A seasonal cycle of the FA composition of particulate organic matter from surface waters, Chlorophyll-a maximum layer and bottom sea ice, sampled during the MOSAiC expedition in the Central Arctic Ocean (2019-2020), suggests the importance of phylogenetic and environmental drivers. To improve our understanding of these different drivers, we conducted culture experiments with 32 cold-water algal strains where temperature, light intensity, and nutrient supply were manipulated individually or in combination. The culture experiments were carried out at the Culture Collection of Algae and Protozoa (CCAP; Oban, Scotland), the Roscoff Culture Collection (RCC; Roscoff, France) and the Alfred-Wegener-Institute-Helmholtz-Centre for Polar and Marine Research (AWI; Bremerhaven, Germany). The strains were part of the culture collections, had been isolated in the Arctic (25 strains), Southern Ocean (2 strains) or North Atlantic (5 strains), and included diatoms, chlorophytes, haptophytes, cryptophytes, chrysophytes, dinoflagellates and cyanobacteria. Some of the species are Arctic sea ice diatoms (e.g. Nitzschia frigida, Attheya spp.) or pelagic diatoms (e.g. Thalassiosira gravida), while others are non-diatom species that are becoming increasingly prominent in the Arctic, e.g. the coccolithophore Emiliania huxleyi (synonym Gephyrocapsa huxleyi), the prymnesiophyte Phaeocystis pouchetii, the chlorophyte Micromonas spp. and the cyanobacterium Synechococcus spp.. The experiments can be divided into three groups: First, those that tested a low light-low temperature setting, second, those that tested a low light-low temperature and a higher light-higher temperature setting and, third, those that tested the effect of nutrient (nitrate, phosphate and silicate) shortage in combination with low and high light intensity. The first set of experiments was conducted with all 32 strains, the second set with all strains grown at CCAP and AWI, and the third set focuses on the keystone under-ice diatom Melosira arctica. The experiments were run for 4-7 weeks to accumulate sufficient biomass for biomarker extractions (FA and sterols), C:N analysis and light-microscopy of cell size and cell concentration. At the end of the experiments, the algae were filtered onto GF/F filters and deep frozen until analysis. After addition of internal standards for FA and sterols, the filters were saponified with KOH. Thereafter, non-saponifiable lipids (sterols) were extracted with hexane and purified by open column chromatography on silica gel. FA were obtained by adding concentrated HCl to the saponified solution and re-extracted with hexane. Samples were converted into fatty acid methyl esters (FAME) and analysed using an Agilent 6890N gas chromatograph with FID detector. The Clarity chromatography software system (DataApex, Czech Republic) was used for chromatogram data evaluation. FAME were quantified via the internal standard, Tricosanoic acid methyl ester (23:0) (Supelco, Germany) to provide the total amount of FA (TFA) per filter. These FA datasets of cultured algae are presented in a manuscript together with the FA pattern seen in sea ice- and water column POM in the CAO during the MOSAiC expedition and in previously published data from Arctic shelf regions. The manuscript focusses mainly on two important long-chain omega-3 FA (eicosapentaenoic acid and docosahexaenoic acid) that are considered essential for the nutrition of higher trophic levels, including humans, and their production to decline with global temperature rise. Contributions by KS were funded by the UK's Natural Environment Research Council MOSAiC Thematic project SYM-PEL: 'Quantifying the contribution of sympagic versus pelagic diatoms to Arctic food webs and biogeochemical fluxes: application of source-specific highly branched isoprenoid biomarkers'/ (NE/S002502/1). CRM was funded by the NERC National Capability Services and Facilities Programme (NE/R017050/1).

Incoming irradiance at the surface and transmitted through snow and sea ice was measured during a cruise to the Chukchi Sea in August 2019 with the Korean RV Araon using TriOS RAMSES planar radiometers. The data was collected to improve understanding of how the physical and optical properties of various sea ice conditions affect the solar partitioning by snow and sea ice in the Arctic Ocean and how this might affect the ecosystem trophic levels relying on photosynthesis. The data is also used to improve parameterisation in models or for remote sensing applications in order to upscale to a pan-Arctic level. This dataset resulted from the NERC project (NE/R012725/1) Eco-Light, part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF).

