The eMLR(C*) Method to Determine Decadal Changes in the Global Ocean Storage of Anthropogenic CO 2

The determination of the decadal change in anthropogenic CO 2 in the global ocean from repeat hydrographic surveys represents a formidable challenge, which we address here by introducing a seamless new method. This method builds on the extended multiple linear regression (eMLR) approach to identify the anthropogenic CO 2 signal, but in order to improve the robustness of this method, we fit C ∗ rather than dissolved inorganic carbon and use a probabilistic method for the selection of the predictors. In order to account for the multiyear nature of the surveys, we adjust all C ∗ observations of a particular observing period to a common reference year by assuming a transient steady state. We finally use the eMLR models together with global gridded climatological distributions of the predictors to map the estimated change in anthropogenic CO 2 to the global ocean. Testing this method with synthetic data generated from a hindcast simulation with an ocean model reveals that the method is able to reconstruct the change in anthropogenic CO 2 with only a small global bias (<5%). Within ocean basins, the errors can be larger, mostly driven by changes in ocean circulation. Overall, we conclude from the model that the method has an accuracy of retrieving the column integrated change in anthropogenic CO 2 of about ±10% at the scale of whole ocean basins. We expect that this uncertainty needs to be doubled to about ±20% when the change in anthropogenic CO 2 is reconstructed from observations.