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In this paper a numerical stochastic model of the joint non-Gaussian periodically correlated time-series of air temperature and relative humidity is proposed. The model is based on the assumption that real weather processes are periodically correlated random processes with a period equal to 1 day. This assumption takes into account the diurnal variation of real meteorological processes, defined by...
This paper deals with numerical simulation of random fields corresponding to a stochastic structure of atmospheric clouds. We construct numerical models to simulate the optical thickness of stratus clouds as well as indicator fields of broken clouds. To simulate the random fields we use spectral and autoregressive models, as well as a method of nonlinear transformations of Gaussian functions.
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