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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Latest update: 02 Nov 2024
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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.