Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

• Published in: Earth System Dynamics
• Main Authors: Landwehr, Sebastian, Volpi, Michele, Haumann, Alexander, Robinson, Charlotte Mary, Thurnherr, Iris, Ferracci, Valerio, Baccarini, Andrea, Thomas, Jenny, Gorodetskaya, Irina V., Tatzelt, Christian, Henning, Silvia, Modini, Robin L., Forrer, Heather J., Lin, Yajuan, Cassar, Nicolas, Simó, Rafel, Hassler, Christel S., Moallemi, Alireza, Fawcett, Sarah E., Harris, Neil R. P., Airs, Ruth, Derkani, Marzieh H., Alberello, Alberto, Toffoli, Alessandro, Chen, Gang, Rodríguez-Ros, P., Zamanillo Campos, Marina, Cortes, Pau, Xue, Lei, Bolas, Conor G., Leonard, Katherine C., Pérez-Cruz, Fernando, Walton, David, Schmale, Julia
• Other Authors: Ministerio de Economía y Competitividad (España), Agencia Estatal de Investigación (España)
• Format: Article in Journal/Newspaper
• Language: English
• Published: European Geosciences Union 2021
• Subjects: Antarctic; Austral; Southern Ocean; The Antarctic; Antarc*
• Online Access: http://hdl.handle.net/10261/258325; https://doi.org/10.5194/esd-12-1295-2021; https://doi.org/10.13039/501100011033; https://doi.org/10.13039/501100003329

75 pages, 8 figures, 3 tables, 6 appendixes, supplement https://doi.org/10.5194/esd-12-1295-2021-supplement.-- Code and data availability: The python code that was used for the analysis and to create the plots is available at https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi, 2021) and as a Renku project https://renkulab.io/projects/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi and Landwehr, 2021). For the availability of the data used in this study please refer to Tables B1 to B8 in Appendix B The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical ...