Stochastic model of the joint time-series of air temperature and atmospheric pressure

In this paper a numerical stochastic model of the joint nonstationary time-series of the air temperature and atmospheric pressure is proposed. The model is based on an 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 the day/night alternation. The input parameters of the model (onedimensional distributions of the air temperature and atmospheric pressure and the correlation structure of the joint time-series) are determined from the data of long-term real observations at weather stations.