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

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Figure C‐ ‐18. Global model perfoormance staatistics for thhe CAMx sennsitivity testts using the PiG subgrid‐sscale puff module m for CAAPTEX Releaase 5 (PiG). C.3.8.1 EEFFECT OF PIG P ON MODDEL PERFORMMANCE FORR CTEX5 Similar too the results s from the ETTEX and CTEEX3 experimeents for CAMMx, whetherr the PiG is used or not haas very little effect on the CAMx model performance and the rankings oof the CAMx model peerformance using the altternative vertical mixingg and horizontal advection solver options. In general, it appears thhat the CAMMx model perrformance wwithout the PPiG is performing slightly better b than itts performance using the PiG. The spatial performa ance statisticcs are somettimes improved and sommetimes deggraded whenn the PiG moduule is invoke ed. Table C‐33 examines tthe effect off PiG treatmment of the trracer using ttwo of the four spatial sta atistics, FMSS and POD. SSlight degraddation of spatial performmance whenn the PiG moduule is invoke ed is noted uusing the OB70, TKE, andd ACM2 Kz ddiffusion commbinations (ffrom ‐3.1% to ‐0.2% for FM MS and fromm ‐11.1% to 00% for POD) . However, CAMX usingg the CMAQ Kz diffusion/advection solver s combbinations expperienced a 00.2% to 0.5% % improvemment for FMSS and no changge for POD. 22
Table C‐3. CAMx FMS and POD spatial performance statistic and model rankings for different model configurations with and without using the PiG subgrid‐scale puff model for CAPTEX Release 5. Model Configuration Without PiG Module With PiG Module NoPiG‐PiG FMS POD FMS POD ΔFMS ΔPOD OB70/BOTT 23.48 33.33 21.54 27.78 ‐1.9% ‐5.6% OB70/PPM 24.62 33.33 22.05 33.33 ‐2.6% 0% TKE/BOTT 23.85 55.56 22.83 55.56 ‐1.0% 0% TKE/PPM 24.6 55.56 21.49 50 ‐3.1% ‐5.6% ACM2/BOTT 23.53 44.44 23.26 33.33 ‐0.3% ‐11.1% ACM2/PPM 23.31 44.44 23.08 44.44 ‐0.2% 0% CMAQ/BOTT 22.48 61.11 22.66 61.11 0.2% 0% CMAQ/PPM 22.66 61.11 23.2 61.11 0.5% 0% Table C‐4 summarizes the RANK model performance statistic for the different CAMx model configurations with and without using the PiG module. The results for the global statistics are somewhat varied across the Kz/advection solver configurations. OB70, ACM2, and CMAQ/BOTT showed slight improvements in their RANK score when using the PiG module (improvements ranged from 0.7% to 5.4%). However, the TKE combinations experienced performance degradations with changes ranging from ‐3.5% to 4.0%. Table C‐4. CAMx RANK model performance statistic and model rankings for different model configurations with and without using the PiG subgrid‐scale puff model for CAPTEX Release 5. Without PiG Module With PiG Module PiG‐NoPiG Model Model Model Configuration RANK Ranking RANK Ranking ΔRANK Percent OB70/BOTT 8 1.33 1.34 8 +0.01 +0.7% OB70/PPM 7 1.34 1.35 7 +0.01 +0.7% TKE/BOTT 4 1.71 1.65 4 ‐0.06 ‐3.5% TKE/PPM 3 1.73 1.67 3 ‐0.07 ‐4.0% ACM2/BOTT 5 1.50 1.58 5 +0.08 +5.0% ACM2/PPM 6 1.48 1.56 6 +0.08 +5.4% CMAQ/BOTT 1 a 1.92 1.95 1 +0.03 +1.5% CMAQ/PPM 2 a a tied 1.92 1.92 2 0.0 0.0% In general, it is difficult to discern a consistent pattern of performance across the Kz/advection solver combinations when using the CAMx subgrid scale PiG module or not. There appears to be only modest benefit in cases where performance improvement is detected and only modest degradation in model performance when the PiG module causes a worsening of model performance. The CAMx PiG module was originally developed primarily to treat the near‐ source chemistry of large point source plumes that can be quite different from its surrounding environment. The decision to employ the CAMx puff module relates not so much in improvement advection and diffusion performance, but rather whether or not it is appropriate to allow emissions of ozone and secondary PM2.5 precursors from large point sources to be instantaneously mixed into the grid and what impact this would have on local chemical reactions. 23
Page 1 and 2:
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
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 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 223 and 224: Figure C‐ ‐15. Global model per
Page 225: Figure C‐ ‐17. Global model per
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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