Improved measurements of land motion from GPS for geoscience applications (sea-level / GIA / tectonics / hydrology / volcanology)

Improved measurements of land motion from GPS for geoscience applications (sea-level / GIA / tectonics / hydrology / volcanology)

Supervisor: Dr Elizabeth Petrie, University of Glasgow (; Prof Peter Clarke, Newcastle University; Dr Surajit Ray, University of Glasgow

Description: Using Global Positioning System (GPS) data to measure the motion of bedrock is highly useful in many areas of geoscience:

• calibrating tide gauges for land motion – long term trends in sea level
• understanding glacial isostatic adjustment (GIA) and elastic rebound as ice load changes, also important for predicting global sea level
• hydrologic loading – e.g. understanding drought in California
• tectonics – monitoring plate motions
• volcanology – detecting ground motion

This project will test innovative strategies for optimising analysis of GPS time series to produce accurate long-term rates and investigate inter-annual effects. It is open to the student to select the application area which they find of most interest.

Dr Petrie has substantial expertise in precise long-term GPS analysis. Prof Clarke will contribute expertise in sidereal filtering and in tectonic applications of GPS if that is the student’s application area of interest. Dr Ray is an expert in statistics, with a particular interest in the technique of functional data analysis applied to environmental datasets.


Rates obtained from GPS time series may be seriously affected by unattributed/unmodelled effects on the GPS. Effects may include offsets (sudden jumps in the time series), ionospheric and tropospheric effects and local environmental changes. The student will investigate one or more of these and develop a novel approach to improve the GPS analysis procedure and/or time series analysis. Depending on the student’s interest and background, the project may be directed more towards: 1) innovation in GPS processing; 2) developments aimed at a particular application area, or 3) innovation in statistical techniques – functional data analysis has not yet been applied to GPS time series. GPS processing of the GPS data will be performed using the GIPSY-X or GAMIT scientific GPS processing software packages.


Year 1: Review existing literature, select GPS dataset of interest, learn to process GPS data in precise scientific GPS software, and develop and run initial tests on a novel strategy suitable to area of student interest.

Year 2: Write paper on testing results, present results at conference. Develop methodology further and perform advanced statistical analysis on time series. Depending on the specific goals agreed by the student and the supervisory team, visit external collaborator/carry out fieldwork. Possible strategies would be: to apply the developed novel techniques to a specific application area data set such as GIA; to further develop innovative statistical techniques for GPS time series; or to develop a second GPS processing advance.

Year 3 – 3.5: Finish analysis, write paper on results, present at conference. Complete thesis.

The above represents a broad general overview of the project – to discuss the potential possibilities for a particular student in more detail, please contact Dr Petrie at the address below in the first instance.

The student will make several visits to Newcastle during the course of the PhD, and depending on the exact application area of interest, one trip to an additional external collaborator, for fieldwork and/or modelling assistance. S/he will become expert in least one scientific GPS processing package, and develop skills in scripting, Matlab, R, statistics, including functional data analysis if the student has the mathematical background needed, and the use of version control. There will be the opportunity for the student to gain a hands-on familiarity with GPS data collection. If the project leans strongly towards a particular application area, further skills will be developed in this area. Technical/paper writing skills and presentation skills will also be developed. Conference attendance is likely to be AGU or EGU once and a second national/international conference.

A variety of backgrounds would be suitable for this project – a degree in any of Earth Science, Physics, Mathematics, Statistics, Computing Science and Engineering would all be useful. Familiarity with Linux and basic programming/scripting skills would be an advantage. For a project with goals focussing more towards developing new statistical frameworks, the student would need a suitably mathematical background. Many of the skills developed would be applicable in a variety of fields post-PhD.

See also

Funding notes: Applicants need to meet NERC studentship eligibility requirements. Funding is available to cover tuition fees for UK and EUapplicants, as well as paying a stipend at the Research Council rate for UK applicants and EU applicants who have been resident in the UK for over 3 years (estimated £14,553 for Session 2017-18).

How to Apply: Please refer to the following website for details on how to apply:

Deadline: 19 January 2018

Start Date: October 2018