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Surface melting of mountain glaciers: the effect of ice surface properties on melt rates

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  • Full or part time
    Dr Mark Smith
    Dr Duncan Quincey
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Recent climate change has impacted glacier volumes worldwide through alteration of glacier mass balance (among other things). Many adjustments are well understood; yet our knowledge of changing surface energy balances remains limited. Glacier surface roughness is an important control on turbulent heat exchange at the ice-atmosphere interface, affecting the surface energy balance and melt rates. The relative contribution of turbulent fluxes is predicted to become more significant in a warming climate. Through shading, ice roughness also determines surface shortwave radiation receipt. Yet, ice roughness is afforded little attention in surface energy balance models and is represented as spatially uniform and static.

Recent advances in geomatics have changed this offering unprecedented resolution topographic data. Consequently, there is increasing attention on characterizing and parameterizing ice surface roughness. This project utilizes recent developments in high-resolution surveying to obtain spatially-distributed and dynamic ice surface roughness maps and relate these to field measurements of aerodynamic roughness heights. Spatial and temporal roughness variations will be incorporated into existing surface melt models and their performance will be validated against observed melt data.

For global impact, we also seek methods of upscaling our ability to map ice surface roughness using more readily available data. Upscaling requires interrogation of space-borne (or air-borne) remote sensing data products and the development of surrogate measurements of surface roughness, using radar backscattering, for example. Previous attempts to make such links were hindered by inadequate field and remote sensing data. However, the launch of TerraSAR-X coupled with advances in ground-based survey techniques means that we are now well-placed to develop surface melt models incorporating spatially-variable roughness from remote sensing data.

Fieldwork for this project will be undertaken on glaciers already being studied by the supervisors, which includes undertaking field work in the Himalayas, Austrian Alps, Greenland, Iceland or Arctic Sweden, or potentially a combination of sites.

In this project you will incorporate spatially variable and dynamic roughness into existing surface melt models and establish the subsequent effect on predicted glacier melting rates. The project can evolve according to your research preferences but key research questions could include:
(1) To what extent does surface roughness vary across and between mountain glaciers? How does this impact glacier melting both in the present day and in a warming climate?
(2) Is surface roughness dynamic? Can the temporal change of roughness through the melt season be predicted? Are their feedbacks between ice surface roughness, albedo and melting?
(3) Does incorporating spatially and temporally variable ice roughness in surface energy balance models improve predictions of melt?
(4) Can relationships between radar backscatter and surface roughness be used to upscale this approach to a regional or global scale?

The successful candidate will benefit from inter-disciplinary training in project specific research methods including GIS-based analysis and topographic surveying using cutting edge technologies (e.g. TLS, SfM), and numerical modelling, both internally and at external workshops. An additional important part of the training will be to attend national and international conferences to present results and gain feedback. The student will be encouraged to submit high quality papers for publication during the project.

Funding Notes

This project is in competition for funding as part of the Leeds-York NERC Doctoral Training Partnership (DTP), for more details see http://www.nercdtp.leeds.ac.uk

How good is research at University of Leeds in Geography, Environmental Studies and Archaeology?

FTE Category A staff submitted: 48.90

Research output data provided by the Research Excellence Framework (REF)

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