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  • Sea ice  (5)
  • Abyssal circulation  (2)
  • American Meteorological Society  (6)
  • University of California Press  (1)
  • American Chemical Society
  • American Physical Society
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  • 2020-2023  (7)
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  • 1930-1934
  • 2022  (7)
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  • American Meteorological Society  (6)
  • University of California Press  (1)
  • American Chemical Society
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  • 2020-2023  (7)
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  • 1
    Publication Date: 2022-03-01
    Description: To examine the atmospheric responses to Arctic sea ice variability in the Northern Hemisphere cold season (from October to the following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily varying sea ice, sea surface temperature, and radiative forcings prescribed during the 1979–2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multimodel ensemble mean (MMEM) shows decreasing sea level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drive a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual covariability between sea ice extent in the Barents–Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the covariability in MMEMs. The interannual sea ice decline followed by a negative North Atlantic Oscillation–like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship.
    Description: Published
    Description: 8419–8443
    Description: 2A. Fisica dell'alta atmosfera
    Description: JCR Journal
    Keywords: Arctic ; Sea ice ; Atmospheric circulation ; Climate models ; 01.01. Atmosphere
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2022-06-21
    Description: Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 52(6),(2022): 1191-1204, https://doi.org/10.1175/jpo-d-21-0242.1.
    Description: A simplified quasigeostrophic (QG) analytical model together with an idealized numerical model are used to study the effect of uneven ice–ocean stress on the temporal evolution of the geostrophic current under sea ice. The tendency of the geostrophic velocity in the QG model is given as a function of the lateral gradient of vertical velocity and is further related to the ice–ocean stress with consideration of a surface boundary layer. Combining the analytical and numerical solutions, we demonstrate that the uneven stress between the ice and an initially surface-intensified, laterally sheared geostrophic current can drive an overturning circulation to trigger the displacement of isopycnals and modify the vertical structure of the geostrophic velocity. When the near-surface isopycnals become tilted in the opposite direction to the deeper ones, a subsurface velocity core is generated (via geostrophic setup). This mechanism should help understand the formation of subsurface currents in the edge of Chukchi and Beaufort Seas seen in observations. Furthermore, our solutions reveal a reversed flow extending from the bottom to the middepth, suggesting that the ice-induced overturning circulation potentially influences the currents in the deep layers of the Arctic Ocean, such as the Atlantic Water boundary current.
    Description: This work was funded by the National Key Research and Development Program of China (Grant 2017YFA0604600), the National Natural Science Foundation of China (Grant 41676019), the Fundamental Research Funds for the Central Universities (Grant 2019B81214), the Postgraduate Research and Practice Innovation Program of Jiangsu Province (Grant KYCX19_0384), and the National Science Foundation (MAS, Grants OPP-1822334, OCE-2122633).
    Keywords: Arctic ; Sea ice ; Channel flows ; Vertical motion ; Ekman pumping ; Idealized models ; Quasigeostrophic models
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-06-06
    Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Liang, Y.-C., Frankignoul, C., Kwon, Y.-O., Gastineau, G., Manzini, E., Danabasoglu, G., Suo, L., Yeager, S., Gao, Y., Attema, J. J., Cherchi, A., Ghosh, R., Matei, D., Mecking, J., Tian, T., & Zhang, Y. Impacts of Arctic sea ice on cold season atmospheric variability and trends estimated from observations and a multimodel large ensemble. Journal of Climate, 34(20), (2021): 8419–8443, https://doi.org/10.1175/JCLI-D-20-0578.s1.
    Description: To examine the atmospheric responses to Arctic sea ice variability in the Northern Hemisphere cold season (from October to the following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily varying sea ice, sea surface temperature, and radiative forcings prescribed during the 1979–2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multimodel ensemble mean (MMEM) shows decreasing sea level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drive a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual covariability between sea ice extent in the Barents–Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the covariability in MMEMs. The interannual sea ice decline followed by a negative North Atlantic Oscillation–like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship.
    Description: We acknowledge support by the Blue-Action Project (the European Union’s Horizon 2020 research and innovation programme, #727852, http://www.blue-action.eu/index.php?id=3498). The WHOI–NCAR group was supported by the U.S. National Science Foundation (NSF) Office of Polar Programs Grants 1736738 and 1737377. Their computing and data storage resources, including the Cheyenne supercomputer (doi:10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory at NCAR. NCAR is a major facility sponsored by the U.S. NSF under Cooperative Agreement No. 1852977. Guillaume Gastineau was granted access to the HPC resources of TGCC under the allocations A5-017403 and A7-017403 made by GENCI. The SST and SIC data were downloaded from the U.K. Met Office Hadley Centre Observations Datasets (http://www.metoffice.gov.uk/hadobs/hadisst). The work by NLeSC was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative. The simulations of IAP AGCM were supported by the National Key R&D Program of China 2017YFE0111800. The NorESM2-CAM6 simulations were performed on resources provided by UNINETT Sigma2–the National Infrastructure for High Performance Computing and Data Storage in Norway (nn2343k, NS9015K).
