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Maike Sonnewald
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Towards neural Earth system modelling by integrating artificial intelligence in Earth system science
C Irrgang, N Boers, M Sonnewald, EA Barnes, C Kadow, J Staneva, ...
Nature Machine Intelligence 3 (8), 667-674, 2021
1442021
Bridging observations, theory and numerical simulation of the ocean using machine learning
M Sonnewald, R Lguensat, DC Jones, PD Dueben, J Brajard, V Balaji
Environmental Research Letters 16 (7), 073008, 2021
852021
Elucidating ecological complexity: Unsupervised learning determines global marine eco-provinces
M Sonnewald, S Dutkiewicz, C Hill, G Forget
Science advances 6 (22), eaay4740, 2020
552020
Unsupervised learning reveals geography of global ocean dynamical regions
M Sonnewald, C Wunsch, P Heimbach
Earth and Space Science 6 (5), 784-794, 2019
512019
Revealing the impact of global heating on North Atlantic circulation using transparent machine learning
M Sonnewald, R Lguensat
Journal of Advances in Modeling Earth Systems 13 (8), e2021MS002496, 2021
332021
Seasonal variability of sea surface height in the coastal waters and deep basins of the Nordic Seas
AI Bulczak, S Bacon, AC Naveira Garabato, A Ridout, MJP Sonnewald, ...
Geophysical Research Letters 42 (1), 113-120, 2015
292015
Explainable artificial intelligence for Bayesian neural networks: Toward trustworthy predictions of ocean dynamics
MCA Clare, M Sonnewald, R Lguensat, J Deshayes, V Balaji
Journal of Advances in Modeling Earth Systems 14 (11), e2022MS003162, 2022
232022
Atlantic meridional ocean heat transport at 26 N: impact on subtropical ocean heat content variability
M Sonnewald, JJM Hirschi, R Marsh, EL McDonagh, BA King
Ocean Science 9 (6), 1057-1069, 2013
162013
Linear predictability: A sea surface height case study
M Sonnewald, C Wunsch, P Heimbach
Journal of Climate 31 (7), 2599-2611, 2018
122018
A barotropic vorticity budget for the subtropical North Atlantic based on observations
IAA Le Bras, M Sonnewald, JM Toole
Journal of Physical Oceanography 49 (11), 2781-2797, 2019
102019
Oceanic dominance of interannual subtropical North Atlantic heat content variability.
M Sonnewald, JJM Hirschi, R Marsh
Ocean Science Discussions 10 (1), 2013
82013
A Southern Ocean supergyre as a unifying dynamical framework identified by physics-informed machine learning
M Sonnewald, KA Reeve, R Lguensat
Communications Earth & Environment 4 (1), 153, 2023
72023
Automated identification of dominant physical processes
BE Kaiser, JA Saenz, M Sonnewald, D Livescu
Engineering Applications of Artificial Intelligence 116, 105496, 2022
72022
A scale-dependent analysis of the barotropic vorticity budget in a global ocean simulation
H Khatri, SM Griffies, BA Storer, M Buzzicotti, H Aluie, M Sonnewald, ...
Authorea Preprints, 2023
42023
Objective discovery of dominant dynamical processes with intelligible machine learning
BE Kaiser, JA Saenz, M Sonnewald, D Livescu
arXiv preprint arXiv:2106.12963, 2021
42021
A Twenty-Year Dynamical Oceanic Climatology: 1994-2013. Part 2: Velocities, Property Transports, Meteorological Variables, Mixing Coefficients
ECCO Consortium
42017
A hierarchical ensemble manifold methodology for new knowledge on spatial data: an application to ocean physics
M Sonnewald
Authorea Preprints, 2023
32023
Regional sensitivity patterns of Arctic Ocean acidification revealed with machine learning
JP Krasting, M De Palma, M Sonnewald, JP Dunne, JG John
Communications Earth & Environment 3 (1), 91, 2022
32022
Southern Ocean Dynamics Under Climate Change: New Knowledge Through Physics-Guided Machine Learning
W Yik, M Sonnewald, MCA Clare, R Lguensat
arXiv preprint arXiv:2310.13916, 2023
22023
Unsupervised classification identifies coherent thermohaline structures in the Weddell Gyre region
DC Jones, M Sonnewald, S Zhou, U Hausmann, AJS Meijers, I Rosso, ...
Ocean Science 19 (3), 857-885, 2023
22023
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Articles 1–20