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

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Table B‐2b. Summary wind direction model performance statistics for the CALMET CTEX3 sensitivity tests. RUN WD Gross Error (deg.) WD Bias (deg.) BASE A 18.06 0.73 BASE B 18.62 ‐0.74 BASE C 23.91 2.63 BASE D 16.92 0.40 BASE E 22.31 2.68 BASE F 23.91 2.63 BASE G NA NA BASE H 18.70 ‐0.79 BASE I 18.22 ‐0.65 BASE J 19.30 ‐0.85 BASE K 16.97 0.38 EXP 1A 18.64 ‐0.72 EXP 1B 17.59 1.15 EXP 1C 26.43 2.99 EXP 1D 27.99 3.11 EXP 3A 17.80 ‐0.82 EXP 3B 16.75 0.98 EXP 3C 25.25 2.57 EXP 3D 27.93 2.94 EXP 4A 17.80 ‐0.82 EXP 4B 16.75 0.98 EXP 4C 25.25 2.57 EXP 4D 27.93 2.94 EXP 5A 16.73 ‐1.00 EXP 5B 15.85 0.72 EXP 5C 20.11 1.42 EXP 5D 28.05 2.43 EXP 6A 16.73 ‐1.00 EXP 6B 15.85 0.72 EXP 6C 20.11 1.42 EXP 6D 28.05 2.43 6
B.2 CONCLUSIONS OF CTEX3 CALMET SENSITIVITY TESTS The evaluation of the CALMET modeling system using the CTEX3 field experiment database is not a true independent evaluation because some of the surface meteorological observations used as the evaluation database are also used as input into CALMET. Thus, care should be taken in the interpretation of the CALMET meteorological model evaluation. In fact, EPA has demonstrated that CALMET’s blending of meteorological observations with MM5 prognostic meteorological model fields can actually produce unrealistic results in the wind fields (e.g., discontinuities around the wind observation sites) at the same time as improving the CALMET statistical model performance at the meteorological monitoring sites. Given these caveats, when looking at the alternative CALMET settings for RMAX1/RMAX2 the CALMET configuration that best matches observed winds is with the 100/200 RMAX1/RMAX2 setting as recommended in the 2009 Clarification Memorandum. Other recommended settings in the 2009 Clarification Memorandum (e.g., use of prognostic meteorological data as the initial first guess wind field) are supported by the CALMET CTEX3 model evaluation. Note that better wind field comparisons using the 2009 Clarification Memorandum recommended settings for RMAX1/RMAX2 was also seen for the CTEX5 CALMET evaluation presented in Appendix A. Although the CALMET meteorological model performance evaluation for alternative model settings support the recommended 100/200 CALMET settings for RMAX1/RMAX2 in the Clarification Memorandum, the evaluation of the CALPUFF/CALMET modeling system for the CTEX3 and CTEX5 field experiments against observed tracer data presented in Chapter 5 come to an alternative conclusion. The CALPUFF/CALMET evaluation against the observed tracer observations in the CTEX3 and CTEX5 experiments found that different RMAX1/RMAX2 configurations produced better CALPUFF/CALMET tracer model performance for the two CAPTEX experiments, but that the 100/200 recommended setting always produced the worst CALPUFF/CALMET model performance. Given the large differences in the in the rankings of the ability of the CALPUFF to reproduce the observed tracer concentrations across the different meteorological model configurations in the two CAPTEX field experiments, it is unclear whether a third experiment would produce another set of rankings. 7
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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
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
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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: Table B‐2a. Summary wind speed mo
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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