Overview

The majority of research performed within the group focuses on ice sheets
and how they interact with the solid Earth (rocks) and influence sea-level change.
The group applies computer models that simulate interactions between ice
sheets and the solid Earth to learn about these components of the Earth
System. Through modeling various types of geophysical observations (e.g.
sea-level change, land motion, changes in gravity and Earth rotation) we aim to
better understand how ice sheets respond to climate change, the influence of
climate change on sea level, and the physical properties of the Earth's interior.
Most of our modeling is performed on standard desktop linux PCs. We recently
purchased a 64 compute node computer cluster to run a more sophisticated
model which can incorporate 3D variations in Earth structure at the global scale.

Some examples of current and past projects are given below to illustrate the
range and type of research we do.

1. Understanding the evolution of the Greenland ice sheet on 1,000 yr to decadal time scales

The Greenland ice sheet (GrIS) has had a fair amount of media coverage lately.
This is because of the potential response of the ice sheet to current global
warming. Recent observations of ice height, flow and mass changes from satellites
indicate that the ice sheet is losing mass at an accelerated rate. However, these
observations only span the past 5-10 years and so it is not clear if these recent
changes mark the beginning of a sustained and rapid disintegration of the ice sheet
or are simply a short term fluctuation that is not an indication of longer term mass loss.
The aim of this project is to improve our understanding of GrIS changes over longer
(10s to 1000s yr) timescales to place the short-term satellite observations in
context. For example, are the recent changes anomalous in the past 1000 yr
history of the ice sheet? How has the ice sheet responded to warm periods in
the past? We address these questions by modeling observations of sea-level
change and ice sheet extent (lateral and height) obtained through the geological
record to place constraints on past evolution of the GrIS.

Here are some recent papers for more information: Simpson et al. (2009), Wake et al. (2009).

2. Constraining solid Earth structure by modeling observations in previously glaciated regions

The Earth is currently experiencing what is known as an interglacial period - a time
characterized by relatively warm temperatures, high sea levels and a low volume of
land ice. As a comparison, only 20,000 years ago the Earth was in the contrasting
state known as a full glacial period when global mean temperatures were 3-5 degrees
lower, sea levels were 120 m lower (on average) and there was 70% more land ice
volume. During the transition between these two end-member states (approximately
20,000 to 7,000 years before present), large ice sheets over North America and
Eurasia completely melted. These ice sheets reached thicknesses of several km in
places which resulted in stresses large enough to deform the Earth. In some areas
the ice sank ~1 km into the Earth. Of course, once the ice melted these areas started
to uplift and they continue to do so today because the rate of deformation is governed
by how fast rocks deep in the Earth can flow (i.e. their viscosity). This natural 'loading'
and 'unloading' process driven by climate change is a wonderful experiment for learning
about the rheology of the Earth (i.e. how Earth materials deform). We take advantage of
this recent, natural Earth forcing by modeling observations of sea-level change and
present-day land motion in previously glaciated regions. There is currently funding to
support an MSc or PhD project on this topic (see Opportunities).

Here are some example studies of using the Global Positioning System (GPS) to measure
land motion and infer the viscosity of the Earth's interior: Milne et al. (2001),
Bradley et al. (2009).

3. Developing models of sea-level change driven by ice sheets

When land ice melts, sea level rises everywhere - right? Well, no, it doesn't.
Global average sea level will increase but the actual sea-level change exhibits a
complex spatial pattern with some areas experiencing a sea-level fall. This counter
intuitive result is due to the fact that ice sheets are large enough and heavy enough
to change land height (through deforming the solid Earth), the gravity field and Earth
rotation as they evolve to a changing climate. Scientists have been developing
models of ice sheet driven sea-level change since the late 1800s. This endeavor is
particularly relevant at this time given the predicted increase in global temperatures
over the coming centuries and the expected contribution of land ice to sea-level
changes around the globe. Sea-level models will have an important role to play in
identifying the areas most at risk from sea-level rise.

For a review of some key ideas see Milne and Shennan (2007).

4. Understanding the processes driving sea-level change in densely populated areas

Sea-level rise is one of the greatest hazards associated with global warming.
Predicting sea-level change in any given region is difficult because of the
various factors that cause sea level to change (climate and non-climate related).
Of key importance in the coming years is the identification of heavily populated
areas that are at the greatest risk to rising sea levels. Some examples include
low lying areas such as Florida and The Netherlands. Other areas that are
particularly vulnerable are those situated on major river deltas such as New
Orleans and Bangladesh. It is important to quantify as best as possible the
processes driving sea-level in these regions to place useful bounds on rates
of possible future rise.

We are currently collaborating with Tor Tornqvist's group at Tulane University in
New Orleans on investigating the processes driving past and present
sea-level change along the US Gulf coast and New Orleans in particular. A host
of processes drive sea-level change in this region: land subsidence due to sediment
loading of the Mississippi Delta (MD), compaction of MD sediments, melting of the
ancient North American ice sheets; and sea surface height changes due to thermal
expansion of the ocean water and the melting of contemporary ice sheets and glaciers.
We aim to determine the relative importance of each process in order to construct a
model that can be applied to make useful predictions of future change. There is
currently funding for an MSc or PhD student to work on this project (see
Opportunities).

For a general review on sea-level rise see Milne et al. (2009).

5. Understanding the causes of large and rapid ice melt events

How fast could sea-level rise in the future? This is clearly an important question
and one that the scientific community is currently trying to answer. Outside the
realm of transient events (earthquakes and tsumanis), ice sheets are the most
effective agent in producing rapid sea-level rise. How quickly can ice sheets
deliver melt water to the oceans? People who model ice sheets are tackling this
question from a first principle perspective. Another approach is to examine the
geological record for large and rapid changes in the past and then to work
backwards - i.e. determine which ice sheet(s) was(were) responsible and then
try and understand the forcing and mechanisms that lead to rapid ice mass loss.
One of the largest and most rapid melt events occurred about 14,000 years ago.
This event, called meltwater pulse IA (mwp-IA), produced a rise in global mean
sea-level of around 20 m in only a few hundred years (rates on the order of a few
metres per century). At present, there is no consensus on the source distribution
of mwp-IA. There are a variety methods that can be used to constrain the source
geometry, one of which involves modeling the spatial pattern in sea-level change
associated with the event. This is work we continue to pursue as more data
become available and models continue to improve. There is currently funding for
an MSc or PhD student to work on this topic (see Opportunities).

Here are some papers on "fingerprinting" the source(s) of mwp-IA: Clark et al. (2002),
Bassett et al. (2005).



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