Accession Number:

ADA551181

Title:

A Hybrid Background Error Covariance Model for Assimilating Glider Data into a Coastal Ocean Model

Descriptive Note:

Journal article

Corporate Author:

NAVAL RESEARCH LAB STENNIS DETACHMENT STENNIS SPACE CENTER MS

Report Date:

2011-06-01

Pagination or Media Count:

13.0

Abstract:

A hybrid background error covariance BEC model for three-dimensional variational data assimilation of glider data into the Navy Coastal Ocean Model NCOM is introduced. Similar to existing atmospheric hybrid BEC models, the proposed model combines low-rank ensemble covariances Bm with the heuristic Gaussian-shaped covariances B0 to estimate forecast error statistics. The distinctive features of the proposed BEC model are the following i formulation in terms of inverse error covariances, ii adaptive determination of the rank m of Bm with information criterion based on the innovation error statistics, iii restriction of the heuristic covariance operator B0 to the null space of Bm, and iv definition of the BEC magnitudes through separate analyses of the innovation error statistics in the state space and the null space of B0. The BEC model is validated by assimilation experiments with simulated and real data obtained during a glider survey of the Monterey Bay in August 2003. It is shown that the proposed hybrid scheme substantially improves the forecast skill of the heuristic covariance model.

Subject Categories:

  • Physical and Dynamic Oceanography

Distribution Statement:

APPROVED FOR PUBLIC RELEASE