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Impact of high resolution modeling on ozone predictions in the Cascadia region Ying Xie and Brian Lamb Laboratory for Atmospheric Research Department of.

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Presentation on theme: "Impact of high resolution modeling on ozone predictions in the Cascadia region Ying Xie and Brian Lamb Laboratory for Atmospheric Research Department of."— Presentation transcript:

1 Impact of high resolution modeling on ozone predictions in the Cascadia region Ying Xie and Brian Lamb Laboratory for Atmospheric Research Department of Civil & Environmental Engineering Washington State University

2 Motivation The need for resolving the topographical features –strongly influenced by the Columbia River Gorge and the Cascade Mountain range –increasing grid resolution is beneficial for improving model results in regions strongly influenced by orographic flows or diurnal circulations The need for resolving small scale variability in precursor emissions –grid models assume uniform and instantaneous dilution of pollutants over the entire gird cell –substantial subgrid scale variability in precursor emissions –VOC-NO x photochemistry is highly nonlinear and often diffusion- limited The effect of high model resolution on air quality simulations remains unknown for the region

3 Methodology MM5/SMOKE/CMAQ modeling system July 1998 ozone episode (July 26-28): –1-hr peak 140 ppb Domain: –nested 4 km/1 km domain –1 km: 280x176 horizontal grid cells, 28 layers in the vertical (1st layer at 19 m) Meteorology: –MM5 v3.7 Emissions: –SMOKE v2.0 –1 km surrogates: population, mileage on roadways, major airport, livestock, and Oregon drycleaners Air quality: –CMAQ v4.6 BC/IC: –4 km: July average MOZART-2 (1990-1999) –1 km: use IC/BC from the 4 km simulation Chemical mechanism: –SAPRC99

4 A & B –Investigate the effects of high resolution met input B & C –Investigate the effects of high resolution emission inventories Simulations and analysis

5 TEMP (k) WSPD (m/s) WDIR (degree) Grid Size4 km1 km4 km1 km4 km1 km Mean Bias0.20.50.00.32-3 Mean Gross Error 2.92.81.4 5554 MM5 Model performance

6 Emissions - NO (15 LST July 27, 1998) 4 km 1 km

7 CMAQ results -NO x concentrations A (4Met/EI)B (1Met_4EI) C (1Met/EI)C - B (1Met/1EI - 1Met_4EI)

8 O 3 Concentrations - High resolution MM5 run B - A (1Met_4EI - 4Met/EI) B (1Met_4EI) A (4Met/EI)

9 O 3 Concentrations - High resolution emissions run C (1Met/EI) B (1Met_4EI) C - B (1Met/1EI - 1Met_4EI)

10 1MET/EI

11 O 3 time series

12 Conclusions Using high resolution meteorological input alone –has a larger impact on the position and peak levels of the O 3 plume –O 3 are higher in the 1 km case in areas where the terrain effects are substantial Using high resolution emissions –affect small-scale features in O 3 patterns mainly within the urban area –both O 3 increases and decreases can be identified

13 Future research Investigate the impact of vertical resolution upon ozone predictions ( 1st layer @ 38 m vs. @ 19 m) Investigate how horizontal and vertical resolution affect the interactions between different processes with process analysis

14 Acknowledgements Thanks to Sally Otterson and Rob Elleman for help with the 1 km input data and setup.

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16 Objectives investigate the impact of high resolution meteorological and photochemical modeling on ozone predictions for the region compare the relative effects of high resolution meteorological input versus high resolution emissions


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