Palmenin Aukio 1, Helsinki, Finland. Email: mikhail.sofiev@fmi.fi

Abstract

The problem of providing dispersion models with meteorological information from general atmospheric models used, for example, for weather forecasting is considered. As part of a generalized meteorological-to-dispersion model interface, a noniterative scheme diagnosing the surface layer characteristics from wind, temperature, and humidity profiles was developed. The scheme verification included long-term comparison with data of meteorological masts at Cabauw, the Netherlands, and Hyytiälä, Finland. The algorithm compatibility and consistency with the High-Resolution Limited-Area Model (HIRLAM) was also checked, as this model is routinely used as a meteorological driver for the Air Quality and Emergency Modeling System (SILAM). The comparison with Cabauw mast data showed a good quantitative agreement between observed and diagnosed heat and momentum fluxes: the temporal correlation coefficient was ∼0.8, bias was less than 10% of the absolute flux levels, regression slope deviated from unity for less than 20% with the intercept being less than 10% of the absolute flux values, and so on. In the case of complex surface features (Hyytiälä mast in forest) the scheme proved to be robust with large deviations appearing only if the input profile data were taken outside the constant-flux layer. Comparison with the HIRLAM model showed qualitatively good agreement but also highlighted several differences between the goals, standards, and methodologies of meteorological and dispersion models. The scheme was implemented in SILAM, which served as the development platform.

Corresponding author address: M. Sofiev, Finnish Meteorological Institute, Erik Palmenin Aukio 1, Helsinki, Finland. Email: mikhail.sofiev@fmi.fi

Save
  • Barker, E. M., and T. L. Baxter, 1975: A note on computation of atmospheric surface layer fluxes for use in numerical modeling. J. Appl. Meteor., 14 , 620622.

    • Search Google Scholar
    • Export Citation
  • Beljaars, A. C. M., and A. A. M. Holtslag, 1991: Flux parameterization over land surfaces for atmospheric models. J. Appl. Meteor., 30 , 327341.

    • Search Google Scholar
    • Export Citation
  • Berkowicz, R., and L. P. Prahm, 1982: Evaluation of the profile method for estimation of surface fluxes of momentum and heat. Atmos. Environ., 16 , 28092819.

    • Search Google Scholar
    • Export Citation
  • Brandt, J., J. H. Christensen, L. M. Frohn, and Z. Zlatev, 2000: Numerical modelling of transport, dispersion, and deposition—Validation against ETEX-1, ETEX-2 and Chernobyl. Environ. Model. Softw., 15 , (6–7). 521531.

    • Search Google Scholar
    • Export Citation
  • Budyko, M. I., 1956: The Heat Balance of the Earth’s Surface (in Russian). Gidrometeoizdat, 255 pp.

  • Businger, J. A., J. C. Wyngaard, Y. Izumi, and E. F. Bradley, 1971: Flux-profile relationships in the atmospheric surface layer. J. Atmos. Sci., 28 , 181189.

    • Search Google Scholar
    • Export Citation
  • Dyer, A. J., 1974: A review of the flux-profile relationships. Bound.-Layer Meteor., 7 , 363372.

  • Fisher, B. E. A., and Coeditors, 1998: Harmonization of the pre-processing of meteorological data for atmospheric dispersion models. COST Action 710—Final Rep., EUR 18195 EN, European cooperation in the field of scientific and technical research, European Commission, 431 pp.

    • Search Google Scholar
    • Export Citation
  • Garrat, J. R., 1994: The Atmospheric Boundary Layer. Cambridge University Press, 316 pp.

  • Genikhovich, E. L., 1999: Double-flux description of the transport of passive scalars in the convective atmospheric boundary layer. Air Pollution Modelling and Its Application XIII, S.-E. Gryning and E. Batchvarova, Eds., Kluwer Academic/Plenum Publishers, 409–416.

    • Search Google Scholar
    • Export Citation
  • Genikhovich, E. L., and G. Osipova, 1984: Determination of the exchange coefficient using data of routine meteorological observations (in Russian). Trans. Main Geophys. Obs., 479 , 6269.

    • Search Google Scholar
    • Export Citation
  • Groisman, P. Ya, and E. L. Genikhovich, 1997: Assessing surface–atmosphere interactions using former Soviet Union standard meteorological network data. Part I: Method. J. Climate, 10 , 21542183.

    • Search Google Scholar
    • Export Citation
  • Högström, U., 1988: Non-dimensional wind and temperature profiles in the atmospheric surface layer: A reevaluation. Bound.-Layer Meteor., 42 , 5578.

    • Search Google Scholar
    • Export Citation
  • Ilvesniemi, H., and C. Liu, 2001: Biomass distribution in a young Scots pine stand, Boreal. Environ. Res., 6 , 38.

  • Laikhtman, D. L., 1970: Physics of the Atmospheric Boundary Layer (in Russian). Hydrometerorological Publishers, 340 pp.

