Depth to sea floor and sea ice thickness data measured at various locations around the Vestfold Hills, Davis station, East Antarctica, during the 2018-19 austral summer. Depth to sea floor and sea ice thickness measures in meters obtained using a weighted tape measure deployed through a hole (5 cm) drilled in the sea ice. Sea ice thickness was determined by snagging the weight on the underside edge of the ice hole as the tape measure was retreived.

During voyage 1 of 1985, sixteen ice cores were drilled from sea ice. Details from those cores include the position they were drilled, length of the core, percentage of the core that was frazil ice, and comments on the state of the core, or observations of the ice make-up. Physical records are archived at the Australian Antarctic Division.

Diatom data from IN2017_V01: These data were generated by Amy Leventer (aleventer@colgate.edu) and undergraduate students at Colgate University, including Isabel Dove, Meghan Duffy, and Meaghan Kendall. All questions regarding the specifics of these data should be directed to Amy Leventer. These data are based on samples collected during research cruise IN2017_V01 of the RV Investigator, co-chief scientists, Leanne Armand and Phil O’Brien. The IN2017-V01post-cruise report is available through open access via the e-document portal through the ANU library. https://openresearch-repository.anu.edu.au/handle/1885/142525 The document DOI: 10.4225/13/5acea64c48693 The preferred citation is: L.K. Armand, P.E. O’Brien and On-board Scientific Party. 2018. Interactions of the Totten Glacier with the Southern Ocean through multiple glacial cycles (IN2017-V01): Post-survey report, Research School of Earth Sciences, Australian National University: Canberra, http://dx.doi.org/10.4225/13/5acea64c48693 Samples for diatom analysis were collected on board ship immediately after core recovery. Samples were dried in an oven at 50 degrees C prior to analytical work. Quantitative diatom slides were prepared according to the settling technique of Warnock and Scherer (2014). Cover slips were adhered to the slides using Norland Optical Adhesive #61. Slides were observed under Olympus CX31, BX50 and BX60, and Zeiss Primo Star light microscopes, using a 100X oil immersion objective for a total magnification of 1000X. A minimum of 400 valves or 10 transects was counted for each slide, depending on the absolute diatom abundance. Interglacial samples were relatively diatom-rich, consequently counts of 400 specimens were possible. However, most glacial samples were diatom-poor, making it very difficult and time-consuming to count 400 specimens. Under these conditions, 10 transects were counted, as has been done in previous studies of sediments with very low diatom concentrations (Rebesco et al., 2014). Valves were only counted if greaster than 50% complete. Diatoms were identified to species level when possible (Crosta et al., 2005; Armand et al., 2005; Cefarelli et al., 2010). Occurrences of biostratigraphic markers were noted and tallied concurrently. Species were considered extinct when observed stratigraphically higher than extinction boundaries as identified by Cody et al. (2008). Station_core Longitude Latitude A005_KC02_PC01 115.623 -64.471 A006_KC03 115.043 -64.463 A042_KC14 116.6403 -64.5387 C012_KC04_PC05 119.3012 -64.675 C013_KC05 119.0183 -64.6538 C015_KC06 118.696 -64.729 C018_KC07 118.498 -64.401 C020_KC08 119.739 -64.794 C022_KC11 120.049 -65.1313 C025_KC12_PC08 120.8635 -64.9538 C038_KC13 119.1035 -64.4828 Armand, L.K., X. Crosta, O. Romero, J. J. Pichon (2005), The biogeography of major diatom taxa in Southern Ocean sediments: 1. Sea ice related species, Paleogeography, Paleoclimatology, Paleoecology, 223, 93-126. Cefarelli, A.O., M. E. Ferrario, G. O. Almandoz, A. G. Atencio, R. Akselman, M. Vernet (2010), Diversity of the diatom genus Fragilariopsis in the Argentine Sea and Antarctic waters: morphology, distribution and abundance, Polar Biology, 33(2), 1463-1484. Cody, R., R. H. Levy, D. M. Harwood, P. M. Sadler (2008), Thinking outside the zone: High-resolution quantitative diatom biochronology for the Antarctic Neogene, Palaeogeography, Palaeoclimatology, Palaeoecology, 260, 92-121, doi:10.1016/j.palaeo.2007.08.020 Crosta, X., O. Romero, L. K. Armand, J. Pichon (2005), The biogeography of major diatom taxa in Southern Ocean sediments: 2. Open ocean related species, Palaeogeography, Palaeoclimatology, Palaeoecology, 223, 66-92. Rebesco, M., E. Domack, F. Zgur, C. Lavoie, A. Leventer, S. Brachfeld, V. Willmott, G. Halverson, M. Truffer, T. Scambos, J. Smith, E. Pettit (2014), Boundary condition of grounding lines prior to collapse, Larson-B Ice Shelf, Antarctica, Science, 345, 1354-1358. Warnock, J. P., R. P. Scherer (2014), A revised method for determining the absolute abundance of diatoms, J. Paleolimnol., doi:10.1007/s10933-014-9808-0 These data were collected to provide paleoceanographic and biostratigraphic information. Amy Leventer, Isabel Dove, Meghan Duffy, and Meaghan Kendall unpublished data

AM01 borehole drilled January 2002. Data collected in series of files over a period of 2 days during production of borehole. Consult Readme file for detail of data files and formats.

