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  1. This dataset includes the concentrations and conditional stability constants of iron-binding organic ligands in samples collected during an extension study of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project and measured by competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-AdCSV). These samples originated from a spring melt field campaign conducted in Utqiaġvik, Alaska. This campaign was designed when the MOSAiC expedition could no longer accommodate spring melt trace metal work. The melt season was a key period of our effort during MOSAiC and necessary for addressing our proposed hypotheses. Using facilities in Utqiaġvik hosted by Ukpeaǵvik Iñupiat Corporation (UIC), we studied sea ice processes during the spring melt cycle from April – June of 2021. Four UAF Scientists participated in the field campaign. During that time, sea ice, snow and water samples were obtained from homogenous, flat, landfast ice at high (2-3 times a week) temporal resolution. 
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  2. Using facilities in Utqiaġvik hosted by Ukpeaǵvik Iñupiat Corporation (UIC), we studied sea ice processes during the spring melt cycle from April – June of 2021. During that time, sea ice, snow and water samples were obtained from homogenous, flat, landfast ice. The dataset produced from this campaign is also unique in that its temporal coverage of the spring melt is higher resolution than any other biogeochemical sampling conducted in this region previously (2-3 times a week for all parameters sampled). The datasets herein include sea ice macronutrients, salinity, temperature, and density; sea ice micronutrients; and bottom ice chlorophyll. 
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  3. Abstract

    Microalgae are the main source of the omega‐3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), essential for the healthy development of most marine and terrestrial fauna including humans. Inverse correlations of algal EPA and DHA proportions (% of total fatty acids) with temperature have led to suggestions of a warming‐induced decline in the global production of these biomolecules and an enhanced importance of high latitude organisms for their provision. The cold Arctic Ocean is a potential hotspot of EPA and DHA production, but consequences of global warming are unknown. Here, we combine a full‐seasonal EPA and DHA dataset from the Central Arctic Ocean (CAO), with results from 13 previous field studies and 32 cultured algal strains to examine five potential climate change effects; ice algae loss, community shifts, increase in light, nutrients, and temperature. The algal EPA and DHA proportions were lower in the ice‐covered CAO than in warmer peripheral shelf seas, which indicates that the paradigm of an inverse correlation of EPA and DHA proportions with temperature may not hold in the Arctic. We found no systematic differences in the summed EPA and DHA proportions of sea ice versus pelagic algae, and in diatoms versus non‐diatoms. Overall, the algal EPA and DHA proportions varied up to four‐fold seasonally and 10‐fold regionally, pointing to strong light and nutrient limitations in the CAO. Where these limitations ease in a warming Arctic, EPA and DHA proportions are likely to increase alongside increasing primary production, with nutritional benefits for a non‐ice‐associated food web.

     
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  4. Abstract. Barium is widely used as a proxy for dissolved silicon and particulateorganic carbon fluxes in seawater. However, these proxy applications arelimited by insufficient knowledge of the dissolved distribution of Ba([Ba]). For example, there is significant spatial variability in thebarium–silicon relationship, and ocean chemistry may influence sedimentaryBa preservation. To help address these issues, we developed 4095 models forpredicting [Ba] using Gaussian process regression machine learning. Thesemodels were trained to predict [Ba] from standard oceanographic observationsusing GEOTRACES data from the Arctic, Atlantic, Pacific, and Southernoceans. Trained models were then validated by comparing predictions againstwithheld [Ba] data from the Indian Ocean. We find that a model trained usingdepth, temperature, and salinity, as well as dissolved dioxygen, phosphate,nitrate, and silicate, can accurately predict [Ba] in the Indian Ocean with amean absolute percentage deviation of 6.0 %. We use this model tosimulate [Ba] on a global basis using these same seven predictors in theWorld Ocean Atlas. The resulting [Ba] distribution constrains the Ba budgetof the ocean to 122(±7) × 1012 mol and revealsoceanographically consistent variability in the barium–silicon relationship. We then calculate the saturation state of seawater with respect to barite. This calculation reveals systematic spatial and vertical variations in marine barite saturation and shows that the ocean below 1000 m is at equilibrium with respect tobarite. We describe a number of possible applications for our model outputs, ranging from use in mechanistic biogeochemical models to paleoproxy calibration. Ourapproach demonstrates the utility of machine learning in accurately simulatingthe distributions of tracers in the sea and provides a framework that couldbe extended to other trace elements. Our model, the data used in training and validation, and global outputs are available in Horner and Mete (2023, https://doi.org/10.26008/1912/bco-dmo.885506.2). 
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  5. Abstract

