Himalayan glacier response to future atmospheric forcing
The impact of climate change on glaciers is of great international concern, both because they are a totemic indicator of global warming, but also because in parts of the world such as the Himalaya glaciers feed some of the great regional rivers. Changes to these glaciers will have a profound impact on water resources essential for millions of people living downstream in Bhutan, Nepal, India, Pakistan and China. Focus is often on the role of increased temperatures in altering the rate of glacier melt, but changes in precipitation (the total amount, and also the balance between rain and snow) also play a key role in altering the glacier mass balance. Current climate models typically have resolutions of ~50 km and therefore fail to capture the finer, catchment-scale details of the terrain which are key, both in determining the amount of precipitation and in driving altitudinal temperature gradients that affect the rain / snow balance. This project will make use of state of the art high-resolution (~1.5 km) simulations over the Himalaya to drive a bespoke and dynamic glacier model that accurately simulates the variability in surface energy balance within individual catchments through time and incorporates changes in glacier surface debris thickness as the glacier evolves. By using multiple climate simulations, and by varying the terrain and surface characteristic data on which the glacier model is built, it will thus be possible to test the glacier model sensitivity to these inputs and, ultimately, better quantify uncertainty in predictions of future glacier recession in the region.
Aim: Integrate recent advances in both atmospheric and glacier modelling to produce more detailed and accurate predictions of glacier response to current and future climate change.
This project will bring together expertise from across the university in both atmospheric modelling (Ross) and glaciology (Quincey) to tackle this interdisciplinary challenge through 3 linked objectives:
1. Use novel high-resolution atmospheric simulations to validate and downscale coarser climate simulations of temperature and precipitation.
2. Feed these refined climate inputs into a 3-D glacier energy, mass balance and ice-flow model simulating debris-covered glacier volume and runoff changes, constrained and validated by critical field observations.
3. Test the glacier model sensitivity to the various model inputs in order to quantify uncertainty in glacier changes under future climate scenarios.
Existing climate model runs, such as those used in the CMIP5 project which informed the latest IPCC report, offer long term predictions of temperature and precipitation which are needed to study glacier change over decades, but they do not provide the catchment-scale variations in temperature and snow fall which are required for accurate glacier modelling. Only very recently have high resolutions simulations (~1.5 km) become available for this region which can provide the spatial detail required. These are necessarily only run for short periods (perhaps up to a year) so cannot be directly used to drive the glacier models for long time periods. This project will aim to combine these different existing model data sources to understand the impact of resolution on catchment-level temperatures and snowfall, and hence downscale the long-term climate model results to produce better catchment-scale inputs for the glacier modelling. The glacier model has been specifically developed to capture the dynamics of ice-flow within mountain glaciers and includes the feedbacks between debris transport, ice-flow and mass balance. It will be constrained and validated by field observations of glacier surface characteristics and terrain variability and, critically, interpretations of former glacier extents. Finally, the sensitivity of the results to the glacier model inputs (e.g. climatic variables, terrain, surface characteristics) will be tested in order to quantify the uncertainty in climate predictions of glacier retreat.
The student will benefit from close links with the Met Office through the Met Office Partnership, of which Leeds is a founding member. This will ensure access to the required climate and high resolution model data. The project will also be co-supervised by Dr Ann Rowan at University of Sheffield, who is a specialist in Himalayan glacier modelling and has extensive field experience in the region.
Entry requirements/necessary background for students:
This project would be suitable for students with a good undergraduate or masters degree in Meteorology, Physical Geography, Environmental Science or a related subject (e.g. Maths, Physics, Geophysics). The project will require analysis of large data sets and some modelling so experience in Matlab, python or similar would be valuable, although training is available.
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FTE Category A staff submitted: 79.20
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