Monte Carlo Simulation of Non-stationary Air Temperature Time-Series

Nina Kargapolova

2018

Abstract

Two numerical stochastic models of air temperature time-series are considered in this paper. The first model is constructed under the assumption that time-series are nonstationary. In the second model air temperature time-series are considered as a periodically correlated random processes. Data from real observations on weather stations was used for estimation of models’ parameters. On the basis of simulated trajectories, some statistical properties of rare meteorological events, like sharp temperature drops or long-term temperature decreases in summer, are studied.

Paper Citation

in Harvard Style

Kargapolova N. (2018). Monte Carlo Simulation of Non-stationary Air Temperature Time-Series.In Proceedings of 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-323-0, pages 323-329. DOI: 10.5220/0006833403230329

in Bibtex Style

@conference{simultech18,
author={Nina Kargapolova},
title={Monte Carlo Simulation of Non-stationary Air Temperature Time-Series},
booktitle={Proceedings of 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2018},
pages={323-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006833403230329},
isbn={978-989-758-323-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Monte Carlo Simulation of Non-stationary Air Temperature Time-Series
SN - 978-989-758-323-0
AU - Kargapolova N.
PY - 2018
SP - 323
EP - 329
DO - 10.5220/0006833403230329