  • Louis, J. F., 1979: A parametric model of vertical eddy fluxes in the atmosphere. Bound.-Layer Meteor., 17 , 187202.

  • Louis, J. F., M. Tiedke, and J. F. Geleyn, 1982: A short history of the PBL parameterization at ECMWF. Proc. Workshop on Boundary Layer Parameterization, Reading, United Kingdom, ECMWF, 59–79.

    • Search Google Scholar
    • Export Citation
  • Monin, A. S., and A. M. Yaglom, 1981: Statistical Fluid Mechanics: Mechanics of Turbulence. MIT Press, 900 pp.

  • Nieuwstadt, F. T. M., and H. van Dop, 1982: Atmospheric Turbulence and Air Pollution Modelling. D. Reidel Publishing, 350 pp.

  • Noilhan, J., and S. Planton, 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117 , 536549.

    • Search Google Scholar
    • Export Citation
  • Paulson, C. A., 1970: The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer. J. Appl. Meteor., 9 , 857861.

    • Search Google Scholar
    • Export Citation
  • Rannik, U., 1998: On the surface layer similarity at a complex forest site. J. Geophys. Res., 103 , 86858697.

  • Rannik, U., T. Markkanen, J. Raittila, P. Hari, and T. Vesala, 2003: Turbulence statistics inside and over the forest: Influence on footprint prediction. Bound.-Layer Meteor., 109 , 163189.

    • Search Google Scholar
    • Export Citation
  • Robertson, L., J. Langner, and M. Engardt, 1999: An Eulerian limited-area atmospheric transport model. J. Appl. Meteor., 38 , 190210.

  • Rodrigues, E., B. Navascues, and J. J. Ayuso, 2002: The tiling surface scheme for HIRLAM5: Features and latest results. Proc. SRNWP/HIRLAM Workshop on Surface Processes, Turbulence and Mountain Effects, Madrid, Spain, INM, 55–63.

    • Search Google Scholar
    • Export Citation
  • Sofiev, M., P. Siljamo, I. Valkama, M. Ilvonen, and J. Kukkonen, 2006: A dispersion modelling system SILAM and its evaluation against ETEX data. Atmos. Environ., 40 , 674685. doi:10.1016/j.atmosenv.2005.09.069.

    • Search Google Scholar
    • Export Citation
  • Sofiev, M., M. Galperin, and E. Genikhovich, 2008: Construction and evaluation of Eulerian dynamic core for the air quality and emergency modeling system SILAM. Air Pollution Modelling and Its Application, C. Borrego and A. I. Miranda, Eds., NATO Science for Piece and Security Series C: Environmental Security, Vol. 19, Springer, 699–701.

    • Search Google Scholar
    • Export Citation
  • Stohl, A., and D. J. Thomson, 1999: A density correction for Lagrangian particle dispersion models. Bound.-Layer Meteor., 90 , 155167.

    • Search Google Scholar
    • Export Citation
  • Stohl, A., M. Hittenberger, and G. Wotawa, 1998: Validation of the Lagrangian particle dispersion model FLEXPART against large scale tracer experiments. Atmos. Environ., 24 , 42454264.

    • Search Google Scholar
    • Export Citation
  • Suni, T., and Coauthors, 2003: Long-term measurements of surface fluxes above a Scots pine forest in Hyytiälä, southern Finland, 1996-2001. Boreal Environ. Res., 4 , 287301.

    • Search Google Scholar
    • Export Citation
  • Vesala, T., and Coauthors, 1998: Long-term field measurements of atmosphere-surface interactions in boreal forest combining forest ecology, micrometeorology, aerosol physics and atmospheric chemistry. Trends Heat, Mass Momentum Transfer, 4 , 1735.

    • Search Google Scholar
    • Export Citation
  • Vesala, T., and Coauthors, 2005: Effect of thinning on surface fluxes in a boreal forest. Global Biogeochem. Cycles, 19 , GB2001. doi:10.1029/2004GB002316.

    • Search Google Scholar
    • Export Citation
  • Wessels, H. R. A., 1983: Distortion of the wind field by the Cabauw meteorological tower. KNMI Scientific Rep. 83-15, De Bilt, Netherlands, 37 pp.

    • Search Google Scholar
    • Export Citation
  • Wieringa, J., 1980: A revaluation of the Kansas mast influence on measurements of stress and cup anemometer overspeeding. Bound.-Layer Meteor., 18 , 411430.

    • Search Google Scholar
    • Export Citation
  • Zilitinkevich, S., 1970: Dynamics of the Atmospheric Boundary Layer (in Russian). Hydrometerorological Publishers, 290 pp.

  • Zilitinkevich, S., and P. Calanca, 2000: An extended similarity-theory formulation for the stably stratified atmospheric surface layer. Quart. J. Roy. Meteor. Soc., 126 , 19701985.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 735 500 38
PDF Downloads 222 64 7