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

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data appeared to have a more complete record of PDCH concentrations than the other tracers. Table 3‐3 displays the source characteristics for the PDCH tracer used in the CALPUFF modeling of the July 8, 1980 GP80 experiment. Table 3‐3. Source characteristics for the CALPUFF modeling of the July 8, 1980 GP80 experiment. Total PDCH Release Stack Exit tracer Length of emission height diameter velocity Exit temp. released release rate Source (m) (m) (m/s) (°K) (kg) (hr) (g s ‐1 ) Oklahoma 10.0 1.0 a Ambient 0.001 b Notes: (250) 186 3.0 17.22 a – The stack diameter was set to 1 meter in diameter to conform to previous tracer evaluation studies. b – The exit temperature was assumed to be the same as ambient atmospheric temperature. CALPUFF checks the difference between the stack exit temperature and the surface station temperature. If this difference is less than zero, the difference is set to zero. To insure this condition, an exit temperature of 250 K was input to the model. In the CALPUFF modeling system, each of the three programs (CALMET, CALPUFF, and CALPOST) uses a control file of user‐selectable options to control the data processing. There are numerous options in each and several that can result in significant differences. The following model controls for CALMET and CALPUFF were employed for the analyses with the tracer data. 3.2.1.1 CALMET Options The following CALMET control parameters and options were chosen for the BASE CALPUFF model simulations. The BASE control parameters and options were chosen to be consistent with two previous CALMET/CALPUFF evaluations (Irwin 1997, and EPA 1998a). The most important CALMET options relate to the development of the wind field and were set as follows for the BASE model configuration: NOOBS = 0 Use surface, overwater, and upper air station data IWFCOD = 1 Use diagnostic wind model to develop the 3‐D wind fields IFRADJ = 1 Compute Froude number adjustment effects (thermodynamic blocking effects of terrain) IKINE = 1 Compute kinematic effects IOBR = 0 Do NOT use O’Brien procedure for adjusting vertical velocity IEXTRP = 4 Use similarity theory to extrapolate surface winds to upper layers IPROG = 0 Do NOT use prognostic wind field model output as input to diagnostic wind field model (for observations only sensitivity test) ITPROG = 0 Do NOT use prognostic temperature data output Mixing heights are important in the estimating ground level concentrations. The CALMET options that affect mixing heights were set as follows: IAVEZI = 1 Conduct spatial averaging MNDAV = 3 100km BASE case – Maximum search radius (in grid cells) in averaging process = 1 600km BASE Case HAFANG = 30. Half‐angle of upwind looking cone for averaging 23
ILEVZI = 1 Layer of winds to use in upwind averaging DPTMIN = .001 Minimum potential temperature lapse rate (K/m) in stable layer above convective mixing height DZZI = 200 Depth of layer (meters) over which the lapse rate is computed ZIMIN = 100 100km BASE case – Minimum mixing height (meters) over land = 50 600km BASE Case ZIMAX = 3200 100km BASE case – Maximum mixing height (meters) over land, defined to be the top of the modeling domain = 3000 600km BASE Case A number of CALMET model control options have no default CALMET values, particularly radii of influence values for terrain and surface and upper air observations. The CALMET options that affect radius of influence were set as follows: RMAX1 = 20 Minimum radius of influence in surface layer (km) RMAX2 = 50 Minimum radius of influence over land aloft (km) RMIN = 2 100km BASE case – Minimum radius of influence in wind field interpolation (km) = 0.1 600km BASE Case TERRAD = 10 Radius of influence of terrain features (km) RPROG = 0 Weighting factors of prognostic wind field data (km) A review of the respective CALMET parameters between the 1998 EPA CALMET/CALPUFF evaluation study using CALMET Version 4.0 and the 600 km BASE case scenario in the current CALMET/CALPUFF evaluation using CALMET Version 5.8 indicates differences in some CALMET options. The differences between the two scenarios are presented below in Table 3‐4. All other major CALMET options for 600 km BASE case scenario matched the original 1998 EPA analysis. There were no significant differences between the CALMET parameters 100 km BASE case scenarios for the 1998 (CALMET Version 4.0) and the current evaluation (CALMET Version 5.8). 24
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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
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: compact discs, which were used to o
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
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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
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Table 5‐6. Definition of the CALM
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performance at the monitor location
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35% 30% 25% 20% 15% 10% 5% 0% 35% 3
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40% 35% 30% 25% 20% 15% 10% 5% 0% F
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40% 35% 30% 25% 20% 15% 10% 5% 0% E
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5.4.1.4 Comparison of CALPUFF CTEX3
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0.48 0.36 0.24 0.12 0 ‐0.12 16% 1
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CTEX3 discussed in Section 5.4.1. A
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CALPUFF sensitivity simulations are
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14. Across all the spatial statisti
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sensitivity tests. The “B” seri
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‐0.1 ‐0.2 0 0.8 0.7 0.6 0.5 0.4
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6.0 1994 EUROPEAN TRACER EXPERIMENT
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Figure 6‐2a. Surface synoptic met
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Figure 6‐3a. Distribution of the
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36 kilometers and the vertical stru
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splitting flag near sunset (hour 17
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experienced during the original ETE
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2 1 0 ‐1 ‐2 3 2 1 0 23‐Oct 23
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70% 60% 50% 40% 30% 20% 10% 0% Figu
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Figure 6‐9. Factor of Exceedance
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eceiving a 0.0 score. Figure 6‐13
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Table 6‐1. Summary of model ranki
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plume spread and observed surface c
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Figure 6‐16c. Comparison of spati
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• NoPiG: The tracer emissions wer
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Using the NMSE statistical performa
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6.4.3.2 Effect of PiG on Model Perf
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80 70 60 50 40 30 20 10 0 1 2 3 4 5
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Table 6‐3. Summary of CALPUFF puf
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0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.
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Figure 6‐ ‐22 displays the t sp
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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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