    Keywords: Arctic ; Sea ice ; Atmospheric circulation ; Climate models
    Repository Name: Woods Hole Open Access Server
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  • 4
    Publication Date: 2022-06-07
    Description: The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rabe, B., Heuze, C., Regnery, J., Aksenov, Y., Allerholt, J., Athanase, M., Bai, Y., Basque, C., Bauch, D., Baumann, T. M., Chen, D., Cole, S. T., Craw, L., Davies, A., Damm, E., Dethloff, K., Divine, D., Doglioni, F., Ebert, F., Fang, Y-C., Fer, I., Fong, A. A., Gradinger, R., Granskog, M. A., Graupner, R., Haas, C., He, H., He, Y., Hoppmann, M., Janout, M., Kadko, D., Kanzow, T., Karam, S., Kawaguchi, Y., Koenig, Z., Kong, B., Krishfield, R. A., Krumpen, T., Kuhlmey, D., Kuznetsov, I., Lan, M., Laukert, G., Lei, R., Li, T., Torres-Valdés, S., Lin, L,. Lin, L., Liu, H., Liu, N., Loose, B., Ma, X., MacKay, R., Mallet, M., Mallett, R. D. C., Maslowski, W., Mertens, C., Mohrholz, V., Muilwijk, M., Nicolaus, M., O’Brien, J. K., Perovich, D., Ren, J., Rex, M., Ribeiro, N., Rinke, A., Schaffer, J., Schuffenhauer, I., Schulz, K., Shupe, M. D., Shaw, W., Sokolov, V., Sommerfeld, A., Spreen, G., Stanton, T., Stephens, M., Su, J., Sukhikh, N., Sundfjord, A., Thomisch, K., Tippenhauer, S., Toole, J. M., Vredenborg, M., Walter, M., Wang, H., Wang, L., Wang, Y., Wendisch, M., Zhao, J., Zhou, M., & Zhu, J. Overview of the MOSAiC expedition: physical oceanography. Elementa: Science of the Anthropocene, 10(1), (2022): 1, https://doi.org/10.1525/elementa.2021.00062.
    Description: Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present along-drift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean.
    Description: The following projects and funding agencies contributed to this work: Why is the deep Arctic Ocean Warming is funded by the Swedish Research Council, project number 2018-03859, and berth fees for this project were covered by the Swedish Polar Research Secretariat; The Changing Arctic Ocean (CAO) program, jointly funded by the United Kingdom Research and Innovation (UKRI) Natural Environment Research Council (NERC) and the Bundesministerium für Bildung und Forschung (BMBF), in particular, the CAO projects Advective Pathways of nutrients and key Ecological substances in the ARctic (APEAR) grants NE/R012865/1, NE/R012865/2, and #03V01461, and the project Primary productivity driven by Escalating Arctic NUTrient fluxeS grant #03F0804A; The Research Council of Norway (AROMA, grant no 294396; HAVOC, grant no 280292; and CAATEX, grant no 280531); Collaborative Research: Thermodynamics and Dynamic Drivers of the Arctic Sea Ice Mass Budget at Multidisciplinary drifting Observatory for the Study of the Arctic Climate; National Science Foundation (NSF) projects 1723400, Stanton; OPP-1724551, Shupe; The Helmholtz society strategic investment Frontiers in Arctic Marine monitoring (FRAM); Deutsche Forschungsgemeinschaft (German Research Foundation) through the Transregional Collaborative Research Centre TRR 172 “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” (grant 268020496); The Japan Society for the Promotion of Science (grant numbers JP18H03745, JP18KK0292, and JP17KK0083) and the COLE grant of U. Tokyo; National Key Research and Development Plan Sub-Project of Ministry of Science and Technology of China (2016YFA0601804), “Simulation, Prediction and Regional Climate Response of Global Warming Hiatus”, 2016/07-2021/06; National Science Foundation grant number OPP-1756100 which funded two of the Ice-Tethered Profilers and all the Ice-Tethered Profiler deployments; Chinese Polar Environmental Comprehensive Investigation and Assessment Programs, funded by the Chinese Arctic and Antarctic Administration; Marine Science and Technology Fund of Shandong Province for Qingdao National Laboratory for Marine Science and Technology (Grant: 2018SDKJ0104-1) and Chinese Natural Science Foundation (Grant: 41941012); UK NERC Long-term Science Multiple Centre National Capability Programme “North Atlantic Climate System Integrated Study (ACSIS)”, grant NE/N018044/1; The London NERC Doctoral Training Partnership grant (NE/L002485/1) which funded RDCM; NSF grant number OPP-1753423, which funded the 7Be tracer –measurements; and The Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) through its projects: AWI_OCEAN, AWI_ROV, AWI_ICE, AWI_SNOW, AWI_ECO, AWI_ATMO, and AWI_BGC.
    Keywords: Physical oceanography ; MOSAiC ; Arctic ; Coupled ; Drift ; Sea ice
    Repository Name: Woods Hole Open Access Server
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  • 5
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 51(6),(2021): 1842–1872, https://doi.org/10.1175/JPO-D-20-0153.1.
