Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route

Article describes a probabilistic model (stochastic generator) of spatial-temporal variability of sea ice concentration. Values of the ice concentration are generated at the nodes of the spatial grid with 10 km resolution; the model time step is one day. The change in ice concentration with time (te...

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Published in:Ice and Snow
Main Authors: R. I. May, R. B. Guzenko, O. V. Tarovik, A. G. Topaj, A. V. Yulin
Format: Article in Journal/Newspaper
Language:Russian
Published: Nauka 2022
Subjects:
Q
Online Access:https://doi.org/10.31857/S2076673422010121
https://doaj.org/article/f13804848853446fa230625f0cc1b0fe
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spelling ftdoajarticles:oai:doaj.org/article:f13804848853446fa230625f0cc1b0fe 2023-05-15T17:43:51+02:00 Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route R. I. May R. B. Guzenko O. V. Tarovik A. G. Topaj A. V. Yulin 2022-02-01T00:00:00Z https://doi.org/10.31857/S2076673422010121 https://doaj.org/article/f13804848853446fa230625f0cc1b0fe RU rus Nauka https://ice-snow.igras.ru/jour/article/view/955 https://doaj.org/toc/2076-6734 https://doaj.org/toc/2412-3765 2076-6734 2412-3765 doi:10.31857/S2076673422010121 https://doaj.org/article/f13804848853446fa230625f0cc1b0fe Лëд и снег, Vol 62, Iss 1, Pp 125-140 (2022) вероятностное моделирование сплочённость льда стохастический генератор ледяного покрова ледовые условия цепь маркова навигация в арктике Science Q article 2022 ftdoajarticles https://doi.org/10.31857/S2076673422010121 2023-03-19T01:40:08Z Article describes a probabilistic model (stochastic generator) of spatial-temporal variability of sea ice concentration. Values of the ice concentration are generated at the nodes of the spatial grid with 10 km resolution; the model time step is one day. The change in ice concentration with time (temporal variability) is modeled on the basis of a matrix of transient probabilities (discrete Markov chain), each row of which is a distribution function of the conditional probability of changes in the ice concentration. Spatial variability is determined by empirical probability fields, with which the observed changes in fields of the ice concentration are associated with known conditional probability distribution functions. To identify the parameters of the stochastic generator, satellite data from the OSI SAF project for the period 1987–2019 were used. The generator takes into account seasonal, interannual and climatic variability. Interannual and climatic variability are determined on the basis of a stochastic model of changes in the types of ice coverage. In order to verify the developed stochastic generator, we compared the statistical indicators of observed and calculated ice fields. The results showed that the fieldaverage absolute error of statistical characteristics of the ice concentration (mean and standard deviation) does not exceed 3.3%. The discrepancy between the correlation intervals of ice coverage calculated from the model and measured ice concentration fields does not exceed 2 days. The variograms of the modeled and observed fields have a similar form and close values. As an example, we determined the duration of navigation of Arc4 ice class ships between the Barents and Kara Seas using synthetic fields of the ice concentration reproduced by the stochastic generator. Article in Journal/Newspaper Northern Sea Route Sea ice Directory of Open Access Journals: DOAJ Articles Ice and Snow 62 1 125 140
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language Russian
topic вероятностное моделирование
сплочённость льда
стохастический генератор ледяного покрова
ледовые условия
цепь маркова
навигация в арктике
Science
Q
spellingShingle вероятностное моделирование
сплочённость льда
стохастический генератор ледяного покрова
ледовые условия
цепь маркова
навигация в арктике
Science
Q
R. I. May
R. B. Guzenko
O. V. Tarovik
A. G. Topaj
A. V. Yulin
Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route
topic_facet вероятностное моделирование
сплочённость льда
стохастический генератор ледяного покрова
ледовые условия
цепь маркова
навигация в арктике
Science
Q
description Article describes a probabilistic model (stochastic generator) of spatial-temporal variability of sea ice concentration. Values of the ice concentration are generated at the nodes of the spatial grid with 10 km resolution; the model time step is one day. The change in ice concentration with time (temporal variability) is modeled on the basis of a matrix of transient probabilities (discrete Markov chain), each row of which is a distribution function of the conditional probability of changes in the ice concentration. Spatial variability is determined by empirical probability fields, with which the observed changes in fields of the ice concentration are associated with known conditional probability distribution functions. To identify the parameters of the stochastic generator, satellite data from the OSI SAF project for the period 1987–2019 were used. The generator takes into account seasonal, interannual and climatic variability. Interannual and climatic variability are determined on the basis of a stochastic model of changes in the types of ice coverage. In order to verify the developed stochastic generator, we compared the statistical indicators of observed and calculated ice fields. The results showed that the fieldaverage absolute error of statistical characteristics of the ice concentration (mean and standard deviation) does not exceed 3.3%. The discrepancy between the correlation intervals of ice coverage calculated from the model and measured ice concentration fields does not exceed 2 days. The variograms of the modeled and observed fields have a similar form and close values. As an example, we determined the duration of navigation of Arc4 ice class ships between the Barents and Kara Seas using synthetic fields of the ice concentration reproduced by the stochastic generator.
format Article in Journal/Newspaper
author R. I. May
R. B. Guzenko
O. V. Tarovik
A. G. Topaj
A. V. Yulin
author_facet R. I. May
R. B. Guzenko
O. V. Tarovik
A. G. Topaj
A. V. Yulin
author_sort R. I. May
title Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route
title_short Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route
title_full Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route
title_fullStr Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route
title_full_unstemmed Stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the Northern Sea Route
title_sort stochastic modeling of sea ice concentration fields for assessment of navigation conditions along the northern sea route
publisher Nauka
publishDate 2022
url https://doi.org/10.31857/S2076673422010121
https://doaj.org/article/f13804848853446fa230625f0cc1b0fe
genre Northern Sea Route
Sea ice
genre_facet Northern Sea Route
Sea ice
op_source Лëд и снег, Vol 62, Iss 1, Pp 125-140 (2022)
op_relation https://ice-snow.igras.ru/jour/article/view/955
https://doaj.org/toc/2076-6734
https://doaj.org/toc/2412-3765
2076-6734
2412-3765
doi:10.31857/S2076673422010121
https://doaj.org/article/f13804848853446fa230625f0cc1b0fe
op_doi https://doi.org/10.31857/S2076673422010121
container_title Ice and Snow
container_volume 62
container_issue 1
container_start_page 125
op_container_end_page 140
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