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Biogeosciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/bg-2017-64
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
24 Feb 2017
Review status
This discussion paper is under review for the journal Biogeosciences (BG).
Global high resolution monthly pCO2 climatology for the coastal ocean derived from neural network interpolation
Goulven G. Laruelle1, Peter Landschützer2, Nicolas Gruber3, Jean-Louis Tison1, Bruno Delille4, and Pierre Regnier1 1Department Geoscience, Environment & Society (DGES), Université Libre de Bruxelles, Belgium
2Max Planck Institute for Meteorology, Hamburg, Germany
3Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Switzerland
4Unité d'Oceanographie Chimique, Astrophysics, Geophysics and Oceanography department, University of Liège, Belgium
Abstract. In spite of the recent strong increase in the number of measurements of the partial pressure of CO2 in the surface ocean (pCO2), the air-sea CO2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled both in time and space, and of surface pCO2 exhibiting much higher temporal and spatial variability in these regions compared to the open ocean. Here, we use a modified version of a two-step artificial neural network method (SOM-FFN, Landschützer et al., 2013) to interpolate the pCO2 data along the continental margins with a spatial resolution of 0.25 degrees and with monthly resolution from 1998 until 2014. The most important modifications compared to the original SOM-FFN method are (i) the much higher spatial resolution, and (ii) the inclusion of sea-ice as a predictor of pCO2. The validity of our interpolation, both in space and time, is assessed by comparing the SOM-FFN outputs with pCO2 measurements extracted from the SOCATv3.0 and LDVEO2014 datasets. The new coastal pCO2 product confirms a previously suggested general meridional trend of the annual mean pCO2 in all the continental shelves with high values in the tropics and dropping to values beneath those of the atmosphere at higher latitudes. But significant differences in the seasonality across the ocean basins exist. The shelves of the western and northern Pacific, as well as the shelves in the temperate North Atlantic display particularly pronounced seasonal variations in pCO2, while the shelves in the southeastern Atlantic and in the South Pacific reveal a much smaller seasonality. Overall, the seasonality in shelf pCO2 cannot solely be explained by temperature-induced changes in solubility, but are also the result of seasonal changes in circulation, mixing, and biological productivity. Finally, thanks to this product having been extended to cover open ocean areas as well, it can be readily merged with existing global open ocean products to produce a true global perspective of the spatial and temporal variability of surface ocean pCO2.

Citation: Laruelle, G. G., Landschützer, P., Gruber, N., Tison, J.-L., Delille, B., and Regnier, P.: Global high resolution monthly pCO2 climatology for the coastal ocean derived from neural network interpolation, Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-64, in review, 2017.
Goulven G. Laruelle et al.
Goulven G. Laruelle et al.
Goulven G. Laruelle et al.

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