Report to WESTAR Technical Committee

September 20, 2006

The CMAQ Visibility Model Applied To Rural Ozone In The

Intermountain West

Patrick BarickmanTyler Cruickshank (Perl Programming)

Dave Strohm (HYSPLIT)

Is the model providing good estimates of hourly ozone production and depletion?

Compare observed ozone at the 6 monitors in the domain with model estimates

•Statistical metricsMean normalized biasMean normalized error

•Time series charts

Tools used•GIS•Perl programming•Additional scripts from the RMC•HYSPLIT

Are the CMAQ model results a useful guide for rural ozone analysis?

“Model Performance Evaluation” (MPE) answers this question

Model Sub-domain 12 km CMAQ Domain

Bilinear interpolation 4-cell window around each monitor

Weighted average of 4 cells based on distance of cell center to monitor location

Establishing model value for comparison

Goal <= 15% <= 25%

Monitor MNB MNGE

Rocky Mountain N.P. 4% 16%

Mesa Verde N.P. 3% 14%

Centennial, WY -4% 10%

Pinedale, WY -2% 13%

Gothic, CO 7% 17%

Canyonlands N.P. -3% 12%

Mean Normalized Bias (MNB)Mean Normalized Gross Error (MNGE) Minimum cutoff 50 ppb – only hours with observations > 50 used in bias and gross error calculations

Mean Normalized Bias (MNB): A value of zero would indicate that the model over predictions and model under predictions exactly cancel each other out.

Mean Normalized Gross Error (MNGE): A value of zero would indicate that the model exactly matches the observed values at all points in space/time.

Previous guidance in the modeling community set a goal of: MNB <= 15% and MNGE of <= 25%. This was based on the experience of actual model performance over the years.

Time Series Charts ( North to South )June 1 – July 31, 2002

Pinedale

0

20

40

60

80

100

120

1 55 109 163 217 271 325 379 433 487 541 595 649 703 757 811 865 919 973 1027 1081 1135 1189 1243 1297 1351 1405

Hour

PPB Obs

Model

Centennial, WY

0

20

40

60

80

100

120

1 54 107 160 213 266 319 372 425 478 531 584 637 690 743 796 849 902 955 1008 1061 1114 1167 1220 1273 1326 1379 1432

Hour

PPB Obs

Model

Rocky Mtn. N.P.

0

20

40

60

80

100

120

1 53 105 157 209 261 313 365 417 469 521 573 625 677 729 781 833 885 937 989 1041 1093 1145 1197 1249 1301 1353

Hour

PPB Obs

Model

Time Series Charts ( North to South )

Gothic, CO

0

20

40

60

80

100

120

1 54 107 160 213 266 319 372 425 478 531 584 637 690 743 796 849 902 955 1008 1061 1114 1167 1220 1273 1326 1379 1432

Hour

PPB OBS

Model

Mesa Verde

0

20

40

60

80

100

120

1 52 103 154 205 256 307 358 409 460 511 562 613 664 715 766 817 868 919 970 1021 1072 1123 1174 1225 1276 1327

Hour

PPB Obs

Model

Canyonlands

0

20

40

60

80

100

120

1 53 105 157 209 261 313 365 417 469 521 573 625 677 729 781 833 885 937 989 1041 1093 1145 1197 1249 1301 1353

Hour

PPB Obs

Model

Mesa Verde

30

40

50

60

70

80

90

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

Hour

PPB Obs

Model

Rocky Mtn. N.P.

30

40

50

60

70

80

90

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71

Hour

PPB Obs

Model

July 12-14, 2002

+

Gridded emissions + HYSPLIT creates an alternative view of

average emissions transport to a specific area

Conclusions

• Model performs well for rural ozone predictions

• Good model performance increases confidence in the meteorology and emissions inputs

• Emissions inventory, meteorology, and AQ model have been under continuous development for the past six years and are useful for a variety of issues