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  • Arctic; AWI_PhyOce; pan-Arctic; Physical Oceanography @ AWI  (1)
  • Coastal  (1)
  • Lagrangian modeling  (1)
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  • 1
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    PANGAEA
    In:  Supplement to: Tsubouchi, Takamasa; Bacon, Sheldon; Aksenov, Yevgeny; Naveira Garabato, Alberto C; Beszczynska-Möller, Agnieszka; Hansen, Edmond H; de Steur, Laura; Curry, Beth; Lee, Craig M (2018): The Arctic Ocean seasonal cycles of heat and freshwater fluxes: observation-based inverse estimates. Journal of Physical Oceanography, https://doi.org/10.1175/JPO-D-17-0239.1
    Publication Date: 2024-03-02
    Description: This paper presents the first estimate of the seasonal cycle of ocean and sea ice heat and freshwater (FW) fluxes around the Arctic Ocean boundary. The ocean transports are estimated primarily using 138 moored instruments deployed in September 2005 – August 2006 across the four main Arctic gateways: Davis, Fram and Bering Straits, and the Barents Sea Opening (BSO). Sea ice transports are estimated from a sea ice assimilation product. Monthly velocity fields are calculated with a box inverse model that enforces mass and salt conservation. The volume transports in the four gateways in the period (annual mean ± 1 standard deviation) are -2.1±0.7 Sv in Davis Strait, -1.1±1.2 Sv in Fram Strait, 2.3±1.2 Sv in BSO and 0.7±0.7 Sv Bering Strait (1 Sv = 10^{6} m^ {3} s^{-1}). The resulting ocean and sea ice heat and FW fluxes are 175±48 TW and 204±85 mSv, respectively. These boundary fluxes accurately represent the annual means of the relevant surface fluxes. The ocean heat transport variability derives from velocity variability in the Atlantic Water layer and temperature variability in the upper part of the water column. The ocean FW transport variability is dominated by Bering Strait velocity variability. The net water mass transformation in the Arctic entails a freshening and cooling of inflowing waters by 0.62±0.23 in salinity and 3.74±0.76°C in temperature, respectively, and a reduction in density by 0.23±0.20 kg m^{-3}. The boundary heat and FW fluxes provide a benchmark data set for the validation of numerical models and atmospheric re-analysis products.
    Keywords: Arctic; AWI_PhyOce; pan-Arctic; Physical Oceanography @ AWI
    Type: Dataset
    Format: application/zip, 102 MBytes
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  • 2
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2019. 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-Oceans 124(7), (2019): 4696-4709, doi: 10.1029/2019JC015022.
    Description: The Beaufort Gyre is a key feature of the Arctic Ocean, acting as a reservoir for freshwater in the region. Depending on whether the prevailing atmospheric circulation in the Arctic is anticyclonic or cyclonic, either a net accumulation or release of freshwater occurs. The sources of freshwater to the Arctic Ocean are well established and include contributions from the North American and Eurasian Rivers, the Bering Strait Pacific water inflow, sea ice meltwater, and precipitation, but their contribution to the Beaufort Gyre freshwater accumulation varies with changes in the atmospheric circulation. Here we use a Lagrangian backward tracking technique in conjunction with the 1/12‐degree resolution Nucleus for European Modelling of the Ocean model to investigate how sources of freshwater to the Beaufort Gyre have changed in recent decades, focusing on increase in the Pacific water content in the gyre between the late 1980s and early 2000s. Using empirical orthogonal functions we analyze the change in the Arctic oceanic circulation that occurred between the 1980s and 2000s. We highlight a “waiting room” advective pathway that was present in the 1980s and provide evidence that this pathway was caused by a shift in the center of Ekman transport convergence in the Arctic. We discuss the role of these changes as a contributing factor to changes in the stratification, and hence potentially the biology, of the Beaufort Gyre region.
