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Eric A. Hendricks, Steve R. Diehl, Donald A. Burrows, and Robert Keith

accurate but generally more computationally expensive. Currently, there are limited field data in urban environments that can be used to evaluate the performance of these dispersion models. Thus, their utility for hazard prediction is relatively unknown. The Joint Urban 2003 Atmospheric Dispersion Study (JU2003) was completed to address this data void. It was sponsored by the United States Defense Threat Reduction Agency and the Department of Homeland Security and conducted in July 2003 in Oklahoma

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Stevens T. Chan and Martin J. Leach

which C is the data type being evaluated (e.g., wind speed or tracer concentration), C p is the model result, and C o is the observation, with overbars denoting averages. In the above metrics, FB and MG measure the systematic bias of a model in terms of differences and ratios and NMSE measures the scatter associated with the model output relative to observations. A perfect model would have FAC x = 1.0, FB = 0, MG = 1.0, and NMSE = 0. The SAA, a model performance metric calculated from wind

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Donald A. Burrows, Eric A. Hendricks, Steve R. Diehl, and Robert Keith

, 696 – 710 . Chang , J. C. , and S. R. Hanna , 2004 : Air quality model performance evaluation. Meteor. Atmos. Phys. , 87 , 167 – 196 . Diehl , S. R. , D. T. Smith , and M. Sydor , 1982 : Random-walk simulation of gradient-transfer processes applied to dispersion of stack emission from coal-fired power plants. J. Appl. Meteor. , 21 , 69 – 83 . Diehl , S. R. , D. A. Burrows , E. A. Hendricks , and R. Keith , 2007 : Urban dispersion modeling: Comparison with single

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