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  • 1
    Keywords: Oceanography. ; Environmental sciences. ; Marine ecology -- Arctic Ocean. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (461 pages)
    Edition: 1st ed.
    ISBN: 9789401788632
    DDC: 577.82091632
    Language: English
    Note: Intro -- Contents -- Contributors -- Chapter 1: The Pacific Arctic Region: An Introduction -- 1.1 Introduction -- 1.2 The Pacific Arctic Region -- 1.3 Physical Processes, Hydrography and Sea Ice: Field and Modeling -- 1.4 Atmospheric Forcing and Sea Ice -- 1.5 Physical Processes and Modeling -- 1.6 Carbon Transformations and Cycling -- 1.7 Lower and Upper Trophic Levels and Ecosystem Modeling -- 1.8 Summary -- References -- Chapter 2: Recent and Future Changes in the Meteorology of the Pacific Arctic -- 2.1 Introduction -- 2.2 Climatological Fields -- 2.3 Storms and Temporal Variability -- 2.4 The Differences of the Pacific Sector Relative to the Larger Arctic System -- 2.5 The Future Climate of the Pacific Arctic -- 2.6 Summary -- References -- Chapter 3: Recent Variability in Sea Ice Cover, Age, and Thickness in the Pacific Arctic Region -- 3.1 Introduction -- 3.2 Sea Ice Cover -- 3.2.1 Trends in Sea Ice Cover -- 3.2.2 Interannual Variability in Sea Ice Cover -- 3.3 Sea Ice Age -- 3.3.1 Sea Ice Age Data and Analysis -- 3.3.2 Recent Variability in Sea Ice Age -- 3.4 Sea Ice Thickness -- 3.4.1 Sea Ice Thickness Data and Background -- 3.4.2 Sea Ice Thickness Model Description -- 3.4.3 Sea Ice Thickness Model Validation -- 3.4.4 Recent Variability in Modeled Sea Ice Thickness -- 3.4.5 Potential Mechanisms of Sea Ice Thinning -- 3.5 Implications and Possible Future States -- 3.6 Summary -- References -- Chapter 4: Abrupt Climate Changes and Emerging Ice- Ocean Processes in the Pacific Arctic Region and the Bering Sea -- 4.1 Introduction -- 4.2 Data and Methods -- 4.3 Leading Climate Forcing: Arctic Dipole (DA) Pattern -- 4.4 Investigating Mechanisms Responsible for Arctic Sea Ice Minima Using PIOMAS -- 4.5 Bering Strait Heat Transport and the DA -- 4.6 Modeling the Bering Sea Cold Pool Using CIOM. , 4.7 Modeling Landfast Ice in the Beaufort-Chukchi Seas Using CIOM -- 4.8 Possible Air-Ice-Sea Feedback Loops in the Western Arctic -- 4.9 Summary -- References -- Chapter 5: The Large Scale Ocean Circulation and Physical Processes Controlling Pacific-Arctic Interactions -- 5.1 Introduction -- 5.2 The Northern North Pacific, Gulf of Alaska, and Alaskan Stream -- 5.3 Western Subarctic Gyre -- 5.4 Bering Sea -- 5.5 Chukchi Sea -- 5.6 Beaufort Sea -- 5.7 Heat/Freshwater Content and Sea Ice -- 5.8 Summary -- References -- Chapter 6: Shelf-Break Exchange in the Bering, Chukchi and Beaufort Seas -- 6.1 Introduction -- 6.2 The Bering Shelf-Break -- 6.3 The Chukchi and Beaufort Shelf-Break -- 6.3.1 Shelf-Basin Connections -- 6.3.2 Instabilities of the Shelf-Break Jet -- 6.3.3 Wind-Driven Exchange -- 6.4 Undersea Canyons of the Chukchi and Beaufort Shelves -- 6.4.1 Herald Canyon -- 6.4.2 Barrow Canyon -- 6.4.3 Mackenzie Trough -- 6.5 Polynya-Formed Dense Shelf Water -- 6.6 Summary -- 6.6.1 Bering Shelf-Break -- 6.6.2 Chukchi/Beaufort Shelf-Break -- References -- Chapter 7: On the Flow Through Bering Strait: A Synthesis of Model Results and Observations -- 7.1 Introduction -- 7.2 Model Descriptions -- 7.2.1 Bering Ecosystem Study Ice-Ocean Modeling and Assimilation System (BESTMAS) -- 7.2.2 Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) -- 7.2.3 Naval Postgraduate School Arctic Modeling Effort (NAME) -- 7.2.4 Nucleus for European Modelling of the Ocean (NEMO) with ORCA Configuration -- 7.2.5 Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) -- 7.3 Bering Strait Observational Mooring Data -- 7.4 Results -- 7.5 Discussion -- 7.6 Summary -- References -- Chapter 8: Carbon Fluxes Across Boundaries in the Pacific Arctic Region in a Changing Environment -- 8.1 Introduction -- 8.2 Geographic and Water Mass Features. , 8.2.1 Geographic Definition and Description -- 8.2.2 Water-Mass Characterizations -- 8.3 Pacific Ocean Inflow -- 8.4 Fluxes Across the Arctic Land-Sea Interface -- 8.5 CO 2 Flux Across the Air-Sea Boundary -- 8.5.1 Sea Surface p CO 2 Distribution -- 8.5.2 Air-Sea CO 2 Flux -- 8.6 Impact of Seasonal Sea-Ice Cycle -- 8.7 Overall DIC Budget -- 8.8 Summary -- References -- Chapter 9: Carbon Biogeochemistry of the Western Arctic: Primary Production, Carbon Export and the Controls on Ocean Acidification -- 9.1 Introduction -- 9.2 Primary Production -- 9.2.1 Northern Bering Sea -- 9.2.2 Chukchi Sea -- 9.2.3 Deep Canada Basin -- 9.3 DOC Production -- 9.3.1 Spatial Variability -- 9.3.2 The Use of DOC/Salinity Relationships -- 9.3.3 Dynamical Characterization of tDOC-Inputs & -- Sinks -- 9.4 Export Flux of Particulate Organic Carbon -- 9.4.1 Regional Case Studies -- 9.4.1.1 Chukchi Sea: The Shelf Basin Interaction Study (SBI-II) -- 9.4.1.2 Mackenzie Shelf: Canadian Arctic Shelf Exchange Study (CASES) -- 9.4.1.3 Laptev Sea, Northern Baffin Bay and the Beaufort Sea Shelves -- 9.4.1.4 Eastern and Central Arctic Ocean: Polarstern ARK-XXII/2 Expedition -- 9.4.2 Conclusions -- 9.5 Grazing -- 9.6 Benthic Carbon Cycling -- 9.6.1 Sediment Nutrient Efflux -- 9.7 Contribution of Heterotrophic Bacteria to Carbon Cycling -- 9.7.1 Respiration by Heterotrophic Bacteria -- 9.7.2 Biomass Production by Heterotrophic Bacteria and Phytoplankton -- 9.7.3 Growth Efficiency in the Arctic Ocean -- 9.7.4 Implications for Shelf-Basin Exchange -- 9.8 Ocean Acidification -- 9.8.1 The Bering Sea -- 9.8.2 The Western Arctic Ocean -- 9.9 Summary -- References -- Chapter 10: Biodiversity and Biogeography of the Lower Trophic Taxa of the Pacific Arctic Region: Sensitivities to Climate Change -- 10.1 General Introduction -- 10.2 Phytoplankton in the PAR -- 10.2.1 Introduction. , 10.2.2 Phytoplankton and Sea Ice Algae: An Overview -- 10.2.3 Latitudinal Variation of Phytoplankton Biodiversity and Community Composition in the Western Arctic Ocean -- 10.2.4 Synechococcus -- 10.2.5 Sensitivities to Habitat Changes -- 10.3 Heterotrophic Microbes in the PAR -- 10.3.1 Introduction -- 10.3.2 Viruses -- 10.3.3 Bacterial Diversity -- 10.3.4 Bacterial and Archaeal Diversity Levels in the Arctic Ocean Versus Lower-Latitude Oceans -- 10.3.5 Diversity and Distribution of Heterotrophic Protists -- 10.3.5.1 Diversity of Heterotrophic Protists