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International Conference on Computer Recognition Systems

CORES 2019: Progress in Computer Recognition Systems pp 195–204Cite as

A Deep Learning Approach to Recognition of the Atmospheric Circulation Regimes

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 977))

Abstract

A supervised deep learning approach has been developed to automate recognition of the large-scale atmospheric circulation patterns. The approach is based on an application of the convolution neural network. The reanalysis meteorological fields were used as an input dataset. The dataset was labeled according to the circulation calendar constructed using the subjective Dzerdzeewski classification. One of the key issues for the success of the modeling was found to be a proper data preprocessing. The developed approach has demonstrated an accuracy compared with the more detailed regional classification methods that currently are being widely used for automated synoptic analysis.

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Notes

  1. 1.

    Available via atmospheric-circulation.ru.

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Acknowledgments

Authors highly appreciate discussions of the meteorologic processes with Prof. N.K. Kononova that have been highly encouraging for a presented work.

The work was supported by the Russian Science Foundation (project no. 18-79-10255).

Author information

Authors and Affiliations

  1. Global Energy Problems Laboratory, Moscow Power Engineering Institute, Krasnokazarmennaya 14, 111250, Moscow, Russia

    Victor Luferov & Ekaterina Fedotova

Authors
  1. Victor Luferov
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  2. Ekaterina Fedotova
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Corresponding author

Correspondence to Ekaterina Fedotova .

Editor information

Editors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland

    Robert Burduk

  2. Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland

    Marek Kurzynski

  3. Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland

    Michał Wozniak

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Luferov, V., Fedotova, E. (2020). A Deep Learning Approach to Recognition of the Atmospheric Circulation Regimes. In: Burduk, R., Kurzynski, M., Wozniak, M. (eds) Progress in Computer Recognition Systems. CORES 2019. Advances in Intelligent Systems and Computing, vol 977. Springer, Cham. https://doi.org/10.1007/978-3-030-19738-4_20

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