Search for: All records

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. 

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 The Arctic is warming faster than anywhere else on Earth, prompting glacial melt, permafrost thaw, and sea ice decline. These severe consequences induce feedbacks that contribute to amplified warming, affecting weather and climate globally. Aerosols and clouds play a critical role in regulating radiation reaching the Arctic surface. However, the magnitude of their effects is not adequately quantified, especially in the central Arctic where they impact the energy balance over the sea ice. Specifically, aerosols called ice nucleating particles (INPs) remain understudied yet are necessary for cloud ice production and subsequent changes in cloud lifetime, radiative effects, and precipitation. Here, we report observations of INPs in the central Arctic over a full year, spanning the entire sea ice growth and decline cycle. Further, these observations are size-resolved, affording valuable information on INP sources. Our results reveal a strong seasonality of INPs, with lower concentrations in the winter and spring controlled by transport from lower latitudes, to enhanced concentrations of INPs during the summer melt, likely from marine biological production in local open waters. This comprehensive characterization of INPs will ultimately help inform cloud parameterizations in models of all scales. 

Low-salinity meltwater from Arctic sea ice and its snow cover accumulates and creates under-ice meltwater layers below sea ice. These meltwater layers can result in the formation of new ice layers, or false bottoms, at the interface of this low-salinity meltwater and colder seawater. As part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), we used a combination of sea ice coring, temperature profiles from thermistor strings and underwater multibeam sonar surveys with a remotely operated vehicle (ROV) to study the areal coverage and temporal evolution of under-ice meltwater layers and false bottoms during the summer melt season from mid-June until late July. ROV surveys indicated that the areal coverage of false bottoms for a part of the MOSAiC Central Observatory (350 by 200 m2) was 21%. Presence of false bottoms reduced bottom ice melt by 7–8% due to the local decrease in the ocean heat flux, which can be described by a thermodynamic model. Under-ice meltwater layer thickness was larger below first-year ice and thinner below thicker second-year ice. We also found that thick ice and ridge keels confined the areas in which under-ice meltwater accumulated, preventing its mixing with underlying seawater. While a thermodynamic model could reproduce false bottom growth and melt, it could not describe the observed bottom melt rates of the ice above false bottoms. We also show that the evolution of under-ice meltwater-layer salinity below first-year ice is linked to brine flushing from the above sea ice and accumulating in the meltwater layer above the false bottom. The results of this study aid in estimating the contribution of under-ice meltwater layers and false bottoms to the mass balance and salt budget for Arctic summer sea ice. 

During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of ‘false bottoms’ below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below. 

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future. 

This dataset contains upper ocean temperature and salinity profiles made during July – September, 2020 as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the Central Arctic. The primary aim of these profiles was to capture the stratification of the upper ocean due to meltwater input throughout the summer melt season and the transition to fall freeze-up. The dataset includes data from two instruments: (i) YSI probe, and (ii) Sontek Castaway. The YSI probe was used to take point measurements of temperature and salinity, allowing for more fine-scale profiles in the upper couple of meters. The Sontek Castaway is a small conductivity, temperature, and depth (CTD) device that was used to make profiles over the upper 10s of meters, here typically in complement to the YSI observations, and are processed to 15 centimeters (cm) vertical resolution. Profiles were made in two primary locations: (i) near-surface of leads surrounding the sea ice floe, using both YSI and Castaway, and (ii) upper ocean directly beneath the sea ice, typically using YSI only. A small number of additional observations were made in coincident melt ponds and the upper ocean directly underneath. Details of collection and processing methods, including quality control for both instruments, can be found in data archive descriptions.