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Research Article

Gaussian approximations in filters and smoothers for data assimilation

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Spencer Lunderman, Matthias Morzfeld & Derek J. Posselt. (2021) Using global Bayesian optimization in ensemble data assimilation: parameter estimation, tuning localization and inflation, or all of the above. Tellus A: Dynamic Meteorology and Oceanography 73:1, pages 1-16.
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Sarah A. King, Kazufumi Ito & Daniel Hodyss. (2020) A numerical integration-based Kalman filter for moderately nonlinear systems. Tellus A: Dynamic Meteorology and Oceanography 72:1, pages 1-17.
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Articles from other publishers (10)

Maximilian Ramgraber, Ricardo Baptista, Dennis McLaughlin & Youssef Marzouk. (2023) Ensemble transport smoothing. Part II: Nonlinear updates. Journal of Computational Physics: X 17, pages 100133.
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Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach & Pedram Hassanzadeh. (2023) Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems. Journal of Computational Physics 477, pages 111918.
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Lingfeng Tao, Xuguang Sun, Xiu‐Qun Yang, Jiabei Fang & Zhi‐Qi Zhang. (2023) Effect of Oceanic Stochastic Forcing on Wintertime Atmospheric Decadal Variability Over Midlatitude North Pacific. Journal of Geophysical Research: Atmospheres 128:2.
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Jonathan Poterjoy. (2022) Regularization and tempering for a moment‐matching localized particle filter. Quarterly Journal of the Royal Meteorological Society 148:747, pages 2631-2651.
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Yuming Ba, Jana de Wiljes, Dean S. Oliver & Sebastian Reich. (2021) Randomized maximum likelihood based posterior sampling. Computational Geosciences 26:1, pages 217-239.
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Lars Nerger. (2021) Data assimilation for nonlinear systems with a hybrid nonlinear Kalman ensemble transform filter. Quarterly Journal of the Royal Meteorological Society 148:743, pages 620-640.
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Ian Grooms & Gregor Robinson. (2021) A hybrid particle-ensemble Kalman filter for problems with medium nonlinearity. PLOS ONE 16:3, pages e0248266.
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John Maclean & Elaine T. Spiller. (2021) A surrogate-based approach to nonlinear, non-Gaussian joint state-parameter data assimilation. Foundations of Data Science 3:3, pages 589.
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Hojat Ghorbanidehno, Amalia Kokkinaki, Jonghyun Lee & Eric Darve. (2020) Recent developments in fast and scalable inverse modeling and data assimilation methods in hydrology. Journal of Hydrology 591, pages 125266.
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Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach & Pedram Hassanzadeh. (2022) Deep Learning-Enhanced Ensemble-Based Data Assimilation for High-Dimensional Nonlinear Dynamical Systems. SSRN Electronic Journal.
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