Articles | Volume 18, issue 8
Biogeosciences, 18, 2727–2754, 2021
https://doi.org/10.5194/bg-18-2727-2021
Biogeosciences, 18, 2727–2754, 2021
https://doi.org/10.5194/bg-18-2727-2021

Research article 30 Apr 2021

Research article | 30 Apr 2021

Optimal model complexity for terrestrial carbon cycle prediction

Caroline A. Famiglietti et al.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (05 Mar 2021) by Sönke Zaehle
AR by Caroline Famiglietti on behalf of the Authors (17 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (24 Mar 2021) by Sönke Zaehle
Download
Short summary
Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Altmetrics
Final-revised paper
Preprint