Observation system simulation experiments in the Atlantic Ocean for enhanced surface ocean p CO 2 reconstructions

To derive an optimal observation system for surface ocean p CO 2 in the Atlantic Ocean and the Atlantic sector of the Southern Ocean, 11 observation system simulation experiments (OSSEs) were completed. Each OSSE is a feedforward neural network (FFNN) that is based on a different data distribution and provides ocean surface p CO 2 for the period 2008–2010 with a 5 d time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships, Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical–biogeochemical global ocean model with 0.25 ∘ nominal resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO 2 Atlas (SOCAT) and to improve the accuracy of ocean surface p CO 2 reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the Southern Hemisphere with biogeochemical ARGO floats corresponding to least 25 % of the density of active floats (2008–2010) (OSSE 10) would significantly improve the p CO 2 reconstruction and reduce the bias of derived estimates of sea–air CO 2 fluxes by 74 % compared to ocean model outputs.