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 | 144 | 2021 |
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 | 85 | 2021 |
Elucidating ecological complexity: Unsupervised learning determines global marine eco-provinces M Sonnewald, S Dutkiewicz, C Hill, G Forget Science advances 6 (22), eaay4740, 2020 | 55 | 2020 |
Unsupervised learning reveals geography of global ocean dynamical regions M Sonnewald, C Wunsch, P Heimbach Earth and Space Science 6 (5), 784-794, 2019 | 51 | 2019 |
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 | 33 | 2021 |
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 | 29 | 2015 |
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 | 23 | 2022 |
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 | 16 | 2013 |
Linear predictability: A sea surface height case study M Sonnewald, C Wunsch, P Heimbach Journal of Climate 31 (7), 2599-2611, 2018 | 12 | 2018 |
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 | 10 | 2019 |
Oceanic dominance of interannual subtropical North Atlantic heat content variability. M Sonnewald, JJM Hirschi, R Marsh Ocean Science Discussions 10 (1), 2013 | 8 | 2013 |
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 | 7 | 2023 |
Automated identification of dominant physical processes BE Kaiser, JA Saenz, M Sonnewald, D Livescu Engineering Applications of Artificial Intelligence 116, 105496, 2022 | 7 | 2022 |
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 | 4 | 2023 |
Objective discovery of dominant dynamical processes with intelligible machine learning BE Kaiser, JA Saenz, M Sonnewald, D Livescu arXiv preprint arXiv:2106.12963, 2021 | 4 | 2021 |
A Twenty-Year Dynamical Oceanic Climatology: 1994-2013. Part 2: Velocities, Property Transports, Meteorological Variables, Mixing Coefficients ECCO Consortium | 4 | 2017 |
A hierarchical ensemble manifold methodology for new knowledge on spatial data: an application to ocean physics M Sonnewald Authorea Preprints, 2023 | 3 | 2023 |
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 | 3 | 2022 |
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 | 2 | 2023 |
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 | 2 | 2023 |