Assimilation of Satellite Data in Regional Air Quality Models

  • Richard T. McNider
  • William B. Norris
  • Daniel M. Casey
  • Jonathan E. Pleim
  • Shawn J. Roselle
  • William M. Lapenta
Part of the NATO • Challenges of Modern Society book series (NATS, volume 22)


In regional-scale air-pollution models probably no other source of uncertainty ranks higher than the current ability to specify clouds and soil moisture. Because modeled clouds are highly parameterized, the ability of models to predict the magnitude and spatial distribution of radiative characteristics is highly suspect and subject to large error. While considerable advances have been made in the assimilation of winds and temperatures into regional models (Stauffer and Seaman, 1990), the poor representation of cloud fields from point measurements at National Weather Service stations and the almost total absence of observations of surface moisture availability has made assimilation of these variables difficult if not impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry. Consider the following points relative to these variables.


Surface Albedo Cloud Layer Southern Great Plain Isoprene Emission Photolysis Rate 
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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Richard T. McNider
    • 1
  • William B. Norris
    • 1
  • Daniel M. Casey
    • 1
  • Jonathan E. Pleim
    • 2
  • Shawn J. Roselle
    • 2
  • William M. Lapenta
    • 3
  1. 1.Earth System Science LaboratoryUniversity of Alabama in HuntsvilleHuntsvilleUSA
  2. 2.Atmospheric Science Modeling Division, Air Resources LaboratoryNational Oceanic and Atmospheric AdministrationResearch Triangle ParkUSA
  3. 3.NASA Marshall Space Flight CenterGlobal Hydrology and Climate CenterHuntsvilleUSA

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