Presentation is loading. Please wait.

Presentation is loading. Please wait.

CO budget and variability over the U.S. using the WRF-Chem regional model Anne Boynard, Gabriele Pfister, David Edwards National Center for Atmospheric.

Similar presentations


Presentation on theme: "CO budget and variability over the U.S. using the WRF-Chem regional model Anne Boynard, Gabriele Pfister, David Edwards National Center for Atmospheric."— Presentation transcript:

1 CO budget and variability over the U.S. using the WRF-Chem regional model Anne Boynard, Gabriele Pfister, David Edwards National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA NAQC – 9 March 2011

2 Motivation  Tropospheric CO is a key species in tropospheric chemistry (tracer of pollution and precursor of O3)  Air pollution monitoring is based on surface networks but little spatial coverage and no vertical information  Satellite observations : good spatial coverage and some vertical sensitivity but little information at the surface  Aircraft observations : vertical extension but little spatial coverage  Regional chemistry-transport model  Tropospheric CO is a key species in tropospheric chemistry (tracer of pollution and precursor of O3)  Air pollution monitoring is based on surface networks but little spatial coverage and no vertical information  Satellite observations : good spatial coverage and some vertical sensitivity but little information at the surface  Aircraft observations : vertical extension but little spatial coverage  Regional chemistry-transport model Can we distinguish the different factors that are driving the variations of pollutants at the scale of interest to AQ? => Essential to understand how the surface and tropospheric variability is driven by 3 processes : emissions-chemistry-transport Can we distinguish the different factors that are driving the variations of pollutants at the scale of interest to AQ? => Essential to understand how the surface and tropospheric variability is driven by 3 processes : emissions-chemistry-transport

3 Approach Chemical boundary conditions MOZART-4 2 Meteorological boundary conditions NCEP/GFS Anthropogenic: US EPA NEI 2005 Biogenic: MEGAN Wildfire: Fire INventory from NCAR 1 Emissions 1 [Wiedinmyer et al., 2006, 2010] Regional CTM WRF-Chem CO tracers  Anthropogenic  Chemical  Fire  Inflow 2 [Emmons et al., 2010] Allows to separate out the different CO source contributions Period simulation: 10 June – 10 July 2008 (2 weeks spin up) Horizontal resolution: 24km x 24 km over the U.S.  Surface observations (EPA)  Satellite data (MOPITT)  Aircraft data (ARCTAS campaign) Model Evaluation

4 Model performance: comparison with surface data  Magnitude and variability well reproduced  On average good agreement: R=70%  Slightly low bias: 28 ppbv  Magnitude and variability well reproduced  On average good agreement: R=70%  Slightly low bias: 28 ppbv

5 Rural site (Washington state) Urban site (California state) Model performance: Case studies Surface CO Surface CO tracers Surface CO Surface CO tracers Increase due to anthropogenic and fire emissions underestimated in the model CO inflow is dominant Increase due to anthropogenic and fire emissions underestimated in the model CO inflow is dominant First peak period: fire probably underestimated Second peak period: mismatch probably due to an underestimate of fire emissions and a timing and magnitude problem in anthropogenic emissions Decrease in relative contribution from transported pollution First peak period: fire probably underestimated Second peak period: mismatch probably due to an underestimate of fire emissions and a timing and magnitude problem in anthropogenic emissions Decrease in relative contribution from transported pollution Good agreement but some discrepancies… Increase in the model but not as much as in the obs

6 Model performance: comparison with satellite data MOPITT (V4) Total CO ColumnWRF-Chem AK Total CO Column Globally, similar patterns observed by both WRF-Chem and MOPITT On average, good agreement : R=83% & bias of 1±8% Fire emissions underestimated by the model (California) Boundary conditions overestimated by the model (South and West of U.S.) Globally, similar patterns observed by both WRF-Chem and MOPITT On average, good agreement : R=83% & bias of 1±8% Fire emissions underestimated by the model (California) Boundary conditions overestimated by the model (South and West of U.S.) Average over the period 24 June - 10 July 2008 (1e16 molecules cm -2 )

7 Model performance: comparison with aircraft data Aircraft CO WRF CO DC-8 Flight, 26 June 2008 (1-minute merged data) Altitude CO WRF-chem CO Fire DC-8 Acetonitrile WRF-chem DC-8 Underestimate by a factor of 3-4 Acknowledgments: ARCTAS science team (Glen Diskin for CO data and Armin Wisthaler for CH3CN data) Good agreement but fire emissions underestimated by the model ARCTAS mission: NASA’s Arctic Research of the Composition of the Troposphere from Aircraft and Satellites mission (Spring and Summer 2008) Fire tracer

8 Surface CO tracer contributions over the U.S. 18±14% 14±8% 2±5%63±19% Average over the period 24 June - 10 July 2008 (ppbv) AnthropogenicChemicalFire Inflow Total CO Over the Eastern U.S.: high CO concentrations due to anthropogenic emissions and CO produced chemically In California: high CO concentrations due to anthropogenic and fire emissions CO is coming from the West and the North Over the Eastern U.S.: high CO concentrations due to anthropogenic emissions and CO produced chemically In California: high CO concentrations due to anthropogenic and fire emissions CO is coming from the West and the North Note the different color scale for CO inflow ! 500 70 150 0

9 Can satellite observations be used for AQ monitoring? Surface finest scale variability not captured in the FT but average behavior captured Variability in CO inflow at the surface ≈ FT At higher altitude, variability in inflow dominates the variability in anthropogenic CO => A sounder will observe most of the variability in boundary conditions Variability in CO inflow at the surface ≈ FT At higher altitude, variability in inflow dominates the variability in anthropogenic CO => A sounder will observe most of the variability in boundary conditions CO (ppbv) CO Inflow (ppbv) Thermal IR are sensitive in the lower FT (2-3km)  How much of the surface CO variability is reflected in the FT? Anthropogenic CO (ppbv)  Is CO brought by long distance transport or produced locally?

10 Summary  Model performance :  good agreement with surface, aircraft and satellite data  CO source contributions:  Anthropogenic and CO produced chemically dominant over the Eastern coast  CO inflow dominant over the Western and Northern U.S.  AQ monitoring from satellite :  Finest scale variability seen at the surface is not reflected in the FT but the average behavior is captured  Real need of sensitivity down towards the surface  Multispectral retrieval has a real sensitivity down towards the surface as recently demonstrated by MOPITT V5 [Worden et al., 2010]  Plan to use multispectral techniques for future geostationary AQ observations (e.g GEO-CAPE * ) for CO and O3 *GEO-CAPE: Geostationary Coastal and Air Pollution Events  Model performance :  good agreement with surface, aircraft and satellite data  CO source contributions:  Anthropogenic and CO produced chemically dominant over the Eastern coast  CO inflow dominant over the Western and Northern U.S.  AQ monitoring from satellite :  Finest scale variability seen at the surface is not reflected in the FT but the average behavior is captured  Real need of sensitivity down towards the surface  Multispectral retrieval has a real sensitivity down towards the surface as recently demonstrated by MOPITT V5 [Worden et al., 2010]  Plan to use multispectral techniques for future geostationary AQ observations (e.g GEO-CAPE * ) for CO and O3 *GEO-CAPE: Geostationary Coastal and Air Pollution Events

11 Thank you for your attention!


Download ppt "CO budget and variability over the U.S. using the WRF-Chem regional model Anne Boynard, Gabriele Pfister, David Edwards National Center for Atmospheric."

Similar presentations


Ads by Google