A Spectal Approach to Conditional Simulation

covariance matrix representing grid point’s correlation. For the large fields the Cholesky factorization can be computationally expensive. In this work we present an alternative approach, based on the usage of spectral representation of a conditional process. It is shown that covariance of two arbitrary spectral components could be factorized into functions of corresponding harmonics. In this case the Cholesky decomposition could be considerably simplified. The advantage of the presented approach is its accuracy and computational simplicity.