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

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0.48 0.36 0.24 0.12 0 ‐0.12 16% 12% 8% 4% 0% EXP3A EXP3B EXP3C Pearson's Correlation Coefficient (PCC) (Perfect = 1) EXP 3A EXP 3B EXP 3C EXP 3D EXP 5A EXP 5B EXP 5C Factor of 2 and 5 (Perfect = 100%) EXP 5D EXP3D 36K MMIF Figure 5‐5b. Global model performance statistics for the CTEX3 CALPUFF sensitivity tests using the 36 km MM5 data. EXP5A 5.4.1.3 CALPUFF CTEX3 Model Evaluation using 12 km MM5 Data The spatial model performance statistical metrics for the CTEX3 CALPUFF sensitivity tests using 12 km MM5 data are shown in Figure 5‐6. 81 EXP5B EXP5C 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 EXP5D EXP3A EXP3B 36KM_MMIF EXP3C EXP3D FA2 FA5 Rank (RANK) (Perfect = 4) EXP5A EXP5B EXP5C EXP5D 36KM_MMIF (1‐KS/100) FMS/100 (1‐FB/2) R^2
40% 35% 30% 25% 20% 15% 10% 5% 0% EXP 4A 40% 35% 30% 25% 20% 15% 10% 5% 0% EXP 4A EXP 4B Figure of Metric in Space (FMS) (Perfect = 100%) EXP 4B EXP 4C EXP 4D EXP 6A EXP 6B EXP 6C Probability of Detection (POD) (Perfect = 100%) EXP 4C EXP 4D EXP 6A EXP 6B EXP 6D EXP 6C 12K MMIF EXP 6D Figure 5‐6. Spatial model performance statistics for the CTEX3 CALPUF sensitivity tests that used the 12 km MM5 data. 82 12K MMIF 100% 80% 60% 40% 20% 0% 25% 20% 15% 10% 5% 0% EXP 4A EXP 4A False Alarm Rate (FAR) (Perfect = 0%) EXP 4B EXP 4B EXP 4C EXP 4D EXP 6A EXP 6B Threat Score (TS) (Perfect = 100%) EXP 4C EXP 4D EXP 6A EXP 6B EXP 6C EXP 6C EXP 6D EXP 6D 12K MMIF 12K MMIF
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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
Page 67 and 68: Table 3‐11. CALPUFF/MMIF sensitiv
Page 69 and 70: evaluation studies and evaluate whe
Page 71 and 72: Tables 3‐13 and Figures 3‐2 thr
Page 73 and 74: 140% 120% 100% 80% 60% 40% 20% 0%
Page 75 and 76: 30% 20% 10% 0% ‐10% ‐20% ‐30%
Page 77 and 78: 120% 100% 80% 60% 40% 20% 0% ‐20%
Page 79 and 80: 20% 10% 0% ‐10% ‐20% ‐30% ‐
Page 81 and 82: The fitted Gaussian plume statistic
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Page 85 and 86: 300% 250% 200% 150% 100% 50% 0% 300
Page 87 and 88: 60% 40% 20% 0% ‐20% ‐40% ‐60%
Page 89 and 90: with APS, implementing the slug opt
Page 91 and 92: the amount of time that the tracer
Page 93 and 94: Figure 4‐1. CALPUFF/CALMET UTM mo
Page 95 and 96: compact discs, which were used to o
Page 97 and 98: Table 4‐4. CALPUFF parameters use
Page 99 and 100: Table 4‐8. CALPUFF/MMIF sensitivi
Page 101 and 102: the fitted Gaussian plume is not a
Page 103 and 104: Figure 4‐2. Comparison of predict
Page 105 and 106: Figure 5‐1. Location of Dayton an
Page 107 and 108: MM5 runs, the first without FDDA (i
Page 109 and 110: Table 5‐3. MM5 sensitivity tests
Page 111 and 112: Table 5‐6. Definition of the CALM
Page 113 and 114: performance at the monitor location
Page 115 and 116: 35% 30% 25% 20% 15% 10% 5% 0% 35% 3
Page 117: 40% 35% 30% 25% 20% 15% 10% 5% 0% F
Page 121 and 122: 5.4.1.4 Comparison of CALPUFF CTEX3
Page 123 and 124: 0.48 0.36 0.24 0.12 0 ‐0.12 16% 1
Page 125 and 126: CTEX3 discussed in Section 5.4.1. A
Page 127 and 128: CALPUFF sensitivity simulations are
Page 129 and 130: 14. Across all the spatial statisti
Page 131 and 132: sensitivity tests. The “B” seri
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Page 135 and 136: 6.0 1994 EUROPEAN TRACER EXPERIMENT
Page 137 and 138: Figure 6‐2a. Surface synoptic met
Page 139 and 140: Figure 6‐3a. Distribution of the
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Page 145 and 146: experienced during the original ETE
Page 147 and 148: 2 1 0 ‐1 ‐2 3 2 1 0 23‐Oct 23
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
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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
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Figure 6‐ ‐23a. Global model pe
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Figure 6‐24. Figure of Merit (FMS
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7.0 REFERENCES Anderson, B. 2008. T
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EPA, 1984: Interim Procedures for E
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Mlawer, E.J., S.J. Taubman, P.D. Br
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148 Appendix A Evaluation of the MM
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Table A‐1. Wind speed and wind di
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Table A‐3. Definition of the CTEX
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Figure A‐ ‐1. Wind speed bias (
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Figure A‐ ‐3. Humidity bias and
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Table A‐5. Comparison of CTEX5 MM
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B.1 CALMET MODEL EVALUATION TO IDEN
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Figure B‐ ‐1 displays th he win
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Table B‐2a. Summary wind speed mo
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B.2 CONCLUSIONS OF CTEX3 CALMET SEN
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C.1 INTRODUCTION In this section, t
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C.2.2 HYYSPLIT GLOB BAL STATISTIICS
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The final panel in Figure C‐3 (bo
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Figure C‐ ‐5. Global model m pe
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C.3 CAMX SENSITIVITY TESTS Followin
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ACM2 Kzz combinatio ons rank as the
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Figure C‐ ‐10. Spatial model pe
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Figure C‐ ‐12. Global model per
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Figure C‐ ‐13. Spatial model pe
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Table C‐3. CAMx FMS and POD spati
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Figure C‐ ‐20. False Alarm Rate
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Figure C‐ ‐23. Factor of o Exce
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The PCC values for th he six LRT mo
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The RANK statistical performancce m
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Table C‐55. Summary y of model r
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Results foor the TS me etric are pr
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Figure C‐ ‐35. Factor of o 2 (F
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a negativve FB. The best b performm
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performing model the most often sco
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United States Environmental Protect
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