The interannual variability of the sea ice in the Southern Ocean and its evolution projected for the end of the 21st century are investigated using observations and different types of models. First of all, none of the known atmospheric modes of variability are able to explain much of the total sea ice extent variability in the Southern Ocean. However, they have large influences on the local and regional scales. In particular, the response of the sea ice to the Southern Annular Mode is characterized by a dipole between the Ross Sea and the region around the Antarctic Peninsula caused by a low pressure anomaly in the Amundsen Sea in high SAM-index years. Secondly, the sea ice extent in the different regions seems to be mostly uncorrelated, showing that the total sea ice cover cannot be seen as a single entity, but merely as a combination of regional covers. Finally, it is shown why the projected distribution of sea ice is not a simple extrapolation of the current sea ice trends. The mechanisms responsible for the regional variability of the future sea-ice extents are discussed.

The interannual variability of the sea ice in the Southern Ocean and its evolution projected for the end of the 21st century are investigated using observations and different types of models. First of all, none of the known atmospheric modes of variability are able to explain much of the total sea ice extent variability in the Southern Ocean. However, they have large influences on the local and regional scales. In particular, the response of the sea ice to the Southern Annular Mode is characterized by a dipole between the Ross Sea and the region around the Antarctic Peninsula caused by a low pressure anomaly in the Amundsen Sea in high SAM-index years. Secondly, the sea ice extent in the different regions seems to be mostly uncorrelated, showing that the total sea ice cover cannot be seen as a single entity, but merely as a combination of regional covers. Finally, it is shown why the projected distribution of sea ice is not a simple extrapolation of the current sea ice trends. The mechanisms responsible for the regional variability of the future sea-ice extents are discussed.

The Southern Ocean plays a pre-eminent role in the global carbon-climate system. Model studies show that since the start of the preindustrial era, the region has absorbed about 75% of excess heat and 50% of the oceanic uptake and storage (42±5 PgC) of anthropogenic CO2 emissions. However, due to the spatial and seasonal sparseness of the Southern Ocean CO2 observations (biased toward summer), this role is poorly understood. The seasonal sampling biases have hampered observation-based reconstructions of partial pressure of CO2 at the surface ocean (pCO2) using machine learning (ML) and contributed to the convergence of the root mean squared errors (RMSEs) of ML methods to a common limit known in the literature as the “wall”. The hypothesis here is that addressing the critical missing sampling scale will get the community reconstructions of pCO2 “over the wall”. In this study, I explore the sensitivity of pCO2 reconstructions to these observational scale gaps. Using a scale-sensitive sampling strategy means adopting a sampling strategy which addresses these observational limitations including intra-seasonal as well as seasonal sampling aliases in high eddy kinetic energy and mesoscale-intensive regions. In increasing CO2 sampling efforts in the Southern Ocean using autonomous sampling platforms such as floats, Wave Gliders and Saildrones, the community has tried to answer this problem, but the effectiveness of these efforts has not yet been tested. This study aims to do this evaluation and advance our understanding of the sampling scale sensitivities of surface ocean pCO2 reconstructions from machine-learning techniques and contribute – through a scale-sensitive sampling strategy of observing platforms in the Southern Ocean – to breaking through the proverbial “wall”. This aim was achieved through a series of observing system simulation experiments (OSSEs) applied to a forced mesoscale-resolving (±10km) ocean NEMO-PISCES physics-biogeochemistry model with daily output. In addition to underway ships, the sampling scales of the autonomous sampling platforms such as Floats, WaveGliders and Saildrones, on pCO2 reconstructions were investigated in this series of OSSEs. The primary results showed that two sampling scales, which Saildrones are able to address, are required to improve the RMSE scores of machine-learning techniques and then reduce uncertainties and biases in pCO2 reconstructions. The two sampling scales include (1) the seasonal cycle of the meridional gradients and (2) the intra-seasonal variability. Based on the impacts of these two sampling scales on the RMSE scores and biases, it wasfound that resolving the seasonal cycle of the meridional gradient is the first-order requirement while resolving the intra-seasonal variability is the second. Applying the second-order requirement in the whole Southern Ocean to explore the sensitivity of the clustering choice to the two-step pCO2 reconstruction (clustering- regression). It was found that using an ensemble of clustering methods in this two-step reconstruction performs far much better than using a clustering method. Using these findings, I proposed an observational strategy that is viable and strengthens the limitations in existing underway SOCAT ship- and SOCCOM float-based reconstructions of surface ocean pCO2. More specifically, I proposed a hybrid scale-sensitive sampling strategy for the whole Southern Ocean by integrating underway ships with Saildrones on winter lines. The analysis of these multiple OSSEs indicates that improving the pCO2 reconstructions requires scalesensitive data to supplement the underway ship-based observations gridded in the SOCAT product. It was also found that scale-sensitive data consisting of high-resolution observations ( 1 day) extending over the seasonal cycle and capturing the pCO2 meridional gradients results in breaking through the proverbial “wall”. These findings will contribute to an accurate mean annual global carbon budget which is critical for the trend of the ocean sink feedback on global warming as well as ocean acidification.

