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Ensemble simulations with coupled atmospheric dynamic and dispersion models: Illustrating uncertainties in dosage simulations

  • Thomas T. Warner
  • , Rong Shyang Sheu
  • , James F. Bowers
  • , R. Ian Sykes
  • , Gregory C. Dodd
  • , Douglas S. Henn
    • National Center for Atmospheric Research

    Research output: Contribution to journalArticlepeer-review

    42 Scopus citations

    Abstract

    Ensemble simulations made using a coupled atmospheric dynamic model and a probabilistic Lagrangian puff dispersion model were employed in a forensic analysis of the transport and dispersion of a toxic gas that may have been released near Al Muthanna, Iraq, during the Gulf War. The ensemble study had two objectives, the first of which was to determine the sensitivity of the calculated dosage fields to the choices that must be made about the configuration of the atmospheric dynamic model. In this test, various choices were used for model physics representations and for the large-scale analyses that were used to construct the model initial and boundary conditions. The second study objective was to examine the dispersion model's ability to use ensemble inputs to predict dosage probability distributions. Here, the dispersion model was used with the ensemble mean fields from the individual atmospheric dynamic model runs, including the variability in the individual wind fields, to generate dosage probabilities. These are compared with the explicit dosage probabilities derived from the individual runs of the coupled modeling system. The results demonstrate that the specific choices made about the dynamic-model configuration and the large-scale analyses can have a large impact on the simulated dosages. For example, the area near the source that is exposed to a selected dosage threshold varies by up to a factor of 4 among members of the ensemble. The agreement between the explicit and ensemble dosage probabilities is relatively good for both low and high dosage levels. Although only one ensemble was considered in this study, the encouraging results suggest that a probabilistic dispersion model may be of value in quantifying the effects of uncertainties in a dynamic-model ensemble on dispersion model predictions of atmospheric transport and dispersion.

    Original languageEnglish
    Pages (from-to)488-504
    Number of pages17
    JournalJournal of Applied Meteorology
    Volume41
    Issue number5
    DOIs
    StatePublished - May 2002

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