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Reconstructing surface ocean CO2 from scarce measurements plays animportant role in estimating oceanic CO2 uptake. There are varyingdegrees of differences among the 14 models included in the Surface OceanCO2 Mapping (SOCOM) inter-comparison initiative, in which five modelsused neural networks. This investigation evaluates two neural networks usedin SOCOM, self-organizing maps and feedforward neural networks, andintroduces a machine learning model called a support vector machine for oceanCO2 mapping. The technique note provides a practical guide to selectingthe models

Technical note: Evaluation of three machine learning models for surface ocean CO&lt;sub&gt;2&lt;/sub&gt; mapping

Technical note: Evaluation of three machine learning models for surface ocean CO<sub>2</sub> mapping