Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-03-01
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| Series: | Nonlinear Processes in Geophysics |
| Online Access: | http://www.nonlin-processes-geophys.net/23/59/2016/npg-23-59-2016.pdf |
| Summary: | 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 quasi-geostrophic model. |
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| ISSN: | 1023-5809 1607-7946 |