Numerical Stochastic Model of Non-stationary Time Series of the Wind Chill Index

Stochastic Model of Spatial Fields of the Average Daily Wind Chill Index

“…This method allows one to simulate a non-Gaussian process with the given one-dimensional distributions and the given correlation structure. It is shown in [16] that the mixtures g k (x), k = 1, NS of the two Gaussian distributions will sufficiently approximate the sample histograms of the real average daily WCI. The correlation structure of the field → W is defined by the NS × NS correlation matrix R = r(i, j) NS i,j=1 that is estimated on the real data.…”

“…Let us recall the idea of the MIDF. In the framework of the MIDF, simulating of the field → W with the given densities g k (x), k = 1, NS and the given correlation matrix R comes to an algorithm (let us call it the Algorithm 1) with the three steps [11,16]: Algorithm 1.…”

“…In this paper, a stochastic approach was for the first time applied to studying the spatial fields of the average daily wind chill index (WCI). Earlier, this approach was successfully applied to simulation and forecasting of the WCI time series [16,17]. The field of the WCI was simulated on an irregular grid determined by the location of the weather stations.…”

“…The model proposed could be easily transformed to a model of a conditional random field of the average daily WCI. For the time-series of the WCI, such transformation is presented in [17].…”