Stochastic models of bioclimatic indices time series in the Arctic zone of the Russian Federation

Abstract

In this paper, an approach to the numerical stochastic simulation of time series of two bioclimatic indices (wind chill index and the equivalent-effective temperature) at weather stations located in the Arctic zone of the Russian Federation is considered. The approach is based on the use of so-called “defining formulas”. On the basis of the considered approach, stochastic models of the time series of the considered bioclimatic indices were constructed, numerically implemented and verified. The models are developed on the assumption that the real bioclimatic processes are periodically correlated. The use of this assumption makes it possible to take into account the daily variation of the real processes. We also use the assumption that the real series of the wind chill index and the equivalent-effective temperature are non-Gaussian. To simulate non-stationary non-Gaussian time series, the method of inverse distribution functions is applied. The results of verification of the developed stochastic models showed that many statistical characteristics of simulated trajectories are close to the corresponding characteristics of the real series.