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
• 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
• 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
• 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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