The potential for geostationary remote sensing of NO2 to improve weather prediction
Liu, X., Mizzi, A. P., Anderson, J. L., Fung, I., Cohen, R. C.. (2021). The potential for geostationary remote sensing of NO2 to improve weather prediction. Atmospheric Chemistry and Physics, doi:10.5194/acp-21-9573-2021
Title | The potential for geostationary remote sensing of NO2 to improve weather prediction |
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Author(s) | Xueling Liu, Arthur P. Mizzi, Jeffrey L. Anderson, Inez Fung, Ronald C. Cohen |
Abstract | 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. |
Publication Title | Atmospheric Chemistry and Physics |
Publication Date | Jun 24, 2021 |
Publisher's Version of Record | https://dx.doi.org/10.5194/acp-21-9573-2021 |
OpenSky Citable URL | https://n2t.net/ark:/85065/d7h133st |
OpenSky Listing | View on OpenSky |
CISL Affiliations | CISLVISITORS, TDD, DARES |