Suggested to conduct performance evaluation on episode-by-episode basis or monthby-

month for annual modeling

• Different performance goals & criteria may be needed for gaseous precursors and wet

depositions.

• Benchmarking should be done for the entire modeling system (meteorology, emissions

inventory, and model).

2. Morris, R., et al., “Application of Multiple Models to Simulation Fine Particulate in the

Southeastern US”, National RPO Modeling Meeting, Denver, CO, 2005a.

• Based on model multiple model applications over VISTAS modeling:

1July 1999 & July 2001: CMAQ and CMAQ 36-km & 12-km

2January 2002 & July 2001: CMAQ and CMAQ MADRID 36-km only

3Used same horizontal & vertical grids, CMAQ-to-CAMx emissions, ICs/BCs, but

different MM5 interface (MCIP vs. MM5CAMx).

• Both models performed reasonably well, with CMAQ performing better for SO4 and

CAMx performing better for OM. Both models did not perform well for NO3, soil,

and coarse PM, but CAMx seemed to have much higher positive bias in winter nitrate

than CMAQ

• Used fractional bias and fractional error (instead of normalized ones) to illustrate

model performance because these statistics do not exhibit such extreme fluctuation.

• Demonstrated the usefulness of “soccer goal” plots for MFB & MFE. Suggested

15%/35% (MFB/MFE) for O3, and illustrated 50%/75% for PM2.5 species and bounded

at 100%/200%

• Based on modeling studies described above (July 1999 & 2001), MFE and MFB are

typical in the range of

Sulfate: MFE = 25% ~ 70%, MFB = -25% ~ +51%

Organic: MFE = 30% ~ 75%, MFB = -50% ~ +45%

EC: MFE = 35% ~ 65%, MFB = -30% ~ +40%

• CMAQ performance improved for OM when they adjusted the Kz min value to

1.0 m2/sec (from 0.1m2/sec).

• Data (July 2001) of SO4 and total carbon mass (TCM). Both models seemed to

captured the diurnal and daily trends well for both SO4 & TCM, but the magnitude can

be significantly off for some of the days.

 

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