Biogeochemistry and Physics of the Southern Ocean-Atmosphere System Explored With Data Science

• Main Authors: 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
• Format: Text
• Language: English
• Published: 2021
• Subjects: Antarctic; Austral; Southern Ocean; The Antarctic; Antarc*; Sea ice
• Online Access: https://doi.org/10.5194/esd-2021-16; https://esd.copernicus.org/preprints/esd-2021-16/

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 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 dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve 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, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a 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. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. 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; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as 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 the majority of latent variables, highlighting their importance for a large variety of processes and 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. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.