Assessed by Microscopy -- 10.3.5.2 Diversity of Heterotrophic Protists Assessed by Molecular Genetics -- 10.3.5.3 Biogeographical and Depth Distribution of Heterotrophic Protists -- 10.3.5.4 Heterotrophic Microbes: Future Research -- 10.4 Benthic Fauna of the PAR -- 10.4.1 Introduction -- 10.4.2 Benthic Fauna of the Northern Bering, Chukchi, and Western Beaufort Seas -- 10.4.2.1 Environmental Setting -- 10.4.2.2 General Biogeography -- 10.4.3 Benthic Invertebrate Patterns in the Canadian Beaufort Sea Shelf -- 10.4.3.1 Environmental Setting -- 10.4.3.2 General Biogeography and Biodiversity -- 10.4.4 Deep-Sea Benthos -- 10.4.5 Effect of Climate Change on Benthic Fauna of the PAR -- 10.5 Sea Ice Associated Diversity and Production in the PAR -- 10.5.1 Introduction -- 10.5.2 Primary Producers: Diversity, Abundance and Activity -- 10.5.3 Sea Ice Meiofauna Abundance and Diversity -- 10.5.4 Effects of Climate Change -- 10.6 Biodiversity and Biogeography of Metazoan Zooplankton of the PAR -- 10.6.1 Introduction -- 10.6.2 Species Diversity -- 10.6.3 Zooplankton Advection: Expatriate Analysis -- 10.6.4 Horizontal Zooplankton Community Structure -- 10.6.5 Vertical Distribution of Zooplankton in the Deep Waters of the PAR -- 10.6.6 Long-Term Change -- 10.7 Summary -- References. , Chapter 11: Marine Fishes, Birds and Mammals as Sentinels of Ecosystem Variability and Reorganization in the Pacific Arctic Region -- 11.1 Introduction -- 11.1.1 Ecological Scale -- 11.2 Overview: Ecology of Upper Trophic Level (UTL) Species -- 11.2.1 Fishes and Crabs -- 11.2.1.1 Northern Bering and Chukchi Seas -- 11.2.1.2 Beaufort Sea -- 11.2.2 Marine Birds -- 11.2.2.1 At-Sea Distribution -- 11.2.2.2 Breeding Colonies -- 11.2.2.3 Seasonal Dynamics -- 11.2.3 Marine Mammals -- 11.2.3.1 Core Arctic Species -- 11.2.3.2 Seasonally Migrant Species -- 11.3 Case Studies: Responses of UTL Species to Environmental Variability -- 11.3.1 Fishes and Crabs -- 11.3.1.1 Salmon and Forage Fish in the Northern Bering Sea -- 11.3.1.2 Snow Crab in the Chukchi Sea -- 11.3.1.3 Demersal Fish and Crab in the Beaufort Sea -- 11.3.2 Marine Birds -- 11.3.2.1 Nesting Auklets and the Anadyr Current -- 11.3.3 Eiders During Winter and Migration -- 11.3.4 Marine Mammals -- 11.3.4.1 Timing and Relative Abundance of Bowhead Whales Feeding in the Canadian Beaufort Sea -- 11.3.4.2 Body Condition of Ringed Seals in the Western Canadian Arctic -- 11.3.4.3 Changes in Life-History and Diet of Walruses and Seals in the Northern Bering and Chukchi Seas -- 11.4 UTL Species as Ecosystem Sentinels -- 11.4.1 UTL-Focused Research Framework -- 11.4.1.1 Trophic Interactions -- 11.4.1.2 Foraging Dynamics -- 11.4.1.3 Species Composition -- 11.5 Summary -- 11.5.1 Tracking Biological Responses in an Era of Rapid Change and Extreme Events -- 11.5.2 Integration of Science and Local Knowledge -- 11.6 Personal Communications -- References -- Chapter 12: Progress and Challenges in Biogeochemical Modeling of the Pacific Arctic Region -- 12.1 Introduction -- 12.2 PAR Characteristics Particularly Relevant for Biogeochemical Modeling -- 12.3 A Brief History of PAR Biogeochemical Models. , 12.4 Modeling PAR in 1-D: Introduction and Locations.
