Errors of the day, bred vectors and singular vectors: Implications for ensemble forecasting and data assimilation

Shu Chih Yang, Matteo Corazza, Eugenia Kalnay

Research output: Contribution to journalConference articlepeer-review

Abstract

Several methods for data assimilation and ensemble forecasting were compared by the use of quasi-geostrophic 3D-Var data assimilation simulation system. It was necessary to develop the adjoint of this model to compare 2D-Var with 4D-Var and with the local ensemble Kalman filtering (LEKF). The bred vectors (BV) were obtained through a breeding cycle which started by adding random perturbation to the analysis and the singular vectors (SV) were obtained by assuming that the perturbation behaved linearly with the chosen optimization time interval. The results show that the final SVs have a similar structure as the BVs and both of them have a ability to depict the shape of the background error.

Original languageEnglish
Pages (from-to)227-236
Number of pages10
JournalBulletin of the American Meteorological Society
StatePublished - 2004
EventCombined Preprints: 84th American Meteorological Society (AMS) Annual Meeting - Seattle, WA., United States
Duration: 11 Jan 200415 Jan 2004

Fingerprint

Dive into the research topics of 'Errors of the day, bred vectors and singular vectors: Implications for ensemble forecasting and data assimilation'. Together they form a unique fingerprint.

Cite this