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The geography of numerical mixing in a suite of global ocean models
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  • Ryan M Holmes,
  • Jan D Zika,
  • Stephen M Griffies,
  • Andrew McC. Hogg,
  • Andrew E. Kiss,
  • Matthew H. England
Ryan M Holmes
University of New South Wales

Corresponding Author:[email protected]

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Jan D Zika
University of New South Wales
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Stephen M Griffies
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Andrew McC. Hogg
Australian National University
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Andrew E. Kiss
The Australian National University
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Matthew H. England
University of New South Wales
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Numerical mixing, defined here as the physically spurious diffusion of tracers due to the numerical discretization of advection, is known to contribute to biases in ocean circulation models. However, quantifying numerical mixing is non-trivial, with most studies utilizing specifically targeted experiments in idealized settings. Here, we present a precise, online water-mass transformation-based method for quantifying numerical mixing that can be applied to any conserved variable in global general circulation models. Furthermore, the method can be applied within individual fluid columns to provide a spatially-resolved metric. We apply the method to a suite of global ocean-sea ice model simulations with differing grid spacings and sub-grid scale parameterizations. In all configurations numerical mixing drives across-isotherm heat transport of comparable magnitude to that associated with explicitly-parameterized mixing. Numerical mixing is prominent at warm temperatures in the tropical thermocline, where it is sensitive to the vertical diffusivity and resolution. At colder temperatures, numerical mixing is sensitive to the presence of explicit neutral diffusion, suggesting that much of the numerical mixing in these regions acts as a proxy for neutral diffusion when it is explicitly absent. Comparison of equivalent (with respect to vertical resolution and explicit mixing parameters) $1/4^\circ$ and $1/10^\circ$ horizontal resolution configurations shows only a modest enhancement in numerical mixing at $1/4^\circ$. Our results provide a detailed view of numerical mixing in ocean models and pave the way for future improvements in numerical methods.
Jul 2021Published in Journal of Advances in Modeling Earth Systems volume 13 issue 7. 10.1029/2020MS002333