Nonlocality of scale-dependent eddy mixing at the Kuroshio Extension

Although eddy parameterization schemes are often based on the local assumption, previous studies indicate that the nonlocality of total eddy mixing is prevalent at the Kuroshio Extension (KE). For eddy-permitting climate models, only mixing induced by eddies smaller than the resolvable scale of climate models (L-star) needs to be parameterized. Therefore, here we aim to estimate and predict the nonlocality of scale-dependent eddy mixing at the KE region. We consider the separation scale L-star ranging from 0.2 degrees to 2.5 degrees, which is comparable to the typical resolution of the ocean component of climate models. Using a submesoscale-permitting model solution (MITgcm llc4320) and Lagrangian particles, we estimate the scale-dependent mixing (SDM) nonlocality ellipses and then diagnose the square root of the ellipse area (L-n,L-particle). L-n,L-particle is a metric to quantify the degree of SDM nonlocality. We found that, for all the available L-star values we consider, the SDM nonlocality is prevalent in the KE region, and mostly elevated values of Ln, particle occur within the KE jet. As L-star decreases from 2.5 degrees to 0.2 degrees, the ratio L-n,L-particle/L-star increases from 0.8 to 8.9. This result indicates that the SDM nonlocality is more non-negligible for smaller L-star, which corresponds to climate models with relatively high resolution. As to the SDM nonlocality prediction, we found that compared to the conventional scaling and the curve-fitting methods, the random forest approach can better represent L-n,L-particle, especially in the coastal regions and within the intense KE jet. The area of the Eulerian momentum ellipses well capture the spatial pattern, but not the magnitude, of L-n,L-particle. Our efforts suggest that eddy parameterization schemes for eddy-permitting models may be improved by taking into account mixing nonlocality.

Automated summary

This study aims to estimate and predict the nonlocality of scale-dependent eddy mixing in the Kuroshio Extension region. It found that the nonlocality of mixing is prevalent and becomes more significant with higher resolution. The random forest approach is better at representing the nonlocality of scale-dependent mixing.