Articles | Volume 13, issue 5
Geosci. Model Dev., 13, 2487–2509, 2020
https://doi.org/10.5194/gmd-13-2487-2020
Geosci. Model Dev., 13, 2487–2509, 2020
https://doi.org/10.5194/gmd-13-2487-2020

Methods for assessment of models 29 May 2020

Methods for assessment of models | 29 May 2020

Correcting a bias in a climate model with an augmented emulator

Doug McNeall et al.

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Interactive discussion

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
AR by Douglas McNeall on behalf of the Authors (24 Feb 2020)  Author's response    Manuscript
ED: Publish as is (15 Apr 2020) by David Topping
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Short summary
In the climate model FAMOUS, matching the modelled Amazon rainforest to observations required different land surface parameter settings than for other forests. It was unclear if this discrepancy was due to a bias in the modelled climate or an error in the land surface component of the model. Correcting the climate of the model with a statistical model corrects the simulation of the Amazon forest, suggesting that the land surface component of the model is not the source of the discrepancy.