    Description: Radiocarbon dates of fossil carbonates sampled from sediment cores and the seafloor have been used to infer that deep ocean ventilation during the last ice age was different from today. In this first of two companion papers, the time-averaged abyssal circulation in the modern Atlantic is estimated by combining a hydrographic climatology, observational estimates of volume transports, Argo float velocities at 1000 m, radiocarbon data, and geostrophic dynamics. Different estimates of modern circulation, obtained from different prior assumptions about the abyssal flow and different errors in the geostrophic balance, are produced for use in a robust interpretation of fossil records in terms of deviations from the present-day flow, which is undertaken in Part II. We find that, for all estimates, the meridional transport integrated zonally and averaged over a hemisphere, ⟨Vk⟩, is southward between 1000 and 4000 m in both hemispheres, northward between 4000 and 5000 m in the South Atlantic, and insignificant between 4000 and 5000 m in the North Atlantic. Estimates of ⟨Vk⟩ obtained from two distinct prior circulations—one based on a level of no motion at 4000 m and one based on Argo float velocities at 1000 m—become statistically indistinguishable when Δ14C data are considered. The transport time scale, defined as τk=Vk/⟨Vk⟩, where Vk is the volume of the kth layer, is estimated to about a century between 1000 and 3000 m in both the South and North Atlantic, 124 ± 9 yr (203 ± 23 yr) between 3000 and 4000 m in the South (North) Atlantic, and 269 ± 115 yr between 4000 and 5000 m in the South Atlantic.
    Description: This work has been supported by Grant OCE-1702417 from the U.S. National Science Foundation.
    Keywords: Atlantic Ocean ; Abyssal circulation ; Tracers ; Inverse methods
    Repository Name: Woods Hole Open Access Server
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  • 6
    Publication Date: 2022-12-01
    Description: Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 103(6), (2022): E1502-E1521, https://doi.org/10.1175/bams-d-21-0227.1.
    Description: Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO), assesses the maturity of the required observing system and gives guidance for its development. The Essential Climate Variables (ECVs) are central to GCOS, and the global community must monitor them with the highest standards in the form of Climate Data Records (CDR). Today, a single ECV—the sea ice ECV—encapsulates all aspects of the sea ice environment. In the early 1990s it was a single variable (sea ice concentration) but is today an umbrella for four variables (adding thickness, edge/extent, and drift). In this contribution, we argue that GCOS should from now on consider a set of seven ECVs (sea ice concentration, thickness, snow depth, surface temperature, surface albedo, age, and drift). These seven ECVs are critical and cost effective to monitor with existing satellite Earth observation capability. We advise against placing these new variables under the umbrella of the single sea ice ECV. To start a set of distinct ECVs is indeed critical to avoid adding to the suboptimal situation we experience today and to reconcile the sea ice variables with the practice in other ECV domains.
    Description: PH’s contribution was funded under the Australian Government’s Antarctic Science Collaboration Initiative program, and contributes to Project 6 of the Australian Antarctic Program Partnership (ASCI000002). PH acknowledges support through the Australian Antarctic Science Projects 4496 and 4506, and the International Space Science Institute (Bern, Switzerland) project #405.
    Description: 2022-12-01
    Keywords: Sea ice ; Climate change ; Climatology ; Climate records
    Repository Name: Woods Hole Open Access Server
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  • 7
    Publication Date: 2022-12-16
    Description: Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 52(7), (2022): 1415–1430. https://doi.org/10.1175/JPO-D-21-0147.1.
    Description: Strong subinertial variability near a seamount at the Xisha Islands in the South China Sea was revealed by mooring observations from January 2017 to January 2018. The intraseasonal deep flows presented two significant frequency bands, with periods of 9–20 and 30–120 days, corresponding to topographic Rossby waves (TRWs) and deep eddies, respectively. The TRW and deep eddy signals explained approximately 60% of the kinetic energy of the deep subinertial currents. The TRWs at the Ma, Mb, and Mc moorings had 297, 262, and 274 m vertical trapping lengths, and ∼43, 38, and 55 km wavelengths, respectively. Deep eddies were independent from the upper layer, with the largest temperature anomaly being 〉0.4°C. The generation of the TRWs was induced by mesoscale perturbations in the upper layer. The interaction between the cyclonic–anticyclonic eddy pair and the seamount topography contributed to the generation of deep eddies. Owing to the potential vorticity conservation, the westward-propagating tilted interface across the eddy pair squeezed the deep-water column, thereby giving rise to negative vorticity west of the seamount. The strong front between the eddy pair induced a northward deep flow, thereby generating a strong horizontal velocity shear because of lateral friction and enhanced negative vorticity. Approximately 4 years of observations further confirmed the high occurrence of TRWs and deep eddies. TRWs and deep eddies might be crucial for deep mixing near rough topographies by transferring mesoscale energy to small scales.
    Description: This work was supported by the National Natural Science Foundation of China (92158204, 91958202, 42076019, 41776036, 91858203), the Open Project Program of State Key Laboratory of Tropical Oceanography (project LTOZZ2001), and Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0304).
    Description: 2022-12-16
    Keywords: Abyssal circulation ; Ocean circulation ; Ocean dynamics ; Intraseasonal variability
    Repository Name: Woods Hole Open Access Server
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