CR
Cryospheric Sciences

Larsen C

Do clouds affect melting over Antarctic ice shelves?

Schematic showing the effects of cloud microphysics on the radiative properties of clouds for shortwave solar radiation (a & b) and longwave terrestrial radiation (c & d) [Credit: Ella Gilbert].

The Antarctic Peninsula is the ‘canary in the coalmine’ of Antarctic climate change. In the last half-century it has warmed faster than most other places on Earth, and considerable change has consequently been observed in the cryosphere, with several ice shelves collapsing in part or in full. Representing this change in models is difficult because we understand comparatively little about the effect of atmospheric processes on melting in Antarctica, especially clouds, which are the main protagonists of this Image of the Week…


The Antarctic Peninsula: a part of the southern continent that is surrounded by ice shelves, but also a place that has seen rapid and dramatic changes in the last decades. Until recently, the Antarctic Peninsula was one of the most rapidly warming regions on Earth, with annual mean surface temperatures rising by as much as 2.5°C between the 1950s and early 2000s in some places (Turner et al., 2005; 2016).

That warming has been linked to the demise of the region’s ice shelves: since 1947, more than half of the peninsula’s ice shelves have thinned, lost area, or collapsed entirely (Cook & Vaughan, 2010). Most recently, that includes Larsen C, whose area was reduced by 12% in July 2017 following a calving event where an iceberg four times the size of London broke away from the ice shelf. As a result, the ice shelf has slipped down the rankings from the 4th largest ice shelf on the continent to the 5th largest.

 

What makes ice shelves melt?

Evidence suggests that ice shelves on the peninsula are being warmed mostly from the top down by the atmosphere. This is contrary to what’s happening on other Antarctic ice shelves, like those in West Antarctica that are being eroded from beneath by the warming ocean. Atmospheric processes are much more important over peninsula ice shelves than those elsewhere on the continent.

To understand the effect of the atmosphere on melting at the top of ice shelves, we need to know how much energy is entering the surface of the ice shelf, how much is leaving, and use what’s left over to determine whether there’s residual energy available to melt the ice. That’s the general principle of the surface energy balance, and it’s called a ‘balance’ because it is usually just that – the amount of energy flowing into and out of the ice shelf averages out over the course of say, a year, to produce a net zero sum of energy left for melting. However, there are times when this balance can become either negative, leading to growth of the ice shelf, or positive, leading to ice loss via melting.

 

What affects the surface energy balance?

Many different processes influence the surface energy balance, such as weather patterns and atmospheric motion. For instance, when warm, dry air blows over an ice surface, which happens during ‘foehn‘ wind events (German readers will know this means ‘hairdryer’: a descriptive name for the phenomenon!), this can produce a surplus of energy available for melting (Grosvenor et al., 2014; King et al., 2017; Kuipers Munneke et al., 2018). If the surface temperature reaches 0°C, melting occurs.

 

What do clouds have to do with it?

Clouds also greatly influence the surface energy balance by affecting the amount of radiation that reaches the surface. The amount of incoming solar (shortwave) radiation that reaches the surface, and the amount of terrestrial (longwave) radiation that escapes is affected by what stands in the way – clouds. Of course, this obstacle is important for the surface energy balance because it affects the balance between the energy flowing into and out of the surface. However, the fine-scale characteristics of clouds (aka ‘microphysics’) produce different, often interacting and sometimes competing, effects on the surface energy balance, some of which are shown in the schematic above. Examples of these properties include:

  • Water phase (how much ice and liquid there is)
  • Number concentration (how many particles)
  • Particle size
  • Ice crystal shape

The amount of ice and liquid in a cloud can affect how much energy it absorbs, reflects and emits – for instance, the more liquid a cloud contains, the more energy it emits towards the surface, because it is thicker and tends to be warmer than a cloud with lots of ice. However, clouds made up of lots of tiny liquid droplets also tend to be brighter than ice clouds containing larger crystals, which means they reflect more incoming solar radiation back into space. This example is a typical one where different microphysical properties cause competing effects, which makes them difficult to separate from each other.

 

Radiative forcing (RF, solid bars) and Effective radiative forcing (ERF, hatched bars) of climate change during the Industrial Era (1750-2011) [Credit: adapted from IPCC Fifth Assessment Report, Figure 8.15: pp. 697].

What do we know about Antarctic clouds?

The short answer is: not that much. Clouds are the largest source of uncertainty in our estimates of global climate change (check out the huge range of error in the estimates of cloud-driven radiative forcing in the figure above, from the IPCC’s most recent report), and the science of Antarctic clouds is even more unclear because we don’t have a great deal of data to base our understanding on. To measure clouds directly, we need to fly through them – a costly and potentially dangerous exercise, especially in Antarctica.

 

Flying through a gap in cloud near Jenny Island on the approach to Rothera research station, on the Antarctic Peninsula, at the end of a data collection flight in November 2017 [Credit: Ella Gilbert].

