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

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• When using the “A” series model configuration, the use of higher CALMET resolution does not produce better CALPUFF model performance, however for the “C” and “D” series of CALMET runs use of higher CALMET grid resolution does produce better CALPUFF model performance. • Note that the finding that CALPUFF/CALMET model performance using CALMET wind fields based on setting RMAX1/RMAX2 = 100/200 (i.e., the “B” series) produces worse CALPUFF model performance for simulating the observed atmospheric tracer concentrations is in contrast to the CALMET evaluation that found the “B” series produced winds closest to observations (see Appendices A and B). Since the CALPUFF tracer evaluation is an independent evaluation of the CALMET/CALPUFF modeling system, whereas the CALMET surface wind evaluation is not, the CALPUFF tracer evaluation may be a better indication of the best performing CALMET configuration. The CALMET “B” series approach for blending the wind observations in the wind fields may just be the best approach for getting the CALMET winds to match the observations at the monitoring sites, but at the expense of degrading the wind fields. Table 5‐9. Final Rankings of CALPUFF CTEX3 Sensitivity Tests. Sensitivity RANK MM5 CALGRID Met Ranking Test Statistics (km) (km) RMAX1/RMAX2 Obs 1 36KM_MMIF 1.610 36 ‐‐ ‐‐ ‐‐ 2 12KM_MMIF 1.430 12 ‐‐ ‐‐ ‐‐ 3 EXP3A 1.400 36 12 500/1000 Yes 4 EXP4A 1.400 12 12 500/1000 Yes 5 EXP5C 1.380 36 4 10/100 Yes 6 EXP6C 1.380 12 4 10/100 Yes 7 EXP1C 1.340 36 18 10/100 Yes 8 EXP5A 1.340 36 4 500/1000 Yes 9 EXP6A 1.340 12 4 500/1000 Yes 10 EXP5D 1.310 36 4 ‐‐ No 11 EXP6D 1.310 12 4 ‐‐ No 12 EXP1B 1.300 36 18 100/200 Yes 13 EXP3D 1.300 36 12 ‐‐ No 14 EXP4D 1.300 12 12 ‐‐ No 15 BASEA 1.290 80 18 500/1000 Yes 16 EXP1D 1.290 36 18 ‐‐ No 17 EXP1A 1.280 36 18 500/1000 Yes 18 EXP3B 1.220 36 12 100/200 Yes 19 EXP5B 1.220 36 4 100/200 Yes 20 EXP4B 1.220 12 12 100/200 Yes 21 EXP6B 1.220 12 4 100/200 Yes 22 BASEC 1.170 80 18 10/100 Yes 23 BASEB 1.160 80 18 100/200 Yes 24 EXP3C 1.120 36 12 10/100 Yes 25 EXP4C 1.120 12 12 10/200 Yes 5.4.2 CALPUFF CTEX5 Model Performance Evaluation The model performance of the CALPUFF sensitivity tests for the CTEX5 (October 25, 1983) field experiment are presented below grouped by MM5 grid resolution. The MM5 output were used as input to the CALMET or MMIF meteorological drivers for CALPUFF, as was done for the 87
CTEX3 discussed in Section 5.4.1. As noted in Table 5‐6, CTEX5 CALPUFF sensitivity tests were not performed for the EXP1 and EXP2 series of experiments. 5.4.1.1 CALPUFF CTEX5 Model Evaluation using 80 km MM5 Data The spatial model performance statistics for the CTEX5 CALPUFF sensitivity tests using the 80 km MM5 data are shown in Figure 5‐10. The BASEA and BASEB sensitivity tests are performing the best followed by BASEC, then BASED with 80KM_MMIF coming in last. 80% 70% 60% 50% 40% 30% 20% 10% 0% 50% 40% 30% 20% 10% 0% BASE A BASE A Probability of Detection (POD) (Perfect = 100%) BASE B BASE B BASE C Threat Score (TS) (Perfect = 100%) BASE C BASE D BASE D 80K MMIF 80K MMIF Figure 5‐10. Spatial model performance statistics for the CTEX5 CALPUF sensitivity tests that used the 80 km MM5 data. Although 80KM_MMIF has the lowest FOEX statistic, for all the other global statistic it is the worst or almost worst performing CALPUFF sensitivity test using 80 km MM5 data. BASEA has the best bias, error, FA2 and FA5 statistics of this group with either BASEB or BASEC coming in second and then BASED next to last and 80KM_MMIF last. The RANK composite statistics ranks BASEA (2.06) and BASEC (2.05) the highest followed by BASEB (1.82) and BASED (1.79) next and 80KM_MMIF (1.42) in last. 88 30% 25% 20% 15% 10% 5% 0% 100% 80% 60% 40% 20% 0% Figure of Metric in Space (FMS) (Perfect = 100%) BASE A BASE A BASE B BASE C BASE D False Alarm Rate (FAR) (Perfect = 0%) BASE B BASE C BASE D 80K 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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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
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Page 97 and 98: Table 4‐4. CALPUFF parameters use
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Page 103 and 104: Figure 4‐2. Comparison of predict
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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
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 135 and 136: 6.0 1994 EUROPEAN TRACER EXPERIMENT
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Page 155 and 156: Table 6‐1. Summary of model ranki
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Page 159 and 160: Figure 6‐16c. Comparison of spati
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Page 169 and 170: Table 6‐3. Summary of CALPUFF puf
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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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