Atmospheric Prognostic and Dispersion Model Design for use in the European Ensemble Modeling Exercises

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The Savannah River Technology Center (SRTC) of the Department of Energy (DOE)Savannah River Site (SRS) has been involved with predicting the transport and dispersion of hazardous atmospheric releases for many years. The SRS utilizes an automated, real-time capability for consequence assessment during emergency response to local releases. The emphasis during these situations is to provide accurate guidance as quickly as possible. Consequently, atmospheric transport and dispersion models of a simple physical nature (such as Gaussian plume models) have typically been used in an effort to provide timely responses. However, use of one or two-dimensional (steady-state) winds are inadequate in conditions ... continued below

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Buckley, R. L. October 30, 2003.

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The Savannah River Technology Center (SRTC) of the Department of Energy (DOE)Savannah River Site (SRS) has been involved with predicting the transport and dispersion of hazardous atmospheric releases for many years. The SRS utilizes an automated, real-time capability for consequence assessment during emergency response to local releases. The emphasis during these situations is to provide accurate guidance as quickly as possible. Consequently, atmospheric transport and dispersion models of a simple physical nature (such as Gaussian plume models) have typically been used in an effort to provide timely responses. However, use of one or two-dimensional (steady-state) winds are inadequate in conditions of high spatial and temporal variability (such as during frontal passage). Increased computing capabilities have led to the use of more sophisticated three dimensional prognostic models that may capture some of these higher resolution phenomena. In an ideal situation, the decision-maker would want to use the best model each time an accident occurred. Unfortunately, due to the nonunique nature of solutions to the nonlinear equations governing the atmosphere, model A may perform better than models B and C in one type of weather scenario, and worse during a different situation.Therefore, it is not always possible to distinguish which model is best, especially during a forecast situation. The use of an ensemble approach of averaging results from a variety of model solutions is beneficial to the modeler in providing the DM guidance on model uncertainties. Meteorological forecasts generated by numerical models provide individual realizations of the atmosphere. The resulting wind and turbulence fields are then used to drive atmospheric dispersion (transport and diffusion) models. Although many modeling agencies utilize ensemble-modeling techniques to determine atmospheric model sensitivities of prognostic fields (i.e. wind, temperature, radiation, etc.), the European Union has conducted two programs that are the first to examine atmospheric dispersion model output using an ensemble approach. The research discussed in this report is the result of participation in the latest of these two programs, ENSEMBLE.

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  • 16th conference on Numerical Weather Prediction, Seattle, WA (US), 01/11/2004--01/15/2004

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  • Report No.: WSRC-MS-2003-00690
  • Grant Number: AC09-96SR18500
  • Office of Scientific & Technical Information Report Number: 817232
  • Archival Resource Key: ark:/67531/metadc735929

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  • October 30, 2003

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  • Oct. 18, 2015, 6:40 p.m.

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  • May 4, 2016, 9:30 p.m.

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Buckley, R. L. Atmospheric Prognostic and Dispersion Model Design for use in the European Ensemble Modeling Exercises, article, October 30, 2003; South Carolina. (digital.library.unt.edu/ark:/67531/metadc735929/: accessed September 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.