Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4683-2021
https://doi.org/10.5194/gmd-14-4683-2021
Development and technical paper
 | 
29 Jul 2021
Development and technical paper |  | 29 Jul 2021

Data reduction for inverse modeling: an adaptive approach v1.0

Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller

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Cited articles

Bergamaschi, P., Krol, M., Dentener, F., Vermeulen, A., Meinhardt, F., Graul, R., Ramonet, M., Peters, W., and Dlugokencky, E. J.: Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5, Atmos. Chem. Phys., 5, 2431–2460, https://doi.org/10.5194/acp-5-2431-2005, 2005. a
Brasseur, G. and Jacob, D.: Modeling of Atmospheric Chemistry, Cambridge University Press, Cambridge, 2017. a, b
Brodsky, D. and Watson, B.: Model simplification through refinement, in: Proceedings of Graphics Interface 2000: Montréal, Québec, Canada, 15–17 May 2000. a, b
Buis, A.: GeoCarb: A New View of Carbon Over the Americas, ExploreEarth, available at: https://www.nasa.gov/feature/jpl/geocarb-a-new-view-of-carbon-over-the-americas (last access: 17 July 2020), 2018. a
Crisp, D.: Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2), in: Earth Observing Systems XX, vol. 9607, edited by Butler, J. J., Xiong, X. J., and Gu, X., International Society for Optics and Photonics, SPIE, https://doi.org/10.1117/12.2187291, 1–7, 2015. a, b
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Short summary
Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
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