Sea Ice Changes in the Southwest Pacific Sector of the Southern Ocean During 1 the Last 140,000 Years 2

18 Sea ice expansion in the Southern Ocean is believed to have contributed to glacial-interglacial 19 atmospheric CO₂ variability by inhibiting air-sea gas exchange and influencing the ocean’s 20 meridional overturning circulation. However, limited data on past sea ice coverage over the last 21 140 ka (a complete glacial cycle) have hindered our ability to link sea ice expansion to oceanic 22 processes that affect atmospheric CO 2 concentration. Assessments of past sea ice coverage 23 using diatom assemblages have primarily focused on the Last Glacial Maximum (~21 ka BP) to 24 Holocene, with few quantitative reconstructions extending to the onset of glacial Termination II 25 (~135 ka BP). Here we provide new estimates of winter sea ice concentrations (WSIC) and 26 summer sea surface temperatures (SSST) for a full glacial-interglacial cycle from the 27 southwestern Pacific sector of the Southern Ocean using the Modern Analog Technique (MAT) 28 on fossil diatom assemblages from deep-sea core TAN1302-96. We examine how the timing of 29 changes in sea ice coverage relates

Past Antarctic sea ice coverage has been estimated primarily through diatom-based reconstructions, with most work focusing on the Last Glacial Maximum (LGM), specifically the EPILOG timeslice as outlined in Mix et al. (2001), corresponding to 23 to 19 thousand years ago (ka) before present (BP).During the LGM, these reconstructions suggest that winter sea ice expanded by 7-10° latitude (depending on the sector of the Southern Ocean), which corresponds to substantial expansion of total winter sea ice coverage compared to modern observations (Gersonde et al., 2005;Benz et al., 2016;Lhardy et al., 2021).Currently, only a handful of studies provide quantitative sea-ice coverage estimates back to the penultimate glaciation, Marine Isotope Stage (MIS) 6 (~194 to 135 ka BP) (Gersonde & Zielinksi, 2000;Crosta et al., 2004;Schneider-Mor et al., 2012;Esper & Gersonde 2014a;Ghadi et al. 2020).These studies primarily cover the Atlantic sector, with only one published sea ice record from each of the Indian (SK200-33 from Ghadi et al., 2020), eastern Pacific (PS58/271-1 from Esper & Gersonde, 2014a), and southwestern Pacific sectors (SO136-111 from Crosta et al., 2004).
These glacial-interglacial sea ice records show heterogeneity between sectors in both timing and coverage.While the Antarctic Zone (AZ) in the Atlantic sector experienced early sea ice advance corresponding to MIS 5d cooling (i.e., 115 to 105 ka BP) (Gersonde & Zielinksi, 2000;Bianchi & Gersonde, 2002;Esper & Gersonde, 2014a), the Indian and Pacific sector cores in the AZ show only minor sea ice advances during this time (Crosta et al., 2004;Ghadi et al., 2020).
The lack of spatial and temporal resolution has resulted in significant uncertainty in our ability to evaluate the timing and magnitude of sea ice change during a full glacial cycle across the Southern Ocean, and to link sea ice to glacial-interglacial CO2 variability.
This paper provides new winter sea ice concentration (WSIC) and summer sea surface temperature (SSST) estimates for the southwestern Pacific sector of the Southern Ocean over the last 140 ka BP.WSIC, which is a grid-scale observation of the mean state fraction of ocean area that is covered by sea ice over the sample period, and SSST estimates are produced by applying the Modern Analog Technique (MAT) to fossil diatom assemblages from sediment core TAN1302-96 (59.09°S, 157.05°E, water depth 3099 m).We place this record within the context of sea ice and SSST changes from the region using previously published records from SO136-111 (56.66°S, 160.23°E, water depth 3912 m), which has recalculated WSIC and SSST estimates presented in this study, and nearby marine core E27-23 (59.61°S, 155.23°E; water depth 3182 m) (Ferry et al., 2015).Using these records, we compare the timing of sea ice expansion to early glacial-interglacial CO2 variability to test the hypothesis that the initial CO2 drawdown (~115 to 100 ka BP) resulted from reduced air-sea gas exchange in response to sea ice capping and surface water stratification (Kohfeld and Chase, 2017).We then consider alternative oceanic drivers of early atmospheric CO2 variability and place our SSST estimates within the context of other studies to examine how regional cooling and a weakening in meridional SST gradients might affect air-sea disequilibrium and early CO2 drawdown (Khatiwala et al., 2019).Finally, we compare our WSIC estimates with regional reconstructions of Antarctic Intermediate Water (AAIW) production and subduction variability using previously published carbon isotope analyses on benthic foraminifera from intermediate to deep-water depths in the southwest Pacific sector of the Southern Ocean, to test the hypothesis that sea ice expansion is dynamically linked to AAIW production and variability (Ronge et al., 2015).

