RUSSIAN JOURNAL OF EARTH SCIENCES, VOL. 21, ES6002, doi:10.2205/2021ES000779, 2021

Data analysis for variational assimilation of the surface temperature of the Black and Azov Seas

N. B. Zakharova and E. I. Parmuzin


The paper considers sensing data on the state of the Black and Azov Seas, provided by the shared use center "IKI-Monitoring" and their application in the data assimilation problems. Observation data on the sea surface temperature are obtained from various satellites (Aqua, Terra, SNPP) and instruments (MODIS, VIIRS), measured at different moments and received irregularly and often cover only a part of the investigated water area due to weather conditions and the characteristics of measuring instruments. The paper describes the specifics of the data obtained, the difficulties that had to be faced in the data processing for their correct use in the problems of mathematical modeling of the sea dynamics. An analysis of observation data was carried out which showed the presence of errors in the data. An algorithm is proposed based on the determination of weight coefficients characterizing the proximity of observation data to known verified "reference" values. The weight coefficients are constructed taking into account the received fields of observation data and an additional set of average daily data from the European Copernicus Marine Service. The calculated matrix of weight coefficients is used in the algorithm of variational assimilation of observation data for the numerical model of thermodynamics of the Black and Azov Seas. The results of numerical experiments on variational assimilation of observational data using the constructed weight coefficients are presented. The results of assimilation are compared with near-real time in situ quality control observations.

Received 5 October 2021; accepted 28 October 2021; published 29 November 2021.

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Citation: N. B. Zakharova and E. I. Parmuzin (2021), Data analysis for variational assimilation of the surface temperature of the Black and Azov Seas, Russ. J. Earth Sci., 21, ES6002, doi:10.2205/2021ES000779.