Cryospheric Sciences


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Image of the Week – Antarctica: A decade of dynamic change

Fig. 1 – Annual rate of change in ice sheet height attributable to ice dynamics. Zoomed regions show (a) the Amundsen Sea Embayment and West Marie Byrd Land sectors of West Antarctica, (b) the Bellingshausen Sea Sector including the Fox and Ferrigno Ice Streams and glaciers draining into the George VI ice shelf and (c) the Totten Ice Shelf. The results are overlaid on a hill shade map of ice sheet elevation from Bedmap2 (Fretwell et al. 2013) and the grounding line and ice shelves are shown in grey (Depoorter et al. 2013). [Credit: Stephen Chuter]


Whilst we tend to think of the ice flow in Antarctica as a very slow and steady process, the wonders of satellites have shown over the last two decades it is one of the most dynamic places on Earth! This image of the week maps this dynamical change using all the satellite tools at a scientist’s disposal with novel statistical methods to work out why the change has recently been so rapid.

Why do we care about dynamic changes in Antarctica ?!

The West Antarctic Ice Sheet has the potential to contribute an approximate 3.3 m to global sea level rise (Bamber et al. 2009). Therefore, being able to accurately quantify observed ice sheet mass losses and gains is imperative for assessing not only their current contribution to the sea level budget, but also to inform ice sheet models to help better predict future ice sheet behaviour.

An ice sheet can gain or lose mass primarily through two different processes:

  • changes in surface mass balance (variations in snowfall and surface melt driven by atmospheric processes) or
  • ice dynamics, which is where variations in the flow of the ice sheet (such as an increase in its velocity) leads to changes in the amount of solid ice discharged from the continent into the ocean. In Antarctica ice flow dynamics are typically regulated by the ice shelves that surround the ice sheet; which provide a buttressing stress to help hold back the rate of flow.

Understanding the magnitude of each of these two components is key to understanding the external forcing driving the observed ice sheet changes.

This Image of the Week shows the annual rates of ice sheet elevation change which are attributed to changes in ice dynamics between 2003 and 2013 (Fig. 1) (Martín-Español et al. 2016). This is calculated by combining observations from multiple satellites (GRACE, ENVISAT, ICESat and CryoSat-2) with in-situ GPS measurements in  a Bayesian Hierarchical Model. The challenge we face is that the observations we have of ice sheet change (whether that being total height change from altimetry or mass changes from GRACE) vary on their spatial and temporal scales and can only tell us the total mass change signal, not the magnitudes or proportions of the underlying processes driving it. The Bayesian statistical approach used here takes these observations and separates them proportionally into their most likely processes, aided by prior knowledge of the spatial and temporal characteristics for each process we want to resolve. This allows us reducing the reliance on using forward model outputs to resolve for processes we cannot observe. As a result, it is unique from other methods of determining ice sheet mass change, which rely on model outputs which in some cases have hard to quantify uncertainties.  This methodology has been applied to Antarctica and is currently being used to resolve the sea level budget and its constituent components through the ERC GlobalMass project.

What can we learn from Bayesian statistical approach?

This approach firstly allows us to quantitively assess the annual contribution that the Antarctic ice sheet is making to the global sea level budget, which is vital to better understanding the magnitude each Earth system process is playing in sea level change. Additionally, by being able to break down the total change into its component processes, we can better understand what external factors are driving this change. Ice dynamics has been the dominant component of mass loss in recent years over the West Antarctic Ice Sheet and is therefore the process being focussed on in this image.

Amundsen Sea Embayment : a rapidly thinning area

Since 2003 there have been major changes in the dynamic behaviour over the Amundsen Sea Embayment and West Marie Byrd Land region (Fig 1, inset a). This region is undergoing some of the most rapid dynamical changes across Antarctica, with a 5 m/yr ice dynamical thinning near the outlet of the Pope and Smith Glacier. Additionally the Bayesian hierarchical model results show that dynamic thinning has spread inland from the margins of Pine Island Glacier, agreeing with elevation trends measured by satellite altimetry over the last two decades (Konrad et al. 2016).

These changes are driven primarily by the rapid thinning of the floating ice shelves at the ice sheet margin in this region

The importance of ice dynamics  is also illustrated in Fig 2, which shows  surface processes and ice dynamics components of mass changes over the Amundsen Sea Embayment from the bayesian hierarchical model. Fig 2 demonstrates that ice dynamics is the primary driver of mass losses in the region. Ice dynamic mass loss increased dramatically from 2003-2011, potentially stabilising to a new steady state since 2011.

Fig. 2 – Annual mass changes due to ice dynamics (pink line) and SMB (blue line) for the period 2003-2013 from the Bayesian hierarchical model approach. Red dots represent mass change anomaly (changes from the long term mean) due to surface mass balance calculated by the RACMO2.3 model and allow for comparison with our Bayesian framework results. (calculated from observations of ice velocity and ice thickness at the grounding line and allow for comparison with our Bayesian framework results (Mouginot et al, 2014). [Credit: Fig. 9b from Martín-Español et al., 2016].


