Abstract's details

Investigating vertical land motion and potential systematic errors in altimetry using a filter-based estimation approach

Mohammad-Hadi Rezvani (Discipline of Geography and Spatial Sciences, University of Tasmania, Australia)

Chris Watson (Discipline of Geography and Spatial Sciences, University of Tasmania, Australia); Matt King (Discipline of Geography and Spatial Sciences, University of Tasmania, Australia); Benoit Legresy (CSIRO Marine and Atmospheric Research, Australia)

Event: 2019 Ocean Surface Topography Science Team Meeting

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

Presentation type: Poster

Vertical land motion (VLM) is important for a range of geophysical and climate applications. VLM is used to improve the understanding of solid Earth rheology as is relevant to models of Glacial Isostatic Adjustment or elastic deformation – it is also vital as the connection between relative and absolute estimates of sea level change. We develop a refined filter-based approach to quantify ongoing linear or non-linear land motions, such as those that result from surface mass changes (e.g., those that occur near to glaciers), through combination of data from multi-mission satellite altimeters, long-running tide gauges, and coastal GNSS stations. To this end, a space-time Kalman filter is designed to incorporate multi-mission crossover, altimeter minus gauge, and GNSS observations. This flexible approach allows estimation of linear or non-linear land motions, and considers mission-specific bias drifts. Initial results from testing in the Baltic Sea are present prior to showing results from a global analyses.

Corresponding author:

Mohammad-Hadi Rezvani

Discipline of Geography and Spatial Sciences, University of Tasmania

Australia

mohammadhadi.rezvani@utas.edu.au

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