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The Ocean Circulation Inverse Problem
Abstract
The movement of oceanic water has important consequences for a variety of applications, such as climate change, biological productivity, sea-level change, weather forecasting, and many others. This book addresses the problem of inferring the state of the ocean circulation, understanding it dynamically, and even forecasting it through a quantitative combination of theory and observation. It focuses on so-called inverse methods and related methods of statistical inference. Both time-independent and time-dependent problems are considered, including Gauss-Markov estimation, sequential estimators and adjoint/Pontryagin principle methods. This book is intended for use as a graduate level text for students of oceanography and other related fields. It will also be of interest to working physical oceanographers.
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Citations
Cited by
Chen, Y., & Prinn, R. G. (2006) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2005jd006058 · Cited by 317
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Johnson, B. W., & Wing, B. A. (2020) · Nature Geoscience · doi:10.1038/s41561-020-0538-9 · Cited by 100
Arctic tree rings as recorders of variations in light availability
Stine, A. R., & Huybers, P. (2014) · Nature Communications · doi:10.1038/ncomms4836 · Cited by 62
Kuperman, W., & Roux, P. (2007) · Springer Handbooks · doi:10.1007/978-0-387-30425-0_5 · Cited by 49
Metadata
- Authors
- Wunsch, C.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 1996-06-13
- OpenAlex
- W1598311721
- Cited by
- 817
- References
- 0
- FWCI
- 18.22
- Type
- book
- Language
- en
- Open access
- closed
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- Wunsch, C. (1996). The Ocean Circulation Inverse Problem. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511629570
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
