Technical note: Evaluation of three machine learning models for surface ocean CO2 mapping
Other literature type
(issn: 1812-0792, eissn: 1812-0792)
Reconstructing surface ocean CO<sub>2</sub> from scarce measurements plays an important role in estimating oceanic CO<sub>2</sub> uptake. There are varying degrees of differences among the 14 models included in the Surface Ocean CO<sub>2</sub> Mapping (SOCOM) inter-comparison initiative, in which five models used neural networks. This investigation evaluates two neural networks used in SOCOM, self-organization map and feedforward neural network, and introduces a machine learning model called support vector machine for ocean CO<sub>2</sub> mapping. The technique note provides a practical guide to selecting the models.