Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 2, pp. 40-48
Variational assimilation of satellite data on surface concentration of suspended matter in the Azov Sea
V.S. Kochergin
1 , S.V. Kochergin
1 , S.V. Stanichny
1 1 Marine Hydrophysical Institute RAS, Sevastopol, Russia
Accepted: 11.03.2020
DOI: 10.21046/2070-7401-2020-17-2-40-48
Satellite data allows us to obtain consistent information about the state of the sea surface and changes in spatial structures determined by the concentration of scattering suspension in the optical range. The main problem is the interference caused by, for example, cloud cover. Such interference often completely or partially interrupts the flow of information from the sea surface. Therefore, the task of restoring data for time intervals with missing data (gap filling) is important and relevant. This problem can be solved in various ways, including on the basis of variational assimilation of measurement data, which is implemented by identifying the input parameters of the model. The passive impurity transfer model itself acts as a space-time interpolant and the resulting solution on the used time interval is consistent with the mathematical model and with the measurement data due to the minimization of the prediction quality functional. The performance of the variational identification algorithm is shown on specific data, and the results obtained are compared with successive satellite images of the MODIS scanner. The results obtained showed good consistency of the results of numerical modeling with satellite information due to the minimization of the forecast quality functional, due to model spatial-temporal interpolation, the obtained concentration fields cover the entire water area of the sea of Azov at the time interval of model integration.
Keywords: satellite data, concentration of passive admixture, transport model, Azov Sea, adjoint equation
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