The in situ and satellite data blended for reconstruction of the surface salinity of the Sea of Azov

Abstract

ABSTRACT In this paper, we propose a method for retrieving salinity in the Sea of Azov. The method is based on combining in situ and remote sensing measurements. The operational results of the salinity reconstruction are necessary for the assimilation of thermohaline fields, which is used to set initial conditions to the hydrodynamic model and achieve higher accuracy of its results. The proposed method consists of implementing a general regression between historical in situ measurements and L2 MODIS optical measurements. We used properly calibrated and validated satellite data taken from open internet services. The results show different approaches to obtain the linear regression in spring and summer. Particular emphasis is made on analysing the precision of the reconstructed salinity fields relative to in situ measurements. These estimates are based on the comparison of reconstructed salinity with the long-term seasonal trends on in situ data for the periods of 1990–2018 and 2000–2018. The final reconstructed salinity fields are computed from linear regressions for spring and summer. These reconstructed fields are stored as data sets on a regular grid of the Sea of Azov and they are ready for visualization and use as input data for the ocean circulation models.