Stochastic models of joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure

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Stochastic models of joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure. / Kargapolova, N. A.; Khlebnikova, E. I.; Ogorodnikov, V. A.

In: Communications in Statistics: Simulation and Computation, Vol. 50, No. 12, 2021, p. 3972-3983.

Research output: Contribution to journal › Article › peer-review

BibTeX

@article{31f82ce002604e6380433f494c283625,

title = "Stochastic models of joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure",

abstract = "In this paper two numerical stochastic models of the joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure are proposed. The first 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, determined by the day/night alternation. Within the framework of the second model, real weather processes are considered as non-stationary random processes. The input parameters of both models (one-dimensional distributions and correlation structure of the joint time-series) are determined from the data of long-term real observations at weather stations. The results of the models verification are presented.",

keywords = "Meteorological time-series, Non-Gaussian random process, Non-stationary random process, Periodically correlated random process, Stochastic simulation",

author = "Kargapolova, {N. A.} and Khlebnikova, {E. I.} and Ogorodnikov, {V. A.}",

note = "Publisher Copyright: {\textcopyright} 2019 Taylor & Francis Group, LLC.",

year = "2021",

doi = "10.1080/03610918.2019.1635157",

language = "English",

volume = "50",

pages = "3972--3983",

journal = "Communications in Statistics Part B: Simulation and Computation",

issn = "0361-0918",

publisher = "Taylor and Francis Ltd.",

number = "12",

}

RIS

TY - JOUR

T1 - Stochastic models of joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure

AU - Kargapolova, N. A.

AU - Khlebnikova, E. I.

AU - Ogorodnikov, V. A.

PY - 2021

Y1 - 2021

N2 - In this paper two numerical stochastic models of the joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure are proposed. The first 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, determined by the day/night alternation. Within the framework of the second model, real weather processes are considered as non-stationary random processes. The input parameters of both models (one-dimensional distributions and correlation structure of the joint time-series) are determined from the data of long-term real observations at weather stations. The results of the models verification are presented.

AB - In this paper two numerical stochastic models of the joint non-stationary time-series of air temperature, relative humidity and atmospheric pressure are proposed. The first 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, determined by the day/night alternation. Within the framework of the second model, real weather processes are considered as non-stationary random processes. The input parameters of both models (one-dimensional distributions and correlation structure of the joint time-series) are determined from the data of long-term real observations at weather stations. The results of the models verification are presented.

KW - Meteorological time-series

KW - Non-Gaussian random process

KW - Non-stationary random process

KW - Periodically correlated random process

KW - Stochastic simulation

UR - http://www.scopus.com/inward/record.url?scp=85068188236&partnerID=8YFLogxK

U2 - 10.1080/03610918.2019.1635157

DO - 10.1080/03610918.2019.1635157

M3 - Article

AN - SCOPUS:85068188236

VL - 50

SP - 3972

EP - 3983

JO - Communications in Statistics Part B: Simulation and Computation

JF - Communications in Statistics Part B: Simulation and Computation

SN - 0361-0918

IS - 12

ER -

ID: 20711199