Numerical stochastic simulation of joint non-Gaussian meteorological series
V. A. Ogorodnikov, Elena I. Khlebnikova, S. S. Kosyak · Russian Journal of Numerical Analysis and Mathematical Modelling · 2009
Numerical stochastic simulation algorithms for vector stationary non-Gaussian series are considered. These algorithms allow one to reproduce variations in time for a set of continuous and discrete meteorological values of the daily resolution, such as surface air temperature, indicators of precipitation, wind velocity components, and overall cloudiness. Representations in the form of a mixture of normal distributions and specific threshold transformations of Gaussian processes are used for adequate description of one-dimensional distributions. The model can be used in interpretations of results of climatic simulation for estimation of climate change consequences and in solving various problems of applied climatology.