Articles | Volume 14, issue 7
Geosci. Model Dev., 14, 4495–4508, 2021
https://doi.org/10.5194/gmd-14-4495-2021
Geosci. Model Dev., 14, 4495–4508, 2021
https://doi.org/10.5194/gmd-14-4495-2021

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 et al.

Data sets

Data for GMD 2020-152 Benjamin Toms https://doi.org/10.5281/zenodo.3968896

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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.