Code for ML reconstruction of surface ocean pCO2 using the Large Ensemble Testbed

This repository contains code used for the study "Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling" (Heimdal et al., 2023, https://doi.org/10.5194/bg-2023-160). In this paper, we reconstruct surface ocean pCO2 using the La...

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Bibliographic Details
Main Authors: Heimdal, Thea H., McKinley, Galen, Sutton, Adrienne, Fay, Amanda, Gloege, Lucas, BENNINGTON, VAL
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2024
Subjects:
Southern Ocean
Online Access:https://doi.org/10.5281/zenodo.10966977
Description
Summary:This repository contains code used for the study "Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling" (Heimdal et al., 2023, https://doi.org/10.5194/bg-2023-160). In this paper, we reconstruct surface ocean pCO2 using the Large Ensemble Testbed (Gloege et al., 2021) and the pCO2-Residual method (Bennington et al. (2022), and test the effect of additional sampling in the Southern Ocean.

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