Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
BG | Volume 17, issue 4
Biogeosciences, 17, 1033–1061, 2020
https://doi.org/10.5194/bg-17-1033-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Biogeosciences, 17, 1033–1061, 2020
https://doi.org/10.5194/bg-17-1033-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 26 Feb 2020

Research article | 26 Feb 2020

Estimating causal networks in biosphere–atmosphere interaction with the PCMCI approach

Christopher Krich et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (21 Oct 2019) by Ivonne Trebs
AR by Christopher Krich on behalf of the Authors (06 Dec 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (06 Jan 2020) by Ivonne Trebs
RR by Benjamin L. Ruddell (16 Jan 2020)
ED: Publish as is (20 Jan 2020) by Ivonne Trebs
Publications Copernicus
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Short summary
Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Causal inference promises new insight into biosphere–atmosphere interactions using time series...
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