Anomalously low winter sea ice extent and early retreat in CE 2018 and 2019 challenge previous notions that winter sea ice in the Bering Sea has been stable over the instrumental record, although long-term records remain limited. Here, we use a record of peat cellulose oxygen isotopes from St. Matthew Island along with isotope-enabled general circulation model (IsoGSM) simulations to generate a 5500-year record of Bering Sea winter sea ice extent. Results show that over the last 5500 years, sea ice in the Bering Sea decreased in response to increasing winter insolation and atmospheric CO, suggesting that the North Pacific is highly sensitive to small changes in radiative forcing. We find that CE 2018 sea ice conditions were the lowest of the last 5500 years, and results suggest that sea ice loss may lag changes in CO concentrations by several decades.
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http://dx.doi.org/10.1126/sciadv.aaz9588 | DOI Listing |
Polar Biol
December 2024
Department of Geography, Durham University, South Road, Durham, DH1 3LE UK.
Knowledge of the spatial distribution of many polar seabird species is incomplete due to the remoteness of their breeding locations. Here, we compiled a new database of published and unpublished records of all known snow petrel breeding sites. We quantified local environmental conditions at sites by appending indices of climate and substrate, and regional-scale conditions by appending 30 year mean (1992-2021) sea-ice conditions within accessible foraging areas.
View Article and Find Full Text PDFSci Data
December 2024
University of Oslo, Department of Geosciences, Oslo, 0313, Norway.
Sea ice is a key element of the global Earth system, with a major impact on global climate and regional weather. Unfortunately, accurate sea ice modeling is challenging due to the diversity and complexity of underlying physics happening there, and a relative lack of ground truth observations. This is especially true for the Marginal Ice Zone (MIZ), which is the area where sea ice is affected by incoming ocean waves.
View Article and Find Full Text PDFSci Data
December 2024
Center for Coastal and Ocean Mapping, University of New Hampshire, Durham, NH, USA.
Knowledge about seafloor depth, or bathymetry, is crucial for various marine activities, including scientific research, offshore industry, safety of navigation, and ocean exploration. Mapping the central Arctic Ocean is challenging due to the presence of perennial sea ice, which limits data collection to icebreakers, submarines, and drifting ice stations. The International Bathymetric Chart of the Arctic Ocean (IBCAO) was initiated in 1997 with the goal of updating the Arctic Ocean bathymetric portrayal.
View Article and Find Full Text PDFSci Total Environ
December 2024
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, HGF-MPG Joint Research Group for Deep-Sea Ecology and Technology, Am Handelshafen 12, 27570 Bremerhaven, Germany.
Microplastic (MP) pollution has reached the remotest areas of the globe, including the polar regions. In the Arctic Ocean, MPs have been detected in ice, snow, water, sediment, and biota, but their temporal dynamics remain poorly understood. To better understand the transport pathways and drivers of MP pollution in this fragile environment, this study aims to assess MPs (≥ 11 μm) in sediment trap samples collected at the HAUSGARTEN observatory (Fram Strait) from September 2019 to July 2021.
View Article and Find Full Text PDFNat Commun
December 2024
Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ, USA.
Antarctic sea ice extent has seen a slight increase over recent decades, yet since 2016, it has undergone a sharp decline, reaching record lows. While the precise impact of anthropogenic forcing remains uncertain, natural fluctuations have been shown to be important for this variability. Our study employs a series of coupled model experiments, revealing that with constant anthropogenic forcing, the primary driver of interannual sea ice variability lies in deep convection within the Southern Ocean, although it is model dependent.
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