A satellite-based gravimetric approach to GIA modelling

• In view of the GRACE Follow-On mission, we will study the capability of temporal gravity field from the GRACE data to detect the present gravity variation in the process of Glacial Isostatic Adjustment (GIA). Motivated to reducing the dependency of GIA to the knowledge of the ice load history modelling, also, to researching various GRACE-type signal analysis methodsA number of gravimetric GIA modelling methods are investigated in order to their compatibility with a total number of 515 GPS data points in North America and Fennoscandia. We investigate three mathematical methods, namely regression, principal component, and independent component analysis (ICA) in extracting the GIA signal from the GRACE monthly geoid height. To exploit the GRACE data to their maximum spatial resolution we will utilize some regularization techniques to recover the signal-to-noise ratio of the short wavelengths. One of the results of this investigation is the relative success of the ICA method. We will produce our final gravimetric model using the fast-ICA algorithm of Hyvärinen and Oja (2000). The gravimetric models will be shown to be in a complete agreement with the GPS data and the best GIA forward model for the areas near the centre of the uplifting regions. We will show that the gravimetric method provides a relatively high-resolution GIA model, while largest discrepancies occur in Alaska, and Svalbard collocated with the present ice mass changes.Finally, we assimilate the best gravimetric models and the GPS data into a GIA forward model, for North America and Fennoscandia, while the contribution of the forward model is set to minimum and compare it with the ICE-6g_C (Peltier et al. 2015) model. We found that for the whole area subjected to epeirogenic movement, their discrepancies reach to the extrema at -1.8 and +3.3, and -0.45 and +0.75 mm⁄a, respectively. Further improvement of the gravimetric model is achieved after reducing for the strong hydrological gravity signals.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap (hsv//swe)

NATURAL SCIENCES  -- Earth and Related Environmental Sciences (hsv//eng)

Nyckelord

Innovative Learning

Innovativt lärande

Hållbar stadsutveckling

Sustainable Urban Development

Publikations- och innehållstyp

pop (ämneskategori)

kon (ämneskategori)