Combining Ensemble and Variational Data Assimilation
OREGON STATE UNIV CORVALLIS COLL OF OCEANIC AND ATMOSPHERIC SCIENCES
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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. The primary 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 a comprehensive inter-comparison of an ensemble-based data assimilation system with a 4d-var 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. Ultimately, a single ensemble-var system will be developed. 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.
- Physical and Dynamic Oceanography