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  • 2
    Publication Date: 2022-09-22
    Description: Simulating sea ice drift and deformation in the Arctic Ocean is still a challenge because of the multiscale interaction of sea ice floes that compose the Arctic Sea ice cover. The Sea Ice Rheology Experiment (SIREx) is a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). In SIREx, skill metrics are designed to evaluate different recently suggested approaches for modeling linear kinematic features (LKFs) to provide guidance for modeling small‐scale deformation. These LKFs are narrow bands of localized deformation that can be observed in satellite images and also form in high resolution sea ice simulations. In this contribution, spatial and temporal properties of LKFs are assessed in 36 simulations of state‐of‐the‐art sea ice models and compared to deformation features derived from the RADARSAT Geophysical Processor System. All simulations produce LKFs, but only very few models realistically simulate at least some statistics of LKF properties such as densities, lengths, or growth rates. All SIREx models overestimate the angle of fracture between conjugate pairs of LKFs and LKF lifetimes pointing to inaccurate model physics. The temporal and spatial resolution of a simulation and the spatial resolution of atmospheric boundary condition affect simulated LKFs as much as the model's sea ice rheology and numerics. Only in very high resolution simulations (≤2 km) the concentration and thickness anomalies along LKFs are large enough to affect air‐ice‐ocean interaction processes.
    Description: Plain Language Summary: Winds and ocean currents continuously move and deform the sea ice cover of the Arctic Ocean. The deformation eventually breaks an initially closed ice cover into many individual floes, piles up floes, and creates open water. The distribution of ice floes and open water between them is important for climate research, because ice reflects more light and energy back to the atmosphere than open water, so that less ice and more open water leads to warmer oceans. Current climate models cannot simulate sea ice as individual floes. Instead, a variety of methods is used to represent the movement and deformation of the sea ice cover. The Sea Ice Rheology Experiment (SIREx) compares these different methods and assesses the deformation of sea ice in 36 numerical simulations. We identify and track deformation features in the ice cover, which are distinct narrow areas where the ice is breaking or piling up. Comparing specific spatial and temporal properties of these features, for example, the different amounts of fractured ice in specific regions, or the duration of individual deformation events, to satellite observations provides information about the realism of the simulations. From this comparison, we can learn how to improve sea ice models for more realistic simulations of sea ice deformation.
    Description: Key Points: All models simulate linear kinematic features (LKFs), but none accurately reproduces all LKF statistics. Resolved LKFs are affected strongest by spatial and temporal resolution of model grid and atmospheric forcing and rheology. Accurate scaling of deformation rates is a proxy only for realistic LKF numbers but not for any other LKF static.
    Description: DOE
    Description: HYCOM NOPP
    Description: Innovation Fund Denmark and the Horizon 2020 Framework Programme of the European Union
    Description: National centre for Climate Research, SALIENSEAS, ERA4CS
    Description: German Helmholtz Climate Initiative REKLIM (Regional Climate Change)
    Description: Gouvernement du Canada, Natural Sciences and Engineering Research Council of Canada (NSERC) http://dx.doi.org/10.13039/501100000038
    Description: Environment and Climate Change Canada Grants & Contributions program
    Description: Office of Naval Research Arctic and Global Prediction program
    Description: U.S. Department of Energy Regional and Global Model Analysis program
    Description: National Science Foundation Arctic System Science program
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Description: https://zenodo.org/communities/sirex
    Keywords: ddc:550.285
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2024-04-25
    Description: This bibliography unites the individual data collected by different types of autonomous platforms deployed during MOSAiC in 2019/2020.
