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

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Figure 6‐2c. Surface synoptic meteorological conditions for Europe at 0000 UTC on October 26, 1994 56 hours after the release of the PMCH tracer in ETEX (Source: http://rem.jrc.ec.europa.eu/etex/). Figure 6‐3 displays the spatial distribution of the observed PMCH tracer concentration in pico‐ grams per cubic meter (pgm ‐3 ) 24, 36, 48 and 60 hours after the release in Monterfil, France. During the first 24 hours after the release of the PMCH, the tracer cloud was advected generally east‐northeast from the release point in northwestern France into the Netherlands and Luxembourg and into western Germany. By 36 hours after the initial release, the tracer cloud had advected well into Germany (Figure 6‐3, top right). In this region, the wind flow split between the two cyclonic systems northwest and southeast of Germany (see Figure 6‐2), causing the tracer cloud to essentially bifurcate, with one portion advecting around the core of the cyclonic system over the North Sea, and the other portion advecting southeast towards the cyclonic system in the Balkan Peninsula region. 48 and 60 hours after the tracer release (Figure 6‐3, lower panels), the tracer cloud stretches from Norway to the Black Sea in a narrow northwest to southeast orientation. 101
Figure 6‐3a. Distribution of the observed PMCH tracer concentrations (pgm ‐3 ) 24 (top right), 36 (top right), 48 (bottom left) and 60 (bottom right) hours after the release. 6.2 MODEL CONFIGURATION AND APPLICATION 6.2.1 Experimental Design The objectives of the LRT model evaluation using the ETEX field study database was somewhat different than the other three tracer test evaluations. In the GP80, SRL75 and CAPTEX tracer test LRT model evaluations, one major objective was an evaluation of the CALPUFF LRT dispersion model using two different sets of meteorological inputs, one based on the CALMET diagnostic wind model and the other using the MMIF WRF/MM5 pass‐through tool. However, in the ETEX LRT model tracer test evaluation an objective was to use the same meteorological inputs in all of the LRT dispersion models. This approach is similar to the one taken by Chang and co‐workers (2003) who conducted an evaluation of three Lagrangian puff models (HPAC/SCIPUFF, VLSTRACK, and CALMET/CALPUFF). While all three puff models are based on a Gaussian puff formulation, these models varied significantly in terms of the level of sophistication of their technical formulation. Chang and co‐workers (2003) proposed a framework to perform an objective and meaningful evaluation when such models vary significantly in their formulation. A primary focus of their model evaluation framework 102
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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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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
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
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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 131 and 132: sensitivity tests. The “B” seri
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Page 135 and 136: 6.0 1994 EUROPEAN TRACER EXPERIMENT
Page 137: Figure 6‐2a. Surface synoptic met
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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
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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
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
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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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