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

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0% ‐5% ‐10% ‐15% ‐20% ‐25% Figure 5‐13a. Global model performance statistics for the CTEX5 CALPUFF sensitivity tests using the 36 km MM5 data. 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1.2 1 0.8 0.6 0.4 0.2 0 EXP 3A EXP 3A EXP 3A Factor of Exceedance (FOEX) (Perfect = 0%) EXP 3B EXP 3B EXP 3C EXP 3D EXP 5A EXP 5B Fractional Bias (FB) (Perfect = 0) EXP 3C EXP 3D EXP 5A 16% 14% 12% 10% 8% 6% 4% 2% 0% EXP 5B EXP3A EXP 5C EXP 5C EXP3B EXP 5D EXP3C Pearson's Correlation Coefficient (PCC) (Perfect = 1) EXP 3B EXP 3C EXP 3D EXP 5A EXP 5B EXP 5C EXP 5D 36K MMIF 36K MMIF Figure 5‐13b. Global model performance statistics for the CTEX5 CALPUFF sensitivity tests using the 36 km MM5 data (higher values indicate better performance). 5.4.2.3 CALPUFF CTEX5 Model Evaluation using 12 and 4 km MM5 Data The spatial statistics for the CALPUFF/CALMET and CALPUFF/MMIF sensitivity tests using the 12 km MM5 data along with the 4 km MM5 CALPUFF/MMIF sensitivity test are given in Figure 5‐ 91 20 15 10 5 0 60% 50% 40% 30% 20% 10% 0% EXP 3A EXP 3A Factor of 2 and 5 (Perfect = 100%) EXP 5D EXP3D 36K MMIF EXP5A EXP5B EXP5C 2.5 2 1.5 1 0.5 0 Normalized Mean Square Error (NMSE) (Perfect = 0) EXP 3B EXP 3B EXP 3C EXP 3C EXP 3D EXP 3D EXP 5A EXP 5A EXP 5B EXP 5B EXP 5C EXP 5C EXP 5D Kolmogorov‐Smirnov Parameter (KSP) (Perfect = 0%) EXP5D EXP3A 36KM_MMIF EXP3B EXP3C FA2 FA5 Rank (RANK) (Perfect = 4) EXP3D EXP5A EXP5B EXP5C EXP5D 36KM_MMIF EXP 5D (1‐KS/100) FMS/100 (1‐FB/2) R^2 36K MMIF 36K MMIF
14. Across all the spatial statistics, EXP6A performs the best with EXP4A, EXP4B, EXP6B and 4KM_MMIF next best and 12KM_MMIF being worst. 80% 70% 60% 50% 40% 30% 20% 10% 0% 35% 30% 25% 20% 15% 10% 5% 0% EXP 4A EXP 4A Figure of Metric in Space (FMS) (Perfect = 100%) EXP 4B EXP 4B EXP 4C EXP 4D EXP 6A EXP 6B EXP 6C EXP 6D Probability of Detection (POD) (Perfect = 100%) EXP 4C EXP 4D EXP 6A EXP 6B EXP 6C EXP 6D 4K MMIF 12K MMIF 4K MMIF 12K MMIF 50% 40% 30% 20% 10% 0% Figure 5‐14. Spatial model performance statistics for the CTEX5 CALPUF sensitivity tests that used the 12 and 4 km MM5 data. The lowest error of the 12 km MM5 CALPUFF sensitivity tests is given by EXP4B and EXP6A‐C, with 12KM_MMIF having the highest error (Figure 5‐15). EXP6B has the lowest bias follows by EXP6C and EXP4B, with 12KM_MMIF having the largest bias. EXP6A and EXP6B have the most model predictions within a factor of 2 of the observations and EXP4C has the most within a factor of 5. The CALMET/CALPUFF correlation coefficients range from 0.57 to 0.76 with EXP4A (0.76) and EXP6C (0.75) have the highest values and EXP6B (0.57) having the lowest value. The 4KM_MMIF has an even lower correlation coefficient (0.48) with the 12KM_MMIF having no to slight anti‐correlation with the observed values (‐0.07). According to the RANK composite statistics the best performing 12 km CALPUFF sensitivity test in EXP6C (2.19) followed by EXP6A (2.02) and EXP4A (1.98) with 12KM_MMIF (1.28) performing worst. 92 100% 80% 60% 40% 20% 0% EXP 4A EXP 4A EXP 4B EXP 4B False Alarm Rate (FAR) (Perfect = 0%) EXP 4C EXP 4C EXP 4D EXP 6A EXP 6B EXP 6C Threat Score (TS) (Perfect = 100%) EXP 4D EXP 6A EXP 6B EXP 6C EXP 6D 4K MMIF EXP 6D 12K MMIF 4K 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
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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%
Page 77 and 78: 120% 100% 80% 60% 40% 20% 0% ‐20%
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Page 81 and 82: The fitted Gaussian plume statistic
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Page 89 and 90: with APS, implementing the slug opt
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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
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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 and 118: 40% 35% 30% 25% 20% 15% 10% 5% 0% F
Page 119 and 120: 40% 35% 30% 25% 20% 15% 10% 5% 0% E
Page 121 and 122: 5.4.1.4 Comparison of CALPUFF CTEX3
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Page 125 and 126: CTEX3 discussed in Section 5.4.1. A
Page 127: CALPUFF sensitivity simulations are
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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 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
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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
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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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