Water mass transformation variability in the Weddell Sea in Ocean Reanalyses

Bailey, Shanice T.; Jones, C. S.; Abernathey, Ryan; Gordon, Arnold L.; Yuan, Xiaojun

doi:10.5194/egusphere-2022-129

Cited by 5 publications

(7 citation statements)

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“…Code and data availability. WMT budgets can be found in the author's GitHub repository (https://github.com/ shanicetbailey/chapter1/tree/v1.0.0, last access: 1 March 2023; https://doi.org/10.5281/zenodo.7776037, Bailey, 2023). The analysis-ready copies of the datasets used for calculating the budgets can be found in the cloud through the Pangeo Catalog (https://catalog.pangeo.io/browse/master/ocean/, Pangeo Catalog, 2023).…”

Section: Discussionmentioning

confidence: 99%

Water mass transformation variability in the Weddell Sea in ocean reanalyses

et al. 2023

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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.

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Section: Discussionmentioning

confidence: 99%

Water mass transformation variability in the Weddell Sea in ocean reanalyses

et al. 2023

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“…For example, Azaneu et al (2014) showed that AABW in the ECCO2 reanalysis is formed by deep convection in the Weddell Sea rather than by on-shelf dense water production and subsequent descent down the continental slope (Menemenlis et al, 2008). A range of data assimilation products (ECMWF-ORAS4 (Balmaseda et al, 2013), CFSR (Saha et al, 2010), MyOcean-UR025.4 (Ferry et al, 2012), ECCO2 (Menemenlis et al, 2008), ECCOV4r4 (Forget et al, 2015), SODA 2.2.4 (Carton and Giese, 2008;Ray, 2011, andSOSE (Mazloff et al, 2010)) are compared in Dotto et al (2014); Aguiar et al (2017), andBailey et al (2023). While some of these reanalyses formed AABW at realistic rates (e.g., ECCOV4r4, SODA, and SOSE), all of the models did not well capture the spatial distribution and variability of AABW compared with observations.…”

Section: Data Assimilation Modelingmentioning

confidence: 99%

Observing Antarctic Bottom Water in the Southern Ocean

Silvano,

Purkey,

Gordon

et al. 2023

Front. Mar. Sci.

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Dense, cold waters formed on Antarctic continental shelves descend along the Antarctic continental margin, where they mix with other Southern Ocean waters to form Antarctic Bottom Water (AABW). AABW then spreads into the deepest parts of all major ocean basins, isolating heat and carbon from the atmosphere for centuries. Despite AABW’s key role in regulating Earth’s climate on long time scales and in recording Southern Ocean conditions, AABW remains poorly observed. This lack of observational data is mostly due to two factors. First, AABW originates on the Antarctic continental shelf and slope where in situ measurements are limited and ocean observations by satellites are hampered by persistent sea ice cover and long periods of darkness in winter. Second, north of the Antarctic continental slope, AABW is found below approximately 2 km depth, where in situ observations are also scarce and satellites cannot provide direct measurements. Here, we review progress made during the past decades in observing AABW. We describe 1) long-term monitoring obtained by moorings, by ship-based surveys, and beneath ice shelves through bore holes; 2) the recent development of autonomous observing tools in coastal Antarctic and deep ocean systems; and 3) alternative approaches including data assimilation models and satellite-derived proxies. The variety of approaches is beginning to transform our understanding of AABW, including its formation processes, temporal variability, and contribution to the lower limb of the global ocean meridional overturning circulation. In particular, these observations highlight the key role played by winds, sea ice, and the Antarctic Ice Sheet in AABW-related processes. We conclude by discussing future avenues for observing and understanding AABW, impressing the need for a sustained and coordinated observing system.

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“…(They additionally propose a method for decomposing spurious numerical mixing into cabelling and non-cabelling components, but this requires implementing intrusive new diagnostics, so we neglect it here for simplicity). Bailey et al (2023) generalizes the approach from latitude coordinates to a rectangular region with vertical walls. Holmes et al (2021) use a conceptually similar approach to quantify spurious diathermal transports in individual columns, but lose the direct connection to the integrated water mass budgets, such as the boundary-normal transports, as a result.…”

Section: Introductionmentioning

confidence: 99%

Water Mass Transformation Budgets in Finite-Volume Generalized Vertical Coordinate Ocean Models

Drake

2023

Preprint

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Water mass transformation theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models but these tools, in practice, face multiple challenges to implementation and are therefore under-utilized. Most prior work evaluates only some of the simpler or more accessible terms in the water mass budget; meanwhile, the few full budget calculations in the literature are either limited to idealized model configurations and geometrically-simple domains or else have required heroic efforts that are neither scalable nor portable to other ocean models or research questions.We begin with a pedagogical derivation of key results of classical water mass transformation theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of finite-volume general vertical coordinate (FV-GVC) ocean models, including the identification of a non-negligible remainder term as the spurious numerical mixing due to advection scheme discretization errors. We illustrate key aspects of the methodology through an example application to diagnostics from a polygonal sub-region of a Baltic Sea regional configuration of the Modular Ocean Model v6 (MOM6). Finally, we briefly describe a stack of xarray-enabled Python packages for evaluating water mass budgets in FV-GVC models, which is intended to be model-agnostic and available for community use and development.

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Water mass transformation variability in the Weddell Sea in Ocean Reanalyses

Cited by 5 publications

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Water mass transformation variability in the Weddell Sea in ocean reanalyses

Water mass transformation variability in the Weddell Sea in ocean reanalyses

Observing Antarctic Bottom Water in the Southern Ocean

Water Mass Transformation Budgets in Finite-Volume Generalized Vertical Coordinate Ocean Models

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