Singular-spectral climate models

In this paper, the singular spectrum analysis method is used to construct data models for the Onega Lake basin: time series of air temperature, precipitation, and runoff of the Shuya, Suna, and Vodla rivers. The model is represented by a trend, seasonality, and noise formed from the components of th...

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Main Author: Belashev Boris
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/23/e3sconf_aees2025_01019.pdf
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author Belashev Boris
author_facet Belashev Boris
author_sort Belashev Boris
collection DOAJ
description In this paper, the singular spectrum analysis method is used to construct data models for the Onega Lake basin: time series of air temperature, precipitation, and runoff of the Shuya, Suna, and Vodla rivers. The model is represented by a trend, seasonality, and noise formed from the components of the singular decomposition of a special matrix of the time series of data. The model is used to describe the variability of the time series variability, reconstruct gaps, and perform a forecast. Models with different numbers of noise components included in the seasonal component are analyzed. It is shown that stable estimates are provided by a model composed of components with large eigenvaIues is proposed to consider the estimates of such a model as local climate data and compare them with the results of global climate modeling. Modeling has confirmed typical regimes of air temperature and runoff fluctuations in the main rivers of the Onega Lake basin.
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publishDate 2025-01-01
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record_format Article
series E3S Web of Conferences
spelling doaj-art-fe22a77f9f794437b8d244e6f4806b2e2025-08-20T02:09:34ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016230101910.1051/e3sconf/202562301019e3sconf_aees2025_01019Singular-spectral climate modelsBelashev Boris0Karelian research Center of Russian Academy of Sciences Institute of GeologyIn this paper, the singular spectrum analysis method is used to construct data models for the Onega Lake basin: time series of air temperature, precipitation, and runoff of the Shuya, Suna, and Vodla rivers. The model is represented by a trend, seasonality, and noise formed from the components of the singular decomposition of a special matrix of the time series of data. The model is used to describe the variability of the time series variability, reconstruct gaps, and perform a forecast. Models with different numbers of noise components included in the seasonal component are analyzed. It is shown that stable estimates are provided by a model composed of components with large eigenvaIues is proposed to consider the estimates of such a model as local climate data and compare them with the results of global climate modeling. Modeling has confirmed typical regimes of air temperature and runoff fluctuations in the main rivers of the Onega Lake basin.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/23/e3sconf_aees2025_01019.pdf
spellingShingle Belashev Boris
Singular-spectral climate models
E3S Web of Conferences
title Singular-spectral climate models
title_full Singular-spectral climate models
title_fullStr Singular-spectral climate models
title_full_unstemmed Singular-spectral climate models
title_short Singular-spectral climate models
title_sort singular spectral climate models
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/23/e3sconf_aees2025_01019.pdf
work_keys_str_mv AT belashevboris singularspectralclimatemodels