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

More documents

Recommendations

Info

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
Page 1 and 2:
Documentation of the Evaluation of
Page 3 and 4:
FOREWARD This report documents the
Page 5 and 6:
2.4.3 ATMES‐II Model Evaluation A
Page 7 and 8:
EXECUTIVE SUMMARY ABSTRACT The CALP
Page 9 and 10:
OVERVIEW OF APPROACH Up to six LRT
Page 11 and 12:
CALPUFF performance is evaluated by
Page 13 and 14:
Table ES‐2. ATMES‐II spatial an
Page 15 and 16:
• CALPUFF tended to overstate the
Page 17 and 18:
• The best performing CALPUFF con
Page 19 and 20:
2009a). The key findings from the C
Page 21 and 22:
1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2
Page 23 and 24:
2.4 2 1.6 1.2 0.8 0.4 0 EXP4A EXP4B
Page 25 and 26:
Figure ESS‐4. RANK statistical pe
Page 27 and 28:
Evaluatioon of Six LRT T Dispersion
Page 29 and 30:
Table ES‐6. Summary of model rank
Page 31 and 32:
eproduce the northwest to southeast
Page 33 and 34:
ETEX LRT Dispersion Model Sensitivi
Page 35 and 36:
CONCLUSIONS OF LRT DISPERSION MODEL
Page 37 and 38:
The CAMx and CALGRID Eulerian photo
Page 39 and 40:
July 1980. Both experiments examine
Page 41 and 42:
1.3 ORGANIZATION OF REPORT Chapter
Page 43 and 44:
puffs expand until they exceed the
Page 45 and 46:
that performance evaluation be base
Page 47 and 48:
The ETEX real‐time LRT modeling p
Page 49 and 50:
The ETEX study has formulated the f
Page 51 and 52:
In this study we expand the LRT mod
Page 53 and 54:
AM ∩ AP FMS = × 100% (2‐2) A
Page 55 and 56:
Factor of α (FAα): FAα represent
Page 57 and 58:
3.0 1980 GREAT PLAINS FIELD STUDY 3
Page 59 and 60:
compact discs, which were used to o
Page 61 and 62:
ILEVZI = 1 Layer of winds to use in
Page 63 and 64:
MCHEM = 0 No chemical transformatio
Page 65 and 66:
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
Page 83 and 84: 0% ‐10% ‐20% ‐30% ‐40% ‐5
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 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
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: 14. Across all the spatial statisti
Page 133 and 134: ‐0.1 ‐0.2 0 0.8 0.7 0.6 0.5 0.4
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
Page 141 and 142: 36 kilometers and the vertical stru
Page 143 and 144: splitting flag near sunset (hour 17
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
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 and 198:
B.1 CALMET MODEL EVALUATION TO IDEN
Page 199 and 200:
Figure B‐ ‐1 displays th he win
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 223 and 224:
Page 225 and 226:
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
show all

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

Create successful ePaper yourself

Delete template?

Save as template?