Calanus hyperboreus dominates the copepod biomass in the high Arctic. It forms an important intermediate trophic level in the Central Arctic food web, grazing on algae and protists and serving as prey for a large range of other zooplankton, fish and seabirds. Their unique lipids (20:1, 22:1 fatty acids and fatty alcohols) can be traced within the Arctic megafauna from seals to whales and polar bears, as these energy-rich lipids are crucial body reserves for the dark season. During the MOSAiC expedition in the Central Arctic Ocean (CAO, 2019-2020), C. hyperboreus adult females (AF) and subadult copepodites stages (CV) were sampled weekly to fortnightly. A range of nets were used to sample either horizontally underneath the sea ice or vertically from maximum 2000 m through the water column. Onboard, ~10 AF and ~20 CV of C. hyperboreus were sorted from each catch, photographed, rinsed with freshwater to remove salt and frozen at -80C for subsequent analysis of their total dry mass (DM), lipid content and a suite of trophic markers, including bulk stable isotopes (BSI), phytosterols (PS), total fatty acids (TFA), total fatty alcohols (TFAlc), and highly-branched isoprenoids (HBI). During the time of their seasonal descent at the end of summer, vertical sampling of C. hyperboreus was intensified and additional parameters were analysed, e.g. the FA and FAlc composition of their storage lipids (neutral lipids, NLFA, NLFAlc) and membrane lipids (polar lipids, PLFA, PLFAlc), the carbon isotopic composition of key FA and FAlc (CSIA-FA; CSIA-FAlc), and the tissue density. By combining this array of trophic markers, valuable information about the body conditions and feeding history of these copepods can be linked to their life cycle and vertical distribution. The initial separation of the various trophic markers was carried out at the University of Plymouth. After estimating the total DM, subsamples for BSI were sent to the Littoral, Environment and Societies Joint Research Unit stable isotope facility (CNRS - University of La Rochelle, France) for analysis. Three internal standards were added to the samples used for lipid analysis to quantify the TFA, TFAlc, PS and HBI content. As a first step, the total lipid content of the animals was extracted in dichloromethane : methanol. The lipid samples were split into two equal subsamples, one was sent to the Alfred-Wegener-Institute (AWI) in Bremerhaven/Germany for FA and FAlc analyses and the second was used for PS and HBI analyses in Plymouth. This dataset is linked to a manuscript that compares the trophic marker composition of C. hyperboreus from the surface vs. deep ocean to understand drivers, benefits, and risks of their seasonal migration in the CAO. The manuscript focusses mainly on the copepod descent in late summer and the changes in body conditions and trophic marker composition over the winter months. Contributions by KS were funded by the UK's Natural Environment Research Council MOSAiC Thematic project SYM-PEL: "Quantifying the contribution of sympagic versus pelagic diatoms to Arctic food webs and biogeochemical fluxes: application of source-specific highly branched isoprenoid biomarkers" (NE/S002502/1). CJA, RGC, CEG, KMS and RJ were funded by the US National Science Foundation Office of Polar Programs (OPP-1824447 and OPP-1824414).

This data set provides processed Ku- and Ka-band fully-polarimetric backscatter and derived polarimetric parameters from hourly scans, acquired using the KuKa radar, during Legs 1, 2, 4 and 5 of the 2019-2020 MOSAiC International Arctic Drift Expedition. Scans were acquired during winter (Legs 1 and 2), advanced melt (leg 4) and freeze-up (Leg 5) seasons, from various Remote Sensing (RS) sites, located in the MOSAiC ice floe. The first deployment of the KuKa radar was on 18 October 2019 at RS1 site and the radar was retreated (due to ice break up) on 18th November. The radar was redeployed on 29th November at RS2 site until 13th December when cracks were observed at the site and the instrument was turned off and moved to a safe location. The radar was redeployed at RS3 site and started measuring again on 21st December 2019 until 31st January 2020, after which the radar was taken off the RS site to conduct maintenance. The radar was not operational during Leg 3. During Leg 4, the radar was operational between 25th June and 19th July 2020, and later retreated back to the ship, for deployment in Leg 5. The radar was deployed on 24th August 2020 and operational until the end of the MOSAiC expedition. The dataset was collected by MOSAiC Team ICE participants and processed by Vishnu Nandan at the University of Manitoba, Canada. This work was funded in part through NERC grant NE/S002510/1, the Canada 150 Chair Program and the European Space Agency PO 5001027396. The authors thank Marine Environmental Observation, Prediction and Response Network (MEOPAR) Postdoctoral Fellowship grant to Vishnu Nandan. The authors also thank the crew of R/V Polarstern and all scientific members of the MOSAiC expedition for their support in field logistics and field data collection. ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set (see 'Related Data Set Metadata' link below) has been corrected for a bug that was found in the original KuKa radar processing chain.

