Name
Title | ||
|---|---|---|
A Time-parallel Approach to Strong-constraint Four-dimensional Variational Data Assimilation. |
Abstract | ||
|---|---|---|
A parallel-in-time algorithm based on an augmented Lagrangian approach is proposed to solve four-dimensional variational (4D-Var) data assimilation problems. The assimilation window is divided into multiple sub-intervals that allows parallelization of cost function and gradient computations. The solutions to the continuity equations across interval boundaries are added as constraints. The augmented Lagrangian approach leads to a different formulation of the variational data assimilation problem than the weakly constrained 4D-Var. A combination of serial and parallel 4D-Vars to increase performance is also explored. The methodology is illustrated on data assimilation problems involving the Lorenz-96 and the shallow water models. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.jcp.2016.02.040 | Journal of Computational Physics |
Keywords | DocType | Volume |
Variational data assimilation,Time parallel variational data assimilation,Adjoint sensitivity analysis,Augmented Lagrangian | Journal | 313 |
Issue | ISSN | Citations |
C | 0021-9991 | 4 |
PageRank | References | Authors |
0.50 | 12 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vishwas Rao | 1 | 17 | 4.39 |
| Adrian Sandu | 2 | 325 | 58.93 |