Study Site and Age Determination
We reconstruct diatom-based WSIC and SSST using marine sediment core TAN1302-96 (59.09°S, 157.05°E, water depth 3099 m) (Figure 1).The 364 cm core was collected in March 2013 using a gravity corer during the return of the RV Tangaroa from the Mertz Polynya in Eastern Antarctica (Williams et al., 2013).The core is situated in the western Pacific sector of the Southern Ocean, on the southwestern side of the Macquarie Ridge, approximately 3-4° south of the average position of the Polar Front (PF) at 157°E (Sokolov & Rintoul, 2009).
Figure 1: Map of the southwestern Pacific sector of the Southern Ocean including the study site, TAN1302-96 (blue circle), and additional published cores providing sea ice extent data, SO136-111 and E27-23 (green circles), SST reconstructions (red circles), and d 13 C of benthic foraminifera (yellow circles).Note that some cores may not appear present in the figure because of their proximity to other cores.Data for all cores are provided in Table 2. Dashed lines show the average location of the Subtropical and Polar Fronts (Smith et al., 2013;Bostock et al., 2015), and red and blue lines show mean positions of modern summer sea ice (SSI) and winter sea ice (WSI) extents, respectively (Reynolds et al., 2002;2007).
The age model for TAN1302-96 (Figures 2 and 3) was based on a combination of radiocarbon dating of mixed foraminiferal assemblages and stable oxygen isotope stratigraphy on Neogloboquadrina pachyderma (180-250 µm).Seven accelerator mass spectrometry (AMS) 14 C samples were collected (Table A1 in Appendix A) and consisted of mixed assemblages of planktonic foraminifera (N.pachyderma and Globigerina bulloides, >250 µm).Three of the seven radiocarbon samples (NZA 57105, 57109, and 61429) were previously published in Prebble et al. (2017), and four additional samples (OZX 517-520) were added to improve the dating reliability (Table A1 in Appendix A).OZX 519 and OZX 520 produced dates that were not distinguishable from background (>57.5 ka BP) and were subsequently excluded from the age model.The TAN1302-96 oxygen isotopes were run at the National Institute of Water and Atmospheric Research (NIWA) using the Kiel IV individual acid-on-sample device and analysed using Finnigan MAT 252 Mass Spectrometer.The precision is ±0.07%for δ 18 O and ±0.05% for δ 13 C.
The age model was constructed using the 'Undatable' MATLAB software by bootstrapping at 10% and using an x-factor of 0.1 (Lougheed & Obrochta, 2019), which scales Gaussian distributions of sediment accumulation uncertainty (Table A2 in Appendix A).Below 100 cm, 9 tie points were selected at positions of maximum change in δ 18 O and were correlated to the LR04 benthic stack (Lisiecki & Raymo, 2005) Uncertainty associated with stratigraphic correlation to the LR04 stack has been estimated to be ± 4 ka (Lisiecki & Raymo, 2005).We used a conservative marine reservoir age (MRA) for radiocarbon calibration of 1000 +/-100 years, in line with regional estimates in Paterne et al. (2019) and modelled estimates by Butzin et al. (2017;2020).The age model shows that TAN1302-96 extends to at least 140 ka BP, capturing a full glacial-interglacial cycle.Linear sedimentation rates (LSR) in TAN1302-96 were observed to be higher during interglacial periods, averaging ~3.5 cm ka -1 , compared to glacial periods, averaging ~2.5 cm ka -1 .It is worth noting that there can be significant MRA variability over time due changes in ocean ventilation, sea ice coverage, and wind strength, specifically in the polar high latitudes (Heaton et al., 2020), and as a result, caution should be taken when interpreting the precision of radiocarbon dates.For more information on age model construction and selection, refer to the supplemental online materials (SOM).(Lisiecki & Raymo, 2005).Two radiocarbon dates, OZX 519 & 520 (at 130 and 170 cm, respectively), were not included in the age model as they produced dates that were NDFB (not distinguishable from background).

