of an operational evaluation of ozone and PM2.5 model performance. Note that model predictions

from the ramp-up days should be excluded from the analysis of model performance.

18.4.1 Ozone Operational Evaluation

Statistics:It is recommended that, at a minimum, the following three statistical measuresbe calculated for hourly ozone and 8-hourly maxima ozone over the episode days in an attainment

demonstration.

• Mean Normalized Bias (MNB): This performance statistic averages the model/observation

residual, paired in time, normalized by observation, over all monitor times/locations. A

value of zero would indicate that the model over predictions and model under predictions

exactly cancel each other out. The calculation of this measure is shown in Equation 18.1.

(18.1)

• Mean Normalized Gross Error (MNGE): This performance statistic averages the absolute

value of the model/observation residual, paired in time, normalized by observation, over

all monitor times/locations. A value of zero would indicate that the model exactly

matches the observed values at all points in space/time. The calculation of this measure is

shown in Equation 18.2.

Average Peak Prediction Bias and Error: These are measures of model performance that

assesses only the ability of the model to predict daily peak 1-hour and 8-hour ozone. They

are calculated essentially the same as the mean normalized bias and error (Equation 18.1

and 18.2), except that they only consider daily maxima data (predicted versus observed) at

each monitoring location. In the attainment test, models are used to calculate relative

response factors near monitoring sites by taking the ratio of the average 8-hour daily

maximum concentrations calculated for the future and current cases. Thus, the model's

ability to predict observed mean 8-hour daily maxima is an important indicator of model

performance.

Appendix A provides other statistics such as mean bias, mean error, mean fractional bias,

mean fractional error, root mean square error, correlation coefficients, etc. which should also be

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