The onset of  dynamic thinning can also be seen in glaciers draining into the Getz Ice Shelf, which is experiencing high localised rates of ice shelf thinning up to 66.5 m per decade (Paolo et al. 2015) . This corroborates with ice speed-up recently seen in the region (Chuter et al. 2017; Gardner et al. 2018). We have limited field observations of ice characteristics in this region and therefore more extensive surveys are required to fully understand causes of this dynamic response.

Bellingshausen Sea Sector :  Not as stable as previously thought…

 The Bellingshausen Sea Sector (Fig 1, inset b) was previously considered relatively a dynamically stable section of the Antarctic coastline, however recent analysis from a forty year record of satellite imagery has shown that the majority of the grounding line in this region has retreated  (Christie et al. 2016). This is reflected in the presence of a dynamic thinning signal in the bayesian hierarchical model results near the Fox and Ferrigno Ice streams and over some glaciers draining into the George VI ice shelf, which have been observed from CryoSat-2 radar altimetry (Wouters et al. 2015). The dynamic changes in this region over the last decade highlight the importance of continually monitoring all regions of the ice sheet with satellite remote sensing in order to understand the what the long term response over multiple decades is to changes in the Earth’s climate and ocean forcing.


Multiple  satellite missions have allowed us to measure changes occurring across the ice sheet in unprecedented detail over the last decade. The launch of the GRACE-Follow On mission earlier this week and the expected launch of ICESat-2 in September will ensure this capability continues well into the future. This will provide much needed further observations to allow us to understand ice sheet dynamics over time scales of multiple decades. The bayesian hierarchical approach being demonstrated will be developed further to encompass these new data sets and extend the results into the next decade. In addition to satellite measurements, the launch of the International Thwaites Glacier Collaboration  between NERC and NSF will provide much needed field observations for the Thwaites Glacier region of the Amundsen Sea Embayment, to better understand whether it has entered a state of irreversible instability .

The  Bayesian hierarchical model mass trends shown here (Martín-Español et al. 2016) are available from the UK Polar Data Centre. In addition, the time series has been extended until 2015 and is available on request from Stephen Chuter ( This work is part of the ongoing ERC GlobalMass project, which aims to attribute global sea level rise into its constituent components using a Bayesian Hierarchical Model approach. The GlobalMass project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 69418.


Christie, Frazer D. W. et al. 2016. “Four-Decade Record of Pervasive Grounding Line Retreat along the Bellingshausen Margin of West Antarctica.” Geophysical Research Letters 43(11): 5741–49.

Chuter, S.J., A. Martín-Español, B. Wouters, and J.L. Bamber. 2017. “Mass Balance Reassessment of Glaciers Draining into the Abbot and Getz Ice Shelves of West Antarctica.” Geophysical Research Letters 44(14).

Gardner, Alex S. et al. 2018. “Increased West Antarctic and Unchanged East Antarctic Ice Discharge over the Last 7 Years.” Cryosphere 12(2): 521–47.

Martín-Español, Alba et al. 2016. “Spatial and Temporal Antarctic Ice Sheet Mass Trends, Glacio-Isostatic Adjustment, and Surface Processes from a Joint Inversion of Satellite Altimeter, Gravity, and GPS Data.” Journal of Geophysical Research: Earth Surface 121(2): 182–200.

Mouginot, J, E Rignot, and B Scheuchl. 2014. “Sustained Increase in Ice Discharge from the Amundsen Sea Embayment, West Antarctica, from 1973 to 2013.” Geophysical Research Letters 41(5): 1576–84.

Paolo, Fernando S, Helen A Fricker, and Laurie Padman. 2015. “Volume Loss from Antarctic Ice Shelves Is Accelerating.” Science 348(6232): 327–31.

Edited by Violaine Coulon and Sophie Berger

Stephen Chuter is a post-doctoral research associate in Polar Remote Sensing and Sea Level at the University of Bristol. He combines multiple satellite and ground observations of ice sheet and glacier change with novel statistical modelling techniques to better determine their contribution to the global sea level budget. He tweets as @StephenChuter and can be found at Contact email:

Image of the Week — Biscuits in the Permafrost

Fig. 1: A network of low-centred ice-wedge polygons (5 to 20 m in diameter) in Adventdalen, Svalbard [Credit: Ben Giles/Matobo Ltd]

In Svalbard, the snow melts to reveal a mysterious honeycomb network of irregular shapes (fig. 1). These shapes may look as though they have been created by a rogue baker with an unusual set of biscuit cutters, but they are in fact distinctive permafrost landforms known as ice-wedge polygons, and they play an important role in the global climate.

Ice-wedge polygons: Nature’s biscuit-cutter

In winter, cracks form when plummeting air temperatures cause the ground to cool and contract. O’Neill and Christiansen (2018) used miniature accelerometers to detect this cracking, and found that it causes tiny earthquakes, with large magnitude accelerations (from 5 g to at least 100 g (where g = normal gravity)!). Water fills the cracks when snow melts. When the temperature drops, the water refreezes and expands, widening the cracks. Over successive winters, the low tensile strength of the ice compared to the surrounding sediment means that cracking tends to reoccur in the ice. As the cycle of cracking, infilling, and refreezing continues over centuries to millennia, ice wedges develop.

