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

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Figure C‐ ‐7. Spatial model m performance stattistics for the CAMx sennsitivity testss without ussing the PiG ssubgrid‐scale e puff moduule (NoPiG) ffor CAPTEX Release 3. C.3.2 Gloobal Statistical Performmance for CTEX3 NoPiG EExperimentss Figures CC‐8 and C‐9 displays d the global statisstics for the CCAMx NoPiGG sensitivity and containn the statisticaal metrics wh here the besst performing model hass the, respecctively, lowest and higheest score. Foor the FOEX metric, the vertical diffuusion algoritthm that hass the best sccore was the ACM2 alggorithm with h scores of 33.26% (ACM22/BOTT) andd 3.6% (ACMM2/PPM). Thhe next best vertical ddiffusion algo orithm/adveection solverr combinatioon was OB700/BOTT withh a ‐3.8% FOEEX score. Thhe CMAQ/BO OTT (9.1%) aand CMAQ/PPPM (9.6%) have the higghest (worstt) FOEX scorees. For the NNMSE statistical perform perform best (28 to 30 3 pgm NMSE scores with er configuraations. Cons also the bbest perform scheme ( (Figure C‐8, for both of the FB an For the wwithin a facto are the bbest perform combinations perfor but the CCMAQ comb For the PPCC metric, t with valuues ranging f overall. Interestingly ‐3 mance metricc, the ACM2 and TKE verrtical diffusioon schemes ) (Figure C‐8, toop right). Booth OB70 sceenarios yieldded the poorrest rror values mmore than twwice that of tthe other Kzz/advection ssolver sistent with both FOEX aand NMSE, the ACM2 veertical diffusiion scheme is ming methodd according to the FB annd KSP metrics followed by the TKE bottom left) ). The OB70 vertical difffusion algorithm performms the pooreest nd KSP metrics. or of 2 and 5 metrics (FAA2/FA5, Figuure C‐9, top), , the ACM2 combinationns ming with values of 8.8%/ /17.1% and 8.2%/16.3% %. The TKE and CMAQ m similarly, with the TKE options haaving slightlyy higher FA2 percentagees, inations exhhibit higher FFA5 percentages than thhe TKE. the CMAQ and TKE combbinations yieeld the best correlation performancce from 0.54 too 0.63 with CCMAQ havingg slightly higgher correlattion values y, for most oother spatial and global sstatistical caategories forr the NoPiG ttests 10
ACM2 Kzz combinatio ons rank as the best perfforming. Hoowever, the AACM2 Kz combinations have the lowest PCC corre elation valuees of the four Kz combinations, with values of 0. 22 and 0.300. Figure C‐ ‐8. Global model m perforrmance statistics for thee CAMx senssitivity testss without ussing the PiG ssubgrid‐scale e puff moduule for CAPTTEX Release 3. The final panel in Fig gure C‐9 (botttom right) ddisplays the overall RANK statistic. TThe RANK statistics orders the model m perfoormance of tthe CAMx coonfigurationss without PiGG as follows: 1. TKE/PPM (1.9 97) 2. CMAQ/PPM (1.91) ( 3. TKE/BOTT (1. 89) 4. AACM2/PPM ( 1.87) 5. CMAQ/BOTT (1.83) (tied) ) 6. AACM2/BOTT (1.83) (tied) 7. OOB70/PPM (1 1.67) 8. OOB70/BOTT ( 1.56) Based onn this analysi is, the TKE KKz coefficientts is the bestt performingg vertical difffusion approoach followed closely by CMAQ. C As noted previouusly, the verrtical diffusioon algorithmm has a greatter effect onn CAMx model performance comparred to the chhoice of horizontal advecction solverss. 11
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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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Page 169 and 170: Table 6‐3. Summary of CALPUFF puf
Page 171 and 172: 0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.
Page 173 and 174: Figure 6‐ ‐22 displays the t sp
Page 175 and 176: Figure 6‐ ‐23a. Global model pe
Page 177 and 178: Figure 6‐24. Figure of Merit (FMS
Page 179 and 180: 7.0 REFERENCES Anderson, B. 2008. T
Page 181 and 182: EPA, 1984: Interim Procedures for E
Page 183 and 184: Mlawer, E.J., S.J. Taubman, P.D. Br
Page 185 and 186: 148 Appendix A Evaluation of the MM
Page 187 and 188: Table A‐1. Wind speed and wind di
Page 189 and 190: Table A‐3. Definition of the CTEX
Page 191 and 192: Figure A‐ ‐1. Wind speed bias (
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: C.3 CAMX SENSITIVITY TESTS Followin
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 and 238: Table C‐55. Summary y of model r
Page 239 and 240: Results foor the TS me etric are pr
Page 241 and 242: Figure C‐ ‐35. Factor of o 2 (F
Page 243 and 244: a negativve FB. The best b performm
Page 245 and 246: performing model the most often sco
Page 247: United States Environmental Protect
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