    Description: The underpinning high‐resolution NEMO simulation was performed using the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk). ARIANE simulations were performed using the JASMIN data analysis environment (http://www.jasmin.ac.uk). Lagrangian analysis was carried out using computational tool ARIANE developed by B. Blanke and N. Grima. Arctic dynamic topography/geostrophic currents data were provided by the Centre for Polar Observation and Modelling, University College London (www.cpom.ucl.ac.uk/dynamic_topography; Armitage et al., 2016). The funding for A. Proshutinsky was provided by the NSF under grants supporting the Beaufort Gyre Observing System since 2003 (1845877, 1719280, 1604085) and by the Woods Hole Oceanographic Institution. Y. Aksenov was supported from the NERC Program “The North Atlantic Climate System Integrated Study (ACSIS), NE/N018044/1 and from the project “Advective pathways of nutrients and key ecological substances in the Arctic (APEAR)” NE/R012865/1, as a part of the joint UK/Germany “Changing Arctic Ocean” Programme. A. Yool and E. Popova were supported by NERC grants CLASS NE/R015953/1, and National Capability in Ocean Modelling. We acknowledge the FAMOS (http://web.whoi.edu/famos/) program for providing a framework for many fruitful discussions which thoroughly enhanced this work. Finally, we thank the two anonymous reviewers who greatly improved this work with their insightful input.
    Description: 2019-12-26
    Keywords: Beaufort Gyre ; Lagrangian modeling ; NEMO ; particle tracking
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-11-10
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in [citation], doi:[doi]. Gommenginger, C., Chapron, B., Hogg, A., Buckingham, C., Fox-Kemper, B., Eriksson, L., Soulat, F., Ubelmann, C., Ocampo-Torres, F., Nardelli, B. B., Griffin, D., Lopez-Dekker, P., Knudsen, P., Andersen, O., Stenseng, L., Stapleton, N., Perrie, W., Violante-Carvalho, N., Schulz-Stellenfleth, J., Woolf, D., Isern-Fontanet, J., Ardhuin, F., Klein, P., Mouche, A., Pascual, A., Capet, X., Hauser, D., Stoffelen, A., Morrow, R., Aouf, L., Breivik, O., Fu, L., Johannessen, J. A., Aksenov, Y., Bricheno, L., Hirschi, J., Martin, A. C. H., Martin, A. P., Nurser, G., Polton, J., Wolf, J., Johnsens, H., Soloviev, A., Jacobs, G. A., Collard, F., Groom, S., Kudryavtsev, V., Wilkin, J., Navarro, V., Babanin, A., Martin, M., Siddorn, J., Saulter, A., Rippeth, T., Emery, B., Maximenko, N., Romeiser, R., Graber, H., Azcarate, A. A., Hughes, C. W., Vandemark, D., da Silva, J., Van Leeuwen, P. J., Naveira-Garabato, A., Gemmrich, J., Mahadevan, A., Marquez, J., Munro, Y., Doody, S., & Burbidge, G. SEASTAR: A mission to study ocean submesoscale dynamics and small-scale atmosphere-ocean processes in coastal, shelf and polar seas. Frontiers in Marine Science, 6, (2019):457, doi:10.3389/fmars.2019.00457.
    Description: High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at these scales are rare. There is increasing recognition of the role played by small scale ocean processes in ocean-atmosphere coupling, upper-ocean mixing and ocean vertical transports, with advanced numerical models and in situ observations highlighting fundamental changes in dynamics when scales reach 1 km. Numerous scientific publications highlight the global impact of small oceanic scales on marine ecosystems, operational forecasts and long-term climate projections through strong ageostrophic circulations, large vertical ocean velocities and mixed layer re-stratification. Small-scale processes particularly dominate in coastal, shelf and polar seas where they mediate important exchanges between land, ocean, atmosphere and the cryosphere, e.g., freshwater, pollutants. As numerical models continue to evolve toward finer spatial resolution and increasingly complex coupled atmosphere-wave-ice-ocean systems, modern observing capability lags behind, unable to deliver the high-resolution synoptic measurements of total currents, wind vectors and waves needed to advance understanding, develop better parameterizations and improve model validations, forecasts and projections. SEASTAR is a satellite mission concept that proposes to directly address this critical observational gap with synoptic two-dimensional imaging of total ocean surface current vectors and wind vectors at 1 km resolution and coincident directional wave spectra. Based on major recent advances in squinted along-track Synthetic Aperture Radar interferometry, SEASTAR is an innovative, mature concept with unique demonstrated capabilities, seeking to proceed toward spaceborne implementation within Europe and beyond.
    Description: CG and AM received funding from the United Kingdom Centre for Earth Observation Instrumentation SEASTAR+ project (Contract No. RP10G0435A02). PVL was supported by the European Research Council (ERC) CUNDA project 694509 under the European Union Horizon 2020 Research and Innovation Program.
    Keywords: Satellite ; Air sea interactions ; Upper ocean dynamics ; Submesoscale ; Coastal ; Marginal ice zone ; Radar ; Along-track interferometry
    Repository Name: Woods Hole Open Access Server
    Type: Article
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