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

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without regard to the scientific legitimacy of the options selected” (EPA, 2009a). The CALPUFF working group noted that when running CALMET with prognostic meteorological model (e.g., WRF and MM5) output as input, the CALMET diagnostic effects and blending of meteorological observations with the WRF/MM5 output degraded the WRF/MM5 meteorological fields. Thus, the 2009 IWAQM Phase 2 Reassessment Report recommended CALMET settings with an objective to try and “pass through” the WRF/MM5 meteorological model output as much as possible for input into CALPUFF. However, further testing of CALMET and CALPUFF by EPA’s CALPUFF workgroup found that the recommended CALMET settings in the May 2009 IWAQM Phase 2 Reassessment Report did not achieve the intended result to “pass through” the WRF/MM5 meteorological variables as CALMET still re‐diagnosed some and modified other meteorological variables thereby degrading the WRF/MM5 meteorological fields. Based in part of CALMET evaluations using tracer test field study databases (presented in Appendix B of this report), EPA determined interim CALMET settings that produced the best CALMET performance when compared to observed surface winds and on August 31, 2009 released a Clarification Memorandum “Clarification on EPA‐FLM Recommended Settings for CALMET” (EPA, 2009b) with new recommended settings for CALMET. In the August 2009 Clarification Memorandum, EPA reiterated the desire to “pass through” meteorology from the WRF/MM5 prognostic meteorological models to CALPUFF, but the CALMET model at this time was incapable of achieving that objective. In the meantime, EPA has developed the Mesoscale Model Interface (MMIF) software that where possible directly converts prognostic meteorological output data from the MM5 or WRF models to the parameters and formats required for direct input into the CALPUFF dispersion model thereby bypassing CALMET. Version 1.0 of MMIF was developed in June 2009 (Emery and Brashers, 2009) with versions 2.0 (Brashers and Emery, 2011) and 2.1 (Brashers and Emery, 2012) developed in, respectively, September 2011 and February 2012; we expect that MMIF Version 2.1 will be publicly released in February 2012. MMIF specifically processes geophysical and meteorological output files generated by the fifth generation mesoscale model (MM5) or the Weather Research and Forecasting (WRF) model (Advanced Research WRF [ARW] core, versions 2 and 3) and reformats the MM5/WRF output for input into CALPUFF.. The EPA CALPUFF workgroup has been evaluating CALPUFF using CALMET and MMIF meteorological drivers using data from several historical tracer field studies. In addition to a reevaluation of CALPUFF using CALMET and MMIF for the GP80 and SRL75 tracer studies that were used in the 1998 EPA CALPUF tracer evaluation report (EPA, 1998a), the CALPUFF workgroup has also evaluated CALPUFF using CALMET and MMIF meteorological drivers along with 5 other LRT dispersion models for the 1983 Cross Appalachian Tracer Experiment (CAPTEX). CALPUFF, along with four other LRT dispersion models, were also evaluated using data from the 1994 European Tracer Experiment (ETEX). 1.2 PURPOSE The purpose of this report is to document the evaluation of the CALPUFF LRT dispersion model using data from four atmospheric tracer experiment field study databases. This includes the comparison of the CALPUFF model performance using meteorological inputs based on the CALMET and MMIF software and comparison of the CALPUFF model performance with other LRT dispersion models. 3
1.3 ORGANIZATION OF REPORT Chapter one provides a background and purpose for the study. In Chapter 2, the four tracer field study experiments and LRT dispersion models used in the model performance evaluation are summarized. Chapter 2 also summarizes related previous studies and the approach and methods for the model performance evaluation of the LRT dispersion models. Chapters 3, 4, 5 and 6 contain the evaluation of the LRT dispersions models using the GP80, SRL75, CAPTEX and ETEX tracer study field experiment data. References are provided in Chapter 7. Appendix A contains an evaluation of the MM5 and CALMET meteorological models using the CAPTEX Release #5 (CTEX5) database. Appendix B presents the evaluation of the CALMET meteorological model using the CAPTEX Release #3 (CTEX3) database that was used in part to formulate the EPA‐FLM recommended settings in the 2009 Clarification Memorandum (EPA, 2009b). Results of the evaluation of six LRT dispersion models using the CAPTEX tracer field experiments are presented in Appendix C. 4
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: July 1980. Both experiments examine
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
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the amount of time that the tracer
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Figure 4‐1. CALPUFF/CALMET UTM mo
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compact discs, which were used to o
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Table 4‐4. CALPUFF parameters use
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Table 4‐8. CALPUFF/MMIF sensitivi
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the fitted Gaussian plume is not a
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Figure 4‐2. Comparison of predict
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Figure 5‐1. Location of Dayton an
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MM5 runs, the first without FDDA (i
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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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