1 / 15

Statistics- Definitions and Issues; Deriving “Unbiased Symmetric” Metrics

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.

lynn
Télécharger la présentation

Statistics- Definitions and Issues; Deriving “Unbiased Symmetric” Metrics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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

  2. Introduction

  3. CMAQ Community Multiscale Air QualityModel • 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

  4. Symmetry: overprediction and underprediction are treated proportionately

  5. BNMBF: symmetry , (Range) -∞ to +∞, + is overprediction – is underprediction

  6. ENMEF: 0 to +∞

  7. 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

  8. Test of Metrics

  9. Test of Metrics (Continued) :11 models from IPCC (2001) (nss-SO42-)

  10. 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)

  11. Application of new Metrics for CMAQ evaluation Jan. 8 to Feb. 18, 2002

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

  13. Contacts: Brian K. Eder email: eder@hpcc.epa.gov www.arl.noaa.gov/ www.epa.gov/asmdnerl

More Related