Accelerating the spin-up of Ensemble Kalman Filtering
| dc.creator | Kalnay, Eugenia | |
| dc.creator | Yang, Shu-Chih | |
| dc.date | 2008-06-01 | |
| dc.date.accessioned | 2026-07-07T09:42:09Z | |
| dc.date.available | 2026-07-07T09:42:09Z | |
| dc.description | A scheme is proposed to improve the performance of the ensemble-based Kalman Filters during the initial spin-up period. By applying the no-cost ensemble Kalman Smoother, this scheme allows the model solutions for the ensemble to be "running in place" with the true dynamics, provided by a few observations. Results of this scheme are investigated with the Local Ensemble Transform Kalman Filter (LETKF) implemented in a Quasi-geostrophic model, whose original framework requires a very long spin-up time when initialized from a cold start. Results show that it is possible to spin up the LETKF and have a fast convergence to the optimal level of error. The extra computation is only required during the initial spin-up since this scheme resumes to the original LETKF after the "running in place" is achieved. | |
| dc.description | 11 pages, 2 figures presented in 3rd Ensemble Data Assimilation Workshop in Austin, Texas | |
| dc.identifier | https://arxiv.org/abs/0806.0180 | |
| dc.identifier | http://arxiv.org/abs/0806.0180 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/162081 | |
| dc.subject | Chaotic Dynamics | |
| dc.title | Accelerating the spin-up of Ensemble Kalman Filtering | |
| dc.type | text |