Abstract's details

Revisiting land motion and sea level trends in the north-eastern Adriatic Sea with satellite altimetry and tide gauge data

Stefano Vignudelli (National Research Council of Italy, Institute of Biophysics, Italy)

CoAuthors

Giorgio Baldin (Italian Institute for Environmental Protection and Research, Italy); Francesco De Biasio (National Research Council of Italy, Institute of Polar Sciences and Ca’ Foscari University, Italy)

Event: 2020 Ocean Surface Topography Science Team Meeting (virtual)

Session: Science I: Climate data records for understanding the causes of global and regional sea level variability and change

Presentation type: Type Forum only

Contribution: PDF file

Abstract:

This study presents a linear inverse approach to estimate precise sea level trends based on the combination of satellite and in situ observations. Satellite altimetry is used to derive the rate of absolute sea level height. Tide gauge (TG) stations are used to derive the rate of relative sea level height. The method is tested in the northern Adriatic Sea at six tide gauges and verified where co-located GPS measurements exist to estimate vertical land motion (VLM). Compared to previous studies, the novelty here is that the proposed method is not constrained to use same rates of absolute sea level height for each couple of TGs, thus permitting the application to a wider region. The computed VLMs from the joint use of altimetry and tide gauges mostly show similarities in signs and magnitude with those from GPS, even considering the different periods used for the processing of the VLM estimates from GPS. Using the VLM rates calculated with the inverse approach, the absolute SL rates at the six TGs is estimated by adding VLM rates derived from the altimetry dataset to the observed relative SL rate (1974-2018). We found that the absolute SL rates have sample mean 2.43 mm yr-1, and sample standard deviation 0.18 mm yr-1.
 
Stefano Vignudelli
National Research Council of Italy, Institute of Biophysics
Italy
vignudelli@pi.ibf.cnr.it