Articles | Volume 18, issue 2
https://doi.org/10.5194/gmd-18-483-2025
https://doi.org/10.5194/gmd-18-483-2025
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: 20 Apr 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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