Project Details
Description
This proposal builds upon previous, ONR-funded development of the ROMS framework to improve the ocean modeling and prediction capabilities of the U.S. Navy. We have developed state-of-the-art variational ocean data assimilation and ensemble prediction systems based on conventional practices in operational numerical weather prediction. In addition, we have developed algorithms to quantify the impact of the observations in an analysis/forecast system and the uncertainty in the resulting circulation estimates. I propose to focus my research on the following tasks: (i) variational data assimilation (4D-Var) algorithms, (ii) nested 4D-Var, (iii) nonlinear model algorithms, (iv) documentation, training, and workshops. The proposed work in the 4D-Var algorithms will focus on several outstanding issues including spatial non-isotropic, non-homogeneous, and isopycnic error covariances; updates to the conjugate gradient solver, reduced resolution in the inner loops, and non-diagonal observation error covariances. We propose, in collaboration with Prof. A. Moore (separate proposal) to extend the current 4D-Var system so it is compatible with ROMS nesting capabilities and allow data assimilation to be carried out concurrently across multiple grids. The work on the nonlinear algorithms will focus on the development of additional idealized and realistic applications to test all the nested grid topologies (mosaic, composite, refinement, and composite-refinement subclasses), quadratic and conservative interpolation in nesting contact regions, Lagrangian drifters across nested grids, and pre- and post-processing Matlab scripts to facilitate the setting of complex nesting applications. I also propose to continue the web-based documentation in WikiROMS, and organizing annual workshops and tutorials.
Status | Active |
---|---|
Effective start/end date | 3/22/16 → … |
Funding
- U.S. Navy: $296,000.00
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.