    Radium isotopes, which are sourced from sediments, are useful tools for studying potential climate‐driven changes in the transfer of shelf‐derived elements to the open Arctic Ocean. Here we present observations of radium‐228 and radium‐226 from the Siberian Arctic, focusing on the shelf‐basin boundary north of the Laptev and East Siberian Seas. Water isotopes and nutrients are used to deconvolve the contributions from different water masses in the study region, and modeled currents and water parcel back‐trajectories provide insights on water pathways and residence times. High radium levels and fractions of meteoric water, along with modeled water parcel back‐trajectories, indicate that shelf‐ and river‐influenced water left the East Siberian Shelf around 170°E in 2021; this is likely where the Transpolar Drift was entering the central Arctic. A transect extending from the East Siberian Slope into the basin is used to estimate a radium‐228 flux of 2.67 × 107atoms m−2 d−1(possible range of 1.23 × 107–1.04 × 108atoms m−2 d−1) from slope sediments, which is comparable to slope fluxes in other regions of the world. A box model is used to determine that the flux of radium‐228 from the Laptev and East Siberian Shelves is 9.03 × 107atoms m−2 d−1(possible range of 3.87 × 107–1.56 × 108atoms m−2 d−1), similar to previously estimated fluxes from the Chukchi Shelf. These three shelves contribute a disproportionately high amount of radium to the Arctic, highlighting their importance in regulating the chemistry of Arctic surface waters.

     
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  6. First-year sea-ice thickness, draft, salinity, temperature, and density were measured during near-weekly surveys at the main first-year ice coring site (MCS-FYI) during the MOSAiC expedition (legs 1 to 4). The ice cores were extracted either with a 9-cm (Mark II) or 7.25-cm (Mark III) internal diameter ice corers (Kovacs Enterprise, US). This data set includes data from 23 coring site visits and were performed from 28 October 2019 to 29 July 2020 at coring locations within 130 m to each other in the MOSAiC Central Observatory. During each coring event, ice temperature was measured in situ from a separate temperature core, using Testo 720 thermometers in drill holes with a length of half-core-diameter at 5-cm vertical resolution. Ice bulk practical salinity was measured from melted core sections at 5-cm resolution using a YSI 30 conductivity meter. Ice density was measured using the hydrostatic weighing method (Pustogvar and Kulyakhtin, 2016) from a density core in the freezer laboratory onboard Polarstern at the temperature of –15°C. Relative volumes of brine and gas were estimated from ice salinity, temperature and density using Cox and Weeks (1983) for cold ice and Leppäranta and Manninen (1988) for ice warmer than –2°C.The data contains the event label (1), time (2), and global coordinates (3,4) of each coring measurement and sample IDs (13, 15). Each salinity core has its manually measured ice thickness (5), ice draft (6), core length (7), and mean snow height (22). Each core section has the total length of its top (8) and bottom (9) measured in situ, as well estimated depth of section top (10), bottom (11), and middle (12). The depth estimates assume that the total length of all core sections is equal to the measured ice thickness. Each core section has the value of its practical salinity (14), isotopic values (16, 17, 18) (Meyer et al., 2000), as well as sea ice temperature (19) and ice density (20) interpolated to the depth of salinity measurements. The global coordinates of coring sites were measured directly. When it was not possible, coordinates of the nearby temperature buoy 2019T66 were used. Ice mass balance buoy 2019T66 installation is described in doi:10.1594/PANGAEA.938134. Brine volume (21) fraction estimates are presented only for fraction values from 0 to 30%. Each core section also has comments (23) describing if the sample is from a false bottom, from rafted ice or has any other special characteristics.Macronutrients from the salinity core, and more isotope data will be published in a subsequent version of this data set. 
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  7. Abstract

    Determining the proportions of Atlantic and Pacific Ocean seawater entering the Arctic Ocean is important both for understanding the mass balance of this basin as well as its contribution to formation of North Atlantic deep water. To quantify the distribution and amount of Pacific and Atlantic origin seawater in the western Arctic Ocean, we used dissolved Ga in a four‐component linear endmember mixing model. Previously, nutrients, combined in their Redfield ratios, have been used to separate Pacific‐ and Atlantic‐derived waters. These nutrient tracers are not conservative in practice, and there is a need to find quantities that are conserved. Dissolved Ga concentrations show measurable contrast between Atlantic and Pacific source waters, shelf‐influenced waters show little impact of shelf processes on the dissolved Ga distribution, and dissolved Ga in the Arctic basins is conserved along isopycnal surfaces. Thus, we explored the potential of Ga as a new parameter in Arctic source water deconvolution. The Ga‐informed deconvolution was compared to that generated with the NO3:PO4relationship. While distributions of the water masses were qualitatively similar, the Ga‐based deconvolution predicted higher amounts of Pacific water at depths between 150 and 300 m. The Ga‐based decomposition yields a smoother transition between the halocline and Atlantic layers, while nutrient‐based solutions have sharper transitions. A 1‐D advection‐diffusion model was used to constrain estimates of vertical diffusivity (Kz). The Ga‐based Kzestimates agreed better with those from salinity and temperature than the nutrient method. The Ga‐based approach implies greater vertical mixing between the Pacific and Atlantic waters.

     
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