Iron plays an important role in the regulation of biological productivity and the carbon cycle of the Southern Ocean. Recently, synchrotron X-ray spectromicroscopy revealed that molar iron to silicon (Fe:Si) ratios in living diatom samples collected from surface waters and ice in the coastal Antarctic are significantly higher than reported dissolved Fe:Si ratios of Circumpolar Deep Water. Upwelling of Circumpolar Deep Water is a dominant source of iron and silicon to coastal Southern Ocean surface waters. Thus with higher Fe:Si ratios, diatom production preferentially depletes dissolved iron relative to silicon, potentially contributing to perennial iron limitation in this region. Combining diatom and water column dissolved iron and silicon datasets with a simple inverse box model we estimate the regional coupled iron and silicon budget. Upwelling of subsurface waters cannot supply enough iron to balance the loss due to diatom production, which indicates that the closed budget requires additional iron sources or additional methods of silicon removal. To evaluate the ecological and biogeochemical impacts of the high Fe:Si ratio, a three-dimensional ocean biogeochemistry and ecosystem model is used to simulate the sensitivity of ocean productivity and nutrient cycling to a wide range of Fe:Si ratios in modeled diatoms. The Fe:Si ratio of diatoms regulates the surface iron and macronutrient distribution in vast regions beyond the Southern Ocean. A globally higher Fe:Si ratio strongly decreases subpolar productivity and is partially compensated by the moderate increase in subtropical productivity. Our results indicate that the Fe:Si ratio of diatoms has a global impact controlling the distribution of both micro- and macro-nutrients and associated biological production.

No description available.

No description available.

The Southern Ocean (SO) is a critical component in the global ocean conveyor. As the only conduit linking the Atlantic, Indian and Pacific Oceans, as well as an important region of upwelling and water mass formation, it is thought to have played a key role in modulating Earth’s past climate. Changes in the circulation of SO deep and bottom waters over the last 1.5 million years are investigated using stable carbon isotope $δ^{13}C$ measurements made on the tests of the benthic foraminfer Cibicidoides ($δ^{13}C_{b}$), and the rare earth element concentrations and Neodymium isotope ($ɛ_{Nd}$) values of marine sediments and their authigenic ferromanganese coatings. Being a proxy for past seawater nutrient contents, $δ^{13}C_{b}$ provides important insights into both past ocean circulation and the potential storage of remineralised organic carbon within the deep ocean, while simultaneously providing information on the past ventilation state of the deep ocean interior. As seawater $ɛ_{Nd}$ remains unaffected by biological fractionation or air-sea exchange processes, reconstructions of past deep and bottom water $ɛ_{Nd}$ provides a tool with which to study past changes in the circulation and mixing of these water masses. A suite of previously published late Holocene (0-6 ka) and Last Glacial Maximum (LGM; 18-24 ka) $δ^{13}C_{b}$ data are used alongside newly acquired $δ^{13}C_{b}$ data from the Amundsen Sea in the eastern Pacific sector of the SO to investigate past changes in the pattern of circum-Antarctic seawater carbon isotope composition. The $δ^{13}C$ signature of deep and bottom waters was much more heterogenous during the LGM than the late Holocene, with negative $δ^{13}C$ excursions occurring within the Atlantic and Indian sectors of the SO below c. 2-3 km water depth. Some of this negative $δ^{13}C$ signal was advected through the SO to the Pacific sector, but this appears to have been restricted by bathymetric barriers within the SO. New $δ^{13}C_{b}$ data spanning the last 800 ka from the Amundsen Sea are presented and suggest differing modes of bottom water formation in the Atlantic vs Pacific sectors of the SO during glacial periods of the last 800 ka. An authigenic $ɛ_{Nd}$ record measured on sediments from a core located in the deep Indian Ocean is used to investigate the palaeocirculation history of modified Circumpolar Deep Water (mCDW) within the Indian Ocean during the last 1.5 million years. Shifts towards more radiogenic $ɛ_{Nd}$ values during glacial periods are interpreted as reflecting a decreased entrainment of deep waters sourced in the North Atlantic (Northern Component Water, NCW) within CDW, which led to a reduced advection of an unradiogenic $ɛ_{Nd}$ NCW signal to the core site. $ɛ_{Nd}$ and REE measurements made on sediments from two cores located on the Pacific-Antarctic Ridge in the western Pacific sector of the SO (to the north of the Ross Sea Embayment) are used to reconstruct the bottom water palaeocirculation in this region across the last 540 ka. The proportion and $ɛ_{Nd}$ signature of Ross Sea Bottom Water (RSBW) bathing these core sites has fluctuated throughout the last 540 ka. These fluctuations suggest the rate and location of bottom water formation within the Ross Sea, and the supply of terrigenous material with radiogenic $ɛ_{Nd}$ values with which to isotopically `labelled' RSBW, may have changed in the past.

