Biblio
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Collective Damage Growth Controls Fault Orientation in Quasibrittle Compressive Failure. Physical Review Letters 122, (2019).
Connections between data assimilation and machine learning to emulate a numerical model. Proceedings of the 9th International Workshop on Climate informatics: CI 2019 (2019).doi:10.5065/y82j-f154
Copernicus Marine Service Ocean State Report, Issue 3. Journal of operational oceanography. Publisher: The Institute of Marine Engineering, Science & Technology 12, (2019).
Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models. Nonlinear processes in geophysics 26, (2019).
Effects of the tropospheric large-scale circulation on European winter temperatures during the period of amplified Arctic warming. International Journal of Climatology (2019).doi:10.1002/joc.6225
Estimating model evidence using ensemble‐based data assimilation with localization – The model selection problem. Quarterly Journal of the Royal Meteorological Society 145, (2019).
The European Climate Research Alliance (ECRA): Collaboration from bottom-up. Advances in Geosciences 46, (2019).
From Observation to Information and Users: The Copernicus Marine Service Perspective. Frontiers in Marine Science (2019).doi:10.3389/fmars.2019.00234
Impact of ocean and sea ice initialisation on seasonal prediction skill in the Arctic. Journal of Advances in Modeling Earth Systems 11, (2019). Abstract
Impact of sparse profile sampling on the reconstruction of subsurface ocean temperature from surface information. Proceedings of the 9th International Workshop on Climate informatics: CI 2019 (2019).doi:10.5065/y82j-f154
Investigating the relationship between volume transport and sea surface height in a numerical ocean model. Ocean Science 15, (2019).
Key indicators of Arctic climate change: 1971–2017. Environmental Research Letters 14, (2019). Abstract
Learning the hidden dynamics of ocean temperature with neural networks. Proceedings of the 9th International Workshop on Climate informatics: CI 2019 (2019).doi:10.5065/y82j-f154
Observational needs for improving ocean and coupled reanalysis, S2S Prediction, and decadal prediction. Frontiers in Marine Science 6:391, (2019).
Observing System Evaluation Based on Ocean Data Assimilation and Prediction Systems: On-Going Challenges and a Future Vision for Designing and Supporting Ocean Observational Networks. Frontiers in Marine Science (2019).doi:10.3389/fmars.2019.00417
