**Author details**

In this chapter, a more robust inverse method (called LIPWC-COV) has been proposed and tested in the Northern Adriatic Sea, where GPS data are available to conduct a realistic assessment of uncertainties. The results show that the classical approach of estimating VLMs provides less accurate trends than the LIPWC-COV method, and with lower errors. Moreover, the LIPWC-COV has demonstrated to

In this chapter, the experimental SLCCI data set (high resolution along track) coastal sea level product (developed within SLCCI project) has been also assessed in the Gulf of Trieste, as it was possible only at that site. The retrieval is particularly problematic in the gulf area due to the complex morphology of the land. The trends calculated with the gridded and along track datasets show some differences, probably due to the different methodologies used in the generation of the products. This study offers a more consolidated and improved understanding of the sea level trend variability in the Northern Adriatic Sea. The next step is to extend the

The authors want to thank the European Space Agency, which propelled the Climate Change Initiative to produce a climate quality record of sea level from satellite altimetry. Likewise, the authors express gratitude to the European Union for making available the satellite altimetry data record through the Copernicus Earth Observation Programme Services. The authors also want to acknowledge Centro Previsioni e Segnalazioni Maree (CPSM) and Alvise Papa for providing tide gauge data under the CNR-ISP/CPSM technical–scientific collaboration agreement 2019–2022; the CNES distribution service AVISO+ for the dynamic atmospheric correction data; the Italian Institute for Environmental Protection and Research (ISPRA) for providing tide gauge and GPS data; CNR-ISMAR and Fabio Raicich for the time series of the Trieste tide gauge; PSMSL, national Oceanographic Centre, Liverpool, UK, for making available the tide gauge global record. The authors thank the SONEL Data Centre and the Nevada Geodetic Laboratory (NGL) for processing and making available the GPS trend global record. Finally, we acknowledge CPSM for funding the "Vento da Satellite+" project on the development of satellite data in storm surge forecasting; ESA who funded the "HYDROCOASTAL" project (ESA contract No. 4000129872/20/I-DT), and the "SL\_CCI Bridging Phase" project (ESA contract No. 4000109872/13/I-NB), from which some of the images in this chapter

compare better than the classic method with GPS derived VLMs.

*Geodetic Sciences - Theory, Applications and Recent Developments*

application of the new methodology to the Mediterranean Sea.

**Acknowledgements**

were adapted.

**116**

Stefano Vignudelli<sup>1</sup> \* and Francesco De Biasio<sup>2</sup>

1 National Research Council of Italy, Institute of Biophysics, Pisa, Italy

2 National Research Council of Italy, Institute of Polar Sciences and Ca' Foscari University, Venice, Italy

\*Address all correspondence to: stefano.vignudelli@pi.ibf.cnr.it

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
