FN Archimer Export Format PT J TI Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition BT AF Landwehr, Sebastian Volpi, Michele Haumann, F. Alexander Robinson, Charlotte M. Thurnherr, Iris Ferracci, Valerio Baccarini, Andrea Thomas, Jenny Gorodetskaya, Irina Tatzelt, Christian Henning, Silvia Modini, Rob L. Forrer, Heather J. Lin, Yajuan Cassar, Nicolas Simó, Rafel Hassler, Christel Moallemi, Alireza Fawcett, Sarah E. Harris, Neil Airs, Ruth Derkani, Marzieh H. Alberello, Alberto Toffoli, Alessandro Chen, Gang Rodríguez-Ros, Pablo Zamanillo, Marina Cortés-Greus, Pau Xue, Lei Bolas, Conor G. Leonard, Katherine C. Perez-Cruz, Fernando Walton, David Schmale, Julia AS 1:1;2:2;3:3,4;4:5;5:6,7;6:8;7:1,13;8:9;9:10,11;10:12;11:12;12:13;13:14,15;14:16,17,18;15:16,17;16:19;17:9,20;18:13;19:14;20:8;21:21;22:22;23:23;24:22;25:13;26:19;27:19;28:19;29:24;30:25;31:11,26;32:2,27;33:4;34:1; FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:;15:;16:;17:;18:;19:;20:;21:;22:;23:;24:;25:;26:;27:;28:;29:;30:;31:;32:;33:;34:; C1 Extreme Environments Research Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Swiss Data Science Center, ETH Zurich, Switzerland Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ 08540-6654, USA British Antarctic Survey, Cambridge CB3 0ET, UK Remote Sensing and Satellite Research Group, School of Earth and Planetary Sciences, Curtin University, Kent Street, Bentley, WA 6102, Australia Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway Centre for Environmental and Agricultural Informatics, School of Water, Energy & Environment Cranfield University, College Road, Cranfield MK43 0AL, Bedfordshire, UK Swiss Polar Institute, Lausanne, Switzerland Centre for Environmental and Marine Studies, Department of Physics, University of Aveiro, Aveiro, Portugal Laboratory of Cryospheric Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Leibniz Institute for Tropospheric Research, Leipzig, Germany Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland Department of Oceanography, University of Cape Town, 7701, Cape Town, South Africa Earth, Ocean and Atmospheric Science Department, Florida State University, Tallahassee, FL 32306, USA Division of Earth and Climate Sciences, Nicholas School of the Environment, Duke University, Durham, NC 27708, USA Laboratoir des sciences de l'environnement marin, University of Brest, Brest, France Duke Kunshan University, Kunshan, Suzhou, Jiangsu, China Institut de Ciències del Mar (ICM-CSIC), Barcelona, Catalonia, Spain Department F.-A. Forel for Environmental and Aquatic Sciences, University of Geneva, Geneva, Switzerland Plymouth Marine Laboratory, Plymouth PL1 3DH, UK Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, VIC 3010, Australia Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan Department of Chemistry, College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA ITOPF Ltd., London EC1Y 1DT, UK Cooperative Institute for Research in Environmental Sciences at the University of Colorado, Boulder, CO 80309, USA Department of Computer Science at ETH Zurich, Zurich, Switzerland C2 EPFL, SWITZERLAND ETH ZURICH, SWITZERLAND UNIV PRINCETON, USA BRITISH ANTARCTIC SURVEY (BAS), UK UNIV CURTIN, AUSTRALIA ETH ZURICH, SWITZERLAND UNIV BERGEN, NORWAY UNIV CRANFIELD, UK SWISS POLAR INST, SWITZERLAND UNIV AVEIRO, PORTUGAL EPFL, SWITZERLAND LEIBNIZ INST TROPOSPHER RES, GERMANY PAUL SHERRER INST, SWITZERLAND UNIV CAPE TOWN, SOUTH AFRICA UNIV FLORIDA STATE, USA UNIV DUKE, USA UBO, FRANCE DUKE KUNSHAN UNIVERSITY, CHINA ICM CSIC, SPAIN UNIV GENEVA, SWITZERLAND PML, UK UNIV MELBOURNE, AUSTRALIA UNIV TOKYO, JAPAN UNIV NEW YORK, USA ITOPF LTD., UK UNIV COLORADO, USA ETH ZURICH, SWITZERLAND UM LEMAR IN WOS Cotutelle UMR DOAJ copubli-europe copubli-int-hors-europe copubli-sud IF 5.458 TC 10 UR https://archimer.ifremer.fr/doc/00739/85133/90100.pdf https://archimer.ifremer.fr/doc/00739/85133/90101.pdf https://archimer.ifremer.fr/doc/00739/85133/90541.pdf https://archimer.ifremer.fr/doc/00739/85133/90542.pdf LA English DT Article AB 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 gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question. PY 2021 PD NOV SO Earth System Dynamics SN 2190-4979 PU Copernicus GmbH VL 12 IS 4 UT 000723912200001 BP 1295 EP 1369 DI 10.5194/esd-12-1295-2021 ID 85133 ER EF