Full‐Depth Reconstruction of Long‐Term Meridional Overturning Circulation Variability From Satellite‐Measurable Quantities via Machine Learning

Full‐Depth Reconstruction of Long‐Term Meridional Overturning Circulation Variability From Satellite‐Measurable Quantities via Machine Learning

Abstract The meridional overturning circulation (MOC) plays a crucial role in the global distribution of heat, carbon, and other climate‐relevant tracers. Monitoring the evolution of MOC is essential for understanding climate variability, yet direct MOC observations are sparse and geographically lim...

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Bibliographic Details
Main Authors: Huaiyu Wei, Kaushik Srinivasan, Andrew L. Stewart, Aviv Solodoch, Georgy E. Manucharyan, Andrew McC. Hogg
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2025-07-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
meridional overturning circulation
machine learning
neural network
satellite observation
physical oceanography
ocean bottom pressure
Online Access:https://doi.org/10.1029/2024MS004915
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https://doi.org/10.1029/2024MS004915

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