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Observing System Simulation Experiments (OSSEs) Using a Regional Air Quality Application for Evaluation

  • Pius LeeEmail author
  • Robert Atlas
  • Gregory Carmichael
  • Youhua Tang
  • Brad Pierce
  • Arastoo Pour Biazar
  • Li Pan
  • Hyuncheol Kim
  • Daniel Tong
  • Weiwei Chen
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

Satellite-based and high-altitude airborne remotely sensed air quality data complement land-based and routinely commercial-flight and other measurement-campaign acquired remotely sensed and in situ observations. It is important to optimize the combination and placement of these wide ranges of measurements and data acquisition options for cost-effectiveness. Under this initiative we attempt to quantify the gain by a regional state-of-the-science chemical data assimilation and chemical transport modeling system when incremental sets of observation are acquired into the system. This study represents a first step in a series of steps to ingest such proposed incremental additions of observation. The efficacy of such proposals is quantified systematically by Observation Simulation System Experiments (OSSEs). We compared two end-to-end regional air quality forecasting simulations using: (a) the Weather Forecasting and Research (WRF) regional application initialized by the U.S. national Weather Service (NWS) Global Forecasting System (GFS) coupled with the U.S. Environmental Protection Agency Community Multi-scale Air Quality (CMAQ) chemical model (Byun and Schere 2006), and (b) the same as above but with a new GFS enhanced by assimilating a fictitious addition of Atmospheric Infrared Sounder (AIRS) retrieved radiances at 13 km spatial resolution at nadir from a proposed geostationary satellite positioned over 75oW staring over the U.S. Both sensitivity runs were performed in 12 km horizontal grid resolution and with daily initialization for 12 days between July 29 and August 9 2005. Noticeable forecast skill improvement in surface concentration for O3 and particulate matter smaller than 2.5 µm in diameter (PM2.5) was achieved.

Keywords

Aerosol Optical Depth Geostationary Satellite National Weather Service Global Forecast System Observe System Simulation Experiment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pius Lee
    • 1
    Email author
  • Robert Atlas
    • 2
  • Gregory Carmichael
    • 3
  • Youhua Tang
    • 1
    • 4
  • Brad Pierce
    • 5
  • Arastoo Pour Biazar
    • 6
  • Li Pan
    • 1
    • 4
  • Hyuncheol Kim
    • 1
    • 4
  • Daniel Tong
    • 1
    • 4
    • 7
  • Weiwei Chen
    • 1
    • 8
  1. 1.Air Resources Laboratory (ARL)NOAACollege ParkUSA
  2. 2.Atlantic Oceanographic and Meteorological LaboratoryNOAAMiamiUSA
  3. 3.Department of Chemical and Biochemical EngineeringUniversity of IowaIowa CityUSA
  4. 4.Cooperative Institutes for Satellite and ClimateUniversity of MarylandCollege ParkUSA
  5. 5.National Environmental Satellite and Information Service (NESDIS)MadisonUSA
  6. 6.Department of Atmospheric ScienceUniversity AlabamaHuntsvilleUSA
  7. 7.Center for Spatial Information Science and SystemsGeorge Mason UniversityFairfaxUSA
  8. 8.Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchunChina

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