Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 30, issue 2
Articles | Volume 30, issue 2
https://doi.org/10.5194/npg-30-195-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-30-195-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 2
Research article
 | 
28 Jun 2023
Research article |  | 28 Jun 2023

Data-driven methods to estimate the committor function in conceptual ocean models

Valérian Jacques-Dumas, René M. van Westen, Freddy Bouchet, and Henk A. Dijkstra

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Latest update: 26 Dec 2024
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Short summary
Computing the probability of occurrence of rare events is relevant because of their high impact but also difficult due to the lack of data. Rare event algorithms are designed for that task, but their efficiency relies on a score function that is hard to compute. We compare four methods that compute this function from data and measure their performance to assess which one would be best suited to be applied to a climate model. We find neural networks to be most robust and flexible for this task.
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