Simulation of strongly non-Gaussian processes using Karhunen–Loeve expansion

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Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014, methodology): “The procedure was refined in [24] for highly skewed non-Gaussian processes.”
Solving elliptic problems with non-Gaussian spatially-dependent random coefficients (2009, methodology): “In [7], the Karhunen–Loève expansion was employed to simulate non-Gaussian processes.”
The stochastic finite element method: Past, present and future (2009, methodology): “The method offers a unified framework for the simulation of homogeneous and nonhomogeneous stochastic fields and has been further improved in order to cover the case of highly skewed distributions [142].”
Simulation of simply cross correlated random fields by series expansion methods (2008, methodology): “[40] recently proposed simulation of non-Gaussian processes via Karhunen–Loéve expansion with uncorrelated non-Gaussian coefficients of zero mean and unit variance.”