Diatom Analysis
TAN1302-96 was sampled every 3-4 cm throughout the core except between 130-180 cm, where samples were collected every 10 cm due to limited availability of sample materials (Table A3 in Appendix A).Diatom slide preparation followed two procedures.The first approach approximated the methods outlined in Renberg (1990), while the second followed the protocol outlined in Warnock & Scherer (2015).To ensure there were no biases between preparation techniques, results from each technique were first visually compared followed by a comparison of sample means (see Figure B1 in Appendix B).No biases in the data were observed between methods.
The first procedure was conducted at Victoria University of Wellington and Simon Fraser University on samples every 10 cm throughout the core.Sediment samples contained high concentrations of diatoms with little carbonaceous or terrigenous materials, so no dissolving aids were used.Instead, approximately 50 mg of sediment was weighed, placed into a 50 ml centrifuge tube, and topped up with 40 ml of deionized water.Samples were then manually shaken to disaggregate sediment, followed by a 10-second mechanical stir using a vortex machine.Samples were then left to settle for 25 seconds.0.25 mL of the solution was then pipetted onto a microscope slide from a consistent depth, where it was left to dry overnight.
Once the sample had dried, coverslips were permanently mounted to the slide using Permount, a high refractive index mountant.Slides were redone if they contained too many diatoms and identification was not possible, or if they contained too few diatoms (generally <40 specimens per transect).Sediment sample weight was adjusted to achieve the desired dilution.
The second procedure was conducted at Colgate University on samples every 3-4 cm throughout the core.Oven-dried samples were placed into a 20 ml vial with 1-2 ml of 10% H2O2 and left to react for up to several days, followed by a brief (2-3 second) ultrasonic bath to disaggregate samples.The diatom solution was then added into a settling chamber, where microscope coverslips were placed on stages to collect settling diatoms.The chamber was gradually emptied through an attached spigot, and samples were evaporated overnight.Cover slips were permanently mounted onto the slides with Norland Optical Adhesive #61, a mounting medium with a high refractive index.
Diatom identification was conducted at Simon Fraser University using a Leica Leitz DMBRE light microscope using standard microscopy techniques.Following transverses, a minimum of 300 individual diatoms were identified at 1000x magnification from each sample throughout the core.Individuals were counted towards the total only if they represented at least one-half of the specimen so that fragmented diatoms were not counted twice.
Identification was conducted to the highest taxonomic level possible, either to the species or species-group level.Taxonomic identification was conducted using numerous identification materials, including (but not limited to): Fenner et al. (1976); Fryxell & Hasle (1976;1980); Johansen & Fryxell (1985); Hasle & Syversten (1997); Cefarelli et al. (2010); and Wilks & Armand (2017).The relative abundances were calculated by dividing the number of identified specimens of a particular species by the total number of identified diatoms from the sample.
Based on previously established taxonomic groups (Crosta et al., 2004), diatoms were grouped into one of three categories based on temperature preference and sea ice tolerance.The following main taxonomic groups were used (Table 1): [1] Sea Ice Group: representing diatoms that thrive in or near the sea ice margin in SSTs generally ranging from -1 to 1 °C.
[2] Permanent Open Ocean Zone (POOZ): representing diatoms that thrive in open ocean conditions, with SSTs generally ranging from ~2 to 10 °C.
Table 1: Species comprising each of the diatom taxonomic groups (updated from Crosta et al., 2004).

Modern Analog Technique
Past WSIC and SSST (January to March) were estimated for TAN1302-96 and recalculated for SO136-111 by applying the Modern Analog Technique (MAT) to the fossil diatom assemblages, as outlined in Crosta et al. (1998;2020).Summer (January to March) SST was estimated because it is considered to be a better explanatory variable than spring or annual SST (Esper et al., 2010;Esper & Gersonde, 2014b).The MAT reference database used for this analysis is comprised of 249 modern core top samples (analogs) located primarily in the Atlantic and Indian sectors from ~40°S to the Antarctic coast.The age of the core tops included in the reference database have been assessed through radiocarbon and/or isotope stratigraphy when possible.Core tops were visually evaluated for selective diatom dissolution, so it is believed that sub-modern assemblages contain well-preserved and unbiased specimens.
Modern SSST and WSIC were interpolated from the reference core locations using a 1°x1° grid from the World Ocean Atlas (Locarnini et al., 2013) through the Ocean Data View (Schlitzer, 2005).The MAT was applied using the "bioindic" package (Guiot & de Vernal, 2011) through the R-platform.Fossil diatom assemblages were compared to the modern analogs using 33 species or species-groups to identify the five most similar modern analogs using both the LOG and CHORD distance.The dissimilarity threshold, above which the fossil assemblages are considered to be too dissimilar to the modern dataset, is fixed at the first quartile of random distances (Crosta et al., 2020).The reconstructed SSST and WSIC are the distance-weighted mean of the climate values associated with the selected modern analog (Guiot et al., 1993;Ghadi et al., 2020).Both MAT approaches produce an R 2 value of 0.96 and a root mean square error of prediction (RMSEP) of ~1°C for SSST, and an R 2 of 0.93 and a RMSEP of 10% for WSIC (Ghadi et al. 2020).As outlined in Ferry et al., (2015), we consider <15% WSIC to represent an absence of winter sea ice, 15-40% WSIC as present but unconsolidated, and >40% to represent consolidated winter sea ice.

TAN1302-96 Diatom Assemblage Results
In this core, fifty-one different species or species groups were identified, of which 33 were used in the transfer function.These 33 species represent >82% of the total diatom assemblages (mean of 92%).Permanent Open Ocean Zone (POOZ) diatoms made up the largest proportion of diatoms identified, representing between 72-91% of the assemblage (Figure 4), with higher values observed during warmer interstadial periods of MIS 1, 3, and 5. Sea ice diatoms made up the second most abundant group, representing between 0.5-7.5% of the assemblage, with higher values observed during cooler stadial periods (MIS 2, 4, and 6).The Sub-Antarctic Zone group had relatively low abundances, with higher values occurring during warmer interstadial periods (MIS 5 and the Holocene) and briefly during MIS 4 at ~65 ka BP.
Figure 4: Diatom assemblages results from TAN1302-96 separated into % contribution from each taxonomic group (Sea ice Group, POOZ, and SAZ; see Table 1) over a full glacial-interglacial cycle.Using the Modern Analog Technique (MAT), winter sea ice concentration (WSIC) and summer sea surface temperature (SSST) were estimated and compared against the δ 18 O signature of TAN1302-96.