Subsurface ice wedge growth causes small changes in the ground surface microtopography. There are linear depressions, known as troughs, above the ice wedges (fig. 2). Adjacent to the troughs, the soil is pushed up into raised rims. From these raised rims, the elevation drops off into the polygon centre, forming low-centred polygons (fig. 2a).

Shaping Arctic landscapes

Permafrost in the Northern hemisphere is warming due to increasing air temperatures (Romanovsky et al. (2010). As air temperatures rise, the active layer (the ground that thaws each summer and refreezes in winter) deepens.

As permafrost with a high ice content thaws out, the ice melts and the ground subsides. On the other hand, permafrost containing no ice does not experience subsidence. Consequently, permafrost thaw can cause differential subsidence in ice-wedge polygon networks. This re-arranges the surface microtopography: ice wedges melt, the rims collapse into the troughs, and the polygons become flat-centred and then eventually high-centred (fig. 2b and c; Lara et al. (2015)). Wedge ice is ~20 % of the uppermost permafrost volume, and so this degradation could have a big impact on the shape of Arctic landscapes.

Are ice wedge polygons climate amplifiers?

Fig. 2: Schematic diagrams of polygon types and features [Credit: Wainwright et al. (2015)].

The transition from low-centred to high-centred ice-wedge polygons affects water distribution across the polygonal ground. The rims of low-centred polygons tend to block water drainage, whereas the troughs facilitate relatively fast and effective drainage of water from the polygonal networks (Liljedahl et al., 2012). So, during summer, the centres of low-centred polygons are frequently flooded with stagnant water, whereas the central mounds of high centred polygons are well drained (and good to sit on at lunchtime!). The contrast in hydrology influences vegetation, surface energy transfer, and biogeochemistry, in turn influencing carbon cycling and the release of greenhouse gases into the atmosphere.

High-centred polygons can have increased carbon dioxide emissions compared to low-centred polygons, on account of their lower soil moisture, reduced cover of green vascular vegetation and the well-drained soil (Wainwright et al., 2015). On the other hand, once plant growth during peak growing season is accounted for, this can actually cause a net drawdown of carbon dioxide in high-centred polygons (Lara et al., 2015). In contrast, there is general agreement that low-centred polygons are associated with high summer methane flux (Lara et al., 2015; Sachs et al., 2010; Wainwright et al., 2015). This is due to multiple interacting environmental factors. Firstly, low centred polygons have a higher temperature, which increases methane production rates. Secondly, they also have moister soil, which decreases the consumption of methane, owing to the lower oxygen availability. Thirdly, the low-centred polygons often have more vascular plants that help transport the methane away from its production site and up into the atmosphere. Lastly, the low-centred polygons had higher concentrations of aqueous total organic carbon, which provides a good food source for methanogens.


As the climate warms, ice wedge polygons will increasingly degrade. The challenge now is to figure out whether the transition from low-centred to high-centred polygons will enhance or mitigate climate warming. This depends on the balance between the uptake and release of methane and carbon dioxide, as well as the rate of transition from high- to low-centred polygons.

Further Reading

Lara, M.J., et al. (2015), Polygonal tundra geomorphological change in response to warming alters future CO2 and CH4 flux on the Barrow Peninsula. Global Change Biology, 21(4), 1634-1651

Liljedahl, A.K., et al. (2016), Pan-Arctic ice-wedge degradation in warming permafrost and its influence on tundra hydrology. Nature Geoscience, 9, 312-316.

Wainwright, H.M., et al. (2015), Identifying multiscale zonation and assessing the relative importance of polygons geomorphology on carbon fluxes in an Arctic tundra ecosystem. Journal of Geophysical Research: Biogeosciences, 707-723.

On permafrost instability: Image of the Week – When the dirty cryosphere destabilizes! | EGU Cryosphere Blog

On polygons in wetlands: Polygon ponds at sunset | Geolog

Edited by Joe Cook and Sophie Berger

Eleanor Jones is a NERC PhD student on the EU-JPI LowPerm project based at the University of Sheffield and the University Centre in Svalbard. She is investigating the biogeochemistry of ice-wedge polygon wetlands in Svalbard. She tweets as @ElouJones. Contact Email:

Image of the Week – Cure from the Cold?

Image of the Week – Cure from the Cold?

Humans rely on antibiotics for survival, but over time they are becoming less effective. So-called ‘superbugs’ are developing resistance to our most important drugs. The key to this global issue may be found in the cryosphere, where extreme microbiologists are hunting for new compounds in the cold that could help us win the war against antimicrobial resistance.

Discovering drugs in Earth’s coldest places

Antimicrobial resistance poses a global threat predicted to cause 10 million deaths per year by 2050.

