Objective analysis methods for combining observations with background/first-guess fields differ in their theoretical basis: Cressman and successive correction methods use empirically weighted, iterative interpolation schemes, while optimal interpolation (OI) is explicitly derived by minimizing the statistical (least-squares) error variance of the analysis, using observation and background error covariances.
Optimal interpolation is a statistical estimation technique that derives its interpolation weights by formally minimizing the expected error variance of the analyzed field, using known...
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