The potential for geostationary remote sensing of NO 2 to improve weather prediction

Liu, Xueling; Mizzi, Arthur P.; Anderson, Jeffrey L.; Fung, Inez; Cohen, Ronald C.

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 NOinline-formula2 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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Liu, Xueling / Mizzi, Arthur P. / Anderson, Jeffrey L. / et al: The potential for geostationary remote sensing of NO2 to improve weather prediction. 2021. Copernicus Publications.

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