Combining Ensemble and Variational Data Assimilation
Abstract
The long-term goal of this project is to develop and apply practical methods for data assimilation to improve the short-range prediction of mesoscale ocean variability. OBJECTIVES A key objective of this work is to develop an ocean data assimilation system that exploits the strengths of both the ensemble-based (e.g., Evensen 2003; Houtekamer and Mitchell 1998; Tippett et al. 2003) and variational (e.g., Bennett 2002) approaches to data assimilation. The first step in this project is to perform an inter-comparison of an ensemble-based data assimilation system with a 4dVar system for a suite of coastal model configurations. The second step is to identify the strengths and weaknesses of each system and to improve both systems by borrowing components from the other system. It is our goal to develop a hybrid ensemble-var system. We will investigate the extent to which the ensemble-var system can outperform both the ensemble-based and variational approaches, both in terms of forecast skill (accuracy) and computational efficiency (throughput).
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2013
- Accession Number
- ADA599186
Entities
People
- Alexander Kurapov
- Peter R. Oke
Organizations
- Oregon State University