The potential for geostationary remote sensing of NO2 to improve weather prediction

Observations of winds in the planetary boundary layer remain sparse making it challenging to simulate and predict atmospheric conditions that are most important for describing and predicting urban air quality. Short-lived chemicals are observed as plumes whose location is affected by boundary layer winds and whose lifetime is affected by boundary layer height and mixing. Here we investigate the application of data assimilation of NO2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of wind fields in the boundary layer.

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Author Liu, Xueling
Mizzi, Arthur P.
Anderson, Jeffrey L.
Fung, Inez
Cohen, Ronald C.
Publisher UCAR/NCAR - Library
Publication Date 2021-06-24T00:00:00
Digital Object Identifier (DOI) Not Assigned
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:14:53.679967
Metadata Record Identifier edu.ucar.opensky::articles:24522
Metadata Language eng; USA
Suggested Citation Liu, Xueling, Mizzi, Arthur P., Anderson, Jeffrey L., Fung, Inez, Cohen, Ronald C.. (2021). The potential for geostationary remote sensing of NO2 to improve weather prediction. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7h133st. Accessed 16 June 2025.

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