University of Hong Kong Featured PhD Programmes
University of Leeds Featured PhD Programmes
The University of Manchester Featured PhD Programmes

Variability in snow melt-out associated with boreal forest structure (EE/DRFGEO7P/61940)


Department of Geography & Environmental Sciences

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
Dr N Rutter No more applications being accepted Competition Funded PhD Project (Students Worldwide)

About the Project

A key challenge in reducing uncertainty in climate model projections of future land surface temperatures is to adequately represent the recently observed rapid poleward retreat of late spring boreal Northern Hemisphere snow cover extent (SCE). Poor representation of interactions between snow, vegetation cover, and climate in boreal regions has been identified as the likely source of the uncertainty. As such, improved understanding of these snow-vegetation-atmosphere processes and will be necessary in order to improve agreement between simulated and observed SCE. To accomplish this objective, the PhD student will utilize a suite of geospatial data to quantify the influence of boreal forest structure on the timing of spring snowmelt and related land surface properties, and also to assess representation of key related variables in climate models. The project will involve using satellite observations to characterise the influence of forest type (e.g. evergreen needleleaf vs. deciduous broadleaf) and forest density on the rate and timing of snowmelt across the boreal biome. This information will then be used in conjunction with a combination of satellite and atmospheric reanalysis data to quantify how interaction between forests and SCE impacts local and global climate. Additionally, assessment of SCE-vegetation relationships in climate models used in the latest IPCC report will be made with satellite observations. Identification of spatial patterns of divergence between observed and modelled SCE, along with the underlying causes through examination of variables related to surface energy dynamics, will provide information that can be used to improve model representation of snow-vegetation-climate interactions.

Enquiries regarding this studentship should be made to: Dr Nick Rutter, [Email Address Removed], +44 (0) 191 227 4735

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/
Please ensure you quote the advert reference above on your application form.

Funding Notes

The full-time studentship provides full support for tuition fees, and an annual tax-free stipend at RCUK rates (for 2015/16 this is £14,057 p.a.)

References

Pearson, R. G., S. J. Phillips, M.M. Loranty, P. S. A. Beck, T. Damoulas, S. J. Knight, and S. J. Goetz, 2013, Shifts in Arctic vegetation and associated feedbacks under climate change, Nature Climate Change, doi:10.1038/nclimate1858.

Rutter, N., and 50 others, 2009: Evaluation of forest snow processes models (SnowMIP2). Journal of Geophysical Research-Atmospheres, 114, D06111.

Derksen, C., and R. Brown, 2012: Spring snow cover extent reductions in the 2008-2012 period exceeding climate model projections. Geophysical Research Letters, 39, L19504.
Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.



FindAPhD. Copyright 2005-2020
All rights reserved.