66 research outputs found

    On the Oceanic Communication Between the Western Subartic Gyre and the Deep Bering Sea

    Get PDF
    The article of record as published may be found at http://dx.doi.org/10.1016/j.dsr.2012.04.001Sparse information is available on the communication between the northern North Pacific and the southern Bering Sea. We present results from a multi-decadal simulation of a high-resolution, pan-Arctic ice-ocean model to address the long-term mean and variability and synthesize limited observations in the Alaskan Stream, Western Subarctic Gyre, and southern Bering Sea. While the mean circulation in the Bering Sea basin is cyclonic, during the 26-year simulation meanders and eddies are continuously present throughout the region, which is consistent with observations from Cokelet and Stabeno (1997). Prediction (instead of prescription) of the Alaskan Stream and Aleutian throughflow allows reproduction of meanders and eddies in the Alaskan Stream and Kamchatka Current similar to those that have been observed previously (e.g. Crawford et al., 2000; Rogachev and Carmack, 2002; Rogachev and Gorin, 2004). Interannual variability in mass transport and property fluxes is particularly strong across the western Aleutian Island Passes, including Buldir Pass, Near Strait, and Kamchatka Strait. Much of this variability can be attributed to the presence of meanders and eddies found both north and south of the passes, which are found to directly cause periodic flow reversals and maxima in the western passes. Given that modeled flow reversals and maxima last for time periods ranging between three months and two years, short-term observations (months to few years) may not be representative of the actual mean flow. These extremes in the communication across the Aleutian Island Passes have a large impact on the oceanic environmental conditions in the southern Bering Sea and could directly impact biological species there and further downstream. Therefore, we identify a need for continuous monitoring of the flow through Buldir Pass, Near, and Kamchatka straits.Energy Climate and Environmental Sciences Division of the Biological and Environmental Research programNational Science Foundation Office of Polar ProgramsOffice of Naval ResearchUS Department of Defense High Performance Computer Modernization Program (HPCMP), for computer resource

    A Spatial Evaluation of Arctic Sea Ice and Regional Limitations in CMIP6 Historical Simulations

    Get PDF
    17 USC 105 interim-entered record; under review.The article of record as published may be found at http://dx.doi.org/10.1175/JCLI-D-20-0491.1The Arctic sea ice response to a warming climate is assessed in a subset of models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6), using several metrics in comparison with satellite observations and results from the Pan-Arctic Ice Ocean Modeling and Assimilation System and the Regional Arctic System Model. Our study examines the historical representation of sea ice extent, volume, and thickness using spatial analysis metrics, such as the integrated ice edge error, Brier score, and spatial probability score. We find that the CMIP6 multimodel mean captures the mean annual cycle and 1979–2014 sea ice trends remarkably well. However, individual models experience a wide range of uncertainty in the spatial distribution of sea ice when compared against satellite measurements and reanalysis data. Our metrics expose common and individual regional model biases, which sea ice temporal analyses alone do not capture. We identify large ice edge and ice thickness errors in Arctic subregions, implying possible model specific limitations in or lack of representation of some key physical processes. We postulate that many of them could be related to the oceanic forcing, especially in the marginal and shelf seas, where seasonal sea ice changes are not adequately simulated. We therefore conclude that an individual model’s ability to represent the observed/reanalysis spatial distribution still remains a challenge. We propose the spatial analysis metrics as useful tools to diagnose model limitations, narrow down possible processes affecting them, and guide future model improvements critical to the representation and projections of Arctic climate change.U.S. NavyDepartment of Energy (DOE)Regional and Global Model Analysis (RGMA)Office of Naval Research (ONR)Arctic and Global Prediction (AGP)National Science Foundation (NSF)Arctic System Science (ARCSS)Ministry of Science and Higher Education in PolandDOE: 89243019SSC0036DESC0014117ONR: N0001418WX00364NSF: IAA1417888IAA160360

    On the variability of the Bering Sea Cold Pool and implications for the biophysical environment

