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Acceptance criteria for urban dispersion model evaluation
Authors:Steven Hanna  Joseph Chang
Institution:1. Hanna Consultants, Kennebunkport, ME, 04046, USA
2. Homeland Security Studies and Analysis Institute, Arlington, VA, 22206, USA
Abstract:The authors suggested acceptance criteria for rural dispersion models’ performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude <0.67 (i.e., the relative mean bias is less than a factor of 2); the normalized mean-square error should be <6 (i.e., the random scatter is less than about 2.4 times the mean); and the fraction of predictions that are within a factor of two of the observations (FAC2) should be >0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be <0.50, when the threshold is three times the instrument’s limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense’s Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance criteria are satisfied at over half of the field experiments.
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