Alexander Fleming’s 1928 discovery of penicillin- a compound produced from a fungus had an antimicrobial effect transformed life expectancy in the 20th century and kick-started the antibiotic revolution. Since then, most antibiotic drugs have been extracted from soil-dwelling microbes such as bacteria and fungi.

We can exploit these compounds produced by microbes to limit the growth of other microbes that are harmful to humans. The chemical structure of these compounds forms the basis of most antibiotics used today to treat microbial infections. However, soil has become an exhausted environment for drug discovery and researchers are turning to other environments in the search for new antimicrobial drugs.

One of these environments is the cryosphere, where diverse habitats in snow, glaciers, ice sheets and sea ice are dominated by microbes. Multiple stresses such as low temperature, high UV intensity, limited nutrient availability and variable salinity mean this extreme environment naturally favours only the hardiest microbes. In order to thrive, it is likely that microbes produce a variety of chemical warfare against their competitors, making the cryosphere a potentially rich reserve for bioprospecting new antimicrobial compounds.

Glacier microbes: all grown up!

Cultivation (growing microbes in a nutrient-containing growth medium in the laboratory) is a valuable technique for discovering new antimicrobial drugs because it allows scientists to take microbes from the environment and grow them in controlled conditions. In the cryosphere, glacier microbiologists have previously shown that many of the cultivable bacteria from these environments demonstrate potent antimicrobial activity. At least 219 novel natural products have been discovered thus far in polar organisms. In the face of widespread glacier and ice sheet melting, microbiologists must move quickly to find and cultivate these potential ‘cures from the cold’.

Fig. 2: A range of different single colonies isolated from a dilute sample of cryoconite, collected from the Foxfonna glacier, Svalbard in 2016. Samples have been grown on a range of different growth mediums [Credit: A. Debbonaire].

Microbial wars help humanity

Once bacteria have grown, we can exploit them. Any weaponry they produce to fend off competition can be extracted and tested against other microbes. We can assess their array of weapons by placing the growing bacteria under different stresses and seeing what compounds they produce to counteract it. Moreover, bacteria can be grown alongside other bacteria/fungi, increasing the likelihood that they fight each other by producing new chemical warfare that we can then use (Figure 3).

We can also test how powerful these weapons of microbial war are using a simple 24-hour test. By adding them to known concentrations of harmful bacteria such as Staphylococcus aureus (think MRSA) we can then monitor the bacterial growth over time after adding the potential antibiotic compounds. Little growth indicates that the new compounds are wreaking havoc and inhibiting growth – we have a new defence!

Fig. 3: Microbes grown from glacier samples compete with one another in a biochemical arms race [Credit: A. Debbonaire].

Cultivation’s “1% problem”

Cultivation is not the only way to bioprospect in the cold, especially because only 1% of the total microbial diversity of an environment is able to grow on growth media, meaning 99% of that diversity goes undiscovered. Our alternative is a technique known as metagenomics, which has been increasingly applied in the cryosphere over the past few years.

Metagenomics is an expensive but fast method of sequencing all DNA within an environmental sample to identify the microbial population that has been demonstrated to be extremely useful for glacier surface ecosystems and can even now be achieved on-site in extreme locations in the cryosphere in a relatively short time. However, metagenomics will only identify which microbes are present, not necessarily their capability, or more importantly, what compounds they produce when under stress. Both techniques combined are now applicable to exploring the cryosphere and provide the most robust approach to drug discovery in the cryosphere. In the war of microbe versus microbe, metagenomics shows which weapons may, or may not, be used; but cultivation provides a detailed analysis of the battle plan.

In summary…

The battle against drug-resistant microbes may be one of the major challenges facing humanity in the twenty-first century. Traditional sites for drug-discovery are being exhausted and researchers are turning to Earth’s coldest reaches to find stressed-out microbes that could provide us with new weaponry to fight the emerging ‘superbugs’. In this melting biome, researchers must act fast to gather the ‘cures from the cold’, exploiting the microbial life in the cryosphere to tackle a global threat to humanity.


Further reading

Edited by Joe Cook and Clara Burgard

Aliyah Debbonaire is a PhD student at the Interdisciplinary Centre for Environmental Microbiology (Aberystwyth University). Her research aims to bioprospect extreme environments for life-saving drug candidates. She tweets as @Gnarliyah.

Image of the Week – Why is ice colourful?

Image of the Week – Why is ice colourful?

When you think of glacier ice, what colour first springs to mind? Maybe white, blue or transparent? Well, glacier ice can, in fact, be mesmerising and multi-coloured! Our image of the week shows thin sections of glacier ice under polarised light. These sections were cut from block samples of two Alpine glaciers in Switzerland (Chli Titlis and Grenzgletscher).  

In these images the individual ice crystals (Fig. 1 ) can be easily distinguished due to the different colours (see previous post about sea ice) and most of them are large (Fig. 1 ) due to the relatively high temperature of the glaciers they originate from; ice crystals grow faster at high temperatures, close to zero!

