Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1595-2022
https://doi.org/10.5194/gmd-15-1595-2022
Methods for assessment of models
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23 Feb 2022
Methods for assessment of models | Highlight paper |  | 23 Feb 2022

Using neural network ensembles to separate ocean biogeochemical and physical drivers of phytoplankton biogeography in Earth system models

Christopher Holder, Anand Gnanadesikan, and Marie Aude-Pradal

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Latest update: 27 Mar 2024
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Short summary
It can be challenging to understand why Earth system models (ESMs) produce specific results because one can arrive at the same result simply by changing the values of the parameters. In our paper, we demonstrate that it is possible to use machine learning to figure out how and why particular components of an ESM (such as biology or ocean circulations) affect the output. This work could be applied to observations to improve the accuracy of the formulations used in ESMs.