Correcting a bias in a climate model with an augmented emulator

McNeall, Doug; Williams, Jonny; Betts, Richard; Booth, Ben; Challenor, Peter; Good, Peter; Wiltshire, Andy

doi:https://doi.org/10.5194/gmd-13-2487-2020

Articles | Volume 13, issue 5

https://doi.org/10.5194/gmd-13-2487-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-13-2487-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 5

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, Jonny Williams, Richard Betts, Ben Booth, Peter Challenor, Peter Good, and Andy Wiltshire

Supplement

https://doi.org/10.5194/gmd-13-2487-2020-supplement

Data sets

Data, code and paper D. McNeall, J. Williams, R. Betts, B. Booth, P. Challenor, P. Good, and A. Wiltshire https://doi.org/10.5281/zenodo.3755497

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.