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Global Lagrangian Atmospheric Dispersion Model

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The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data.

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  1. V. V. Penenko and A. E. Aloyan, Models and Methods for Environmental Protection Problems (Nauka, Novosibirsk, 1985) [in Russian].

    Google Scholar 

  2. A. Stohl, C. Forster, A. Frank, et al., “Technical Note: The Lagrangian Particle Dispersion Model FLEXPART Version 6.2,” Atmos. Chem. Phys. 5 (9), 2461–2474 (2005).

    Article  Google Scholar 

  3. R. R. Draxler and G. D. Rolph, HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model, NOAA Air Resources Laboratory, College Park, MD, 2013.

    Google Scholar 

  4. R. H. Maryon, F. B. Smith, B. J. Conway, and D. M. Goddard, “The U.K. nuclear accident model,” Prog. Nucl. Energy 26 (2), 85–104 (1991).

    Article  Google Scholar 

  5. A. Ganshin, T. Oda, M. Saito, et al., “A global coupled Eulerian–Lagrangian model and 1 × 1 km CO2 surface flux dataset for high-resolution atmospheric CO2 transport simulations,” Geosci. Model Dev. 5, 231–243 (2012).

    Article  Google Scholar 

  6. Lagrangian Modeling of the Atmosphere, Ed. by J. Lin, D. Brunner, C. Gerbig, et al. (American Geophysical Union, Washington, DC, 2013). doi 10.1029/2012GM001263

  7. A. Lukyanov, H. Nakane, and V. Yushkov, “Lagrangian estimation of ozone loss in the core and edge region of the Arctic polar vortex 1995/1996: Model results and observations,” J. Atmos. Chem. 44 (2), 191–210 (2003).

    Article  Google Scholar 

  8. M. Uliasz and R. A. Pielke, “Implementation of Lagrangian particle dispersion model for mesoscale and regional air quality studies,” in Air Pollution, Ed. by P. Zannetti, C. A. Brebia, J. E. Garcia, and G. Ayala Milian (Computational Mechanics Publications, Southampton 1993), pp. 157–164.

    Google Scholar 

  9. J. Saltbones, A. Foss, and J. Bartnicki, “Norwegian Meteorological Institute’s real-time dispersion model SNAP (Severe Nuclear Accident Program): Runs for ETEX and ATMES II experiments with different meteorological input,” Atmos. Environ. 32 (24), 4277–4283 (1998).

    Article  Google Scholar 

  10. I. Pisso, E. Real, K. S. Law, et al., “Estimation of mixing in the troposphere from Lagrangian trace gas reconstructions during long-range pollution plume transport,” J. Geophys. Res. 114, D19301 (2009). doi 10.1029/2008JD011289

    Article  Google Scholar 

  11. A. V. Gan’shin, A. N. Luk’yanov, V. U. Khattatov, et al., “Volcanic ash over the Russian Federation territory after the volcanic eruption in Iceland on April 14, 2010 from the data of model simulations and observations,” Russ. Meteorol. Hydrol. 37 (9), 598–603 (2012).

    Article  Google Scholar 

  12. D. P. Dee, S. M. Uppala, A. T. Simmons, et al., “The ERA-Interim reanalysis: Configuration and performance of the data assimilation system,” Q. J. R. Meteorol. Soc. 137, 553–597 (2011). doi 10.1002/qj.828

    Article  Google Scholar 

  13. E. Kalnay, M. Kanamitsu, R. Kistler, et al., “The NCEP/NCAR 40-year reanalysis project,” Bull. Am. Meteorol. Soc. 77 (3), 437–471 (1996).

    Article  Google Scholar 

  14. W. Peters, A. R. Jacobson, C. Sweeney, et al., “An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker,” Proc. Natl. Acad. Sci. U. S. A. 104 (48), 18925–18930 (2007).

    Article  Google Scholar 

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Correspondence to A. N. Lukyanov.

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Original Russian Text © A.N. Lukyanov, A.V. Gan’shin, R.V. Zhuravlev, Sh.Sh. Maksyutov, A.V. Varlagin, 2015, published in Izvestiya AN. Fizika Atmosfery i Okeana, 2015, Vol. 51, No. 5, pp. 570–577.

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Lukyanov, A.N., Gan’shin, A.V., Zhuravlev, R.V. et al. Global Lagrangian Atmospheric Dispersion Model. Izv. Atmos. Ocean. Phys. 51, 505–511 (2015).

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