This data set provides processed Ku- and Ka-band fully-polarimetric backscatter and derived polarimetric parameters from hourly scans, acquired using the KuKa radar, during Legs 1, 2, 4 and 5 of the 2019-2020 MOSAiC International Arctic Drift Expedition. Scans were acquired during winter (Legs 1 and 2), advanced melt (Leg 4) and freeze-up (Leg 5) seasons, from various Remote Sensing (RS) sites, located in the MOSAiC ice floe. The first deployment of the KuKa radar was on 18 October 2019 at RS1 site and the radar was retreated (due to ice break up) on 18th November. The radar was redeployed on 29th November at RS2 site until 13th December when cracks were observed at the site and the instrument was turned off and moved to a safe location. The radar was redeployed at RS3 site and started measuring again on 21st December 2019 until 31st January 2020, after which the radar was taken off the RS site to conduct maintenance. The radar was not operational during Leg 3. During Leg 4, the radar was operational between 25th June and 19th July 2020, and later retreated back to the ship, for deployment in Leg 5. The radar was deployed on 24th August 2020 and operational until the end of the MOSAiC expedition. The dataset was collected by MOSAiC Team ICE participants and processed by Vishnu Nandan at the University of Manitoba, Canada. This work was funded in part through NERC grant NE/S002510/1, the Canada 150 Chair Program and the European Space Agency PO 5001027396. The authors thank Marine Environmental Observation, Prediction and Response Network (MEOPAR) Postdoctoral Fellowship grant to Vishnu Nandan. The authors also thank the crew of R/V Polarstern and all scientific members of the MOSAiC expedition for their support in field logistics and field data collection.

The dataset contains 3 data files. Firstly, it contains one set of stable isotope compositions expressed as delta13C, d15N, d34S values recovered from fish muscle from a variety of species captured in September 2019 across the Barents Sea as part of the joint IMR-PINRO Barents Sea Ecosystem Survey. Samples were collected by Dr Matthew Cobain and Dr Kim Vane, and isotope data analysed at the university of Southampton. A second dataset contains delta13C and delta18O compositions of fish otolith carbonate recovered from a subset of the same fish. A final sheet contains the full metadata associated with each fish sampled on the survey. All samples were processed by Dr Matthew Cobain or Prof Clive Trueman and stable isotope values determined at the University of Southampton. Funding: Project was funded under the NERC Changing Arctic Ocean project, Coldifsh (NE/R012520/1).

