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

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Table B‐1. CTEX3 CALMET sensitivity simulations performed for the CTEX3 database. RUN CALMET MM4/MM5 NOOBS RMAX1/RMAX2 IPROG Resolution Resolution BASE A 18‐km 80‐km MM4 0 500/1000 STEP 1 BASE B 18‐km 80‐km MM4 0 500/1000 First Guess BASE C 18‐km 80‐km MM4 0 10/100 First Guess BASE D 18‐km 80‐km MM4 0 100/200 First Guess BASE E 18‐km 80‐km MM4 0 10/100 STEP 1 BASE F 18‐km 80‐km MM4 0 10/100 First Guess BASE G A 18‐km 80‐km MM4 2 NA First Guess BASE H 18‐km NA 0 500/1000 NA BASE I 18‐km NA 0 100/200 NA BASE J 18‐km NA 0 10/100 NA BASE K 18‐km 80‐km MM4 0 100/200 First Guess B EXP 1A 18‐km 36‐km MM5 0 500/1000 First Guess EXP 1B 18‐km 36‐km MM5 0 100/200 First Guess EXP 1C 18‐km 36‐km MM5 0 10/100 First Guess EXP 1D 18‐km 36‐km MM5 2 NA First Guess EXP 3A 12‐km 36‐km MM5 0 500/1000 First Guess EXP 3B 12‐km 36‐km MM5 0 100/200 First Guess EXP 3C 12‐km 36‐km MM5 0 10/100 First Guess EXP 3D 12‐km 36‐km MM5 2 NA First Guess EXP 4A 12‐km 12‐km MM5 0 500/1000 First Guess EXP 4B 12‐km 12‐km MM5 0 100/200 First Guess EXP 4C 12‐km 12‐km MM5 0 10/100 First Guess EXP 4D 12‐km 12‐km MM5 2 NA First Guess EXP 5A 4‐km 36‐km MM5 0 500/1000 First Guess EXP 5B 4‐km 36‐km MM5 0 100/200 First Guess EXP 5C 4‐km 36‐km MM5 0 10/100 First Guess EXP 5D 4‐km 36‐km MM5 2 NA First Guess EXP 6A 4‐km 12‐km MM5 0 500/1000 First Guess EXP 6B 4‐km 12‐km MM5 0 100/200 First Guess EXP 6C 4‐km 12‐km MM5 0 10/100 First Guess EXP 6D 4‐km 12‐km MM5 2 NA First Guess A. Base G CALMET simulation obtained an Error in MIXDT2 – HTOLD so run not completed B. Base K did not do any diagnostic adjustments to the wind fields 2
Figure B‐ ‐1 displays th he wind speeed and direcction model performancce statistical metric for the Base A thhrough Base K CALMET ssensitivity teest simulatioons that usedd either the 80 km MM44 or no prognnostic meteo orological moodel data ass input. The dark gray baar representts the CALMET model coonfiguration that is consistent with tthe recommendations inn the Augustt 31, 2009 Clarificattion Memora andum. Thee numerical vvalues of thee model perfformance sttatistics are providedd in Table B‐2 2. CALMET ssensitivity simulations BBase D, H, I and K are thee best performing simulatio ons for winds from this ggroup. Base D is the currrent recommmended CALLMET settings, whereas Base H and I use no MM4 data and Baase K is like BBase D only CCALMET doees not perfoorm any diag gnostic windd field adjusttments. Thee wind speedd statistics foor Base D annd K are identtical, wherea as the ones ffor Base H and I are slighhtly worse thhan Base D aand K. The wwind directionn statistics fo or Base D and K are almoost identical and again thhe ones for Base H and I are slightly wworse. Figure B‐ ‐1. Wind speed and winnd direction comparisonns with obseervations for CTEX3 CALLMET sensitivitty simulations. 3
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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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Page 149 and 150: 70% 60% 50% 40% 30% 20% 10% 0% Figu
Page 151 and 152: Figure 6‐9. Factor of Exceedance
Page 153 and 154: eceiving a 0.0 score. Figure 6‐13
Page 155 and 156: Table 6‐1. Summary of model ranki
Page 157 and 158: plume spread and observed surface c
Page 159 and 160: Figure 6‐16c. Comparison of spati
Page 161 and 162: • NoPiG: The tracer emissions wer
Page 163 and 164: Using the NMSE statistical performa
Page 165 and 166: 6.4.3.2 Effect of PiG on Model Perf
Page 167 and 168: 80 70 60 50 40 30 20 10 0 1 2 3 4 5
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: B.1 CALMET MODEL EVALUATION TO IDEN
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 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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