Computational Oceanography + Climate @ NYU
Computational Oceanography + Climate @ NYU
People
News
Publications
Code & Data
Simons Center
Contact
Light
Dark
Automatic
Source Themes
A new conceptual model of global ocean heat uptake
We formulate a new conceptual model, named “MT2”, to describe global ocean heat uptake, as simulated by atmosphere–ocean general …
J.M. Gregory
,
J Bloch-Johnson
,
M.P. Couldrey
,
E Exarchou
,
S.M. Griffies
,
T Kuhlbrodt
,
Emily Newsom
,
O.A. Saenko
,
T. Suzuki
,
Q. Wu
,
S. Urakawa
,
Laure Zanna
PDF
Cite
DOI
Discovering causal relations and equations from data
Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur …
G. Camps-Valls
,
A. Gerhardus
,
U. Nimad
,
G. Varando
,
G. Martius
,
E. Balaguer-Ballester
,
R. Vinuesa
,
E. Diaz
,
Laure Zanna
,
J. Runge
PDF
Cite
DOI
Background Pycnocline depth constrains Future Ocean Heat Uptake Efficiency
The Ocean Heat Uptake Efficiency (OHUE) quantifies the ocean’s ability to mitigate surface warming through deep heat …
Emily Newsom
,
Laure Zanna
,
J. M. Gregory
PDF
Cite
DOI
Remote Versus Local Impacts of Energy Backscatter on the North Atlantic SST Biases in a Global Ocean Model
The use of coarse resolution and strong grid-scale dissipation has prevented global ocean models from simulating the correct kinetic …
C-Y Chang
,
A. Adcroft
,
Laure Zanna
,
R. Hallberg
,
S.M. Griffies
PDF
Cite
DOI
Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks
Vertical mixing parameterizations in ocean models are formulated on the basis of the physical principles that govern turbulent mixing. …
A. Sane
,
B. G. Reichl
,
A. Adcroft
,
Laure Zanna
PDF
Cite
DOI
Generative data-driven approaches for stochastic subgrid parameterizations in an idealized ocean model
Subgrid parameterizations of mesoscale eddies continue to be in demand for climate simulations. These subgrid parameterizations can be …
Pavel Perezhogin
,
C. Fernandez-Granda
,
Laure Zanna
PDF
Cite
DOI
Implementation and Evaluation of a Machine Learned Mesoscale Eddy Parameterization into a Numerical Ocean Circulation Model
We address the question of how to use a machine learned (ML) parameterization in a general circulation model (GCM), and assess its …
C. Zhang
,
Pavel Perezhogin
,
C. Gultekin
,
A. Adcroft
,
C. Fernandez-Granda
,
Laure Zanna
PDF
Cite
DOI
Deep learning of systematic sea ice model errors from data assimilation increments
Data assimilation is often viewed as a framework for correcting short-term error growth in dynamical climate model forecasts. When …
W. Gregory
,
M. Bushuk
,
A. Adcroft
,
Y. Zhang
,
Laure Zanna
PDF
Cite
DOI
Data-driven multiscale modeling of subgrid parameterizations in climate models
We propose a multiscale approach for predicting quantities in dynamical systems which is explicitly structured to extract information …
K. Otness
,
J. Bruna
,
Laure Zanna
PDF
Cite
DOI
Exploring the non-stationarity of coastal sea level probability distributions
Studies agree on a significant global mean sea level rise in the 20th century and its recent 21st century acceleration in the satellite …
Fabrizio Falasca
,
Andrew Brettin
,
Laure Zanna
,
S. M. Griffies
,
J. Yin
,
M. Zhao
PDF
Cite
DOI
«
»
Cite
×