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Stochastic Modeling of Sea Ice Concentration to Assess Navigation Conditions along the Northern Sea Route

  • SEA, RIVER AND LAKE ICE
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Abstract

This article describes a probabilistic model (stochastic generator) of spatiotemporal variability of sea ice concentration. The values of the concentration are generated at the nodes of the spatial grid with 10‑km resolution; the model time step is 1 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 concentration. Spatial variability is determined by empirical probability fields, with which the observed changes in fields of 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 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 compare the statistical indicators of observed and calculated ice fields. The results show that the field-average absolute error of statistical characteristics of the ice concentration (average 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 determine the duration of navigation of Arc4 ice class ships between the Barents and Kara seas using synthetic fields of the concentration reproduced by the stochastic generator.

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Funding

This study was supported by the Russian Science Foundation, project no. 23-19-00039.

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Authors and Affiliations

  1. Krylov State Research Center, St. Petersburg, Russia

    R. I. May & O. V. Tarovik

  2. Arctic and Antarctic Research Institute, St. Petersburg, Russia

    R. B. Guzenko & A. V. Yulin

  3. St. Petersburg State University, St. Petersburg, Russia

    R. I. May

  4. LLC Bureau Hyperborea, St. Petersburg, Russia

    O. V. Tarovik & A. G. Topaj

Authors
  1. R. I. May
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  2. R. B. Guzenko
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  3. O. V. Tarovik
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  4. A. G. Topaj
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  5. A. V. Yulin
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Correspondence to R. I. May.

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May, R.I., Guzenko, R.B., Tarovik, O.V. et al. Stochastic Modeling of Sea Ice Concentration to Assess Navigation Conditions along the Northern Sea Route. Izv. Atmos. Ocean. Phys. 59 (Suppl 1), S57–S69 (2023). https://doi.org/10.1134/S0001433823130091

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  • DOI: https://doi.org/10.1134/S0001433823130091

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