Fortran Subroutines for Computing the Optimal Interpolation Formula - ISBN:0705802086

Fortran Subroutines for Computing the Optimal Interpolation Formula

Date: 21 April 2011, 01:35

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The first data assimilation methods were called the "objective analyses" (e.g., Cressman algorithm). The breakthrough in the field of data assimilation was achieved by L. Gandin (1963) who introduced the "statistical interpolation" (or "optimal interpolation") method.
His work developed the previous ideas of Kolmogorov. That method is a 3DDA method and is a type of regression analyses, which utilizes information about the spatial distributions of covariance functions of the errors of the "first guess" field (previous forecast) and "true field".
These functions are never known. However, the different approximations were assumed.
In fact the optimal interpolation algorithm is the reduced version of the Kalman filtering (KF) algorithm, when the covariance matrices are not calculated from the dynamical equations, but are pre-determined in advance.
This book is to explain how to compute the function $\Omega$ which interpolates values of a function of one variable $f(x)$ at $n$ distinct points provides the smallest possible value.

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