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  • Jones, C. Spencer  (3)
  • 1
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2023
    In:  Journal of Advances in Modeling Earth Systems Vol. 15, No. 4 ( 2023-04)
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 15, No. 4 ( 2023-04)
    Abstract: We present a recipe for using Lagrangian filtering to filter waves from the ocean surface velocity field Removing super‐inertial energy using Lagrangian filtering preserves some super‐inertial energy in the Eulerian frame Preserved velocities are associated with convergent fronts, suggesting Lagrangian filtering retains transport‐active nongeostrophic flows
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 2462132-8
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  • 2
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2023
    In:  Journal of Advances in Modeling Earth Systems Vol. 15, No. 10 ( 2023-10)
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 15, No. 10 ( 2023-10)
    Abstract: Neural networks reasonably reconstruct surface vorticity, strain and divergence, from sea surface height Neural networks naturally filter wave divergence, leaving only the desired divergence associated with fronts Transfer learning shows promise when task‐specific data is limited but data from reasonably close simulations is available
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 2462132-8
    Location Call Number Limitation Availability
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  • 3
    Online Resource
    Online Resource
    Copernicus GmbH ; 2023
    In:  Ocean Science Vol. 19, No. 2 ( 2023-04-04), p. 381-402
    In: Ocean Science, Copernicus GmbH, Vol. 19, No. 2 ( 2023-04-04), p. 381-402
    Abstract: Abstract. This study investigates the variability of water mass transformation (WMT) within the Weddell Gyre (WG). The WG serves as a pivotal site for the Meridional Overturning Circulation (MOC) and ocean ventilation because it is the primary origin of the largest volume of water mass in the global ocean: Antarctic Bottom Water (AABW). Recent mooring data suggest substantial seasonal and interannual variability of AABW properties exiting the WG, and studies have linked the variability to the large-scale climate forcings affecting wind stress in the WG region. However, the specific thermodynamic mechanisms that link variability in surface forcings to variability in water mass transformations and AABW export remain unclear. This study explores how current state-of-the-art data-assimilating ocean reanalyses can help fill the gaps in our understanding of the thermodynamic drivers of AABW variability in the WG via WMT volume budgets derived from Walin's classic WMT framework. The three ocean reanalyses used are the following: Estimating the Circulation and Climate of the Ocean state estimate (ECCOv4), Southern Ocean State Estimate (SOSE) and Simple Ocean Data Assimilation (SODA). From the model outputs, we diagnose a closed form of the water mass budget for AABW that explicitly accounts for transport across the WG boundary, surface forcing, interior mixing and numerical mixing. We examine the annual mean climatology of the WMT budget terms, the seasonal climatology and finally the interannual variability. Our finding suggests that the relatively coarse resolution of these models did not realistically capture AABW formation, export and variability. In ECCO and SOSE, we see strong interannual variability in AABW volume budget. In SOSE, we find an accelerating loss of AABW during 2005–2010, driven largely by interior mixing and changes in surface salt fluxes. ECCO shows a similar trend during a 4-year time period starting in late 2007 but also reveals such trends to be part of interannual variability over a much longer time period. Overall, ECCO provides the most useful time series for understanding the processes and mechanisms that drive WMT and export variability in the WG. SODA, in contrast, displays unphysically large variability in AABW volume, which we attribute to its data assimilation scheme. We also examine correlations between the WMT budgets and large-scale climate indices, including El Niño–Southern Oscillation (ENSO) and Southern Annular Mode (SAM), and find no strong relationships.
    Type of Medium: Online Resource
    ISSN: 1812-0792
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2183769-7
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