    Keywords: Atmosphere; autonomous platform; distributed network; drift; MOSAiC; MOSAiC_ATMOS; MOSAiC_ICE; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Oceans; Sea ice; snow
    Type: Dataset
    Format: 71 datasets
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  • 4
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Polar research 22 (2003), S. 0 
    ISSN: 1751-8369
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geography , Geosciences
    Notes: To evaluate improvements in modelling Arctic sea ice, we compare results from two regional models at 1/12° horizontal resolution. The first is a coupled ice-ocean model of the Arctic Ocean, consisting of an ocean model (adapted from the Parallel Ocean Program, Los Alamos National Laboratory [LANL]) and the “old” sea ice model. The second model uses the same grid but consists of an improved “new” sea ice model (LANL/CICE) with a simple ocean mixed layer. Both models are forced with European Centre for Medium-range Weather Forecasts reanalysis data for 1979–1993. A comparison of the two sea ice models focuses on the winter of 1987 to emphasize the internal ice stress and to minimize biases towards a particular Arctic climate regime. The “new” sea ice model gives improved ice deformation and drift fields. These improvements are associated at least in part with the multi-category representation of the ice thickness distribution and more realistic parameterization of the ice strength. Long, narrow features in ice divergence and shear fields resemble those observed in SAR imagery, except that their average width is overestimated, possibly due to insufficient horizontal resolution. We also compare the mean sea ice drift and its decadal variability in two “old” sea ice models at different horizontal resolutions: 18-km and 9-km. We find no significant change in ice drift between the two models, except in areas of significant ice-ocean interactions due to more realistic ocean currents and water mass properties in the 9-km model.
    Type of Medium: Electronic Resource
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  • 5
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    Elsevier
    In:  Ocean Modelling, 137 . pp. 21-39.
    Publication Date: 2020-01-02
    Description: Oceanic fluxes through Fram Strait may significantly contribute to climate variations in the Arctic. However, their observations are difficult. Here, a 26-year numerical model simulation is used to derive oceanic proxies for interannual variability in heat fluxes through Fram Strait. It is found that variability in the cross-slope gradient of sea surface height (SSH) across the West Spitsbergen Current (WSC) can explain about 90% of the variance of winter and annual mean volume transports of Atlantic water at 79°N. Given the strong covariance between the simulated heat flux in the slope current along Svalbard and the corresponding volume transport, variability of the SSH gradient across the WSC is also found to account for about 80% of the variance of heat flux associated with the northward flow through Fram Strait. Moreover, variations in the SSH gradient across the Arctic Slope Current (ASC) northeast of Svalbard at 31°E explain about 85% of the variance of heat flux there and about 80% of the variance of the net heat flux upstream through Fram Strait. Finally, about 85% and 75% of the variance of the net heat flux through Fram Strait is associated with anomalies of the eastward volume transport and depth-averaged core velocity in the ASC, respectively. These relations indicate that monitoring of the flow in the ASC, even with a single current meter mooring, or of the SSH gradient across this current derived from either in situ or remote measurements may provide useful proxies for the heat import to the Arctic Ocean.
    Type: Article , PeerReviewed
    Format: text
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  • 6
    Publication Date: 2022-04-01
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 7
    Publication Date: 2022-05-25
    Description: Author Posting. © Arctic Institute of North America, 2010. This article is posted here by permission of Arctic Institute of North America for personal use, not for redistribution. The definitive version was published in Arctic 63 (2010): 179-194.
    Description: The annual migration of bowhead whales (Balaena mysticetus) past Barrow, Alaska, has provided subsistence hunting to Iñupiat for centuries. Bowheads recurrently feed on aggregations of zooplankton prey near Barrow in autumn. The mechanisms that form these aggregations, and the associations between whales and oceanography, were investigated using field sampling, retrospective analysis, and traditional knowledge interviews. Oceanographic and aerial surveys were conducted near Barrow during August and September in 2005 and 2006. Multiple water masses were observed, and close coupling between water mass type and biological characteristics was noted. Short-term variability in hydrography was associated with changes in wind speed and direction that profoundly affected plankton taxonomic composition. Aggregations of ca. 50–100 bowhead whales were observed in early September of both years at locations consistent with traditional knowledge. Retrospective analyses of records for 1984–2004 also showed that annual aggregations of whales near Barrow were associated with wind speed and direction. Euphausiids and copepods appear to be upwelled onto the Beaufort Sea shelf during Eor SEwinds. A favorable feeding environment is produced when these plankton are retained and concentrated on the shelf by the prevailing westward Beaufort Sea shelf currents that converge with the Alaska Coastal Current flowing to the northeast along the eastern edge of Barrow Canyon.
