Three machine learning models were investigated for the reconstruction of global surface ocean CO2
concentration. They include self-organization map (SOM), feed forward neural network (FNN), and support vector machine (SVM). Our results show that the SVM performs the best, the FNN the second, and the SOM the worst. While the SOM does not have over fitting problem, it is sensitive to data scaling and its discrete interpolation may not be good for some applications.