We use a numerical ocean model to evaluate the hypothesis that the continental shelves are significant sources of dissolved iron to the Southern Ocean. We simulate the distribution of passive tracers released from the 18 different continental shelf regions of the extra-tropical southern hemisphere oceans using an offline, eddy-permitting transport model. The circulation fields are taken from the Southern Ocean State Estimate, and we only simulate the transport of inert tracers focusing on the physical transport pathways. The resulting tracer fields are then compared with the remotely sensed ocean color data, revealing a remarkable resemblance between the distributions of shelf-source tracers and the climatological surface chlorophyll-a concentrations. We further analyze the spatial pattern of simulated tracer fields in relation to satellite ocean color data. Dynamic ocean features such as the Southern Ocean fronts and coastal waters are reflected in both the tracer model and the observed biological productivity. Our results support the overall importance of continental shelves as a potential source region for dissolved iron. The relative importance of different shelf regions is found to vary significantly depending on the relevant circulation features.

Magister Scientiae (Biodiversity and Conservation Biology) / 2022-01-31

<p>The Arctic Ocean and Western Antarctic Peninsula (WAP) are the fastest warming regions on the planet and are undergoing rapid climate and ecosystem changes. Until we can fully resolve the coupling between biological and physical processes we cannot predict how warming will influence carbon cycling and ecosystem function and structure in these sensitive and climactically important regions. My dissertation centers on the use of high-resolution measurements of surface dissolved gases, primarily O2 and Ar, as tracers or physical and biological functioning that we measure underway using an optode and Equilibrator Inlet Mass Spectrometry (EIMS). Total O2 measurements are common throughout the historical and autonomous record but are influenced by biological (net metabolic balance) and physical (temperature, salinity, pressure changes, ice melt/freeze, mixing, bubbles and diffusive gas exchange) processes. We use Ar, an inert gas with similar solubility properties to O2, to devolve distinct records of biological (O2/Ar) and physical (Ar) oxygen. These high-resolution measurements that expose intersystem coupling and submesoscale variability were central to studies in the Arctic Ocean, WAP and open Southern Ocean that make up this dissertation. </p><p>Key findings of this work include the documentation of under ice and ice-edge blooms and basin scale net sea ice freeze/melt processes in the Arctic Ocean. In the WAP O2 and pCO2 are both biologically driven and net community production (NCP) variability is controlled by Fe and light availability tied to glacial and sea ice meltwater input. Further, we present a feasibility study that shows the ability to use modeled Ar to derive NCP from total O2 records. This approach has the potential to unlock critical carbon flux estimates from historical and autonomous O2 measurements in the global oceans.</p> / Dissertation