Report to WESTAR Technical Committee September 20, 2006 The CMAQ Visibility Model Applied To Rural Ozone In The Intermountain West Patrick Barickman Tyler 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 metrics  Mean normalized bias  Mean 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% MonitorMNBMNGE Rocky Mountain N.P.4%16% Mesa Verde N.P.3%14% Centennial, WY-4%10% Pinedale, WY-2%13% Gothic, CO7%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

Time Series Charts ( North to South )

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