Observation System Simulation Experiments in the Atlantic Ocean for enhanced surface ocean pCO2 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 eleven Observation System Simulation Experiments (OSSEs) were completed. Each OSSE is a Feed-Forward Neural Network (FFNN) that is based on a different data distributi...
| Main Authors: | , , |
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| Format: | Text |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/os-2021-17 https://os.copernicus.org/preprints/os-2021-17/ |
| Summary: | To derive an optimal observation system for surface ocean p CO 2 in the Atlantic Ocean and the Atlantic sector of the Southern Ocean eleven Observation System Simulation Experiments (OSSEs) were completed. Each OSSE is a Feed-Forward 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 day time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships (VOS), 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. |
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