Global high-resolution monthly <i>p</i>CO<sub>2</sub> climatology for the coastal ocean derived from neural network interpolation

Articles | Volume 14, issue 19

https://doi.org/10.5194/bg-14-4545-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/bg-14-4545-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 14, issue 19

Research article

|

13 Oct 2017

Research article |

| 13 Oct 2017

Global high-resolution monthly pCO₂ climatology for the coastal ocean derived from neural network interpolation

Goulven G. Laruelle, Peter Landschützer, Nicolas Gruber, Jean-Louis Tison, Bruno Delille, and Pierre Regnier

The version 4 of the SOCAT database D. C. E. Bakker et al. http://www.socat.info/upload/SOCAT_v4.zip

The observation-based global monthly gridded sea surface pCO2 product P. Landschutzer et al. https://www.nodc.noaa.gov/ocads/oceans/SPCO2_1982_2015_ETH_SOM_FFN.html

The LDEOv2015 database T. Takahashi et al. http://cdiac.ornl.gov/oceans/LDEO_Underway_Database/

The global atmospheric reanalysis ERA-interim datasets D. P. Dee et al. http://doi.wiley.com/10.1002/qj.828

SST and SSS data S. A. Good et al. https://doi.org/10.1002/2013JC009067

The bathymetry used is the global ETOPO2 database US Department of Commerce http://www.ngdc.noaa.gov/mgg/fliers/06mgg01.html

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