Now we know the answer to “what is the colour of ice?” can not be simply answered with “transparent”, the obvious follow-up question is:

Why is ice colourful?

While ice is, of course, transparent (Fig. 2 ) – when we see it as icicles on the roof, as fern frost on a window or as ice cubes in our gin and tonic, it can have any colour – if you look at it in special light – polarised light (Fig. 3 ).

Figure 2: A thin section of ice (~0.3 mm thick) appears transparent under normal light conditions [Credit: Johanna Kerch]

Linearly polarised light is produced by putting a filter in front of a light source. Before being polarised, the light is an electromagnetic wave that vibrates in many directions. The polarising filter, which looks a bit like a very small picket fence, only lets light through that vibrates in the direction of the “gaps in the fence”. If we have two such filters and put them in a row, but rotate the second filter by 90° no light will come through because polarised light from the first filter will not fit through the gaps at the second filter. However, if we put a very thin slice of glacier ice between the two filters we begin to see the colours!

This effect can be observed because ice is birefringent. This means, that light travelling through the ice is split into two parts by the crystal structure of the ice. To help you understand, we have created this analogy: imagine a pair of children who enter a forest side-by-side and hand-in-hand, but they split up to travel through the forest. One part of the light (one child) can travel faster than the other because, it is interacting less with the crystal lattice (less dense part of the forest) . At the end of their separated journey through the ice sample the two parts of light recombine (children are hand-in-hand again), but because they were travelling at different speeds they will be out of phase, meaning the recombined light will have a different polarisation than it did when it entered the ice after passing through the first polariser (one child will be a bit behind the other, rather than side-by-side). Only in case where the new polarisation is 90° rotated can the light pass through the second filter.

Figure 3: Left: transparent ice thin section (0.3 mm thick) on a glass plate during measurement viewed from the side without polarisers. Right: thin section between two polarisers shows crystals in ice section in different colours [Credit: Johanna Kerch].

However, it gets a bit more complicated, white light is a collection of lots of different waves with different wave lengths,  which corresponds to different colours (shorter wave lengths are bluish, longer wave lengths are reddish and in between there is yellow-green). Each of these wave lengths is split up (as described above) when entering the ice sample. So each wave length has two waves travelling with different speeds (imagine a whole group of children who arrive at the forest in pairs, hand-in-hand, forced to split up to go through the forest single file). After exiting the ice sample, the two parts for each wave length recombine (children are back in pairs), and each pair of of waves, at a given wave length has a new polarisation direction. Not all of them can pass the second filter, only those wave lengths where the new polarisation is 90° rotated. Therefore, instead of white light only light of specific colours completes it’s journey through the second filter, to be seen by the observer – all the other colours are swallowed (all the children that don’t make it are eaten by wild animals in the forest!!). Because different crystals in a slice of glacier ice are oriented in various directions, they exert different amounts of birefringence on the light passing through them, this means they appear in different colours when viewed through the second polarising filter (Fig. 3 ). So…that’s cool and allowed us to make a wild analogy about children in a forest, but why is this scientifically useful?

Polarisation Microscopy

The technique by which we examine the ice between crossed polarisers to map the different crystals is called polarisation microscopy. The multi-coloured images of thin ice slices allow us to understand the orientation of the individual crystals, which is important to understand the mechanical properties of glacier ice – but this is another story, for another blog post.

Right, now we have to go and rescue some children from a forest!

Further Reading

Personal note on outreach:

From my experience in the ice laboratory most people, especially children, are immediately captured by the birefringence effect in ice. It’s a great starting point to get them interested in glaciological issues!

Edited by Emma Smith

Johanna Kerch is a postdoctoral researcher at Alfred-Wegener-Institute in Bremerhaven. Her research focus is on crystal-preferred orientation and microstructure of glacier ice and how it links to other physical properties in ice and the deformation mechanisms in glacier ice. She has studied cold and temperate glacier ice from various sites in the Alps and has recently been involved in making measurements of the physical properties of the EGRIP ice core. She tweets as @JohannaKerch.

Image of the week — Making pancakes

A drifting SWIFT buoy surrounded by new pancake floes. [Credit: Maddie Smith]

It’s pitch black and twenty degrees below zero; so cold that the hairs in your nose freeze. The Arctic Ocean in autumn and winter is inhospitable for both humans and most scientific equipment. This means there are very few close-up observations of sea ice made during these times.

Recently, rapidly declining coverage of sea ice in the Arctic Ocean due to warming climate and the impending likelihood of an ‘ice-free Arctic’ have increased research and interest in the polar regions. But despite the warming trends, every autumn and winter the polar oceans still get cold, dark, and icy. If we want to truly understand how sea ice cover is evolving now and into the future, we need to better understand how it is growing as well as how it is melting.

