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Abstract Water Mass Transformation (WMT) theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models; in practice, however, these methods can be challenging to implement and interpret, and therefore remain under‐utilized. Our aim is to demonstrate the feasibility of diagnosing all terms in the water mass budget and to exemplify their usefulness for scientific inquiry and model development by quantitatively relating water mass changes, overturning circulations, boundary fluxes, and interior mixing. We begin with a pedagogical derivation of key results of classical WMT theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of Finite‐Volume Generalized 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 the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). We verify the convergence of our WMT diagnostics by brute‐force, comparing time‐averaged (“offline”) diagnostics on various vertical grids to timestep‐averaged (“online”) diagnostics on the native model grid. Finally, we briefly describe a stack of xarray‐enabled Python packages for evaluating WMT budgets in FV‐GVC models (culminating in the newxwmbpackage), 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
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 WMT variability via WMT volume budgets derived from Walin’s classic WMT framework, using three state-of-the-art, data-assimilating ocean reanalyses: 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. In ECCO and SOSE, we see strong interannual variability in AABW volume budget. In SOSE, we find an accelerating loss of AABW, driven largely by interior mixing and changes in surface salt fluxes. ECCO shows a similar trend during a 3-yr time period beyond what is covered in SOSE, but also reveals such trends to be part of interannual variability over a much longer time period. Overall, ECCO provides the most useful timeseries for understanding the processes and mechanisms that drive WMT and export variability. SODA, in contrast, displays unphysically large variability in AABW volume, which we attribute to its data assimilation scheme. We examine correlations between the WMT budgets and large-scale climate indices, including ENSO and SAM; no strong relationships emerge, suggesting that these reanalysis products may not reproduce the AABW export pathways and mechanisms hypothesized from observations.
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- Award ID(s):
- 1553593
- PAR ID:
- 10347387
- Date Published:
- Journal Name:
- Ocean science discussions
- ISSN:
- 1812-0822
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/egusphere-2022-129
