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Tellus A: Dynamic Meteorology and Oceanography Volume 52, 2000 - Issue 3

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Original Articles

An adaptive variational method for data assimilation with imperfect models

Jian ZhuMeteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan;Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, Kawaguchi Center Building 12fl., 4-1-8 Honmachi, Kawaguchi, Saitama332-0012, Japan;Institute of Atmospheric Physics, Chinese Academy of Science, Beijing100029, ChinaCorrespondence[email protected]

Masafumi KamachiMeteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan

Pages 265-279 | Received 08 Feb 1999, Accepted 18 Oct 1999, Published online: 15 Dec 2016

Cite this article
https://doi.org/10.3402/tellusa.v52i3.12265

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Articles from other publishers (5)

Matthew Levine & Andrew Stuart. (2022) A framework for machine learning of model error in dynamical systems. Communications of the American Mathematical Society 2:7, pages 283-344.
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Ionel M. Navon. 2009. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications 21 65 .

Mi-Seon Lee & Dong-Kyou Lee. (2003) An Application of a Weakly Constrained 4DVAR to Satellite Data Assimilation and Heavy Rainfall Simulation. Monthly Weather Review 131:9, pages 2151-2176.
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Masafumi Kamachi, Tsurane Kuragano, Noriya Yoshioka, Jiang Zhu & Francesco Uboldi. (2001) Assimilation of Satellite Altimetry into a Western North Pacific Operational Model. Advances in Atmospheric Sciences 18:5, pages 767-786.
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Bin Wang, Xiaolei Zou & Jiang Zhu. (2000) Data assimilation and its applications. Proceedings of the National Academy of Sciences 97:21, pages 11143-11144.
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