Nilas or thin sheets of sea ice [Credit: Brocken Inaglory (distributed via Wikimedia Commons) ]

Sea ice formation

Sea ice formation during the autumn and winter is complex. Interactions between ocean waves and sea ice cover determine how far waves penetrate into the ice, and how the sea ice forms in the first place. If the ocean is still, sea ice forms as large, thin sheets called ‘nilas’. If there are waves on the ocean surface, sea ice forms as ‘pancake’ floes – small circular pieces of ice. As the Arctic transitions to a seasonally ice-free state, there are larger and larger areas of open water (fetch) over which ocean surface waves can travel and gain intensity. Over time, with the continued action of waves in the ice, pancake ice floes develop raised edges —  as seen in our image of the week — from repeatedly bumping into each other. Pancake ice is becoming more common in the Arctic, and it is already very common in the Antarctic, where almost all of the sea ice grows and melts every year.

Nilas vs pancakes

Nilas and pancake sea ice are different at the crystal level (see previous post), and regions of pancake ice and nilas of the same age may have different average ice thickness and ice concentration. As a result, the interaction of the ocean and atmosphere in these two ice types may be very different. Gaps of open water between pancake ice floes allow heat fluxes to be exchanged between the ocean and atmosphere – which can have very different temperatures during winter. Nilas and pancakes also interact with waves differently – nilas might simply flex with a low-intensity wave field, or break into pieces if disturbed by large waves, while pancakes bob around in waves, causing a viscous damping of the wave field. The two ice types have very different floe sizes (see previous posts here and here). Nilas is by definition is a large, uniform sheet of ice; pancake floes are initially very small and grow laterally as more frazil crystals in the ocean adhere to their sides, and multiple floes weld together into sheets of cemented pancakes.

How to make observations?

Sea ice models have only recently begun to be able to separate different sizes of sea ice. This allows more accurate inclusion of growth and melt processes that occur with the different sea ice types. However, observations of how sea ice floe size changes during freeze-up are required to inform these new models, and these observations have never been made before. Pancake sea ice floes are often around only 10 cm in diameter initially, which is far too small to observe by satellite. This means that observations of pancake growth need to be made close-up, but the dynamic ocean conditions in which pancakes are created makes it difficult to deploy instruments in-situ. So how can we observe pancake sea ice in this challenging environment?

In a recent paper (Roach et al, 2018), we used drifting wave buoys, called SWIFTs, to capture the growth of sea ice floes in the Arctic Ocean. SWIFTs are unique platforms (see image of the week) which drift in step with sea ice floes, recording air temperature, water temperature, ocean wave data and – crucially for sea ice – images of the surrounding ice. Analysis of the series of images captured has provided the first-ever measurements of pancake freezing processes in the field, giving unique insight into how pancake floes evolve over time as a result of wave and freezing conditions. This dataset has been compared with theoretical predictions to help inform the next generation of sea ice models. The new models will allow researchers to investigate whether describing physical processes that occur on the scale of centimetres is important for prediction of the polar climate system.

Edited by Sophie Berger

Lettie Roach is a PhD student at Victoria University of Wellington and the National Institute for Water and Atmospheric Research in New Zealand. Her project is on the representation of sea ice in large-scale models, including model development, model-observation comparisons and observation of small-scale sea ice processes.  




Maddie Smith is a PhD student at the Applied Physics Lab at the University of Washington in Seattle, United States. She uses observations to improve understanding of air-sea interactions in polar, ice-covered oceans.

Image of the Week – Super-cool colours of icebergs

Image of the Week – Super-cool colours of icebergs

It is Easter weekend! And as we do not want you to forget about our beloved cryosphere, we provide you with a picture nearly as colourful as the Easter eggs: very blue icebergs! What makes them so special? This is what this Image of the Week is about…

What are icebergs made of?

Fig.2: An iceberg with ‘scallop’ indentations [Credit: Stephen Warren].

Icebergs are chunks of ice which break off from land ice, such as glaciers or ice sheets (as you’ll know if you remember our previous post on icebergs). This means that they are mostly made up of glacial ice, which is frozen freshwater from accumulated snowfall. However, in some places where ice sheets extend to the coastline, making an ice shelf, icebergs can be made up of a different type of ice too.


Ice shelves can descend far down into the ocean. Seawater in contact with the ice at depth in the ocean is cooled to the freezing temperature. Because the freezing temperature decreases with decreasing pressure, if the seawater moves upwards in the ocean, it will have a temperature lower than the freezing temperature at that depth. That means it’s super-cooled – the seawater temperature is below the freezing temperature, but it hasn’t become a solid. The seawater cannot last for long in this state and freezes to the base of ice shelves as marine ice, which is seawater frozen at depth. The marine ice can help stabilize the ice shelf as it is less susceptible to fractures than glacial ice. Icebergs that calve from Antarctic ice shelves can sometimes be mixtures of glacial ice (on the top) and marine ice (on the bottom).


What can icebergs tell us?

Icebergs which tip over can tell us about processes that happen at the base of ice shelves. For example, scallops on the ice (the small indentations that can be seen in the second picture) can show the size of turbulent ocean eddies in the ocean at the ice shelf base. Basal cavities or channels show where oceanic melt had a large impact. Any colours visible in the iceberg can also give us information.

Fig.3: Marine ice containing organic matter, giving a greenish appearance [Credit: Stephen Warren].

