Stoсhastic model of the time series of the average daily bioclimatic index of severity of climatic regime

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Abstract

In this paper, a numerical stochastic model of the time series of the average daily bioclimatic index of severity of climatic regime is proposed and validated. This model is based on an assumption that real weather processes are non-stationary random processes on a year-long interval. In this assumption, the model takes into account the seasonal variation of the real meteorological processes. The input parameters of the model are determined from the data of long-term real observations at weather stations. It is shown that the trajectories of the model proposed are close in their statistical properties to the real time series of the bioclimatic index under consideration. The results related to studying the influence of a climate change on the time series of the average daily bioclimatic index of severity of climatic regime are given.

Original languageEnglish
Title of host publication33rd Annual European Simulation and Modelling Conference 2019, ESM 2019
EditorsPilar Fuster-Parra, Oscar Valero Sierra
PublisherEUROSIS
Pages185-189
Number of pages5
ISBN (Electronic)9789492859099
Publication statusPublished - 1 Jan 2019
Event33rd Annual European Simulation and Modelling Conference, ESM 2019 - Plama de Mallorca, Spain
Duration: 28 Oct 201930 Oct 2019

Publication series

Name33rd Annual European Simulation and Modelling Conference 2019, ESM 2019

Conference

Conference33rd Annual European Simulation and Modelling Conference, ESM 2019
CountrySpain
CityPlama de Mallorca
Period28.10.201930.10.2019

Keywords

  • Bioclimatic Index of Severity of Climatic Regime
  • Climate Change
  • Non-stationary Random Process
  • Stochastic Simulation
  • Time-series Analysis

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