GOME-2 NO2 and the NOAA Air Quality Program

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GOME-2 NO2 and the NOAA Air Quality
Program Trevor Beck, Shobha Kondragunta, Lawrence
Flynn, NOAA/NESDIS Kelly Chance and Thomas
Kurosu Harvard/SAO Chuanyu Xu and Qiang Zhao,
IMSG September 2007 Tropospheric NO2 Workshop

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National Mandates related to Air Quality
Air Quality Forecast H.R. 4 Energy Policy Act of
2002 (Senate Amendment) EPA-NOAA Agreements EPA
Administrator and Dept. of Commerce Deputy
Secretary signed MOU/MOA for AQ forecasting May
6, 2003 Regulatory NAAQS (Assessment/Monitoring)
Clean Air Act - EPA Administrator required to
periodically review and revise National Ambient
Air Quality Standards in accordance with latest
state of the science Public Health
Tracking Nationwide Health Tracking Bills
introduced S.2054 and H.R.4061 EPA-CDC
Agreement EPA Administrator and Dept. of HHS
Secretary signed MOU related to ENPHT September
30, 2002
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Air Quality Forecast Program

• Congressional mandate (2002) to NOAA to develop
  an air quality forecast system that can enable
  mitigation of health effects caused by episodes
  of poor air quality
• Ozone and aerosols (PM2.5) are primary pollutants
  leading to poor air quality
• Predictions are provided to state/local air
  quality forecasters and to the public
• Operational deployment schedule (WRF-CMAQ
  system)
• Current Eastern US (ozone)?
• Current Eastern US (PM2.5 developmental)?
• 2008 Continental US (ozone)?
• 2009 Entire US (ozone)?
• 2011 Eastern US (PM2.5)?
• Collaboration between NOAA and US EPA

http//www.weather.gov
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Slant Column Fitting

• Fitting Algorithm supplied by Chance Kurosu
• NO2 Xsections prepared from BIRA data.
• FM3 Xsections, BIRA Xsections were explored.
• O2-O2 and H20, prepared for the fitted GOME-2
  Bandpass.
• RRS Ring signal prepared be K. Chance for GOME-2.
• Fitting Window Optimized, currently using 429.9nm
  to 450.2nm.

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NO2 VCD from SAF and NESDIS

• 1, August, 2007. Global view.
• The SAF NO2 VCD is about 10 higher.
• Problem with NO2 X-section just discovered, will
  be fixed and optimization of fitting window will
  be repeated.

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Cloud Ozone Algorithm

• The heritage OMI/TOMS algorithm is being used to
  derive effective cloud fractions GOMTO3.
• Cloud top Height from Climatology. This
  shortcoming will be remedied.
• Total ozone derived from 3 channels. There
  appears to be a polarization correction issues
  that affect the short channels in GOMTO3.
  Presently the TO3 is sufficient and will be
  improved.

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Shortcomings

• Current AMF's less than adequate.
• Plan to address by using or emulating OMNO2B AMF
  treatment.
• Planning to do online RT calculations for AMF.

• Revisit fitting cross sections repeat
  optimization.
• Bring in Cloud Top Pressure information
• Oxygen A-Band.
• O2-O2 absorption
• RRS at Ca lines, similar to OMCLDRR, GOME-2
  signal at 385nm is strong, RRS likely to produce
  good results.( Joiner, Vasilkov).

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OMI and GOME-2 Applications for NCEP Air Quality
Forecasting Systems

• Evaluation of WRF-CMAQ NO2 predictions over CONUS
• CMAQ urban area over-titration problem. Is there
  too much NOx in the model destroying ozone?
• Assimilation of radiances and retrievals (NO2,
  O3, SO2, aerosols) into NCEP Gridpoint
  Statistical Interpolation (GSI) variational
  assimilation system to account for missing
  sources and sinks

California Ozone Underprediction problem
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Preliminary Work
CMAQ

• Studying an early August ozone pollution event
  over the U.S (August 1-6, 2007) predicted by CMAQ
  and observed by GOME-2
• GOME-2 NO2 biased low

GOME-2
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Plans for 2008

• Produce AveKern vector for retrievals.
• Improved AMF treatment.
• Begin tropospheric NO2 for Americas with emphasis
  on CONUS.

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ACC Project Objectives and Goals

• How to use NO2 data from multiple satellites in
  improving air quality forecasts
• Boresma et al. (2007) showed that diurnal
  variations in NO2 can be captured by processing
  OMI and SCIAMACHY data with a common algorithm
• Expected outcome
• A recommendation to National Weather service
  (NWS) to use satellite-derived NO2 products to
  improve operational air quality forecasts
• Via assimilation of NO2 to improve initial and
  boundary conditions
• Via constraining NOx emissions using inverse
  modeling approaches

• NO2 diurnal variations
• Temporally varying sources
• Temporally varying sinks
• Physical processes
• transport
• dry and wet deposition

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NWS Applications

• NWS uses Community Multiscale Air Quality (CMAQ)
  model for operational ozone forecast guidance
• Specifications
• CMAQ transport driven by Eta12 winds
• CONUS coverage
• 12 km X 12 km
• 23 sigma layers (model top near 200 mb)?
• 6 hr cycling and 48 hour forecast for ozone
• Model initial/boundary conditions and emissions
  are prescribed

• NWS providing surface ozone and PM2.5 forecasts
• Forecast accuracy depends on the accuracy of
  transport, chemistry and physics, and emissions
  (natural and anthropogenic)?
• Important to get ozone and aerosol precursors
  like NO2 and SO2 right in the model
• Availability of routine data from satellites will
  become useful for model verification and
  improvement via data assimilation

NO2 hv ? NO O
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EPA use of Satellite-derived NO2 Product

• Improve NOx emissions
• Inventories uncertain. Difficulty incorporating
  natural sources (biomass burning, soil,
  lightning)?
• Understand long-range transport of NOx
• Accountability studies
• Are control strategies (e.g., Clean Air
  Interstate Rule) working?
• Expansion of on-going projects to include GOME-2
  and OMI NO2 products
• Using SCIAMACHY data along with surface observed
  and predicted (CMAQ model) NO2 to understand the
  representativeness of column NO2 with surface NOx
  emissions
• Differences between rural and urban area NOx
  emissions
• Understanding retrievals from multiple sensors so
  trends using NO2 data from multiple sensors can
  be objectively interpreted

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Acknowledgements

• OMI and GOME-2 NO2 work supported by
  NASA/NOAA/DoD Joint Center for Satellite Data
  Assimilation (JCSDA)?
• Satellite data assimilation work supported by
  GOES-R Program
• Computational resources for model simulation
  provided by NWS/NCEP. Model framework support
  provided by Jeff McQueen and Pius Lee of NWS/NCEP
• EUMETSAT provides GOME-2 L1B in NRT