Why are icebergs different colours?

Like snow (see this previous post), different types of ice appear different colours. A typical iceberg is white because it is covered with dense snow, and snowflakes reflect all wavelengths of ice equally. The albedo of snow, which is the proportion of the incident light or radiation that is reflected by a surface, is very high (nearly 1). Glacial ice is compressed snow, meaning it has fewer light-scattering air bubbles, so light can penetrate deeper than in snow, and more yellows and reds from the visible spectrum are absorbed. This results in a bubbly blue colour, with a slightly lower albedo than snow. Marine ice does not have bubbles, but light can be scattered by cracks, resulting in clear blue ice (see our Image of the Week). However, if the seawater from which the marine ice was formed contained organic matter, like algae and plankton, the resulting marine ice can have a yellowish or even green appearance (Fig. 3). If the marine ice formed near the base of an ice shelf where it meets the sea floor, it could contain sediment, giving it a dirty or black appearance.

So the colour of icebergs can tell us something about how ice was formed hundreds of metres below the ocean surface. You could even say that was super-cool…

Further reading

  • Warren, S. G., C. S. Roesler, V. I. Morgan, R. E. Brandt, I. D. Goodwin, and I. Allison (1993), Green icebergs formed by freezing of organic-rich seawater to the base of Antarctic ice shelves, J. Geophys. Res., 98(C4), 6921–6928, doi:10.1029/92JC02751.
  • Morozov, E.G., Marchenko, A.V. & Fomin, Y.V. Izv. (2015): Supercooled water near the Glacier front in Spitsbergen, Atmos. Ocean. Phys. 51(2), 203-207.
  • Image of the Week – Ice Ice Bergy
  • Image of the Week – Fifty shades of snow

This post is based on a talk by Stephen Warren presented at AMOS-ICSHMO2018

Edited by Clara Burgard

Lettie Roach is a PhD student at Victoria University of Wellington and the National Institute for Water and Atmospheric Research in New Zealand. Her project is on the representation of sea ice in large-scale models, including model development, model-observation comparisons and observation of small-scale sea ice processes.  


Image of the Week – Geothermal heat flux in Antarctica: do we really know anything?

Spatial distributions of geothermal heat flux: (A) Pollard et al. (2005) constant values, (B) Shapiro and Ritzwoller (2004): seismic model, (C) Fox Maule et al. (2005): magnetic measurements, (D) Purucker (2013): magnetic measurements, (E) An et al. (2015): seismic model and (F) Martos et al. (2017): high resolution magnetic measurements. The color scale is truncated at 30 and 80 mW m-2. The black line locates the grounding line. Note, (B)-(F) are in order of publication from oldest to most recent. [Credit: Brice Van Liefferinge, (2018), PhD thesis]

Geothermal heat flux is the major unknown when we evaluate the temperature and the presence/absence of water at the bed of the Antarctic Ice Sheet. This information is crucial for the Beyond Epica Oldest Ice project, which aims to find a continuous ice core spanning 1.5 million years (see this previous post). A lot of work has been done* to determine geothermal heat flux under the entire Antarctic Ice Sheet, and all conclude that additional direct measurements are necessary to refine basal conditions! However direct measurements are difficult to obtain, due to the thick layer of ice that covers the bedrock. Our new image of the week goes over what we currently know about the geothermal heat flux in Antarctica and presents the five data sets that currently exist. But first, let’s see where this heat flux come from?

What determines geothermal heat flux and how can we estimate it?

Heat flux measured at the surface of the Earth has two sources: (i) primordial heat remaining from when the Earth formed and (ii) contemporary-sourced heat coming from radioactive isotopes present in the mantle and the crust. This heat, concentrated in the Earth’s centre, can propagate to the surface through both conduction in the solid earth (inner core and crust) and convection in the liquid-viscous earth (outer core, lower and upper mantles). The net heat flux to reach the surface of the crust and penetrate the overlying ice is what we refer to as the ‘geothermal heat flux’. Wherever the crust is thinner, convection in the mantle can transfer heat more efficiently to the surface. In those locations, the net geothermal heat flux is higher, and vice versa. At mid-ocean ridges and in active volcanic areas, the heat can be delivered almost directly to the surface by advection (i.e. by the movement of magma), therefore leading to a higher net surface geothermal heat flux (think of Iceland, where the shallow crust allows them to take advantage of geothermal heat flux directly).

As a result, we know that the geology determines the magnitude of the geothermal heat flux and the geology is not homogeneous underneath the Antarctic Ice Sheet:  West Antarctica and East Antarctica are significantly distinct in their crustal rock formation processes and ages.

Nowadays, five independent global geothermal heat flux data sets exist: Shapiro and Ritzwoller, (2004); Fox Maule et al., (2005); Purucker, (2013); An et al., (2015); Martos et al., (2017) (see image of the week). All geothermal heat flux data sets compiled and currently used have been inferred from the properties of the crust and the upper mantle, as geology dictates the magnitude of geothermal heat flux spatially. Let’s see together how the estimation of geothermal heat flux has evolved over the years….

