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Numerical Investigation of the Direct Variational Algorithm of Data Assimilation in the Urban Scenario

Atmospheric and Oceanic Optics volume 31, pages 678–684 (2018)Cite this article

Abstract

The performance of a direct variational data assimilation algorithm with quasi-independent data assimilation at individual steps of the splitting scheme has been studied in a realistic scenario of air pollution assessment in the city of Novosibirsk by monitoring system data. For operation under conditions of a sparse monitoring network, an algorithm with minimization of the spatial derivative of the uncertainty (control) function adjusted to data assimilation is proposed. The use of the spatial derivative minimization increases the smoothness of the uncertainty (control functions) reconstructed, which has a positive effect on the reconstruction quality in the scenario considered.

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Authors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090, Russia

    A. V. Penenko, Zh. S. Mukatova & V. V. Penenko

  2. Siberian Regional Hydrometeorological Research Institute, Novosibirsk, 630099, Russia

    A. V. Gochakov

  3. V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences, Tomsk, 634055, Russia

    P. N. Antokhin

Authors
  1. A. V. Penenko
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  2. Zh. S. Mukatova
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  3. V. V. Penenko
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  4. A. V. Gochakov
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  5. P. N. Antokhin
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Corresponding author

Correspondence to A. V. Penenko.

Additional information

Original Russian Text © A.V. Penenko, Zh.S. Mukatova, V.V. Penenko, A.V. Gochakov, P.N. Antokhin, 2018, published in Optika Atmosfery i Okeana.

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Penenko, A.V., Mukatova, Z.S., Penenko, V.V. et al. Numerical Investigation of the Direct Variational Algorithm of Data Assimilation in the Urban Scenario. Atmos Ocean Opt 31, 678–684 (2018). https://doi.org/10.1134/S102485601806012X

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  • DOI: https://doi.org/10.1134/S102485601806012X

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