Standard

Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation. / Akenteva, M. S.; Kargapolova, N. A.

In: Russian Meteorology and Hydrology, Vol. 48, No. 7, 07.2023, p. 614-623.

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

Harvard

Akenteva, MS & Kargapolova, NA 2023, 'Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation', Russian Meteorology and Hydrology, vol. 48, no. 7, pp. 614-623. https://doi.org/10.3103/S1068373923070087

APA

Akenteva, M. S., & Kargapolova, N. A. (2023). Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation. Russian Meteorology and Hydrology, 48(7), 614-623. https://doi.org/10.3103/S1068373923070087

Vancouver

Akenteva MS, Kargapolova NA. Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation. Russian Meteorology and Hydrology. 2023 Jul;48(7):614-623. doi: 10.3103/S1068373923070087

Author

Akenteva, M. S. ; Kargapolova, N. A. / Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation. In: Russian Meteorology and Hydrology. 2023 ; Vol. 48, No. 7. pp. 614-623.

BibTeX

@article{e764d0aa72e94a6c894a3bd309628698,
title = "Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation",
abstract = "A stochastic weather generator is proposed in the paper. The model is designed for the numerical simulation of joint time series of surface air temperature, wind speed, and relative air humidity with a three-hour resolution at weather stations located in the Russian Arctic. The proposed weather generator allows taking into account the non-Gaussian form of one-dimensional distributions of meteorological parameters and the diurnal variations inherent to real series. The results of verifying the proposed model are presented, and the prospects of its further application are briefly described.",
keywords = "Russian Arctic, non-Gaussian random process, stochastic modeling, stochastic weather generator",
author = "Akenteva, {M. S.} and Kargapolova, {N. A.}",
note = "The research was supported by the Russian Science Foundation (grant 21-71-00007). Публикация для корректировки.",
year = "2023",
month = jul,
doi = "10.3103/S1068373923070087",
language = "English",
volume = "48",
pages = "614--623",
journal = "Russian Meteorology and Hydrology",
issn = "1068-3739",
publisher = "PLEIADES PUBLISHING INC",
number = "7",

}

RIS

TY - JOUR

T1 - Development of a Stochastic Weather Generator for Simulating Meteorological Time Series in the Arctic Zone of the Russian Federation

AU - Akenteva, M. S.

AU - Kargapolova, N. A.

N1 - The research was supported by the Russian Science Foundation (grant 21-71-00007). Публикация для корректировки.

PY - 2023/7

Y1 - 2023/7

N2 - A stochastic weather generator is proposed in the paper. The model is designed for the numerical simulation of joint time series of surface air temperature, wind speed, and relative air humidity with a three-hour resolution at weather stations located in the Russian Arctic. The proposed weather generator allows taking into account the non-Gaussian form of one-dimensional distributions of meteorological parameters and the diurnal variations inherent to real series. The results of verifying the proposed model are presented, and the prospects of its further application are briefly described.

AB - A stochastic weather generator is proposed in the paper. The model is designed for the numerical simulation of joint time series of surface air temperature, wind speed, and relative air humidity with a three-hour resolution at weather stations located in the Russian Arctic. The proposed weather generator allows taking into account the non-Gaussian form of one-dimensional distributions of meteorological parameters and the diurnal variations inherent to real series. The results of verifying the proposed model are presented, and the prospects of its further application are briefly described.

KW - Russian Arctic

KW - non-Gaussian random process

KW - stochastic modeling

KW - stochastic weather generator

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85176283769&origin=inward&txGid=eed52675a35f9c2b1e9cb2f83a72ef3f

UR - https://www.mendeley.com/catalogue/1a7c75d7-d78f-3b70-9e7c-365207eec849/

U2 - 10.3103/S1068373923070087

DO - 10.3103/S1068373923070087

M3 - Article

VL - 48

SP - 614

EP - 623

JO - Russian Meteorology and Hydrology

JF - Russian Meteorology and Hydrology

SN - 1068-3739

IS - 7

ER -

ID: 59564414