At some point in the modeling process, an assessment of model

performance is required. Specifying rigid rejection/acceptance

criteria has not been supported by model developers nor by decision

makers participating in previous modeling efforts. Instead,

performance measures derived from previous photochemical model

applications may provide a reasonable benchmark for model performance.

Also, graphical procedures reveal qualitative relationships

between predicted and observed concentrations that can be used in

model performance evaluation.

Poor performance may necessitate (1) delaying model

applications until further diagnostic testing and quality assurance

checks are reflected in the input data base, or (2) selecting

another meteorological episode for modeling. However, this is not

a valid reason for delaying SIP attainment demonstration submittals

beyond the dates required in the 1990 CAAA. Also, cases where good

model performance is shown should be reviewed as well, because

compensating errors can induce spurious agreement among observed

and predicted values.

5.1 Performance Measures

This section describes recommended graphical and statistical

performance measures for ozone predictions. These measures should

be applied for modeling results beginning on the second day of the

modeled episode. As described in Section 3.1, the first day is

eliminated to mitigate the effects of specifying initial conditions

arbitrarily. Performance measures should also be considered for

ozone precursors wherever possible, based on availability of

monitored data. Obvious problems exist in comparing model

predictions with observed values. The UAM output represents

volumetric (e.g., 25 km3), 1-hour average concentrations, but air

quality data represent point locations with various sampling

periods. This "incommensurability" may lead to considerable

uncertainty in the comparisons, especially for precursor species

that are not buffered chemically and may have been sampled at

locations not representative of areawide concentrations.



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