This dataset presents the input and output data from a set of sensitivity experiments to simulate the evolution of the Laurentide ice sheet in the Early Holocene (10-7 thousand years ago). These data are presented in the manuscript "Simulating the Early Holocene demise of the Laurentide Ice Sheet with BISICLES (public trunk revision 3298)". Simulating the demise of the Laurentide Ice Sheet covering the Hudson Bay in the early Holocene is important for understanding the role of accelerated changes in ice sheet topography and melt in the '8.2 ka event', a century long cooling of the Northern Hemisphere by several degrees. Freshwater released from the ice sheet through a surface mass balance instability (known as the saddle collapse) has been suggested as a major forcing for the 8.2 ka event, but the temporal evolution of this pulse has not been constrained. Dynamical ice loss and marine interactions could have significantly accelerated the ice sheet demise, but simulating such processes requires computationally expensive models that are difficult to configure and are often impractical for simulating past ice sheets. Here, we developed an ice sheet model setup for studying the Laurentide Ice Sheet's Hudson Bay saddle collapse and the associated meltwater pulse in unprecedented detail using the BISICLES ice sheet model, an efficient marine ice sheet model of the latest generation, capable of refinement to kilometre-scale resolution and higher-order ice flow physics. The setup draws on previous efforts to model the deglaciation of the North American Ice Sheet for initialising the ice sheet temperature, recent ice sheet reconstructions for developing the topography of the region and ice sheet, and output from a general circulation model for a representation of the climatic forcing. The modelled deglaciation is in agreement with the reconstructed extent of the ice sheet and the associated meltwater pulse has realistic timing. Furthermore, the peak magnitude of the modelled meltwater equivalent (0.07-0.13 Sv) is compatible with geological estimates of freshwater discharge through the Hudson Strait. The results demonstrate that while improved representation of the glacial dynamics and marine interactions are key for correctly simulating the pattern of early Holocene ice sheet retreat, surface mass balance introduces by far the most uncertainty. The new model configuration presented here provides future opportunities to quantify the range of plausible amplitudes and durations of a Hudson Bay ice saddle collapse meltwater pulse and its role in forcing the 8.2 ka event. Ilkka Matero was funded by the Leeds-York Natural Environment Research Council (NERC) Spheres Doctoral Training Partnership (NE/L002574/1). The contribution from Ruza Ivanovic was partly supported by NERC grant NE/K008536/1. Lauren Gregoire is funded by a UKRI Future Leaders Fellowship (MR/S016961/1). The work made use of the N8 HPC facilities, which are provided and funded by the N8 consortium and EPSRC (EP/K000225/1) and co-ordinated by the Universities of Leeds and Manchester.

We present a new bathymetric compilation of the greater South Georgia region, here defined by a bounding box of ~900km (45W to 19W) by ~580km (63S to 50S) and covering an area of 530,000 km2. The region includes the South Georgia shelf, the Shag Rock shelf (to the west of South Georgia), the surrounding continental slopes and adjacent deep sea. This bathymetry grid was compiled from a variety of different data sources including multibeam swath bathymetry collected from scientific cruises undertaken by British Antarctic Survey (BAS), Alfred Wegener Institute (AWI) and the Institute of Geophysics, University of Texas. The grid has been constructed using a layered hierarchy dependent on accuracy of each dataset. The data is available as a 100m resolution GeoTIFF, ESRI ascii grid or KMZ file of elevation data along with a shapefile indicating the spatial coverage of all the contributing datasets. This work was supported by the National Environmental Research Council (grant number NE/L002531/1). For further information regarding the creation of this dataset please refer to doi:10.1038/srep33163.

In-situ underwater images were gathered during the expedition JR17003a of RRS James Clark Ross to the eastern Antarctic Peninsula in March 2018. The BAS' Shallow Underwater Camera System (SUCS) has been used to estimate faunal density, biomass and species abundance of the benthos and to provide an overview of the conditions of the underwater landscape. Funding was provided by NERC urgency grant NE/R012296/1 'Benthic biodiversity under Antarctic ice-shelves - baseline assessment of the seabed exposed by the 2017 calving of the Larsen-C Ice Shelf'.

We present extensive new bathymetric compilation over Anvers-Hugo Trough, Perrier Trough and Palmer Deep, here defined by the following bounding box: 66.15 to 64.0 W, 65.25 to 63.6 S. This bathymetry grid was compiled from a variety of different data sources including multibeam swath bathymetry collected from scientific cruises undertaken by British Antarctic Survey (BAS), United Kingdom Hydrographic Office, or acquired during RVIB Nathaniel B. Palmer, HMS Protector and RV Maurice Ewing expeditions. The data is available as a 30m resolution grid either in a NetCDF format using WGS84 coordinate system (EPSG: 4326) or in an ESRI ASCII interchange raster format in standard Antarctic polar stereographic coordinates (EPSG 3031). The grid have been created using the MB-system mbgrid program. For further information regarding the creation of this dataset please refer to the associated article and the supplementary information.