Description: Large amounts of atmospheric carbon can be exported and retained in the deep sea on millennial time scales, buffering global warming. However, while the Barents Sea is one of the most biologically productive areas of the Arctic Ocean, carbon retention times were thought to be short. Here we present observations, complemented by numerical model simulations, that revealed a deep and widespread lateral injection of approximately 2.33 kt C d−1 from the Barents Sea shelf to some 1,200 m of the Nansen Basin, driven by Barents Sea Bottom Water transport. With increasing distance from the outflow region, the plume expanded and penetrated into even deeper waters and the sediment. The seasonally fluctuating but continuous injection increases the carbon sequestration of the Barents Sea by 1/3 and feeds the deep sea community of the Nansen Basin. Our findings combined with those from other outflow regions of carbon-rich polar dense waters highlight the importance of lateral injection as a global carbon sink. Resolving uncertainties around negative feedbacks of global warming due to sea ice decline will necessitate observation of changes in bottom water formation and biological productivity at a resolution high enough to quantify future deep carbon injection.

Description: The growth of phytoplankton at high latitudes was generally thought to begin in open waters of the marginal ice zone once the highly reflective sea ice retreats in spring, solar elevation increases, and surface waters become stratified by the addition of sea-ice melt water. In fact, virtually all recent large-scale estimates of primary production in the Arctic Ocean (AO) assume that phytoplankton production in the water column under sea ice is negligible. However, over the past two decades, an emerging literature showing significant under-ice phytoplankton production on a pan-Arctic scale has challenged our paradigms of Arctic phytoplankton ecology and phenology. This evidence, which builds on previous, but scarce reports, requires the Arctic scientific community to change its perception of traditional AO phenology and urgently revise it. In particular, it is essential to better comprehend, on small and large scales, the changing and variable icescapes, the under-ice light field and biogeochemical cycles during the transition from sea-ice covered to ice-free Arctic waters. Here, we provide a baseline of our current knowledge of under-ice blooms (UIBs), by defining their ecology and their environmental setting, but also their regional peculiarities (in terms of occurrence, magnitude, and assemblages), which is shaped by a complex AO. To this end, a multidisciplinary approach, i.e., combining expeditions and modern autonomous technologies, satellite, and modeling analyses, has been used to provide an overview of this pan-Arctic phenological feature, which will become increasingly important in future marine Arctic biogeochemical cycles.

Description: The Arctic Ocean is a sentinel for climate change as it warms more than twice faster than the global average. A long list of alterations have already been documented. The future implications for primary producers and consequently for the entire ecosystem and biogeochemical cycles are still uncertain. The objective of this project is to identify tipping points in the Arctic phytoplankton dynamics, their environmental drivers and their implications for biogeochemical cycles using biogeochemical modeling.

Description: Being a vast carbon pool, ocean is an important component of the climate system. It absorbs not only the heat trapped by the greenhouse gasses in the atmosphere, but also a quarter of the anthropogenic carbon dioxide (CO2) emissions itself. Ocean carbon uptake, however, decreases the pH in seawater that has negative implications for marine life. Despite the progress over the last decades, observational data is still sparse in the global oceans. Moreover, there are still gaps in understanding key processes and relevant feedbacks of global ocean carbon source/sink in response to atmospheric CO2 scenarios. Marine biogeochemical models are helpful tools to bridge these gaps. In this study we coupled the Finite-volumE Sea ice-Ocean Model (FESOM2.1) to the Regulated Ecosystem Model (REcoM2). Compared to the previous version FESOM1.4-REcoM2, the model utilizes a new dynamical core based on a finite volume discretization instead of finite elements, but retains the biogeochemical part. Mocsy2.0 computes carbonate chemistry including water vapor correction. It operates on variable mesh resolution. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of small-scale dynamics in key regions at affordable computational cost. Here we present an assessment of the ocean and biogeochemical states simulated with FESOM2.1-REcoM2 in a relatively low spatial resolution global configuration forced with JRA55-do atmospheric reanalysis. A bias present in the previous model version FESOM1.4-REcoM2 in annual mean global ocean-atmosphere CO2 flux can be significantly reduced. Besides, the computational efficiency is about 2-3 times higher than FESOM1.4-REcoM2. Thus, the new coupled model is a promising tool for ocean biogeochemical modelling applications.

Description: Abstract Primary production in the Central Arctic Ocean (CAO) is limited by light and bioavailable nutrients. With the decline of the sea-ice cover in recent decades, and the resulting increase in light availability, nitrate limitation has been speculated to become more prominent. We used an eddy-permitting biogeochemical model simulation to estimate nitrate advective fluxes at different spatio-temporal scales (synoptic, mesoscale and sub-mesoscale) over the 1985–2015 period. We found that the pan-Arctic continental slope contributes disproportionately to the Dissolved Inorganic Nitrogen supply and that this supply is intensifying through two main processes: lateral eddy transport and upwelling. Despite this increasing supply in nitrate and an intensification of ocean dynamics, the nutrient supply is decreasing everywhere else in the central basins and the simulation indicates that the CAO is still shifting from light to nutrient limitation.

