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

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Figure C‐ ‐9. Global model m perforrmance statistics for thee CAMx senssitivity testss without ussing the PiG ssubgrid‐scale e puff moduule for CAPTTEX Release 3. C.3.3 SPATIAL PERFO ORMANCE FFOR CTEX3 PPIG EXPERIMMENTS Figure C‐ ‐10 displays the CAMx sppatial modell performance statistics for the senssitivity tests that were runn using the PiG P subgrid‐sscale puff moodule. For the FMS stattistic, the CMMAQ Kz/BOTTT combination has the best perforrmance at 366.2%. TKE/BBOTT and TKE/PPM followed closely with FMS scorres of 36% and 35.6% reespectively. OB70 exhibits the pooreest performaance with 233.5% for FMS. For the FFAR statistic, ACM2/Bottt has the besst score (61. 5%) followed by TKE/BOOTT and ACM2/PPPM (62.8% and a 63% resppectively). OOB70 exhibitted the poorrest performmance with a 72% FAR. For the POD me etric, the TKEE/BOTT commbination performs substantially bettter than thee other Kz/ /advection solver s combiinations (44. .4%). Both OOB70 scenariios showed tthe poorest performaance at 13.9%. For the TTS spatial meetric, the CMMAQ/PPM exxhibits the beest score with 30.6% followed by TK KE/BOTT andd CMAQ/BOOTT(25.4% annd 23.3% resspectively). OB70 again performss poorest with a TS valuee of 10.2% foor both adveection solver combinatioons. Consistent with the ETEX spatial results, theere are muchh smaller diffferences in the model pperformancee using thee two advect tion solvers ffor the POD and TS statiistics compaared to differrences betwween Kz optionns. In summary, the effe ect of using tthe CAMx suubgrid scale puff modulee appears to slightly deggrade performaance in comparison to thhe NoPiG exxperiments. A similar paattern was nooted in the spatial sttatistics com mpared to thee NoPiG expperiments wiith the ACM2, CMAQ, annd TKE Kz algorithmms performin ng similarly, with the oldder OB70 opption exhibiting much pooorer overalll performaance. 12
Figure C‐ ‐10. Spatial model perfoormance staatistics for the CAMx CTTEX3 sensitivvity tests using the PiG ssubgrid‐scale e puff moduule (PiG). C.3.4 GLLOBAL STATI ISTICAL PERFORMANCEE FOR CTEX3 CAMX PIG SSENSITIVITYY TESTS Figures CC‐11 and C‐12 displays thhe global staatistics for th two figurres containin ng the statisttical metricss where the respectivvely, lowest and highest score. For tthe FOEX me the biggeest effect wa as the TKE annd CMAQ alggorithms wit combinations exhibit t significantly poorer FOOEX performa and ‐16.99% (OB70/PP PM).With thhe NMSE stattistical perfo vertical ddiffusion schemes perforrms best (388 – 42 pgm scenarioss yielded the e poorest scoores with er Kz/advecction solver configuratio c ons (111 – 11 left), the ACM2 comb binations haave the best combinations follow with valuess 0.82/0.83 ( performaance with va alues of 1.188/1.19 (BOTT For the wwithin a facto or of 2 and 5 metrics (FA CMAQ arre very similar for FA2, bbut the TKE K followed by CMAQ. There is essentially no d horizontaal advection solvers. Acccording to t the best performing vertical diffuusion approa (0.33/0.444 – BOTT/PPM)ACM2 hhas the lowe The final panel in Fig gure C‐12 (boottom right) statistics orders the model m perfoormance of t 1. CMAQ/PPM (1.86) ( ‐3 rror values m 16 pgm ‐3 he CAMx NoPiG sensitiviity tests withh the best performming model has the, etric, the verrtical diffusioon algorithmm has th scores neear zero. Thee OB70 ance with vaalues of ‐13. 6% (OB70/BBOTT) ormance meetric, the ACMM2 and TKE ) (Figure C‐111, top right) ). Both OB70 more than twwice that of tthe other ). For fractional bias (Figuree C‐11, bottoom scores with 0.58/0.59 (BBOTT/PPM). . TKE Kz BOTT/PPM) . OB70 again has the pooorest FB T/PPM). A2 and FA5, Figure C‐12, , top), ACM22, TKE, and Kz option cleearly performms best for tthe FA5 mettric, difference in the PCC staatistic using tthe two he PCC metrric (Figure C‐11, bottom right), CMAAQ is ach (0.52/0. 59 – BOTT/PPPM) followed by TKE st PCC valuees with scorees 0.17 – 0.223 (BOTT/PPM). displays thee overall RANNK statistic. The RANK the CAMx coonfigurationss with PiG ass follows: 13
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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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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 and 214: C.3 CAMX SENSITIVITY TESTS Followin
Page 215: ACM2 Kzz combinatio ons rank as the
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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