AM02 borehole drilled December 2000. Several caliper profiles obtained as a 'first look' at borehole closure rates. Consult Readme file for detail of data files and formats.

Radiolarian data from IN2017_V01 These data were generated by Kelly-Anne Lawler (corresponding author, kelly-anne.lawler@anu.edu.au) with taxonomic assistance from Dr Giuseppe Cortese. These data are based on samples collected during voyage IN2017_V01 of the RV Investigator, co-chief scientists, Leanne Armand and Phil O’Brien. The IN2017-V01 post-cruise report is available through open access via the e-document portal through the ANU library. https://openresearch-repository.anu.edu.au/handle/1885/142525 The preferred citation is: L.K. Armand, P.E. O’Brien and On-board Scientific Party. 2018. Interactions of the Totten Glacier with the Southern Ocean through multiple glacial cycles (IN2017-V01): Post-survey report, Research School of Earth Sciences, Australian National University: Canberra, http://dx.doi.org/10.4225/13/5acea64c48693 Samples for radiolarian analysis were collected on board immediately after core recovery. Samples were air dried at ambient temperature (~21 degrees C), and their processing in preparation for microscopy was based on the method of Cortese and Prebble (2015). Cover slips were adhered to the slides using Canada Balsam and slides were observed using Olympus BH-2 inverted light microscope at up to 400x magnification. Slides were first counted to determine absolute radiolarian abundance (ARA) and, for samples where ARA was high enough, more than 400 individuals were identified per sample to species/subspecies or genus level. Taxonomic nomenclature used while preparing the dataset was per Lazarus et al. (2015) with additional clarification sought from the World Register of Marine Species (WoRMS Editorial Board, 2018) and radiolaria.org (radiolaria.org, 2018). Station_core Longitude Latitude C013_KC05 119.0183 -64.6538 C022_KC11 120.049 -65.1313 These data were collected to provide palaeoceanographic information. Cortese, G., and Prebble, J. (2015). A radiolarian-based modern analogue dataset for palaeoenvironmental reconstructions in the southwest Pacific. Marine Micropaleontology, 118, 34-49. WoRMS Editorial Board, (2018). World Register of Marine Species. Available from http://www.marinespecies.org at VLIZ. Lazarus, D. B., Suzuki, N., Caulet, J.-P., Nigrini, C., Goll, I., Goll, R., Dolven, J.K. Diver, P. and Sanfilippo, A., (2015). An evaluated list of Cenozic-Recent radiolarian species names (Polycystinea), based on those used in the DSDP, ODP and IODP deep-sea drilling programs. Zootaxa, 3999(3), 310-333. radiolaria.org, 2018. radiolaria.org, (http://www.radiolaria.org/) Kelly-Anne Lawler and Giuseppe Cortese unpublished data

Note - these data should be used with caution. The chief investigator for the dataset has indicated that a better quality dataset exists, but the AADC have been unable to attain it for archive. In addition to snow pits dug by other groups, several snow pits were dug at IMB/AWS deployment sites and at snow mast sites. Dates, locations, personnel, and purpose are listed in Table 1. Many of the data files include the raw weight measurements including the mass of the snow density shovel along with the snow. This needs to be corrected using the snow density shovel weight appropriate to each pit. Table 1 Snow Pits (comma separated) Date,Location,Personnel,Comments 2012-10-04,Floe 3 radiometer site,Katie,Full-depth snow density profile for evaluation of SMP data 2012-10-08,Floe 4 drift mast,Katie,Full-depth snow density profile for evaluation of SMP data 2012-10-14,Floe 6 buoy 1,Katie,Full-depth snow density profile for evaluation of SAMS WHOI-3 data 2012-10-14,Floe 6 buoy 2,Katie,Full-depth snow density profile for evaluation of SAMS WHOI-5 data 2012-10-20,Floe 7 drift mast,Ted,Snow pit to characterise snow at ice station 7 drift mast site 2012-10-23,Floe 7 drift mast,Katie,Full-depth snow density profile for evaluation of SMP data 2012-10-28,Helicopter buoy install,Petra,Snow pit for evaluation of SAMS- WHOI-4 buoy data 2012-10-29,Helicopter buoy install,Petra,Snow pit for evaluation of SAMS- TASI2-1 buoy data 2012-11-01,Floe 8,Ted,Snow pit for evaluation of WHOI-2 buoy data 2012-11-04,Floe 6 buoy re-install,Ted,Snow pit for evaluation of WHOI-6 buoy data