Description: Remotely-sensed Ocean color data offer a unique opportunity for studying variations of bio-optical properties which is especially valuable in the Arctic Ocean (AO) where in situ data are sparse. In this study, we re-processed the raw data from the Sea-viewing Wide Field-of-View (SeaWiFS, 1998–2010) and the MODerate resolution Imaging Spectroradiometer (MODIS, 2003–2016) ocean-color sensors to ensure compatibility with the first ocean color sensor, namely, the Coastal Zone Color Scanner (CZCS, 1979–1986). Based on a bio-regional approach, this study assesses the quality of this new homogeneous pan-Arctic Chl a dataset, which provides the longest (but non-continuous) ocean color time-series ever produced for the AO (37 years long between 1979 and 2016). We show that despite the temporal gaps between 1986 and 1998 due to the absence of ocean color satellite, the time series is suitable to establish a baseline of phytoplankton biomass for the early 1980s, before sea-ice loss accelerated in the AO. More importantly, it provides the opportunity to quantify decadal changes over the AO revealing for instance the continuous Chl a increase in the inflow shelves such as the Barents Sea since the CZCS era.

Description: The presence of liquid or ice as cloud phase determines the climate radiative effect of Arctic clouds, and thus, their contribution to surface warming. Biogenic aerosols from phytoplankton production localized in leads or open water were shown to act as cloud condensation nuclei (liquid phase) or ice nuclei (ice phase) in remote regions. As extensive measurements of biogenic aerosol precursors are still scarce, we conduct a modelling study and use acidic polysaccharides (PCHO) and transparent exopolymer particles (TEP) as tracers. In this study, we integrate processes of algal PCHO excretion during phytoplankton growth or under nutrient limitation and processes of TEP formation, aggregation and also remineralization into the ecosystem model REcoM2. The biogeochemical processes are described by two functional phytoplankton and two zooplankton classes, along with sinking detritus and several (in)organic carbon and nutrient classes. REcoM2 is coupled to the finite-volume sea ice ocean circulation model FESOM2 with a high resolution of up to 4.5 km in the Arctic. We will present the first results of simulated TEP distribution and seasonality patterns at pan-Arctic scale over the last decades. We will elucidate drivers of the seasonal cycle and will identify regional hotspots of TEP production and its decay. We will also address possible impacts of global warming and Arctic amplification of the last decades in our evaluation, as we expect a strong effect of global warming on microbial metabolic rates, phytoplankton growth, and composition of phytoplankton functional types. The results will be evaluated by comparison to a set of in-situ measurements (PASCAL, FRAM, MOSAiC). It is further planned that an atmospheric aerosol-climate model will build on the modeled biogenic aerosol precursors as input to quantify the net aerosol radiative effects. This work is part of the DFG TR 172 Arctic Amplification.

Description: Climate warming and related drivers of soil thermal change in the Arctic are expected to modify the distribution and dynamics of carbon contained in perennially frozen grounds. Thawing of permafrost in the Mackenzie River watershed of northwestern Canada, coupled with increases in river discharge and coastal erosion, triggers the release of terrestrial organic matter (OMt) from the largest Arctic drainage basin in North America into the Arctic Ocean. While this process is ongoing and its rate is accelerating, the fate of the newly mobilized organic matter as it transits from the watershed through the delta and into the marine system remains poorly understood. In the framework of the European Horizon 2020 Nunataryuk programme, and as part of the Work Package 4 (WP4) Coastal Waters theme, four field expeditions were conducted in the Mackenzie Delta region and southern Beaufort Sea from April to September 2019. The temporal sampling design allowed the survey of ambient conditions in the coastal waters under full ice cover prior to the spring freshet, during ice breakup in summer, and anterior to the freeze-up period in fall. To capture the fluvial-marine transition zone, and with distinct challenges related to shallow waters and changing seasonal and meteorological conditions, the field sampling was conducted in close partnership with members of the communities of Aklavik, Inuvik and Tuktoyaktuk, using several platforms, namely helicopters, snowmobiles, and small boats. Water column profiles of physical and optical variables were measured in situ, while surface water, groundwater, and sediment samples were collected and preserved for the determination of the composition and sources of OMt, including particulate and dissolved organic carbon (POC and DOC), and colored dissolved organic matter (CDOM), as well as a suite of physical, chemical, and biological variables. Here we present an overview of the standardized datasets, including hydrographic profiles, remote sensing reflectance, temperature and salinity, particle absorption, nutrients, dissolved organic carbon, particulate organic carbon, particulate organic nitrogen, CDOM absorption, fluorescent dissolved organic matter intensity, suspended particulate matter, total particulate carbon, total particulate nitrogen, stable water isotopes, radon in water, bacterial abundance, and a string of phytoplankton pigments including total chlorophyll. Datasets and related metadata can be found in (10.1594/PANGAEA.937587).

Description: In the version of this article initially published, author Cora Hörstmann was wrongly listed with a second affiliation with the Department of Ecoscience–Applied Marine Ecology and Modelling, Aarhus University rather than the Mediterranean Institute of Oceanography (MIO), Marseille, France. Furthermore, references 83–97, now found in the Supplementary Tables caption, were wrongly cited in the Data Availability section. The errors have been corrected in the HTML and PDF versions of the article.