PhD Position on ‘A Statistical Approach to Improve Ice sheet Mass Changes Estimates from Remote Sensing'
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Employer: Delft University of Technology |
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Job location: Delft Netherlands |
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Apply before: 04 Apr 2021 |
Summary
You will combine the complementary strengths of gravimetry and altimetry, exploiting their differences in spectral and process characteristics in a statistical framework informed by a-priori information from, e.g., surface mass balance models, ice flow velocity models, and GIA models. The ultimate goal of your work is to provide regional estimates of mass changes of the ice sheet together with a robust uncertainty assessment; separate the contribution of ice dynamics and surface processes such as snowfall and melt; and identify temporal variations in these processes through a state-space approach.
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Ice loss of the Antarctic and Greenland ice sheets is one of the major sources of current sea level rise and their contribution is expected to increase in the coming decades. Estimates of their total mass loss based on different satellite observations show a good agreement, but when considering regional changes, significant differences are noticed. This is partly due to the different way of measuring the ice sheets. The GRACE/GRACE-FO gravimetry satellites measure mass changes directly, but have a low spatial resolution and are sensitive to mass redistribution outside the ice sheets, among others in the solid earth (glacial isostatic adjustment – GIA). Altimeter satellites - for example CryoSat-2 and ICESat-2 - provide a much higher spatial resolution, but measure elevation changes, which then need to be converted to mass changes, which comes with its own uncertainties.
In this project, you will combine the complementary strengths of gravimetry and altimetry, exploiting their differences in spectral and process characteristics in a statistical framework informed by a-priori information from, e.g., surface mass balance models, ice flow velocity models, and GIA models. The ultimate goal of your work is to provide regional estimates of mass changes of the ice sheet together with a robust uncertainty assessment; separate the contribution of ice dynamics and surface processes such as snowfall and melt; and identify temporal variations in these processes through a state-space approach.
This position is a part of the larger 'Dutch Polar Climate and Cryosphere Consortium' project, funded by the NWO Netherlands Polar Programme. Your results will provide essential input for estimates of relative sea level change and for validation of ice sheet model development efforts within the consortium.
We aim to start the project early 2021. During the project you will be supervised by a team of TU Delft experts and interact with project partners at Utrecht University, the Netherlands Royal Meteorological Institute, Vrije Universiteit Amsterdam, and the Royal Netherlands Institute for Sea Research. In addition to an exciting research project and a friendly and stimulating work environment, we can offer you a generous funds for scientific travel.
Requirements
need-to-haves:
MSc in Geodesy, Aerospace Engineering, Remotes Sensing, Statistics or related fields.
A solid background in (Bayesian) statistics.
Strong programming skills and experience in development of data processing algorithms.
Good reporting and presentation skills.
Very good level of written and spoken English (for non-native English speakers: TOEFL-score > 100 or IELTS > 7).
Ability to work independently and to critically assess own results.
nice-to-haves:
Affinity with ice sheet processes.
Experience with satellite altimetry and/or GRACE gravimetry.
Experience in handling large data sets and parallel computing, high performance computing or cloud computing.
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