    Description: This work was supported by NSF Grants OPPPP-0436131 to C. Ashjian (S. Braund Subcontract), OPPPP-0436110 to R. Campbell, OPPPP-0436127 to W. Maslowski, OPPPP-0436009 to C. Nicolson and J. Kruse, OPPPP-043166 to S. Okkonen, and OPPPP-0435956 to Y. Spitz, E. Sherr, and B. Sherr.
    Keywords: Bowhead whale ; Plankton ; Oceanography ; Beaufort Sea ; Subsistence whaling
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 8
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C04S15, doi:10.1029/2006JC003728.
    Description: The summer circulations and hydrographic fields of the Kara Sea are reconstructed for mean, positive and negative Arctic Oscillation regimes employing a variational data assimilation technique which provides the best fit of reconstructed fields to climatological data and satisfies dynamical and kinematic constraints of a quasi-stationary primitive equation ocean circulation model. The reconstructed circulations agree well with the measurements and are characterized by inflow of 0.63, 0.8, 0.51 Sv through Kara Gate and 1.18, 1.1, 1.12 Sv between Novaya Zemlya and Franz Josef Land, for mean climatologic conditions, positive and negative AO indexes, respectively. The major regions of water outflow for these regimes are the St. Anna Trough (1.17, 1.21, 1.34 Sv) and Vilkitsky/Shokalsky Straits (0.52, 0.7, 0.51 Sv). The optimized velocity pattern for the mean climatological summer reveals a strong anticyclonic circulation in the central part of the Kara Sea (Region of Fresh Water Inflow, ROFI zone) and is confirmed by ADCP surveys and laboratory modeling. This circulation is well pronounced for both high and low AO phases, but in the positive AO phase it is shifted approximately 200 km west relatively to its climatological center. During the negative AO phase the ROFI locaion is close to its climatological position. The results of the variational data assimilation approach were compared with the simulated data from the Hamburg Shelf Ocean Model (HAMSOM) and Naval Postgraduate School 18 km resolution (NPS-18) model to validate these models.
    Description: This research is supported by the Frontier Research System for Global Change, through JAMSTEC, Japan, and by the National Science Foundation Office of Polar Programs (under cooperative agreements OPP-0002239 and OPP-0327664 with the International Arctic Research Center, University of Alaska Fairbanks). The development of the data assimilation system, utilized in this study, was also supported by NSF grant OCE-0118200.
    Keywords: Kara Sea ; Variational approach ; Numerical modeling
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 9
    Publication Date: 2022-05-25
    Description: © The Author(s), 2014]. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Progress in Oceanography 136 (2015): 201-222, doi:10.1016/j.pocean.2014.08.012.
    Description: The Bering–Chukchi–Beaufort (BCB) population of bowhead whales (Balaena mysticetus) ranges across the seasonally ice-covered waters of the Bering, Chukchi, and Beaufort seas. We used locations from 54 bowhead whales, obtained by satellite telemetry between 2006 and 2012, to define areas of concentrated use, termed “core-use areas”. We identified six primary core-use areas and describe the timing of use and physical characteristics (oceanography, sea ice, and winds) associated with these areas. In spring, most whales migrated from wintering grounds in the Bering Sea to the Cape Bathurst polynya, Canada (Area 1), and spent the most time in the vicinity of the halocline at depths 〈75 m, which are within the euphotic zone, where calanoid copepods ascend following winter diapause. Peak use of the polynya occurred between 7 May and 5 July; whales generally left in July, when copepods are expected to descend to deeper depths. Between 12 July and 25 September, most tagged whales were located in shallow shelf waters adjacent to the Tuktoyaktuk Peninsula, Canada (Area 2), where wind-driven upwelling promotes the concentration of calanoid copepods. Between 22 August and 2 November, whales also congregated near Point Barrow, Alaska (Area 3), where east winds promote upwelling that moves zooplankton onto the Beaufort shelf, and subsequent relaxation of these winds promoted zooplankton aggregations. Between 27 October and 8 January, whales congregated along the northern shore of Chukotka, Russia (Area 4), where zooplankton likely concentrated along a coastal front between the southeastward-flowing Siberian Coastal Current and northward-flowing