Filling the gap

In somewhere like Antarctica where we don’t have much observational data, we have to rely on other tools. That’s where computer models can be really useful – so long as we can be confident in the results they produce. Unfortunately, that’s part of the problem. Cloud properties and their effects on the surface energy balance are complex: we know that much. But modelling those properties is even more complex, because we have to simplify things to be able to turn them into computer code.

There is hope though! Recent studies (e.g. Listowski et al., 2017) have shown that models can more realistically represent Antarctic cloud microphysics if they use more sophisticated ‘double moment’ schemes, which are able to simulate more microphysical properties. With more accurate microphysics comes better representation of the surface energy balance, and improved estimates of melt over Antarctic ice shelves.

 

Further reading

  • On the effect of foehn on wintertime melting over Larsen C:

Kuipers Munneke, P., Luckman, A. J., Bevan, S. L., Gilbert, E., Smeets, C. J. P. P., Van Den Broeke, M. R., Wang, W., Zender, C., Hubbard, B., Ashmore, D., Orr, A. King, J. C. (2018). Intense winter surface melt on an Antarctic ice shelf. Geophysical Research Letters 45, 7615–7623. doi:10.1029/2018GL077899

  • On clouds in Antarctica:

Lachlan-Cope, T. (2010). Antarctic clouds. Polar Research 29 (2), 150–158. doi:10.1111/j.1751-8369.2010.00148.x

  • On modelling cloud microphysics over the Antarctic Peninsula:

Listowski, C., & Lachlan-Cope, T. (2017). The Microphysics of Clouds over the Antarctic Peninsula – Part 2: modelling aspects within Polar WRF. Atmospheric Chemistry and Physics 17, 10195-10221. doi:10.5194/acp-17-10195-2017

Edited by Clara Burgard


Ella Gilbert is a PhD student at the British Antarctic Survey, where she uses climate modelling and observational data to understand the drivers of melt on the Larsen C ice shelf. She’s a big fan of clouds, polar science, and science communication. You can find her on Twitter @Dr_Gilbz, on her website www.larsenc.com, or the old fashioned way by email.

Back to the Front – Larsen C Ice Shelf in the Aftermath of Iceberg A68!

Back to the Front – Larsen C Ice Shelf in the Aftermath of Iceberg A68!

Much of the Antarctic continent is fringed by ice shelves. An ice shelf is the floating extension of a terrestrial ice mass and, as such, is an important ‘middleman’ that regulates the delivery of ice from land into the ocean: for much of Antarctica, ice that passes from land into the sea does so via ice shelves. I’ve been conducting geophysical experiments on ice for over a decade, using mostly seismic and radar methods to determine the physical condition of ice and its wider system, but it’s only in the last couple of years that I’ve been using these methods on ice shelves. The importance of ice shelf processes is becoming more widely recognised in glaciological circles: after hearing one of my seminars last year, a glaciology professor told me that he was revising his previous opinion that ice shelves were largely ‘passengers’ in the grand scheme of things and this recognition is becoming more common. Slowly, we are coming to appreciate that ice shelves have their own specific dynamics and, moreover, that they are the drivers of change on other ice masses.


The MIDAS Project

In 2015, I joined the MIDAS project – led by Swansea and Aberystwyth Universities and funded by the Natural Environment Research Council – dedicated to investigating the effects of a warming climate on the Larsen C ice shelf in West Antarctica (Fig. 1). My role was to to assist with geophysical surveys (Fig. 2) on the ice shelf – but more about that later!

Figure 2: Adam Booth overseeing seismic surveys on the Larsen C ice
shelf in 2015 [Credit: Suzanne Bevan].

Larsen C is located towards the northern tip of the Antarctic Peninsula, and is one of a number of “Larsen neighbours” that fringe its eastern cost. MIDAS turns out to have been an extremely timely study, culminating in 2017 just as Larsen C hit the headlines by calving one of the largest icebergs – termed A68 – ever recorded. On 12th July 2017, 12% of the Larsen C area was sliced away by a sporadically-propagating rift through the eastern edge of the shelf, resulting in an iceberg with 5800 km2 area (two Luxembourgs, one Delaware, one-quarter Wales…). As of 14th October 2017 (Fig. 1), A68 is drifting into the Weddell Sea, with open ocean between it and Larsen C. See our previous post “Ice ice bergy” to find out more about how and why ice berg movement is monitored.

The aftermath of A68

As colossal as A68 (Fig, 1) is, its record-breaking statistics are only (hnnngh…) the tip of the iceberg, and of greater significance is the potential response of what remains of Larsen C. This potential is best appreciated by considering what happened to Larsen B, a northern neighbour of Larsen C. In early 2002, over 3000 km2 of Larsen B Ice Shelf underwent a catastrophic collapse, disintegrating into thousands of smaller icebergs (and immortalised in the music of the band British Sea Power). Rewind seven years further back, to 1995: Larsen B calved an enormous iceberg, exceeding 1700 m2 in area. An ominous extrapolation from this is that large iceberg calving somehow preconditions ice shelves to instability, and several models of Larsen C evolution suggest that it could follow Larsen B’s lead and become more vulnerable to collapse over the coming years.