    Get PDF
    The article of record as published may be found at http://dx.doi.org/10.1371/ journal.pone.0266180The Bering Sea experiences a seasonal sea ice cover, which is important to the biophysical environment found there. A pool of cold bottom water (<2 ?C) is formed on the shelf each winter as a result of cooling and vertical mixing due to brine rejection during the predominately local sea ice growth. The extent and distribution of this Cold Pool (CP) is largely controlled by the winter extent of sea ice in the Bering Sea, which can vary considerably and recently has been much lower than average. The cold bottom water of the CP is important for food security because it delineates the boundary between arctic and subarctic demersal fish species. A northward retreat of the CP will likely be associated with migration of subarctic species toward the Chukchi Sea. We use the fully-coupled Regional Arctic System Model (RASM) to examine variability of the extent and distribution of the CP and its relation to change in the sea ice cover in the Bering Sea during the period 1980–2018. RASM results confirm the direct correlation between the extent of sea ice and the CP and show a smaller CP as a consequence of realistically simulated recent declines of the sea ice cover in the Bering Sea. In fact, the area of the CP was found to be only 31% of the long-term mean in July of 2018. In addition, we also find that a low ice year is followed by a later diatom bloom, while a heavy ice year is followed by an early diatom bloom. Finally, the RASM probabilistic intra-annual forecast capability is reviewed, based on 31-member ensembles for 2019– 2021, for its potential use for prediction of the winter sea ice cover and the subsequent summer CP area in the Bering Sea.This work was supported by the US National Science Foundation (GEO/PLR ARCSS IAA1417888 and IAA1603602), the US Department of Energy (DOE) Regional and Global Model Analysis (RGMA) (89243019SSC0036 and DESC0014117), and the Office of Naval Research (ONR) Arctic and Global Prediction (AGP) (N0001418WX00364). The Department of Defense (DOD) High Performance Computer Modernization Program (HPCMP) provided computer resources.This work was supported by the US National Science Foundation (GEO/PLR ARCSS IAA1417888 and IAA1603602), the US Department of Energy (DOE) Regional and Global Model Analysis (RGMA) (89243019SSC0036 and DESC0014117), and the Office of Naval Research (ONR) Arctic and Global Prediction (AGP) (N0001418WX00364). The Department of Defense (DOD) High Performance Computer Modernization Program (HPCMP) provided computer resources

    Intrusion of warm Bering/Chukchi waters onto the shelf in the western Beaufort Sea

    Get PDF
    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.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.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

    Causes and evolution of winter polynyas north of Greenland

    Get PDF
    During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s−1) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere.</p

    On the circulation, water mass distribution, and nutrient concentrations of the western Chukchi Sea

    Get PDF
    17 USC 105 interim-entered record; under review.The article of record as published may be found at https://doi.org/10.5194/os-18-29-2022Substantial amounts of nutrients and carbon enter the Arctic Ocean from the Pacific Ocean through the Bering Strait, distributed over three main pathways. Water with low salinities and nutrient concentrations takes an eastern route along the Alaskan coast, as Alaskan Coastal Water. A central pathway exhibits intermediate salinity and nutrient concentrations, while the most nutrient-rich water enters the Bering Strait on its western side. Towards the Arctic Ocean, the flow of these water masses is subject to strong topographic steering within the Chukchi Sea with volume trans port modulated by the wind field. In this contribution, we use data from several sections crossing Herald Canyon collected in 2008 and 2014 together with numerical modelling to investigate the circulation and transport in the western part of the Chukchi Sea. We find that a substantial fraction of water from the Chukchi Sea enters the East Siberian Sea south of Wrangel Island and circulates in an anticyclonic direction around the island. This water then contributes to the high nutrient waters of Herald Canyon. The bottom of the canyon has the highest nutrient concentrations, likely as a result of addition from the degradation of organic matter at the sediment surface in the East Siberian Sea. The flux of nutrients (nitrate, phosphate, and silicate) and dissolved inorganic carbon in Bering Summer Water and Winter Water is computed by combining hydrographic and nutrient observations with geostrophic transport referenced to lowered acoustic Doppler current profiler (LADCP) and surface drift data. Even if there are some general similarities between the years, there are differences in both the temperature–salinity and nutrient characteristics. To assess these differences, and also to get a wider temporal and spatial view, numerical modelling results are applied. According to model results, high-frequency variability dominates the flow in Herald Canyon. This leads us to conclude that this region needs to be monitored over a longer time frame to deduce the temporal variability and potential trends.The science was financially supported by: US National Science Foundation (Grant Number: GEO/PLR ARCSS 575 IAA#1417888), the Department of Energy (DOE) Regional and Global Model Analysis (RGMA), the Swedish Research Council Formas (contract no. 2018-01398), and the Swedish Research Council (contract nos. 621-2006-3240, 621-2010-4084, and 2012-1680). This work was carried out with logistic support from the Knut and Alice Wallenberg Foundation and from Swedish Polar Research Secretariat. The Department of Defense (DOD) High Performance Computer Modernization Program (HPCMP) provided computer resources. This study was also supported by the Russian Scientific Foundation (grant no. # 21-77-580 30001).The science was financially supported by: US National Science Foundation (Grant Number: GEO/PLR ARCSS 575 IAA#1417888), the Department of Energy (DOE) Regional and Global Model Analysis (RGMA), the Swedish Re search Council Formas (contract no. 2018-01398), and the Swedish Research Council (contract nos. 621-2006-3240, 621-2010-4084, and 2012-1680). This work was carried out with logistic support from the Knut and Alice Wallenberg Foundation and from Swedish Polar Research Secretariat. The Department of Defense (DOD) High Performance Computer Modernization Program (HPCMP) provided computer resources. This study was also supported by the Russian Scientific Foundation (grant no. # 21-77-580 30001)

