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

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

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

Approach

Chemical boundary conditions

MOZART-42

Meteorological boundary conditionsNCEP/GFS

Anthropogenic: US EPA NEI 2005Biogenic: MEGANWildfire: Fire INventory from NCAR1

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

Model performance: comparison with surface data

Magnitude and variability well reproduced

On average good agreement: R=70% Slightly low bias: 28 ppbv

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

• 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

Model performance: comparison with satellite data

MOPITT (V4) Total CO Column WRF-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.)

Average over the period 24 June - 10 July 2008 (1e16 molecules cm-2)

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 FireDC-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

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)

Anthropogenic

Chemical Fire 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

Note the different color scale for CO inflow!

500

70

150

0

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

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?

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

Thank you for your attention!