Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 10
Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2995-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2995-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 10
Development and technical paper
 | 
31 May 2023
Development and technical paper |  | 31 May 2023

Testing the reconstruction of modelled particulate organic carbon from surface ecosystem components using PlankTOM12 and machine learning

Anna Denvil-Sommer, Erik T. Buitenhuis, Rainer Kiko, Fabien Lombard, Lionel Guidi, and Corinne Le Quéré

Data sets

Dataset to train, validate and reconstruct POC over the global ocean for 2009–2013 based on PlankTOM12 Anna Denvil-Sommer https://doi.org/10.5281/zenodo.7324781

The global marine particle size distribution dataset obtained with the Underwater Vision Profiler 5 - version 1 R. Kiko, M. Picheral, D. Antoine, M. Babin, L. Berline, T. Biard, E. Boss, P. Brandt, F. Carlotti, S. Christiansen, L. Coppola, L. de la Cruz, E. Diamond-Riquier, X. D. de Madron, A. Elineau, G. Gorsky, L. Guidi, H. Hauss, J.-O. Irisson, L. Karp-Boss, J. Karstensen, D. Kim, R. M. Lekanoff, F. Lombard, R. M. Lopes, C. Marec, A. McDonnell, D. Niemeyer, M. Noyon, S. O'Daly, M. D. Ohman, J. L. Pretty, A. Rogge, S. Searson, M. Shibata, Y. Tanaka, T. Tanhua, J. Taucher, E. Trudnowska, J. S. Turner, A. M. Waite, and L. Stemmann https://doi.org/10.1594/PANGAEA.924375

Model code and software

AnnaDSMS/POC_PlankTOM_ML: POC global re- construction based on PlankTOM12 (POC-v2) Anna Denvil-Sommer https://doi.org/10.5281/zenodo.7326992

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Short summary
Using outputs of global biogeochemical ocean model and machine learning methods, we demonstrate that it will be possible to identify linkages between surface environmental and ecosystem structure and the export of carbon to depth by sinking organic particles using real observations. It will be possible to use this knowledge to improve both our understanding of ecosystem dynamics and of their functional representation within models.
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