Estimation and Calibration of Observation Impact Signals Using the Lanczos Method in NOAA/NCEP Data Assimilation System
Abstract
We use the Lanczos method in the NCEP (the National Centers for Environmental Prediction) Gridpoint Statistical Interpolation (GSI) DA system to look into the important aspects and properties of this method. We apply this method to estimate the observation impact signals (OIS) which are directly related to the analysis error variances. It is found that the smallest eigenvalue of the transformed Hessian matrix converges to one as the number of minimization iterations increases. When more observations are assimilated, the convergence becomes slower and more eigenvectors are needed to retrieve the observation impacts. It is also found that the OIS over data-rich regions can be represented by the eigenvectors with dominant eigenvalues. We have proposed four different calibration schemes to compensate for the missing trailing eigenvectors. Results show that the method with proper calibrations for a small number of eigenvectors enhances and improves the impact signals over regions with more data
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 25, 2012
- Accession Number
- ADA571385
Entities
People
- D. Parrish
- M. S. De Pondeca
- M. S. Wei
- Z. Toth
Organizations
- United States Naval Research Laboratory