The objective of this research is to implement and evaluate a flexible advanced data assimilation system that can be used for basin scale, regional, and high-resolution limited area ocean models. This system will be able to assimilate a wide range of observation types (SST, SSH, ADCP, AUVs, UUVs, and HF radar) into different numerical models with varying resolutions and ocean regions. Data assimilation is critical in providing accurate analysis and predictions of the ocean environment. Optimal interpolation (OI) technology is currently being used to assimilate data operationally. However, these methods are inadequate and need to be updated with more advanced schemes. OI does not allow significant capabilities to use many observation types or propagate the information to correct many of the most significant errors source within nested model systems such as initial and boundary conditions. To enable these capabilities, assimilation systems must be developed that employ variational techniques: the Three-Dimensional Variational (3DVar) and Four-Dimensional Variational (4DVar) technologies that have been developed in meteorological applications. The 4DVar algorithm necessitates the development of the tangent linear and adjoint of the ocean model of interest. Other techniques under consideration are based on Kalman filtering using the ensemble approach.

 

Reference

Ngodock HE, Jacobs GA, Chen M: Ocean Modeling 12: 378, 2006

 

key words

Adjoint model; Ensemble kalman filter; Ocean circulation; Tangent linear model; Variational assimilation;

Citizenship:  Open to U.S. citizens and permanent residents

Level:  Open to Postdoctoral applicants

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