Stochastic Models of Non-stationary Time Series of the Average Daily Heat Index

Nina Kargapolova

Abstract

In this paper two numerical stochastic models of time series of the average daily heat index are considered. In the first model, time series of the heat index are constructed as a function of simulated joint nonstationary time series of air temperature and relative humidity. The second model is constructed under the assumption that time series of the heat index are non-stationary non-Gaussian random processes. Data from real observations at weather stations were used for estimating models’ parameters. On the basis of the simulated trajectories, some statistical properties of rare meteorological events, like long periods of time with high heat index, are studied.

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Paper Citation


in Harvard Style

Kargapolova N. (2019). Stochastic Models of Non-stationary Time Series of the Average Daily Heat Index.In Proceedings of the 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-381-0, pages 209-215. DOI: 10.5220/0007788502090215


in Bibtex Style

@conference{simultech19,
author={Nina Kargapolova},
title={Stochastic Models of Non-stationary Time Series of the Average Daily Heat Index},
booktitle={Proceedings of the 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2019},
pages={209-215},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007788502090215},
isbn={978-989-758-381-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Stochastic Models of Non-stationary Time Series of the Average Daily Heat Index
SN - 978-989-758-381-0
AU - Kargapolova N.
PY - 2019
SP - 209
EP - 215
DO - 10.5220/0007788502090215