Bridging observations, theory and numerical simulation of the ocean using machine learning

Bridging observations, theory and numerical simulation of the ocean using machine learning

Progress within physical oceanography has been concurrent with the increasing sophistication of tools available for its study. The incorporation of machine learning (ML) techniques offers exciting possibilities for advancing the capacity and speed of established methods and for making substantial an...

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Bibliographic Details
Main Authors: Maike Sonnewald, Redouane Lguensat, Daniel C Jones, Peter D Dueben, Julien Brajard, V Balaji
Format: Article
Language:English
Published: IOP Publishing 2021-01-01
Series:Environmental Research Letters
Subjects:
ocean science
physical oceanography
observations
theory
modelling
supervised machine learning
Online Access:https://doi.org/10.1088/1748-9326/ac0eb0

Internet

https://doi.org/10.1088/1748-9326/ac0eb0

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