if the model is responding “adequately” to control measures. Retrospective analyses may be an

important tool to show that the models are responding “correctly” to emissions changes.

18.5.5 Alternative Base Cases (Sensitivity tests)

In some cases it may be useful to evaluate how the response of the model to emissions

reductions varies as a function of alternative model inputs or model algorithms. Outcomes of

these types of sensitivity tests are useful for several purposes. First, the tests can be used to see

whether model performance is especially sensitive to a particular input or combination of inputs

(Arnold, 2003; Gilliland, 2006; Morris, 2006). Second, sensitivity tests may help prioritize

additional data gathering efforts so that a subsequent review/diagnosis can be performed at the

time of a mid-course review or required attainment date. Third, the tests can be used to assess

the robustness of a control strategy. As an example, States/Tribes could consider the effects of

assumed boundary conditions on predicted effectiveness of a control strategy. If the model

response does not differ greatly over a variety of alternative plausible configurations, this

increases confidence in the model results.

The parameters for sensitivity tests can include, but are not limited to: different chemical

mechanisms, finer or coarser grid resolution, meteorological inputs from alternative, credible

meteorological model(s), different initial/boundary conditions, and multiple sets of reasonable

emission projections. Sensitivity tests can and should be applied throughout the modeling

process, not just when model performance is being evaluated. In cases where the operational

model performance is considered to be poor, these tests may help indicate where base case

input/algorithm changes are warranted.

 

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