Articles | Volume 19, issue 3
Biogeosciences, 19, 845–859, 2022
https://doi.org/10.5194/bg-19-845-2022
Biogeosciences, 19, 845–859, 2022
https://doi.org/10.5194/bg-19-845-2022

Research article 10 Feb 2022

Research article | 10 Feb 2022

Reconstruction of global surface ocean pCO2 using region-specific predictors based on a stepwise FFNN regression algorithm

Guorong Zhong et al.

Data sets

Global surface ocean pCO2 product based on a stepwise FFNN algorithm Guorong Zhong https://doi.org/10.12157/iocas.2021.0022

Model code and software

Global surface ocean pCO2 product based on a stepwise FFNN algorithm Guorong Zhong https://doi.org/10.12157/iocas.2021.0022

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Short summary
A predictor selection algorithm was constructed to decrease the predicting error in the surface ocean partial pressure of CO2 (pCO2) mapping by finding better combinations of pCO2 predictors in different regions. Compared with previous research using the same combination of predictors in all regions, using different predictors selected by the algorithm in different regions can effectively decrease pCO2 predicting errors.
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