Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 7
Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4495-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-4495-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 7
Methods for assessment of models
 | 
22 Jul 2021
Methods for assessment of models |  | 22 Jul 2021

Testing the reliability of interpretable neural networks in geoscience using the Madden–Julian oscillation

Benjamin A. Toms, Karthik Kashinath, Prabhat, and Da Yang

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Short summary
We test whether a type of machine learning called neural networks can be used trustfully within the geosciences. We do so by challenging the networks to understand the spatial patterns of a commonly studied geoscientific phenomenon. The neural networks can correctly identify the spatial patterns, which lends confidence that similar networks can be used for more uncertain problems. The results of this study may give geoscientists confidence when using neural networks in their research.
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