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‐0.1<br />

‐0.2<br />

0<br />

0.8<br />

0.7<br />

0.6<br />

0.5<br />

0.4<br />

0.3<br />

0.2<br />

0.1<br />

BASE D<br />

16%<br />

14%<br />

12%<br />

10%<br />

8%<br />

6%<br />

4%<br />

2%<br />

0%<br />

BASED<br />

EXP3B<br />

EXP3D<br />

EXP4B<br />

Pearson's Correlation Coefficient (PCC)<br />

(Perfect = 1)<br />

EXP 3B<br />

EXP 3D<br />

EXP 4B<br />

EXP 4D<br />

EXP 5B<br />

EXP 5D<br />

EXP 6B<br />

EXP 6D<br />

12K MMIF<br />

Factor <strong>of</strong> 2 <strong>and</strong> 5 (Perfect = 100%)<br />

36K MMIF<br />

4K MMIF<br />

EXP4D<br />

EXP5B<br />

80K MMIF<br />

EXP5D<br />

EXP6B<br />

Figure 5‐17b. Global model performance statistics for <strong>the</strong> CTEX5 <strong>CALPUFF</strong> sensitivity tests<br />

using different MM4/MM5 grid resolutions (higher values indicate better performance).<br />

5.4.2.5 Rankings <strong>of</strong> CTEX5 <strong>CALPUFF</strong> Sensitivity Tests using <strong>the</strong> RANK Statistic<br />

Table 5‐10 ranks <strong>the</strong> model performance <strong>of</strong> <strong>the</strong> CTEX5 <strong>CALPUFF</strong> sensitivity tests using <strong>the</strong> RANK<br />

composite statistic. Outside <strong>of</strong> <strong>the</strong> 12KM, 36KM <strong>and</strong> 80KM MMIF <strong>CALPUFF</strong> sensitivity tests<br />

being by far <strong>the</strong> worst performing configurations with RANK values in <strong>the</strong> 1.28 to 1.42 range,<br />

<strong>the</strong> remaining sensitivity tests have RANK values in <strong>the</strong> 1.7 to 2.2 range, with <strong>the</strong> 4KM_MMIF<br />

run being in <strong>the</strong> lower end <strong>of</strong> this range. Examining trends in <strong>the</strong> <strong>CALPUFF</strong> sensitivity tests, <strong>the</strong><br />

EXP6 series that uses <strong>the</strong> highest MM5 (12 km) <strong>and</strong> CALMET (4 km) grid resolution tends to<br />

have better model performance, whereas <strong>the</strong> “B” series <strong>of</strong> sensitivity tests tends to have worst<br />

model performance. Although <strong>the</strong> BASEA scenario is ranked 4 th , <strong>the</strong> o<strong>the</strong>r BASE series using <strong>the</strong><br />

80 km MM5 <strong>and</strong> 18 km CALMET grid resolution have RANK scores on <strong>the</strong> lower end <strong>of</strong> <strong>the</strong><br />

distribution. Based on <strong>the</strong>se results we conclude <strong>the</strong> following for <strong>the</strong> CTEX5 sensitivity tests:<br />

• Use <strong>of</strong> higher MM5 grid resolution (12 km) produces better <strong>CALPUFF</strong> model performance<br />

using both CALMET <strong>and</strong> MMIF.<br />

5.5 CONCLUSIONS OF THE CAPTEX TRACER SENSITIVITY TESTS<br />

There are some differences <strong>and</strong> similarities in <strong>CALPUFF</strong>’s ability to simulate <strong>the</strong> observed tracer<br />

concentrations in <strong>the</strong> CTEX3 <strong>and</strong> CTEX5 field experiments. The overall conclusions <strong>of</strong> <strong>the</strong><br />

evaluation <strong>of</strong> <strong>the</strong> <strong>CALPUFF</strong> model using <strong>the</strong> CAPTEX tracer test field experiment data can be<br />

summarized as follows:<br />

• Regarding use <strong>of</strong> CALMET versus MMIF as a meteorological driver for <strong>CALPUFF</strong>, no<br />

definitive conclusion can be made since <strong>the</strong> <strong>CALPUFF</strong>/MMIF was <strong>the</strong> best performing<br />

model configuration for CTEX3 <strong>and</strong> <strong>the</strong> worst performing configuration for CTEX5.<br />

96<br />

EXP6D<br />

2.4<br />

12KM_MMIF<br />

36KM_MMIF<br />

4KM_MMIF<br />

80KM_MMIF<br />

2<br />

1.6<br />

1.2<br />

0.8<br />

0.4<br />

0<br />

BASED<br />

EXP3B<br />

EXP3D<br />

EXP4B<br />

EXP4D<br />

EXP5B<br />

FA2<br />

FA5<br />

Rank (RANK) (Perfect = 4)<br />

EXP5D<br />

EXP6B<br />

EXP6D<br />

12KM_MMIF<br />

36KM_MMIF<br />

4KM_MMIF<br />

80KM_MMIF<br />

(1‐KS/100)<br />

FMS/100<br />

(1‐FB/2)<br />

R^2

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