Statistics Definitions and Issues Deriving Unbiased Symmetric Metrics

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Statistics- Definitions and Issues Deriving
Unbiased Symmetric Metrics Shaocai Yu,
Brian Eder, Robin Dennis, Shao-Hang Chu,
Stephen Schwartz   Atmospheric Sciences
Modeling Division, NERL Office of Air Quality
Planning and Standards U.S. EPA, RTP, NC
27711. Brookhaven National Laboratory, Upton,
NY 11973 On assignment from Air Resources
Laboratory, NOAA
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Introduction
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CMAQ Community Multiscale Air Quality Model

• Community Model
• Multiscale
• consistent model structures for interaction of
  urban through Continental
  scales
• Multi-pollutant
• ozone, speciated particulate matter,
  visibility, acid deposition
• and air toxics

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Symmetry overprediction and underprediction are
treated proportionately
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BNMBF symmetry , (Range) -8 to 8,
is overprediction is
underprediction
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ENMEF 0 to 8
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Unbiased avoid undue influence of small numbers
in denominator
BNMBF result of sum of indiv. factor bias with
obs (or model) conc. as a weighting function
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• Test of Metrics

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• Test of Metrics (Continued) 11 models from IPCC
  (2001) (nss-SO42-)

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• Test of Metrics (Continued) 11 models for
  nss-SO42-

• Model H best Model A worst
• Models E, G, H acceptable
• If criteria 25 (BNMBF), 35 (ENMEF)

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• Application of new Metrics for CMAQ evaluation

Jan. 8 to Feb. 18, 2002
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• Application of new Metrics (Continued)

Jan. 8 to Feb. 18, 2002
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Contacts
Brian K. Eder email eder_at_hpcc.epa.gov
www.arl.noaa.gov/ www.epa.gov/asmdnerl