TAN1302-96 SSST and WSIC Estimates
There were no non-analog conditions observed in TAN1302-96 samples and all estimates were calculated on five analogs.Estimates of SSST and WSIC from both LOG and CHORD MAT outputs produced similar results (Figure 4).During Termination II, SSST began to rise from ~1°C at 140 ka BP (MIS 6) to ~4.5°C at 132 ka BP (MIS 5e/6 boundary).This warming corresponded with a decrease in WSIC from 48% to approximately 0% over the same time periods (Figure 4).Reconstructed SSST were variable throughout MIS 5e, reaching a maximum value of ~4.5°C at 118 ka BP, after which they declined throughout MIS 5.During this period of SSST decline, winter sea ice was largely absent, punctuated by brief periods during which sea ice was present but unconsolidated (WSIC = ~15% and 17% at 105 and 85 ka BP, respectively).
During MIS 4 (71 to 57 ka BP), SSST cooled to between roughly 1°C and 3°C, and sea ice expanded to 36%, such that it was present but unconsolidated for intervals of a few thousand years.SSST increased slightly from 1.5°C at 61 ka BP (during MIS 4) to ~2.5°C at 50 ka BP (during MIS 3), followed by a general cooling trend into MIS 2. Sea ice appears to have been largely absent during MIS 3 (57 to 29 ka BP), although sampling resolution is low, but increased rapidly to 48% cover during MIS 2 where winter sea ice was consolidated over the core site.During MIS 2, SSST cooled to a minimum of <1°C at 24.5 ka BP.After 18 ka BP, the site rapidly transitioned from cool, ice-covered conditions to warmer, ice-free winter conditions during the early deglaciation.This warming was interrupted by a brief cooling around 13.5 ka BP, following which SSST quickly reached their maximum values of ~5°C at 11.5 ka BP and remained relatively high throughout the rest of the Holocene.Winter sea ice was not present during the Holocene.

SO136-111 SSST and WSIC Recalculation
In core SO136-111, the 33 species included in the transfer function represent values >79% of the total diatom assemblages (mean of 91%).There were no non-analog conditions observed in SO136-111 samples and all estimates were calculated on five analogs.Recalculated estimates of SSST and WSIC from both LOG and CHORD MAT outputs produced similar results for SO136-111 (Figure 5a, 5d).During Termination II, SSST rose from ~2°C at 137 ka BP (MIS 6) to a maximum value of 6°C at 125 ka BP (MIS 5e), corresponding to a rapid decline in WSIC from 37% to ~0% during the same period.SSST remained relatively high (between 4 and 5°C) from 125 ka BP until 115 ka BP where they declined to ~2°C.SSST remained variable from 110 ka BP until ~40 ka BP, fluctuating between ~2°C and 4°C.Winter sea ice was largely absent during MIS 5, with a brief period where sea ice was present but unconsolidated (WSIC = 17% at 84 ka).
Beginning at ~76 ka BP, WSIC began to increase and continued throughout early MIS 4 to a maximum 36% at 69 ka BP.WSIC remained present but unconsolidated throughout most of MIS 3 and 2 with brief periods of absence (WSIC = <15%) lasting a few thousand years.SSST and WSIC reached their coolest values and highest concentration at 24.5 ka before SSST increased to ~5°C and stabilized throughout the Holocene, while WSIC declined to virtually 0% throughout the same period.
The second possible explanation involves lateral sediment redistribution and focusing by the ACC.We estimated sediment focusing for E27-23 using 230 Th data from Bradtmiller et al.
(2009) together with dry bulk density estimated using calcium carbonate content (Froelich, 1991).Both sedimentation rates and focusing factors (FF) for the E27-23 are relatively high (max.= ~35 cm ka -1 and 26, respectively) during the LGM and Holocene, which could influence the reliability of WSIC and SSST estimation (see Figure B2 in Appendix B).Several peaks in focusing occurring around 16, 12, and 3 ka BP appear to closely correspond to periods of peak WSIC (~67%, ~54%, and ~35%, respectively), suggesting a possible link.Lateral redistribution could artificially increase or decrease relative abundances of some diatom groups, which could lead to over-or under-estimations of sea ice coverage.Thorium analysis for TAN1302-96 is beyond the scope of this study; however, future work could help address this uncertainty.
Although we are unable to identify the specific cause of the differences, we suggest considering the results from all cores when drawing conclusions of regional sea ice history.Open Ocean Zone (POOZ) of the Atlantic sector, suggesting a slight cooling and northward expansion of sea ice during MIS 5d (Bianchi & Gersonde, 2002).Our data address this hypothesis by providing insights into early sea ice expansion into the polar frontal zone of the western Pacific sector.