Zooplankton were collected during the winter-spring transition during two cruises of the Aurora Australis: SIPEX in 2007 and SIPEX II in 2012. As part of the collections sea ice cores were collected to describe the ice habitat during the period of zooplankton collections. Ice cores were taken with a 20 cm diameter SIPRE corer and sectioned in the field with an ice core. Temperature was measured in the section using a spike thermometer and slivers of each section were melted without filtered water to record salinity. The remainders of each section were melted at 4oC in filtered seawater and the melted water was used to measure chlorophyll a concentration, and meiofauna species and abundance. Meiofauna were counted and identified using a Leica M12 microscope: to species in most cases and down to stage during 2012.

Overview of the project and objectives: Sea-ice phytoplankton is significantly enriched in 13C (delta 13C-POC) compared to pelagic phytoplankton in adjacent open waters because of carbon limitation in the brine pockets and due to physiological properties such as the presence of Carbon Concentrating Mechanisms (CCM) and/or the uptake of bicarbonate (HCO3-). Melting of sea-ice with release of sea-ice phytoplankton occurs during the growth season, so these isotopically heavy particles, if sinking out of the surface waters, can be expected to be found deeper in the water column. One hypothesis is that the natural carbon isotopic signal of brassicasterol (phytosterol, mainly diatom indicator) in the south Antarctic Bottom Water (AABW), a water mass which is influenced by the Seasonal Ice Zone (SIZ), is enriched compared to northern deep waters signal due to an enhanced contribution of sea-ice diatoms. The objective of this dataset acquisition is to gain information on the delta 13C signal of brassicasterol in sea-ice diatoms and further estimate the contribution of sea-ice algae release in the Southern Ocean biological pump. In the course of the expedition, a second choice has been done to look at the presence of particulate barium in the sea-ice. In the open ocean, presence of particulate barium in the mesopelagic layer is an indicator of remineralisation process. The main idea is that marine snow composed of detritical organic matter (aggregates, faecal pellets, etc.) provides micro-environment favorable for precipitation of excess Barium or Baxs (total particulate Ba minus the lithogenic part; mainly constituted of barite crystals, BaSO4): is there such Baxs components in the sea-ice? Methodology and sampling strategy: Sampling strategy follows ice stations deployment via Bio ice-core type. Most of the time we worked close to / directly on the Trace Metal site following precautions concerning TM sampling (clean suits etc.). When we worked close to the TM site, precautions were not such important because we don't need the same drastic precautions for our own sampling. We work together because we want to propose a set of data which helps to characterize the system of functioning in close relation with TM availability (for that, sampling location have to be as close as possible). Ice melted from ice-core sections (see attached files for more details) is filtered on precombusted GF-F filters (0.7 microns porosity) and filters are stored at -20 degrees C. For particulate Barium sampling, same protocol but filtration on PC filters 0.4 microns, dry over night and store at ambient temperature. At home laboratory (VUB, Brussels, Belgium), sterols samples are analysed via Gas Chromatography - Mass Spectrometer (GC-MS) and Gas Chromatography-combustion column-Isotope Ratio Mass Spectrometer (GC-c-IRMS) after chemical treatment. Barium sample are analysed via Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES).

This dataset is an annual reconstruction of the Interdecadal Pacific Oscillation (IPO), a decadal-scale mode of variability in the Pacific Ocean which has climate impacts across the Pacific Basin. This data is a time series spanning CE 1-2011 inclusive (ie, the Common Era). The time series is reconstructed from three primary annually-resolved proxy series from the Law Dome ice core. These three series are the log-transformed seasonal sea salt concentration for the cool season (June to November), the log-transformed seasonal sea salt concentration for the warm season (December to May) and the annual snowfall accumulation rate. The reconstruction uses a Gaussian kernel correlation reconstruction method (Roberts et al., 2019) with 2000 ensemble members, which provides a mean IPO index value for each year, as well as upper and lower quartiles. The reconstruction target time series was the observed Interdecadal Pacific Oscillation spanning 1870-2020, which had been smoothed using a Gaussian window of 13 years. This Gaussian kernel correlation reconstruction is an evolution/replacement of the method and reconstruction presented in Vance et al., (2015) to reconstruct the IPO. This is now our preferred dataset for the Law Dome IPO reconstruction, and supersedes that published by Vance et al., (2015). The time series (dataset) consists of three columns with column headings as follows: Year – where year is the year from the beginning of the Common Era, ie, ‘436.0’ means the year CE 436, and ‘2009.0’ means the year 2009. IPO (mean) – the mean of the IPO reconstruction index value Std Dev) – the standard deviation of the index value for each year.