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

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0% ‐5% ‐10% ‐15% ‐20% ‐25% 1.2 1 0.8 0.6 0.4 0.2 0 Figure 5‐15a. Global model performance statistics for the CTEX5 CALPUFF sensitivity tests using the 12 km MM5 data. ‐0.1 0 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 EXP 4A EXP 4A EXP 4A EXP 4B EXP 4B Factor of Exceedance (FOEX) (Perfect = 0%) EXP 4C EXP 4C EXP 4D EXP 6A EXP 6B Fractional Bias (FB) (Perfect = 0) EXP 4D EXP 6A 16% 12% 8% 4% 0% EXP 6B EXP4A EXP 6C EXP 6C EXP4B EXP4C Pearson's Correlation Coefficient (PCC) (Perfect = 1) EXP 4B EXP 4C EXP 4D EXP 6A EXP 6B EXP 6C EXP 6D EXP 6D EXP 6D 4K MMIF 4K MMIF Figure 5‐15b. Global model performance statistics for the CTEX5 CALPUFF sensitivity tests using the 12 km MM5 data (higher values indicate better performance). 5.4.2.4 Comparison of CALPUFF CTEX5 Model Evaluation using Different MM5 Grid Resolutions This section analyzes the CALPUFF model performance across different MM5 and CALMET grid resolutions using the “B” and “D” series of CALPUFF/CALMET and the CALPUFF/MMIF 93 12K MMIF 12K MMIF 20 15 10 5 0 60% 50% 40% 30% 20% 10% 0% Factor of 2 and 5 (Perfect = 100%) 4K MMIF EXP4D 12K MMIF EXP6A EXP6B EXP6C EXP6D 2.4 2 1.6 1.2 0.8 0.4 0 4KM_MMIF EXP4A EXP 4A EXP 4A EXP4B Normalized Mean Square Error (NMSE) (Perfect = 0) EXP 4B EXP 4B EXP 4C EXP 4C EXP 4D EXP 4D EXP 6A EXP 6A EXP 6B EXP 6B EXP 6C EXP 6C EXP 6D EXP 6D 4K MMIF Kolmogorov‐Smirnov Parameter (KSP) (Perfect = 0%) 12KM_MMIF EXP4C FA2 FA5 Rank (RANK) (Perfect = 4) EXP4D EXP6A EXP6B EXP6C EXP6D 4KM_MMIF 12KM_MMIF 4K MMIF 12K MMIF 12K MMIF (1‐KS/100) FMS/100 (1‐FB/2) R^2
sensitivity tests. The “B” series (EXP4B, EXP5B, EXP6B and EXP3B) and 4KM_MMIF have the highest FMS values between 25% and 30% with 36KM_MMIF and 80KM_MMIF have the lowest FMS scores between 10% and 15%. Again the “B” series of CALPUFF/MMIF sensitivity tests have the best FAR scores with the worst scores given by the 12KM, 36KM and 80KM MMIF sensitivity tests. The “D” series using no met observations has the worst (highest) FAR scores of the CALPUFF/CALMET sensitivity tests. EXP3B has the best POD value follows by EXP4B with EXP5B, EXP5D, EXP6B and 4KM_MMIF ties for third best; the 12KM, 36KM and 80KM MMIF CALPUFFs have the worst FAR scores. Similar results are seen with the TS statistics with the four top performing sensitivity tests ordered by EXP4B, EXP5B, EXP6B and 4KM_MMIF, 90% 80% 70% 60% 50% 40% 80% 70% 60% 50% 40% 30% BASE D BASE D EXP 3B EXP 3B EXP 3D EXP 3D False Alarm Rate (FAR) (Perfect = 0%) EXP 4B EXP 4D EXP 5B EXP 5D EXP 6B EXP 6D 12K MMIF Probability of Detection (POD) (Perfect = 100%) EXP 4B EXP 4D EXP 5B EXP 5D EXP 6B EXP 6D 12K MMIF 36K MMIF 4K MMIF 36K MMIF Figure 5‐16. Spatial model performance statistics for the CTEX5 CALPUF sensitivity tests using different MM4/MM5 grid resolutions. Although EXP5D has the lowest error, the “B” series of sensitivity tests consistency have the lowest bias and error (Figure 5‐17). The 12KM_MMIF has the highest bias and error followed by the 80KM_MMIF sensitivity test. The “D” series of sensitivity tests have the best (lowest) KS parameter at ~30% with the “B” series of tests have the worst (highest) KSP at ~50% with the other sensitivity test in between. 94 80K MMIF 4K MMIF 80K MMIF 35% 30% 25% 20% 15% 10% 50% 40% 30% 20% 10% 0% Figure of Metric in Space (FMS) (Perfect = 100%) BASE D EXP 3B EXP 3D EXP 4B EXP 4D EXP 5B EXP 5D EXP 6B EXP 6D 12K MMIF 36K MMIF 4K MMIF 80K MMIF Threat Score (TS) (Perfect = 100%) BASE D EXP 3B EXP 3D EXP 4B EXP 4D EXP 5B EXP 5D EXP 6B EXP 6D 12K MMIF 36K MMIF 4K MMIF 80K 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%
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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
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Page 115 and 116: 35% 30% 25% 20% 15% 10% 5% 0% 35% 3
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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 and 128: CALPUFF sensitivity simulations are
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Page 135 and 136: 6.0 1994 EUROPEAN TRACER EXPERIMENT
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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
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Page 163 and 164: Using the NMSE statistical performa
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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
Page 179 and 180: 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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