Hybrid Levenberg–Marquardt and Weak-Constraint Ensemble Kalman Smoother Method

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00458290" target="_blank" >RIV/67985807:_____/16:00458290 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5194/npg-23-59-2016" target="_blank" >http://dx.doi.org/10.5194/npg-23-59-2016</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5194/npg-23-59-2016" target="_blank" >10.5194/npg-23-59-2016</a>

Result language
angličtina
Original language name
Hybrid Levenberg–Marquardt and Weak-Constraint Ensemble Kalman Smoother Method
Original language description
The ensemble Kalman smoother (EnKS) is used as a linear least-squares solver in the Gauss-Newton method for the large nonlinear least-squares system in incremental 4DVAR. The ensemble approach is naturally parallel over the ensemble members and no tangent or adjoint operators are needed. Furthermore, adding a regularization term results in replacing the Gauss-Newton method, which may diverge, by the Levenberg-Marquardt method, which is known to be convergent. The regularization is implemented efficiently as an additional observation in the EnKS. The method is illustrated on the Lorenz 63 model and a two-level quasigeostrophic model.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Project
<a href="/en/project/GA13-34856S" target="_blank" >GA13-34856S: Advanced random field methods in data assimilation for short-term weather prediction</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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