Documentation of the Evaluation of CALPUFF and Other Long ...

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Figure C‐ ‐31 displays the FAR performance mmetrics. FLEXXPART was the best (lowwest) performming model ussing the FAR R statistics with a score oof 61.9%. Thhe next two bbest performming modelss using thee FAR metric c were HYSPLIT (72.2%) aand CAMx (775.6%). SCIPPUFF, CALGRRID, and CALPUFFF had the wo orst (highest) ) FAR scoress with valuess of 79.7%, 884.2%, and 887% respectively. Figure C‐ ‐31. False Alarm Rate (FFAR) statistical performmance metricc for the six LRT models and CAPTEX RRelease 5. Results foor the Proba ability of Dettection (PODD) metric aree presented in Figure C‐332. SCIPUFFF was the best performing model usingg the POD peerformance statistic with a value of 72.2%. CAMMx was the ssecond best performing model usingg POD followwed by HYSPPLIT, FLEXPAART, CALPUFF and CALGGRID. Figure C‐ ‐32. Probab bility of Deteection (POD) ) statistical pperformancee metric for the six LRT models aand CAPTEX Release 5. 34
Results foor the TS me etric are presented in Figgure C‐33. FFLEXPART haad the higheest TS statistics with a score of 25.8% %. HYSPLIT ( (22.7%), CAMMx (21.2%), and SCIPUFFF (18.8%) followed, and CALPUFFF and CALGRID closed ouut with the wworst (lowesst) TS values of 10.3% annd 8.8% respectivvely. Figure C‐ ‐33. Threat Score (TS) statistical peerformance mmetric for thhe six LRT mmodels and CAPTEX RRelease 5. Overall, tthe spatial performance p e for CTEX5 wwas relatively equal betwween FLEXPAART and CAMMx, with CAMMx having th he best perfoormance for the FMS and POD statisstics and FLEEXPART having the best performanc ce for the FAAR and TS staatistics. CALPUFF, SCIPUUFF, and HYSSPLIT were generallyy comparable in their spatial performmance for CTTEX5, with SSCIPUFF showwing marginnally better sccores in all fo our of the sppatial metrics. CALGRID consistentlyy exhibited tthe poorest performaance across all four spattial metrics. C.5.2 GLLOBAL ANAL LYSIS OF MOODEL PERFORRMANCE Figure C‐ ‐34 displays the FOEX peerformance mmetrics for tthe six LRT mmodels. CALLPUFF had thhe best FOEEX score (clos sest to zero) ) with a value of ‐2.6%. The second best performming model using thee FOEX metric is CAMx (44.7%) followwed by HYSPLIT (‐9.2%) aand CALGRIDD (‐11.9%). SCIPUFF and FLEXPART had the ppoorest FOEX scores witth values of 20.4% and ‐ 28.2% respectivvely. 35
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Documentation of the Evaluation of
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FOREWARD This report documents the
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2.4.3 ATMES‐II Model Evaluation A
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EXECUTIVE SUMMARY ABSTRACT The CALP
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OVERVIEW OF APPROACH Up to six LRT
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CALPUFF performance is evaluated by
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Table ES‐2. ATMES‐II spatial an
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• CALPUFF tended to overstate the
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• The best performing CALPUFF con
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2009a). The key findings from the C
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1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2
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2.4 2 1.6 1.2 0.8 0.4 0 EXP4A EXP4B
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Figure ESS‐4. RANK statistical pe
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Evaluatioon of Six LRT T Dispersion
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Table ES‐6. Summary of model rank
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eproduce the northwest to southeast
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ETEX LRT Dispersion Model Sensitivi
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CONCLUSIONS OF LRT DISPERSION MODEL
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The CAMx and CALGRID Eulerian photo
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July 1980. Both experiments examine
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1.3 ORGANIZATION OF REPORT Chapter
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puffs expand until they exceed the
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that performance evaluation be base
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The ETEX real‐time LRT modeling p
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The ETEX study has formulated the f
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In this study we expand the LRT mod
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AM ∩ AP FMS = × 100% (2‐2) A
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Factor of α (FAα): FAα represent
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3.0 1980 GREAT PLAINS FIELD STUDY 3
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compact discs, which were used to o
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ILEVZI = 1 Layer of winds to use in
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MCHEM = 0 No chemical transformatio
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Table 3‐6. CALPUFF/CALMET experim
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Table 3‐11. CALPUFF/MMIF sensitiv
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evaluation studies and evaluate whe
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Tables 3‐13 and Figures 3‐2 thr
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140% 120% 100% 80% 60% 40% 20% 0%
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30% 20% 10% 0% ‐10% ‐20% ‐30%
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120% 100% 80% 60% 40% 20% 0% ‐20%
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20% 10% 0% ‐10% ‐20% ‐30% ‐
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The fitted Gaussian plume statistic
