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Abstract Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km²drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS). These data are aligned into an ice-fixed, lagrangian reference frame such that topographic changes (e.g., snow accumulation) can be observed for time periods of up to six months. Usingin-situmeasurements, we have validated the vertical accuracy of the alignment to ± 0.011 m. This data collection and processing workflow is the culmination of several prior measurement campaigns and may be generally applied for repeat TLS measurements on drifting sea ice. We present a description of the data, a software package written to process and align these data, and the philosophy of the data processing. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide valuable context for co-located measurements. 

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. 

Abstract Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition. 

Abstract Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetry‐derived sea ice thickness. During winter of the MOSAiC Expedition, the “KuKa” dual‐frequency, fully polarized Ku‐ and Ka‐band radar was deployed in “stare” nadir‐looking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches were investigated: dual‐frequency, dual‐polarization and waveform shape, and compared to independent snow depth measurements. Novel dual‐polarization approaches yieldedr²values up to 0.77. Mean snow depths agreed within 1 cm, even for data sub‐banded to CryoSat‐2 SIRAL and SARAL AltiKa bandwidths. Snow depths from co‐polarized dual‐frequency approaches were at least a factor of four too small and had ar²0.15 or lower.r²for waveform shape techniques reached 0.72 but depths were underestimated. Snow depth retrievals using polarimetric information or waveform shape may therefore be possible from airborne/satellite radar altimeters. 

Abstract The formation of platelet ice is well known to occur under Antarctic sea ice, where subice platelet layers form from supercooled ice shelf water. In the Arctic, however, platelet ice formation has not been extensively observed, and its formation and morphology currently remain enigmatic. Here, we present the first comprehensive, long‐term in situ observations of a decimeter thick subice platelet layer under free‐drifting pack ice of the Central Arctic in winter. Observations carried out with a remotely operated underwater vehicle (ROV) during the midwinter leg of the MOSAiC drift expedition provide clear evidence of the growth of platelet ice layers from supercooled water present in the ocean mixed layer. This platelet formation takes place under all ice types present during the surveys. Oceanographic data from autonomous observing platforms lead us to the conclusion that platelet ice formation is a widespread but yet overlooked feature of Arctic winter sea ice growth. 

Samples for the analysis of dissolved nutrients were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) from the water column, sea ice cores and from special events/locations (e.g., leads, melt ponds, brine, incubation experiments). Samples for dissolved inorganic nutrients (NO3 +NO2 , NO2 , PO4 , Si(OH)4, NH4 ) were analysed onboard during PS122 legs 1 to 3, with duplicate samples collected from CTD casts for later analysis of total dissolved nitrogen (TDN) and total dissolved phosphorus (TDP). From leg 4, all samples collected were stored frozen at -20°C for later analysis. Analyses of stored samples were carried out at the AWI Nutrient Facility between January and March 2021. Nutrient analyses onboard and on land were carried out using a Seal Analytical AA3 continuous flow autoanalyser, controlled by the AACE software version 7.09. Best practice procedures for the measurement of nutrients were adopted following GO-SHIP recommendations (Hydes et al., 2010; Becker et al., 2019). Descriptions of sample collection and handling can be found in the various cruise reports (Haas & Rabe, 2023; Kanzow & Damm, 2023; Rex & Metfies, 2023; Rex & Nicolaus, 2023; Rex & Shupe, 2023). Here we provide data from the water column, obtained from the analysis of discrete samples collected from CTD-Rosette casts from Polarstern (https://sensor.awi.de/?site=search&q=vessel:polarstern:ctd_sbe9plus_321) and Ocean City (https://sensor.awi.de/?site=search&q=vessel:polarstern:ctd_sbe9plus_935). Data from sea ice cores and special events are presented elsewhere. Data from sea ice cores and special events are presented elsewhere. For reference, here we included data from CTD-BTL files associated with nutrient samples. These data are presented by Tippenhauer et al. (2023) Polarstern CTD and Tippenhauer et al. (2023) Ocean City CTD. 

Samples for the analysis of dissolved nutrients were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) from the water column, sea ice cores and from special events/locations (e.g., leads, melt ponds, brine, incubation experiments). Samples for dissolved inorganic nutrients (NO3 +NO2 , NO2 , PO4 , Si(OH)4, NH4 ) were analysed onboard during PS122 legs 1 to 3, with duplicate samples collected from CTD casts for later analysis of total dissolved nitrogen (TDN) and total dissolved phosphorus (TDP). From leg 4, all samples collected were stored frozen at -20°C for later analysis. Analyses of stored samples were carried out at the AWI Nutrient Facility between January and March 2021. Nutrient analyses onboard and on land were carried out using a Seal Analytical AA3 continuous flow autoanalyser, controlled by the AACE software version 7.09. Best practice procedures for the measurement of nutrients were adopted following GO-SHIP recommendations (Hydes et al., 2010; Becker et al., 2019). Descriptions of sample collection and handling can be found in the various cruise reports (Haas & Rabe, 2023; Kanzow & Damm, 2023; Rex & Metfies, 2023; Rex & Nicolaus, 2023; Rex & Shupe, 2023). Here we provide data from the water column, obtained from the analysis of discrete samples collected from CTD-Rosette casts from Polarstern (https://sensor.awi.de/?site=search&q=vessel:polarstern:ctd_sbe9plus_321) and Ocean City (https://sensor.awi.de/?site=search&q=vessel:polarstern:ctd_sbe9plus_935). Data from sea ice cores and special events are presented elsewhere. Data from sea ice cores and special events are presented elsewhere. For reference, here we included data from CTD-BTL files associated with nutrient samples. These data are presented by Tippenhauer et al. (2023) Polarstern CTD and Tippenhauer et al. (2023) Ocean City CTD. 

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. 

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. 

Repeated transects have become the backbone of spatially distributed ice and snow thickness measurements crucial for understanding of ice mass balance. Here we detail the transects at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) 2019–2020, which represent the first such measurements collected across an entire season. Compared with similar historical transects, the snow at MOSAiC was thin (mean depths of approximately 0.1–0.3 m), while the sea ice was relatively thick first-year ice (FYI) and second-year ice (SYI). SYI was of two distinct types: relatively thin level ice formed from surfaces with extensive melt pond cover, and relatively thick deformed ice. On level SYI, spatial signatures of refrozen melt ponds remained detectable in January. At the beginning of winter the thinnest ice also had the thinnest snow, with winter growth rates of thin ice (0.33 m month−1 for FYI, 0.24 m month−1 for previously ponded SYI) exceeding that of thick ice (0.2 m month−1). By January, FYI already had a greater modal ice thickness (1.1 m) than previously ponded SYI (0.9 m). By February, modal thickness of all SYI and FYI became indistinguishable at about 1.4 m. The largest modal thicknesses were measured in May at 1.7 m. Transects included deformed ice, where largest volumes of snow accumulated by April. The remaining snow on level ice exhibited typical spatial heterogeneity in the form of snow dunes. Spatial correlation length scales for snow and sea ice ranged from 20 to 40 m or 60 to 90 m, depending on the sampling direction, which suggests that the known anisotropy of snow dunes also manifests in spatial patterns in sea ice thickness. The diverse snow and ice thickness data obtained from the MOSAiC transects represent an invaluable resource for model and remote sensing product development.