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

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For the CTEX3 experiment, the average rankings across the 11 statistics is nearly identical to the rankings produced by the RANK integrated statistic that combines the four of the statistics for correlation (PCC), bias (FB), spatial (FMS) and cumulative distribution (KS) with only HYSPLIT and CALPUFF exchanging places. This switch was due to CALPUFF having lower scores in the FA2 and FA5 metrics compared to HYSPLIT. If not for this, the average rank across all 11 metrics would have been the same as Draxler’s RANK score. However, the analyst should use discretion in relying too heavily upon RANK score without consideration to which performance metrics are important measures for the particular evaluation goals. For example, if performance goals are not concerned with a model’s ability to perform well in space and time, then reliance upon spatial statistics, such as the FMS, in the composite RANK value may not be appropriate. Table ES‐5. Summary of model ranking for the CTEX3 using the ATMES‐II statistical performance metrics and comparing their average rankings to the RANK metric. Statistic 1 st 2 nd 3 rd 4 th 5 th 6 th FMS CAMx SCIPUFF HYSPLIT CALPUFF FLEXPART CALGRID FAR FLEXPART CAMx SCIPUFF CALPUFF HYSPLIT CALGRID POD CAMx FLEXPART SCIPUFF HYSPLIT CALPUFF CALGRID TS FLEXPART CAMx SCIPUFF HYSPLIT CALPUFF CALGRID FOEX HYSPLIT CAMx SCIPUFF CALPUFF CALGRID FLEXPART FA2 CAMx SCIPUFF FLEXPART HYSPLIT CALGRID CALPUFF FA5 CAMx SCIPUFF FLEXPART HYSPLIT CALPUFF CALGRID NMSE FLEXPART CAMx CALPUFF SCIPUFF CALGRID HYSPLIT PCC or R CAMx SCIPUFF CALPUFF CALGRID FLEXPART HYSPLIT FB FLEXPART CAMx SCIPUFF CALPUFF CALGRID HYSPLIT KS HYSPLIT CAMx SCIPUFF CALPUFF FLEXPART CALGRID Avg. Ranking CAMx SCIPUFF FLEXPART HYSPLIT CALPUFF CALGRID Avg. Score 1.55 2.72 3.0 4.0 4.27 5.55 RANK Ranking CAMx SCIPUFF FLEXPART CALPUFF HYSPLIT CALGRID RANK 1.91 1.71 1.44 1.43 1.25 0.98 20
Evaluatioon of Six LRT T Dispersion Models usinng the CTEX55 Database Figure ESS‐5 displays the t RANK model performmance statisstics for the six LRT models and the CTEX5 fieeld experime ent. Figure ESS‐5. RANK st tatistical perrformance mmetric for thhe six LRT moodels and CAAPTEX Releaase 5. Table ES‐ ‐6 summariz zes the rankiings of the six LRT modeels for the 111 performance statistics analyzed for CAPTEX X Release 5 aand comparees the averagging rankingg across the 111 statistics against the RANK me etric rankinggs. Unlike the CTEX3 expperiment, whhere CAMx ( (46%) and FLEXPART (36%) acco ounted for 882% of the first placed raanked modeels, there is a wide variattion of which model was ranked bestt performingg across the 11 statistical metrics in tthe CTEX5 experimeent. In testin ng the efficaacy of the RAANK statisticc, overall rannkings acrosss all eleven statics were obtained d using an avverage modeled rankingg. The averaage rank acrooss all 11 performaance statistic cs and the RRANK model rankings aree as follows: Rank king Averrage of 11 Sttatistics 1. . CAMx 2. . HYSPPLIT 3. . SCIPUUFF 4. . FLEXPART 5. . CALPPUFF 6. . CALGGRID RANK CAMx HYSPLIT CALGRID SCIPUFF FLEXPART CALPUFF The results from CAP PTEX Releasee 5 present aan interestinng case studyy on the usee of the RANK metric too characteriz ze overall moodel performmance. As noted in Tablle ES‐6 and ggiven above, , the relative rranking of models m using the averagee rankings accross the 11 statistical mmetrics is consideraably differen nt than the RRANK scoress after the twwo highest raanked modeels (CAMx annd 21
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: Figure ESS‐4. RANK statistical pe
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%
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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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60% 40% 20% 0% ‐20% ‐40% ‐60%
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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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