    Ecological characteristics of core-use areas used by Bering–Chukchi–Beaufort (BCB) bowhead whales, 2006–2012

    Get PDF
    © 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.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.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

    Late Winter Biogeochemical Conditions Under Sea Ice in the Canadian High Arctic

    Get PDF
    With the Arctic summer sea-ice extent in decline, questions are arising as to how changes in sea-ice dynamics might affect biogeochemical cycling and phenomena such as carbon dioxide (CO2) uptake and ocean acidification. Recent field research in these areas has concentrated on biogeochemical and CO2 measurements during spring, summer or autumn, but there are few data for the winter or winter–spring transition, particularly in the High Arctic. Here, we present carbon and nutrient data within and under sea ice measured during the Catlin Arctic Survey, over 40 days in March and April 2010, off Ellef Ringnes Island (78° 43.11â€Č N, 104° 47.44â€Č W) in the Canadian High Arctic. Results show relatively low surface water (1–10 m) nitrate (<1.3 ”M) and total inorganic carbon concentrations (mean±SD=2015±5.83 ”mol kg−1), total alkalinity (mean±SD=2134±11.09 ”mol kg−1) and under-ice pCO2sw (mean±SD=286±17 ”atm). These surprisingly low wintertime carbon and nutrient conditions suggest that the outer Canadian Arctic Archipelago region is nitrate-limited on account of sluggish mixing among the multi-year ice regions of the High Arctic, which could temper the potential of widespread under-ice and open-water phytoplankton blooms later in the season

    Cyclic and Sleep-Like Spontaneous Alternations of Brain State Under Urethane Anaesthesia

    Get PDF
    Background: Although the induction of behavioural unconsciousness during sleep and general anaesthesia has been shown to involve overlapping brain mechanisms, sleep involves cyclic fluctuations between different brain states known as active (paradoxical or rapid eye movement: REM) and quiet (slow-wave or non-REM: nREM) stages whereas commonly used general anaesthetics induce a unitary slow-wave brain state. Methodology/Principal Findings: Long-duration, multi-site forebrain field recordings were performed in urethaneanaesthetized rats. A spontaneous and rhythmic alternation of brain state between activated and deactivated electroencephalographic (EEG) patterns was observed. Individual states and their transitions resembled the REM/nREM cycle of natural sleep in their EEG components, evolution, and time frame (,11 minute period). Other physiological variables such as muscular tone, respiration rate, and cardiac frequency also covaried with forebrain state in a manner identical to sleep. The brain mechanisms of state alternations under urethane also closely overlapped those of natural sleep in their sensitivity to cholinergic pharmacological agents and dependence upon activity in the basal forebrain nuclei that are the major source of forebrain acetylcholine. Lastly, stimulation of brainstem regions thought to pace state alternations in sleep transiently disrupted state alternations under urethane. Conclusions/Significance: Our results suggest that urethane promotes a condition of behavioural unconsciousness tha
    • 

    corecore