Discrete Inverse and State Estimation Problems: With Geophysical Fluid Applications
By Carl Wunsch. 2006
164 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/c039f8038274b35b1222b8780f106141d94832e8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- R. Bannister
- Andrew M. Moore
- Anuj Karpatne
- Patrick Heimbach
- J. Carton
- Carl Wunsch
- Hernan G. Arango
- Vipin Kumar
Citations in the corpus
- The Regional Ocean Modeling System (ROMS) 4-dimensional variational data assimilation systems Part I - System overview and formulation (2011, background): “Excellent reviews and seminal texts on data assimilation include Bengtsson et al. (1981), Tarantola (1987), Daley (1991), Ghil and Malanotte-Rizzoli (1991), Bennett (1992, 2002) and Wunsch (1996, 2006).”
- Global General Circulation of the Ocean Estimated by the ECCO-Consortium (2009, background): “Some of the roots of WOCE are described in Siedler et al. (2001) and Wunsch (2006a).”
- A review of operational methods of variational and ensemble‐variational data assimilation (2017, methodology): “DA is related to approaches used in other fields and which go by different names, e.g. state estimation (Wunsch, 2012); optimization (Biegler, 1997); history matching (Emerick, 2012); retrieval production (Rodgers, 2000); inverse modelling (Tarantola, 2005)), and there are additionally many ways of…”
- Dynamically and Kinematically Consistent Global Ocean Circulation and Ice State Estimates (2013, methodology): “True Kalman filters are never used for prediction in real geophysical fluid flow problems as they are computationally overwhelming (for more detail, see e.g., Wunsch, 2006).”
- Machine Learning for the Geosciences: Challenges and Opportunities (2017, background): “The Earth system is incredibly complex, with a huge number of potential variables, which may all impact each other, and thus many of which may have to be considered si-4 multaneously [30].”
- A Reanalysis of Ocean Climate Using Simple Ocean Data Assimilation (SODA) (2008, methodology): “…sophisticated alternatives, such as the four-dimensional variational algorithm and full Kalman filter have limitations in terms of high computational expense, increased sensitivity to the quality of the statistical assumptions, and for the full Kalman filter the potential for stability problems.”