The Role of Sea Ice on Early CO
Our data show that, in contrast to the Atlantic sector (Bianchi & Gersonde, 2002), there does not appear to be any evidence of sea ice expansion in the southwestern Pacific during MIS 5d at either the TAN1302-96 or SO136-111 core sites (Figure 5).Unfortunately, the lack of spatially extensive quantitative records extending back to Termination II limits our ability to estimate the timing and magnitude of sea ice changes for regions poleward of 59°S in the southwestern Pacific.We anticipate, however, that an advance in the sea ice edge, consistent with those outlined in Bianchi and Gersonde (2002), likely would have reduced local SST as the sea ice edge advanced closer to the core site.Indeed, the TAN1302-96 SSST record does show a decrease to ~2°C (observed at 108 ka BP), which quickly rebounded to ~4°C by ~102 ka BP (Figure 5).However, this SSST drop occurred roughly 7 ka BP after the initial CO2 reduction, suggesting that the CO2 drawdown event and local SSST reduction may not be linked.Thus, while we cannot rule out the possibility of modest sea ice advances or consolidation of preexisting sea ice (particularly to the south of the core sites), the quantitative WSI and SSST reconstructions suggest that sea ice cover over our core site was limited during glacial inception.
Given that sea ice was not at its maximum extent during the early glacial, it stands to reason that any reductions to air-sea gas exchange in response to the hypothetically expanded sea ice would not have been at its maximum impact either.Previous modeling work has suggested that the maximum impact of sea ice expansion on glacial-interglacial atmospheric CO2 reductions ranged from 5 to 14 ppm (Kohfeld and Ridgwell, 2009).More recent modeling studies are consistent with this range, suggesting a 10 ppm reduction (Stein et al., 2020), while some studies even suggest a possible increase in atmospheric CO2 concentrations due to sea ice expansion (Khatiwala et al., 2019).Furthermore, Stein et al. (2020) suggest that the effects of sea ice capping would have taken place after changes in deep ocean stratification had occurred and would have contributed to CO2 drawdown later during the mid-glacial period.These model results, when combined with our data, suggest that even if modest sea ice advances did take place during the early glacial (i.e., MIS 5d), their impacts on CO2 variability likely would have been modest, ultimately casting doubt on the hypothesis that early glacial CO2 reductions of 35 ppm can be linked solely to the capping and stratification effects of sea ice expansion.

Other Potential Contributors to Early Glacial CO 2 Variability
The changes observed in WSIC and SSST from TAN1302-96 suggest that sea ice expansion was likely not extensive enough early in the glacial cycle for a sea ice capping effect The first possible explanation considers that not all sea ice has the same capacity to facilitate or inhibit air-sea gas exchange.We previously suggested that because sea ice was not at its maximum extent during MIS 5d, the contribution of sea ice on CO2 sequestration would likely not be at its maximum extent either.However, this assumes a linear relationship between sea ice coverage and CO2 sequestration potential.We know that different sea ice properties, such as thickness and temperature, determine overall porosity, with thicker and colder sea ice being less porous and more effective at reducing air-sea gas exchange compared to thinner and warmer sea ice (Delille et al., 2014).It is therefore possible that if modest sea ice advances took place closer to the Antarctic continent (and were therefore not captured by TAN1302-96), they may have been more effective at reducing CO2 outgassing either by experiencing some type of reorganization or consolidation, or through a change in properties such as temperature or thickness.It is also possible that sea ice coverage over some regions leads to more effective capping, while in other regions sea ice growth contributes only to marginal reductions in air-sea gas exchange.This, theoretically, could point to a non-linear response between sea ice expansion and CO2 sequestration potential, and thus modest sea ice growth around the Antarctic continent could have contributed in part to the ~35 ppm initial CO2 drawdown event.
While this is theoretical and cannot be adequately addressed in this analysis, it is worthy of deeper consideration.
The second possible explanation involves changes in the global overturning circulation.-was actually initiated between MIS 5d and MIS 5a (114 to 71 ka BP).Evidence for early changes in abyssal circulation and reductions in deep-ocean overturning have also been detected in Indian Ocean δ 13 C records (Govin et al., 2009).More recently, Indian Ocean eNd records (Williams et al., 2021) have suggested that the abyssal ocean may have responded to sea ice changes around the Antarctic continent early in the glacial cycle, with colder and more saline AABW forming as sea ice expanded near the continent.If indications of an early-glacial response in the global ocean circulation in the Indo-Pacific are correct, these data may also point to an elevated importance of sea ice near the Antarctic continent in triggering early, deep-ocean overturning changes.
The third possible explanation involves changes in surface ocean temperature gradients in the Southern Ocean, and how they could influence air-sea gas exchange.Several recent studies have pointed to the importance of changes to air-sea disequilibrium as a key contributor to CO2 uptake in the Southern Ocean (Eggleston & Galbraith, 2018;Marzocchi & Jansen 2019;Khatiwala et al. 2019).Khatiwala et al. (2019) suggested that modelling studies have traditionally underrepresented (or neglected) the role of air-sea disequilibrium in amplifying the impact of cooling on potential CO2 sequestration in the mid-high southern latitudes during glacial periods.They argue that when the full effects of air-sea disequilibrium are considered, ocean cooling can result in a 44 ppm decrease due to temperature-based solubility effects alone.They attributed this increased impact of SST to a reduction in seasurface temperature gradients explicitly in polar mid-latitude regions (roughly between 40° and 60° north and south).If we compare the SST gradients in the southwest Pacific sector over the last glacial-interglacial cycle (Figure 6), we see an early cooling response between MIS 5e-d corresponding to roughly half of the full glacial cooling, specifically in the cores located south of the modern STF.While not quantified, Bianchi and Gersonde (2002) also described a weakening of meridional SST gradients between the Subantarctic and Antarctic Zones during MIS 5d in the Atlantic sector.Although this analysis is based on sparse data, our SSST reconstructions are consistent with the notion that surface ocean cooling, a weakening of meridional SST gradients, and changes to the overall air-sea disequilibrium could be responsible for at least some portion of the early CO2 drawdown.Further SST estimates from the region, and from the global ocean, are needed to substantiate this hypothesis.

