62 citations · 147 across the 11 of their papers we have counts for
11 papers
Online learning in idealized ocean gyres
James R. Maddison
Ocean turbulence parameterization has principally been based on processed-based approaches, seeking to embed physical principles so that coarser resolution calculations can capture…
A two-dimensional model for eddy saturation and frictional control in the Southern Ocean
J. R. Maddison, D. P. Marshall, J. Mak +1
The reduced sensitivity of mean Southern Ocean zonal transport with respect to surface wind stress magnitude changes, known as eddy saturation, is studied in an idealised analytica…
Scale-awareness in an eddy energy constrained mesoscale eddy parameterization
Julian Mak, James R. Maddison, David P. Marshall +3
There is an increasing interest in mesoscale eddy parameterizations that are scale-aware, normally interpreted to mean that a parameterization does not require re-tuning of paramet…
Step-based checkpointing with high-level algorithmic differentiation
James R. Maddison
Automated code generation allows for a separation between the development of a model, expressed via a domain specific language, and lower level implementation details. Algorithmic…
Acute sensitivity of global ocean circulation and heat content to eddy energy dissipation time-scale
Julian Mak, David P. Marshall, Gurvan Madec +1
The global ocean overturning circulation, critically dependent on the global density stratification, plays a central role in regulating climate evolution. While it is well-known th…
Bayesian comparison of stochastic models of dispersion
Martin T. Brolly, James R. Maddison, Aretha L. Teckentrup +1
Stochastic models of varying complexity have been proposed to describe the dispersion of particles in turbulent flows, from simple Brownian motion to complex temporally and spatial…
Bayesian inference of ocean diffusivity from Lagrangian trajectory data
Y. K. Ying, J. R. Maddison, J. Vanneste
A Bayesian approach is developed for the inference of an eddy-diffusivity field from Lagrangian trajectory data. The motion of Lagrangian particles is modelled by a stochastic diff…
Efficient Large Eddy Simulation for the Discontinuous Galerkin Method
Angus Creech, Adrian Jackson, James Maddison +2
In this paper we present a new technique for efficiently implementing Large Eddy Simulation with the Discontin- uous Galerkin method on unstructured meshes. In particular, we will…
Emergent eddy saturation from an energy constrained eddy parameterisation
Julian Mak, James R. Maddison, David P. Marshall +1
The large-scale features of the global ocean circulation and the sensitivity of these features with respect to forcing changes are critically dependent upon the influence of the me…
A new gauge-invariant method for diagnosing eddy diffusivities
Julian Mak, James R. Maddison, David P. Marshall
Coarse resolution numerical ocean models must typically include a parameterisation for mesoscale turbulence. A common recipe for such parameterisations is to invoke down-gradient m…
Geostrophic balance preserving interpolation in mesh adaptive shallow-water ocean modelling
James R. Maddison, Colin J. Cotter, Patrick E. Farrell
The accurate representation of geostrophic balance is an essential requirement for numerical modelling of geophysical flows. Significant effort is often put into the selection of a…