Abstract
An essential role of the FAMOS international cooperation project is to obtain new marine gravity observations over the Baltic Sea for improving gravimetric geoid modelling. To achieve targeted 5 cm modelling accuracy, it is important to acquire new gravimetric data, as the existing data over some regions are inaccurate and sparse. As the accuracy of contemporary geoid models over marine areas remains unknown, it is important to evaluate geoid modelling outcome by independent data. Thus, this study presents results of a shipborne marine gravity and GNSS campaign for validation of existing geoid models conducted in the eastern section of the Baltic Sea. Challenging aspects for utilizing shipborne GNSS profiles tend to be with quantifying vessel’s attitude, processing of noise in the data and referencing to the required datum. Consequently, the novelty of this study is in the development of methodology that considers the above-mentioned challenges. In addition, tide gauge records in conjunction with an operational hydrodynamic model are used to identify offshore sea level dynamics during the marine measurements. The results show improvements in geoid modelling due to new marine gravimetric data. It is concluded that the marine GNSS profiles can potentially provide complementary constraints in problematic geoid modelling areas.
Acknowledgements
The Estonian Maritime Agency and the Estonian Land Board (ELB) are acknowledged for providing resources for carrying out the Sektori2017 marine gravity and GNSS campaign. Gabriel Strykowski and Jens Emil Nielsen from DTU, Jaanus Metsar and Tõnis Oja from the ELB are thanked for field assistance. Anti Gruno and Karin Kollo from the ELB helped with GNSS post-processing. Liisi Kaleva from Estonian Environmental Agency provided the used raw tide gauge data, which were then checked by Karin Kollo. The two anonymous reviewers are thanked for their contribution to the quality of the final manuscript. The figures of this paper have been generated by the ArcMap 10.6, Autodesk AutoCad and Microsoft Excel. Illustrative data for the figures originates from Eurostat and European Environment Agency websites.