Global Navigation Satellite Systems (GNSS) have revolutionized the ability to monitor
Earth-system processes, such as volcanic and tectonic deformation, with important
implications for natural-hazard assessment. To accurately detect signals of interest,
however, extraneous noise must be filtered from the time series. Surface mass loading
(SML) produces continual deformation of the solid Earth, which manifests ubiquitously
in GNSS receiver-position estimates. Thus, neglecting to account for SML in GNSS analyses
can significantly inhibit the detection of ground motions caused by subtle Earth-system
processes, including aseismic transient deformation at convergent plate boundaries.
Except for Earth’s response to ocean tidal loading, however, most SML response signals
are not routinely removed from GNSS observations. Here, I propose to explore the contributions
of oceanic, atmospheric, and hydrologic mass loading to GNSS-inferred surface displacements
across Japan, Cascadia, and Alaska. By improving the methods of prediction and empirical
estimation of SML-induced deformation, I aim to reduce the variance of GNSS timeseries
and therefore enhance the ability to resolve tectonic processes. In collaboration
with NASA’s Jet Propulsion Laboratory (JPL) and students at the University of Montana,
I will assess contributions from individual SML sources to GNSS-inferred receiver
positions using time series analysis and Earth-deformation modeling. Empirical data
collected byt he GEONET system in Japan and the Plate Boundary Observatory in North
America will be processed using JPL’s GIPSY software. Simulated surface displacements
will be derived from Earth-response functions and global mass-load models, constrained
in part by Earth-system observations from space-based platforms, including satellite
altimetry and NASA’s GRACE mission.
Contact Info
Mail |
Hilary Martens Geosciences University of Montana Missoula, MT 59812 |
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