1 citations · 1 across the 3 of their papers we have counts for
4 papers
Climate-Adaptive and Cascade-Constrained Machine Learning Prediction for Sea Surface Height under Greenhouse Warming
Tianmu Zheng, Ru Chen, Xin Su +3
Machine learning (ML) has achieved remarkable success in climate and marine science. Given that greenhouse warming fundamentally reshapes ocean conditions such as stratification, c…
Adjoint-based online learning of two-layer quasi-geostrophic baroclinic turbulence
Fei Er Yan, Hugo Frezat, Julien Le Sommer +2
For reasons of computational constraint, most global ocean circulation models used for Earth System Modeling still rely on parameterizations of sub-grid processes, and limitations…
Edge-wave phase-shifts versus normal-mode phase-tilts in an Eady problem with a sloping boundary
Julian Mak, Nili Harnik, Eyal Heifetz +2
One mechanistic interpretation of baroclinic instability is that of mutual constructive interference of Rossby edge-waves. While the two edge-waves and their relative phase-shifts…
On the choice of training data for machine learning of geostrophic mesoscale turbulence
F. E. Yan, J. Mak, Y. Wang
'Data' plays a central role in data-driven methods, but is not often the subject of focus in investigations of machine learning algorithms as applied to Earth System Modeling relat…