Sea Ice Expansion and Ocean Circulation
Although the TAN1302-96 WSIC record suggests that sea ice was largely absent at the core site until the mid-glacial (~65 ka BP), the observed changes in sea ice could have modulated regional fluctuations in Antarctic Intermediate Water (AAIW) subduction throughout the glacial-interglacial cycle.The annual growth and decay of Antarctic sea ice plays a critical role in regional water mass formation.Brine rejection results in net buoyancy loss in regions of sea ice formation, while subsequent melt results in freshwater inputs and net buoyancy gains near the ice margin (Shin et al., 2003;Pellichero et al., 2018).This increased freshwater input and buoyancy gain near the ice margin can hinder AAIW subduction, with direct and indirect impacts on both the upper and lower branches of the meridional overturning circulation (Pellichero et al. 2018).
Previous research has used δ 13 C in benthic foraminifera to track changes in the depth of the interface between AAIW and Upper Circumpolar Deep Water (UCDW) (Pahnke and Zahn, 2005;Ronge et al., 2015).Low δ 13 C values are linked to high nutrient concentrations found at depths below ~1500 m in the UCDW, and higher δ 13 C values are associated with the shallower AAIW waters (Figure 5).Marine sediment core MD97-2120 (45.535°S, 174.9403°E, core depth 1210 m) was retrieved from a water depth near the interface between the AAIW and UCDW water masses (Pahnke & Zahn, 2005).Over the last glacial-interglacial cycle, fluctuations in the benthic δ 13 C values from MD97-2120 suggest that the core site was intermittently bathed in AAIW and UCDW, and that the vertical extent of AAIW fluctuated throughout the last glacialinterglacial cycle.Ronge et al. (2015) used the δ 13 C values from MD97-2120 and other core sites to quantify the contributions of AAIW to the waters overlying MD97-2120 (%AAIW, Appendix D).These results suggest that during warm periods, MD97-2120 exhibited more positive δ 13 C values, corresponding to higher %AAIW, while cooler periods exhibited more negative values, corresponding to lower %AAIW (Figure 5).This suggests that during cooler periods, the AAIW-UCDW interface shoaled, reducing the total volume of AAIW and indirectly causing an expansion of UCDW (Ronge et al., 2015).
Our comparison between %AAIW and regional WSIC estimates suggest a strong link between the two (Figure 5).Specifically, we observe that AAIW shoaled and UCDW expanded (i.e., %AAIW is low) during periods when sea ice expansion occurred.In contrast, during periods of low WSIC, a reduced seasonal sea ice cycle, and warmer summer sea surface temperatures (e.g., MIS 5e), %AAIW is observed to be high.This correlation supports the idea that increased concentrations of regional sea ice resulted in a substantial summer freshwater flux into the AAIW source region.This regional freshening likely promoted a shallower subduction of AAIW and a corresponding volumetric expansion of UCDW, which can be seen by the isotopic offset of the δ 13 C values between the reference cores, and also by the increased carbonate dissolution in MD97-2120 during glacial periods (Figure 7) (Pahnke et al., 2003;Ronge et al., 2015).These findings directly link sea ice proxy records to observed changes in ocean circulation and water mass geometry.
Figure 7: Schematic of changes in southwestern Pacific sector sea ice coverage and water mass geometry between interglacial and glacial stages.A) Depicts interglacial conditions where sea ice coverage is minimal and freshwater input from summer sea ice melt is low.This lack of freshwater input allows AAIW to subduct to deeper depths and bath core MD97-2120, capturing the higher δ 13 C signature of the overlying AAIW waters.The AAIW-UCDW interface (red dashed line) is located beneath MD97-2120.CO2 outgassing is occurring as carbon-rich Circumpolar Deep Waters upwell near Antarctica.B) Depicts glacial conditions where sea ice expansion has occurred beyond TAN1302-96, increasing brine rejection, and stabilizing the water column.As a result of the increased sea ice growth, subsequent summer melt increases the freshwater flux into the AAIW source region and increases AAIW buoyancy.This buoyancy gain shoals the AAIW-UCDW interface above core MD97-2120, causing the core site to be bathed in low δ 13 C UCDW.The shoaling of AAIW causes an indirect expansion of CDW, increasing the glacial carbon stocks of the deep ocean while sea ice reduces CO2 outgassing via the capping mechanism.
In addition to its influence on regional freshwater forcing and AAIW reductions, these sea ice changes may also coincide with larger-scale deep ocean circulation changes.The most dramatic increases in winter sea ice observed in TAN1302-96 and SO136-111, along with changes in %AAIW, are initiated during MIS 4. These shifts also correspond to basin-wide changes in benthic δ 13 C values in the Atlantic Ocean that suggest a shoaling in the AMOC during MIS 4 (Oliver et al., 2010;Kohfeld & Chase, 2017).Changes in deep ocean circulation are also recorded in εNd isotope data in the Indian sector of the Southern Ocean (Wilson et al., 2015), suggesting extensive reductions in the AMOC during this period.Recent modelling literature (Marzocchi & Jansen, 2019;Stein et al., 2020) suggests that sea ice formation directly impacts marine carbon storage by increasing density stratification and reducing diapycnal mixing, especially in simulations where brine rejection is enhanced near the Antarctic continental slope and open ocean vertical mixing (and subsequent CO2 outgassing) is reduced (Bouttes et al. 2010;2012;Menviel et al. 2012).These simulations suggest a resulting CO2 sequestration of 20-40 ppm into the deep ocean.
Taken collectively, the available data show that sea ice expansion, AAIW-UCDW shoaling, changes in the AMOC, and a decrease in atmospheric CO2 all occur concomitantly during MIS 4 (Figure 5).It appears likely, therefore, that sea ice expansion during this time influenced intermediate water density gradients through increased freshening and consequent shoaling of AAIW, which may also have increased the efficiency of the carbon pump and increased CO2 uptake by phytoplankton (Sigman et al., 2021).This appears to have occurred while simultaneously influencing deep-ocean density, and therefore stratification, through brine rejection and enhanced deep water formation, which ultimately lead to decreased ventilation (Abernathey et al., 2016).These changes in ocean stratification, combined with the sea ice 'capping' mechanism, appear to agree with both the recent modelling efforts (Stein et al., 2020) and observed proxy data, and fit well within the hypothesis that mid-glacial CO2 variability was primarily the result of a more sluggish overturning circulation (Kohfeld & Chase, 2017).