The enormous mass of the intact ice shelf acts like a dam that blocks the delivery of terrestrial ice into the ocean, and the disappearance of the ice shelf removes so-called ‘backstress’ – essentially ‘breaking the dam’.

Then what? Well, ice shelves are in stress communication with their terrestrial tributaries, therefore processes affecting the shelf can propagate back to the supply glaciers. The enormous mass of the intact ice shelf acts like a dam that blocks the delivery of terrestrial ice into the ocean, and the disappearance of the ice shelf removes so-called ‘backstress’ – essentially ‘breaking the dam’. In the aftermath of Larsen B’s collapse, its tributary glaciers were seen to accelerate, thereby delivering more of their ice into the Weddell Sea. It is this aftermath that we are particularly concerned about, since it’s the accelerated tributaries that promote accelerated sea-level rise. Ice shelf collapse has little immediate impact on sea-level: since it is already floating, the shelf displaces all the water that it ever will. But, in moving more ice from the land to the sea, we risk increased sea levels and, with them, the associated socio-economic consequences.

How can we improve our predictions?

Figure 3: Computational model of the changed stress state, Δτuu, of Larsen C following the calving of A68 (output from BISICLES model, from Stephen Cornford, Swansea University). The stress change is keenly felt at the calving front, but also propagates further upstream [Credit: Stephen Cornford]

A key limitation in our ability to predict the evolution of Larsen C is a lack of observational evidence of how ice shelf stresses evolve in the short-term aftermath of a major calving event. These calving events are rare: we simply haven’t had much opportunity to investigate them, so while our computer predictions are based on valid physics (e.g., Fig. 3) it would be valuable to have actual observations to constrain them. Powerful satellite methods are available for tracking the behaviour of the shelf but these provide only the surface response; Larsen C is around 200 m thick at its calving front so there is plenty of ice that is hidden away from the satellite ‘eye in the sky’, but that is still adapting to the new stress regime. So how can we “see” into the ice?

To address this, we’ve recently been awarded an “Urgency Grant” – Response to the A68 Calving Event (RA68CE) – from NERC to send a fieldcrew to the Larsen C ice shelf, involving researchers from Leeds, Swansea and Aberystwyth, together with the British Geological and British Antarctic Surveys.

Figure 4: Emma Pearce and Dr Jim White preparing seismic equipment – intrepid geophysicists ready to wrap-up warm for field deployment on Larsen C! [Credit: Adam Booth]

The field team – Jim White and Emma Pearce (Fig. 4) – will undertake seismic and radar surveys at two main sites (Fig. 3) to assess the new stress regime around the Larsen C calving front. One of these sites is being reoccupied after seismic surveying in 2008-9, during the Swansea-led SOLIS project, allowing us to make a long-term comparison. These, and two other sites, will also be instrumented with EMLID REACH GPS sensors, to track small-scale ice movements than can’t be captured in the satellite data. The field observations will be supplied to a team of glacial modellers at Swansea University, to allow them to improve future predictions (e.g. Fig. 3), while their remote sensing team continues to monitor the evolving stress state at surface.

It’s truly exciting to be coordinating the first deployment, post A68, on Larsen C. Our data should provide a unique missing piece from the predictive jigsaw of Larsen C’s evolution, ultimately improving our understanding of the causes and effects of large-scale iceberg calving – both for Larsen C and beyond!

 

For ice-hot news from the field, follow Emma Pearce on twitter: @emm_pearce

 

Edited by Emma Smith


Further Reading

  • More information on Larsen C at the project MIDAS website
  • Learn more about ice shelf evolution with the Ice Flows game – eduction by stealth! Also check out the EGU Cryoblog post about it!
  • Borstad et al., 2017; Fracture propagation and stability of ice shelves governed by ice shelf heterogeneity; Geophysical Research Letters, 44, 4186-4194.
  • Wuite et al., 2015; Evolution of surface velocities and ice discharge of Larsen B outlet glaciers from 1995 to 2013. The Cryosphere, 9, 957-969.
  • Cornford et al., 2013; Adaptive mesh, finite volume modelling of marine ice sheets; Journal of Computational Physics, 232, 1, 529-549.

Adam Booth is a lecturer in Exploration Geophysics at the University of Leeds, UK. He is the PI on the NERC-funded project “Ice shelf response to large iceberg calving” (NE/R012334/1). After obtaining his PhD from the University of Leeds in 2008, he held postdoctoral positions at Swansea University and Imperial College London, in which he worked with diverse research applications of near-surface geophysics. He tweets as: @Geophysics_Adam