Source Themes

Implementation of a data-driven equation-discovery mesoscale parameterization into an ocean model

Pavel Perezhogin, C. Zhang, A. Adcroft, C. Fernandez-Granda, Laure Zanna

Remote Versus Local Impacts of Energy Backscatter on the North Atlantic SST Biases in a Global Ocean Model

C-Y Chang, A. Adcroft, Laure Zanna, R. Hallberg, S.M. Griffies

Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks

A. Sane, B. G. Reichl, A. Adcroft, Laure Zanna

Generative data-driven approaches for stochastic subgrid parameterizations in an idealized ocean model

Pavel Perezhogin, C. Fernandez-Granda, Laure Zanna

Implementation and Evaluation of a Machine Learned Mesoscale Eddy Parameterization into a Numerical Ocean Circulation Model

C. Zhang, Pavel Perezhogin, C. Gultekin, A. Adcroft, C. Fernandez-Granda, Laure Zanna

Deep learning of systematic sea ice model errors from data assimilation increments

W. Gregory, M. Bushuk, A. Adcroft, Y. Zhang, Laure Zanna

Causal inference in spatiotemporal climate fields through linear response theory

Fabrizio Falasca, Pavel Perezhogin, Laure Zanna

Data-driven multiscale modeling of subgrid parameterizations in climate models

K. Otness, J. Bruna, Laure Zanna

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

Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges

K. Jakhar, Y. Guan, R. Mojgani, A. Chattopadhyay, P. Hassanzadeh, Laure Zanna