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0% ‐10% ‐20% ‐30% ‐40% ‐5
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300% 250% 200% 150% 100% 50% 0% 300
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60% 40% 20% 0% ‐20% ‐40% ‐60%
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with APS, implementing the slug opt
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the amount of time that the tracer
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Figure 4‐1. CALPUFF/CALMET UTM mo
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compact discs, which were used to o
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Table 4‐4. CALPUFF parameters use
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Table 4‐8. CALPUFF/MMIF sensitivi
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the fitted Gaussian plume is not a
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Figure 4‐2. Comparison of predict
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Figure 5‐1. Location of Dayton an
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MM5 runs, the first without FDDA (i
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Table 5‐3. MM5 sensitivity tests
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Table 5‐6. Definition of the CALM
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performance at the monitor location
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35% 30% 25% 20% 15% 10% 5% 0% 35% 3
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40% 35% 30% 25% 20% 15% 10% 5% 0% F
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40% 35% 30% 25% 20% 15% 10% 5% 0% E
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5.4.1.4 Comparison of CALPUFF CTEX3
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0.48 0.36 0.24 0.12 0 ‐0.12 16% 1
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CTEX3 discussed in Section 5.4.1. A
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CALPUFF sensitivity simulations are
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14. Across all the spatial statisti
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sensitivity tests. The “B” seri
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‐0.1 ‐0.2 0 0.8 0.7 0.6 0.5 0.4
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6.0 1994 EUROPEAN TRACER EXPERIMENT
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Figure 6‐2a. Surface synoptic met
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Figure 6‐3a. Distribution of the
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36 kilometers and the vertical stru
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splitting flag near sunset (hour 17
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experienced during the original ETE
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2 1 0 ‐1 ‐2 3 2 1 0 23‐Oct 23
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70% 60% 50% 40% 30% 20% 10% 0% Figu
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Figure 6‐9. Factor of Exceedance
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eceiving a 0.0 score. Figure 6‐13
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Table 6‐1. Summary of model ranki
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plume spread and observed surface c
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Figure 6‐16c. Comparison of spati
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• NoPiG: The tracer emissions wer
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Using the NMSE statistical performa
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6.4.3.2 Effect of PiG on Model Perf
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80 70 60 50 40 30 20 10 0 1 2 3 4 5
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Table 6‐3. Summary of CALPUFF puf
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0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.
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Figure 6‐ ‐22 displays the t sp
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Figure 6‐ ‐23a. Global model pe
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Figure 6‐24. Figure of Merit (FMS
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7.0 REFERENCES Anderson, B. 2008. T
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EPA, 1984: Interim Procedures for E
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Mlawer, E.J., S.J. Taubman, P.D. Br
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148 Appendix A Evaluation of the MM
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Page 189 and 190: Table A‐3. Definition of the CTEX
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Page 193 and 194: Figure A‐ ‐3. Humidity bias and
Page 195 and 196: Table A‐5. Comparison of CTEX5 MM
Page 197 and 198: B.1 CALMET MODEL EVALUATION TO IDEN
Page 199 and 200: Figure B‐ ‐1 displays th he win
Page 201 and 202: Table B‐2a. Summary wind speed mo
Page 203 and 204: B.2 CONCLUSIONS OF CTEX3 CALMET SEN
Page 205 and 206: C.1 INTRODUCTION In this section, t
Page 207 and 208: C.2.2 HYYSPLIT GLOB BAL STATISTIICS
Page 209 and 210: The final panel in Figure C‐3 (bo
Page 211 and 212: Figure C‐ ‐5. Global model m pe
Page 213 and 214: C.3 CAMX SENSITIVITY TESTS Followin
Page 215 and 216: ACM2 Kzz combinatio ons rank as the
Page 217 and 218: Figure C‐ ‐10. Spatial model pe
Page 219 and 220: Figure C‐ ‐12. Global model per
Page 221 and 222: Figure C‐ ‐13. Spatial model pe
Page 227 and 228: Table C‐3. CAMx FMS and POD spati
Page 229 and 230: Figure C‐ ‐20. False Alarm Rate
Page 231 and 232: Figure C‐ ‐23. Factor of o Exce
Page 233 and 234: The PCC values for th he six LRT mo
Page 235 and 236: The RANK statistical performancce m
Page 237: Table C‐55. Summary y of model r
Page 241 and 242: Figure C‐ ‐35. Factor of o 2 (F
Page 243 and 244: a negativve FB. The best b performm
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Page 247: United States Environmental Protect
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