Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 2
Articles | Volume 18, issue 2
https://doi.org/10.5194/gmd-18-483-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-483-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 2
Development and technical paper
 | 
28 Jan 2025
Development and technical paper |  | 28 Jan 2025

Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation

Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling

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Latest update: 19 Jun 2025
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Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.

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