Abstract
In global ocean models, the representation of small-scale, high-frequency processes considerably influences the large-scale oceanic circulation and its low-frequency variability. This study investigates the impact of stochastic perturbation schemes based on three different subgrid-scale parameterizations in multidecadal ocean-only simulations with the ocean model NEMO at 1° resolution. The three parameterizations are an enhanced vertical diffusion scheme for unstable stratification, the Gent–McWilliams (GM) scheme, and a turbulent kinetic energy mixing scheme, all commonly used in state-of-the-art ocean models. The focus here is on changes in interannual variability caused by the comparatively high-frequency stochastic perturbations with subseasonal decorrelation time scales. These perturbations lead to significant improvements in the representation of low-frequency variability in the ocean, with the stochastic GM scheme showing the strongest impact. Interannual variability of the Southern Ocean eddy and Eulerian streamfunctions is increased by an order of magnitude and by 20%, respectively. Interannual sea surface height variability is increased by about 20%–25% as well, especially in the Southern Ocean and in the Kuroshio region, consistent with a strong underestimation of interannual variability in the model when compared to reanalysis and altimetry observations. These results suggest that enhancing subgrid-scale variability in ocean models can improve model variability and potentially its response to forcing on much longer time scales, while also providing an estimate of model uncertainty.
Highlights
One of the big challenges in ocean modeling is the development of parameterizations that can accurately represent the impact of the unresolved subgrid-scale processes on resolved scales
There are a number of parameters that need to be set for the stochastic perturbation schemes
In this study we have introduced stochastic perturbation schemes to three commonly used subgrid-scale mixing parameterizations in the global 18 ocean model, Nucleus for European Modelling of the Ocean (NEMO), and investigated their impact on low-frequency ocean variability
Summary
One of the big challenges in ocean modeling is the development of parameterizations that can accurately represent the impact of the unresolved subgrid-scale processes on resolved scales. An inadequate representation of such processes can have an impact on the simulated climatic mean state and variability (see, e.g., Kirtman et al 2012) as well as the models’ climatic response to forcing (e.g., Griffies et al 2015). The ocean varies on long time scales and exhibits mesoscale eddies that are much smaller than those found in the atmosphere. It is very difficult and computationally expensive to integrate. Denotes content that is immediately available upon publication as open access
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have