Technical note: Evaluation of three machine learning models for surface ocean CO₂ mapping

Abstract. Reconstructing surface ocean CO₂ from scarce measurements plays an important role in estimating oceanic CO₂ uptake. There are varying degrees of differences among the 14 models included in the Surface Ocean CO₂ Mapping (SOCOM) inter-comparison initiative, in which five models used neural networks. This investigation evaluates two neural networks used in SOCOM, self-organizing maps and feedforward neural networks, and introduces a machine learning model called a support vector machine for ocean CO₂ mapping. The technique note provides a practical guide to selecting the models.