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.
|Title of host publication||32nd Annual European Simulation and Modelling Conference 2018, ESM 2018|
|Editors||Veronique Limere, Dieter Claeys|
|Number of pages||6|
|Publication status||Published - 1 Jan 2018|
|Event||32nd Annual European Simulation and Modelling Conference, ESM 2018 - Ghent, Belgium|
Duration: 24 Oct 2018 → 26 Oct 2018
|Conference||32nd Annual European Simulation and Modelling Conference, ESM 2018|
|Period||24.10.2018 → 26.10.2018|
- Air temperature
- Atmospheric pressure
- Model validation.
- Non-stationary random process
- Periodically correlated process
- Stochastic simulation
- Time-series analysis