Summary & Conclusion
This study presents new WSIC and SSST estimates from marine core TAN1302-96, located in the southwestern Pacific sector of the Southern Ocean.We find that the WSIC remained low during the early glacial cycle (130 to 70 ka BP), expanded during the middle glacial cycle (~65 ka BP), and reached its maximum just prior to the LGM (~24.5 ka BP).These results largely agree with nearby core SO136-111 but display some differences in WSIC magnitude with E27-23.This discrepancy may be explained by differences in statistical applications and/or lateral sediment redistribution, although more analysis is required to determine the exact cause(s).
The lack of changes in SSST and the absence of winter sea ice over the core site during the early glacial suggests that the sea ice capping mechanism and corresponding surface stratification in this region is an unlikely cause for early CO2 drawdown, and that alternative hypotheses should be considered when evaluating the mechanism(s) responsible for the initial drawdown.More specifically, we consider the impact of changes in SSST gradients between ~40˚ to 60˚S and support the idea that changes in air-sea disequilibrium associated with reduced sea-surface temperature gradients could be a potential mechanism that contributed to early glacial reductions in atmospheric CO2 concentrations (Khatiwala et al., 2019).Another key consideration is the potentially non-linear response between sea ice expansion and CO2 sequestration potential (i.e., that not all sea ice is equal in its capacity to sequester carbon).
More analyses are required to adequately address this.
We also observe a strong link between regional sea ice concentrations and vertical fluctuations in the AAIW-UCDW interface.Regional sea ice expansion appears to coincide with the shoaling of AAIW, likely due to the freshwater flux from summer sea ice melt increasing buoyancy in the AAIW formation region.Furthermore, major sea ice expansion and AAIW shoaling occurs during the middle of the glacial cycle and is coincident with previously recognized shoaling in AMOC and mid-glacial atmospheric CO2 reductions, suggesting a mechanistic link between sea ice and ocean circulation.
In conclusion, this paper has focused exclusively on sea ice as a driver of physical changes, but we recognize that these changes in sea ice will be accompanied by multiple processes that interact and compete with each other.Marzocchi & Jansen (2019) note that teasing apart the individual components of CO2 fluctuations is complicated because of interactions between sea ice capping, air-sea disequilibrium, AABW formation rates, and the biological pump.We recognize that these processes may not act independently, and as such, have contributed new data to help advance our collective understanding of the role of sea ice on influencing atmospheric CO2 variability on a glacial-interglacial time scale.

