Graduation Year

2020

Graduation Month

May

Document Type

Thesis

Degree Name

Bachelor of Arts

School or Department

Physics and Astronomy

Major

Physics – Astronomy

Faculty Mentor

Hilary Martens

Faculty Mentor Department

Geosciences

Keywords

GPS, surface mass loading, atmospheric loading, hydrologic loading

Subject Categories

Geophysics and Seismology

Abstract

The Earth’s crust is in continuous motion from changes in fluid pressures associated with the redistribution of mass at the surface. These forces, known as surface mass loading, make up a significant amount of signal within GPS time series. This thesis is broken up into two projects exploring atmospheric and hydrologic pressure-induced crustal responses. The first project focuses on effects of GPS processing on corrections of atmospheric loading. We use data from over 1100 GPS stations within the Western US to investigate crustal displacements from atmospheric surface pressure variations. We find that modeling and removing atmospheric mass loading reduces root mean square (RMS) scatter of residual GPS time series by 16 % on average and up to 50 % for inland stations. We observe a trend of larger RMS reduction with increasing distance from the ocean, due to the inverted barometer effect. We then compare five sets of processed GPS data from three different processing centers (JPL, NGL, UNAVCO) and attempt to isolate possible causes for variations in the GPS displacements. The GPS products with the largest reductions in RMS scatter were generated using the more accurate, high resolution troposphere delays, with the UNAVCO data product providing the best retention of atmospheric mass loading (ATML) in the time series. The retention of ATML in the time series is affected by the temporal resolution of the tropospheric model used in initial processing of raw GPS signal. Mismodeling troposphere delays can lead to an inaccurate distance estimate between satellite and receiver, thereby limiting retention of atmospheric surface pressure-induced crustal displacements in the time series. As such, we recommend using high resolution tropospheric delays when possible. The second project focuses on isolating and quantifying hydrologic loading signal sources within GPS stations near the Columbia River along the Washington-Oregon border. We attempt to correlate seasonal river discharge with horizontal motions present within the GPS time series using particle motions ellipses. We also attempt correlation between sub-seasonal signals of displacement with changes in river discharge measured by USGS river gauges.

Honors College Research Project

No

GLI Capstone Project

no

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© Copyright 2020 Cody T. Norberg