Ocean Spectral Data Assimilation Without Background Error Covariance Matrix
Abstract
Predetermination of background error covariance matrix B is challenging in existing oceandata assimilation schemes such as the optimal interpolation (OI). An optimal spectraldecomposition (OSD) has been developed to overcome such difficulty without using the Bmatrix. The basis functions are eigenvectors of the horizontal Laplacian operator, pre-calculatedon the base of ocean topography, and independent on any observational data and backgroundfields. Minimization of analysis error variance is achieved by optimal selection of the spectralcoefficients. Optimal mode truncation is dependent on the observational data and observationalerror variance and determined using the steep-descending method. Analytical 2D fields of largeand small mesoscale eddies with white Gaussian noises inside a domain with 4 rigid and curvedboundaries are used to demonstrate the capability of the OSD method. The overall errorreduction using the OSD is evident in comparison to the OI scheme. Synoptic monthly griddedworld ocean temperature, salinity, and absolute geostrophic velocity datasets produced with theOSD method and quality controlled by the NOAA National Centers for EnvironmentalInformation (NCEI) are also presented.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2016
- Accession Number
- AD1016665
Entities
People
- Chenwu Fan
- Peter Cheng Chu
- Tetyana M. Margolina
Organizations
- Naval Postgraduate School