Appendices
Appendix A: Age Model & Sampling Depths

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relating to taxonomic identification and/or methodology is an unlikely explanation for the observed WSIC differences.
Finally, the fifth potential cause of differing WSIC estimates is selective diatom preservation (e.g., Pichon et al., 1999;Ragueneau et al., 2000).The similarities between TAN1302-96 and SO136-111 WSIC estimates, along with independent indicators in cores E27-23 and TAN1302-96, suggest that this is unlikely.For E27-23, Bradtmiller et al. (2009) used the consistent relationship between 231 Pa/ 230Th ratios and opal fluxes to suggest that dissolution remained relatively constant between the LGM and Holocene periods.In TAN1302-96, we assigned a semi-quantitative diatom preservation value between 1 (extreme dissolution) and 4 (virtually perfect preservation) for each counted specimen.The average preservation of diatoms for the entire core was 3.38 ± 0.13, with no observed bias based on sedimentation rate or MIS.This assessment, although semi-qualitative, suggests that preservation remained relatively constant (and good) throughout TAN1302-96, and is therefore unlikely to cause large differences in WSIC between the two cores.(Bradtmiller et al., 2009).

Figure 2 :
Figure 2: Age model of TAN1302-96.Red circles indicate the depth of AMS 14 C samples and yellow circles indicate tie points between the TAN1302-96 oxygen isotope stratigraphy and the LR04 benthic stack(Lisiecki & Raymo, 2005).Two radiocarbon dates, OZX 519 & 520 (at 130 and 170 cm, respectively), were not included in the age model as they produced dates that were NDFB (not distinguishable from background).

Figure 3 :
Figure 3: Age model of TAN1302-96.Tie points are depicted as yellow dots and grey shading represents associated uncertainty between tie points.The age model used a marine reservoir calibration of 1000 +/-100 years.
E27-23 (Figure5b), which is located only ~120 km to the southwest of TAN1302-96 (Figure1), the TAN1302-96 core shows lower estimates of WSIC, especially during MIS 3.During early and mid-MIS 2, both cores show similar WSIC estimates, while later in MIS 2 (~17 ka BP), E27-23 reports a maximum WSIC of 72% compared to only 22% at TAN1302-96.A discrepancy between estimates is also observed during the Holocene, with E27-23 reporting sea ice estimates of up to nearly 50% during the mid-Holocene (~6 ka BP), while TAN1302-96 experienced values well below the RMSEP of 10%.Possible explanations for the observed differences in WSIC estimates include: [1] differences in statistical applications; [2] lateral sediment redistribution; [3] differences in laboratory protocols; [4] differences in diatom identification/counting methodology; and [5] selective diatom dissolution.Of these explanations, we believe that [1] and [2] are the most likely candidates and are discussed below (for further discussion on [3], [4], and [5], see Appendix C).The first possible explanation is the use of different statistical applications.Ferry et al. (2015) used a Generalized Additive Model (GAM) to estimate WSIC for both E27-23 and SO136-111, while we have used the MAT for TAN1302-96 and SO136-111.A simple comparison of WSIC estimates between the results in Ferry et al. (2015) and our recalculated WSIC estimates

2
DrawdownKohfeld & Chase (2017) hypothesized that the initial drawdown of atmospheric CO2 (~35 ppm) during the glacial inception of MIS 5d (~115 to 100 ka BP) was primarily driven by sea ice capping and a corresponding stratification of surface waters, which reduced the CO2 outgassing of upwelled carbon-rich waters.This hypothesis is supported by several lines of evidence, including: [1] sea salt sodium (ssNA) archived in Antarctic ice cores, suggesting sea ice expansion near the Antarctic continent (Wolf et al., 2010); [2] δ 15 N proxy data from the central Pacific sector of the Southern Ocean, suggesting increased stratification south of the modernday Antarctic Polar Front (Studer et al., 2015); and [3] diatom assemblages in the Permanent to be solely responsible for early atmospheric CO2 drawdown.This leaves open the question of what may have contributed to early drawdown of atmospheric CO2.In terms of the ocean's role, we highlight three contenders: [1] a potentially non-linear response between sea ice coverage and CO2 sequestration potential; [2] links between sea ice expansion and early changes in global ocean overturning, and [3] the impact of cooling on air-sea disequilibrium in the Southern Ocean.
Kohfeld and Chase (2017) previously examined the timing of changes in δ 13 C of benthic foraminifera solely from the Atlantic basin and observed that the largest changes in the Atlantic Meridional Overturning Circulation (AMOC) coincided with the mid-glacial reductions in atmospheric CO2 changes mentioned above.Subsequent work of O'Neill et al.(2020) examined whole-ocean changes in δ 13 C of benthic foraminifera and noted that the separation between δ 13 C values of abyssal and deep ocean waters -and therefore the isolation of the abyssal ocean

Table 2 :
Additional data on published marine cores used throughout this analysis.

Table A2 :
Tie points used in construction of the TAN1302-96 age model