Stochastic models of joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure

Результат исследования: Научные публикации в периодических изданияхстатья

1 Цитирования (Scopus)

Аннотация

In this paper two numerical stochastic models of the joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure are proposed. The first 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, determined by the day/night alternation. Within the framework of the second model, real weather processes are considered as non-stationary random processes. The input parameters of both models (one-dimensional distributions and correlation structure of the joint time-series) are determined from the data of long-term real observations at weather stations. The results of the models verification are presented.

Язык оригиналаанглийский
ЖурналCommunications in Statistics: Simulation and Computation
DOI
СостояниеОпубликовано - 1 янв 2019

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