Bering Sea waters. The two remaining core-use areas occurred in the Bering Sea: Anadyr Strait (Area 5), where peak use occurred between 29 November and 20 April, and the Gulf of Anadyr (Area 6), where peak use occurred between 4 December and 1 April; both areas exhibited highly fractured sea ice. Whales near the Gulf of Anadyr spent almost half of their time at depths between 75 and 100 m, usually near the seafloor, where a subsurface front between cold Anadyr Water and warmer Bering Shelf Water presumably aggregates zooplankton. The amount of time whales spent near the seafloor in the Gulf of Anadyr, where copepods (in diapause) and, possibly, euphausiids are expected to aggregate provides strong evidence that bowhead whales are feeding in winter. The timing of bowhead spring migration corresponds with when zooplankton are expected to begin their spring ascent in April. The core-use areas we identified are also generally known from other studies to have high densities of whales and we are confident these areas represent the majority of important feeding areas during the study (2006–2012). Other feeding areas, that we did not detect, likely existed during the study and we expect core-use area boundaries to shift in response to changing hydrographic conditions.
    Description: This study is part of the Synthesis of Arctic Research (SOAR) and was funded in part by the U.S. Department of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program through Interagency Agreement No. M11PG00034 with the U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), Office of Oceanic and Atmospheric Research (OAR), Pacific Marine Environmental Laboratory (PMEL). Funding for this research was mainly provided by U.S. Minerals Management Service (now Bureau of Ocean Energy Management) under contracts M12PC00005, M10PS00192, and 01-05-CT39268, with the support and assistance from Charles Monnett and Jeffery Denton, and under Interagency Agreement No. M08PG20021 with NOAA-NMFS and Contract No. M10PC00085 with ADF&G. Work in Canada was also funded by the Fisheries Joint Management Committee, Ecosystem Research Initiative (DFO), and Panel for Energy Research and Development.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 10
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C00A11, doi:10.1029/2008JC004870.
    Description: Wind-driven changes in the path of warm Bering/Chukchi waters carried by the Alaska Coastal Current (ACC) through Barrow Canyon during late summer are described from high-resolution hydrography, acoustic Doppler current profiler–measured currents, and satellite-measured sea surface temperature imagery acquired from mid-August to mid-September 2005–2007 near Barrow, Alaska. Numerical simulations are used to provide a multidecadal context for these observational data. Four generalized wind regimes and associated circulation states are identified. When winds are from the east or east-southeast, the ACC jet tends to be relatively strong and flows adjacent to the shelf break along the southern flank of Barrow Canyon. These easterly winds drive inner shelf currents northwestward along the Alaskan Beaufort coast where they oppose significant eastward intrusions of warm water from Barrow Canyon onto the shelf. Because these easterly winds promote sea level set down over the Beaufort shelf and upwelling along the Beaufort slope, the ACC jet necessarily becomes weaker, broader, and displaced seaward from the Beaufort shelf break upon exiting Barrow Canyon. Winds from the northeast promote separation of the ACC from the southern flank of Barrow Canyon and establish an up-canyon current along the southern flank that is fed in part by waters from the western Beaufort shelf. When winds are weak or from the southwest, warm Bering/Chukchi waters from Barrow Canyon intrude onto the western Beaufort shelf.
    Description: This work was supported in 2005 and 2006 by NSF grants OPP-0436131 and OPP-0436166. In 2007, this work received support through Woods Hole Oceanographic Institution- NOAA Cooperative Institute for Climate and Ocean Research Cooperative Agreement NA17RJ1223 and University of Alaska Fairbanks-NOAA Cooperative Institute for Arctic Research Cooperative Agreement NA17RJ1224. Additional support was provided by the James M. and Ruth P. Clark Arctic Research Initiative Fund at the Woods Hole Oceanographic Institution.
    Keywords: Beaufort index
    Repository Name: Woods Hole Open Access Server
    Type: Article
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