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

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Abstract

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.

Original languageEnglish
Title of host publication32nd Annual European Simulation and Modelling Conference 2018, ESM 2018
EditorsVeronique Limere, Dieter Claeys
PublisherEUROSIS
Pages199-204
Number of pages6
ISBN (Electronic)9789492859051
Publication statusPublished - 1 Jan 2018
Event32nd Annual European Simulation and Modelling Conference, ESM 2018 - Ghent, Belgium
Duration: 24 Oct 201826 Oct 2018

Conference

Conference32nd Annual European Simulation and Modelling Conference, ESM 2018
CountryBelgium
CityGhent
Period24.10.201826.10.2018

Keywords

  • Air temperature
  • Atmospheric pressure
  • Model validation.
  • Non-stationary random process
  • Periodically correlated process
  • Stochastic simulation
  • Time-series analysis

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