Using constant values (Panel A)

The simplest method, which consists in using a constant value of geothermal heat flux over the entire continent, was common at first and is still sometimes used (e.g. sensitivity tests and model intercomparison projects) as it facilitates model inter-comparisons. Pollard et al. (2005), in panel A, used bands of constant geothermal heat flux values (70, 60, 55 and 41 mW m-2), with geothermal heat flux decreasing from West Antarctica to East Antarctica, consistent with the known geology.

2004, a seismic model (Panel B)

Shapiro and Ritzwoller (2004) are the first to propose a geothermal heat flux distribution map based on seismic methods, and not strictly on rock composition. They extrapolate the geothermal heat flux from a global seismic model of the crust and the upper mantle which is an analysis of seismicity all over the world. Regions of the globe are grouped by their similarity in seismic structure. Assuming that a certain magnitude of seismicity represents a certain geothermal heat flux value, they assign geothermal heat flux value to regions where geothermal heat flux cannot be directly measured by using geothermal heat flux data from regions of similar seismicity. The geothermal heat flux spatial distribution obtained, with values up to 80 mW m-2 in West Antarctica and 48 mW m-2 in East Antarctica, agrees with that of Pollard et al. (2005). However, errors associated with this method are quite large, reaching 50% of the geothermal heat flux value.


2005, magnetic measurements (Panel C)

A year later, Fox Maule et al. (2005) derive a geothermal heat flux map based on satellite magnetic measurements and a thermal model. The objective is to determine the depth to the Curie temperature, the temperature at which a material loses its permanent magnetic properties. They set the Curie temperature to 580 °C, while the temperature at the ice-bedrock interface is set at 0 °C. Satellite magnetic measurements allow the calculation of the depth of each of these boundaries. The geothermal heat flux is then obtained using a thermal model of the crust between the depth of the two boundary temperatures. This method also has a large associated error, 60% of the geothermal heat flux value for the East Antarctic interior.

2013, reanalysis of magnetic measurements (Panel D)

In 2013, Purucker updates the Fox Maule et al. (2005) geothermal heat flux map with new magnetic data. The spatial geothermal heat flux pattern obtained still retains the characteristic pattern of low values in West Antarctica and high values in East Antarctica, but predicts lower absolute values for East Antarctica and around the West Antarctic coast.

2015, new seismic model (Panel E)

More recently, An et al. (2015) derive a new geothermal heat flux distribution based on seismic velocities. The method is similar to that used by Shapiro and Ritzwoller (2004). They analyse the Earth’s mantle properties using a new 3D crustal shear velocity model to calculate crustal temperatures and the surface geothermal heat flux. However, their spatial distribution of geothermal heat flux differs quite a bit from the other data sets, particularly in East Antarctica where geothermal heat flux values differ by 10 mW m-2 from those of Shapiro and Ritzwoller (2004). An et al. (2015) find very low geothermal heat flux values at the domes, which is good news for the search of Oldest Ice, but rather high overall values for East Antarctica compared to the other data sets. They explain that the model is invalid for geothermal heat flux values exceeding 90 mW m-2. But such high values should only impact young crust areas, mainly West Antarctica and therefore the variability observed in East Antarctica cannot be explained.

2017, high resolution magnetic measurements (Panel F)

In 2017, Martos et al. provide a high resolution geothermal heat flux map based on the spectral analysis of airborne magnetic data. They use a compilation of all existing airborne magnetic data to determine the depth to the Curie temperature and infer the geothermal heat flux using a thermal model. Their continent-wide spatial distribution of geothermal heat flux obtained agrees with previous studies, but they show higher overall magnitudes of geothermal heat flux including East Antarctica. They report an error of 10 mW m-2 which is interestingly smaller than for the other data sets. However, their data set does not take into account point measurements of geothermal heat flux. The same year, Goodge (2017) calculates an average geothermal heat flux value of 48 mW m-2 for East Antarctica with a standard deviation of 13.6 mW m from the analysis of clasts in the region between Dome A and the Ross Sea. A geothermal heat flux value of 48 mW m-2 is consistent with the mean value of the data sets described above.

All in all

To sum up, although all geothermal heat flux data sets agree on continent scales (with higher values under the West Antarctic ice sheet and lower values under East Antarctica), there is a lot of variability in the predicted geothermal heat flux from one data set to the next on smaller scales. A lot of work remains to be done …

* (e.g. Shapiro and Ritzwoller, 2004; Fox Maule et al., 2005; Purucker, 2013; An et al., 2015; Fisher et al., 2015; Parrenin et al., 2017; Seroussi et al., 2017; Martos et al., 2017; Goodge, 2017)


Van Liefferinge, B., Pattyn, F., Cavitte, M. G. P., Karlsson, N. B., Young, D. A., Sutter, J., and Eisen, O.: Promising Oldest Ice sites in East Antarctica based on thermodynamical modelling, The Cryosphere Discuss.,, in review, 2018.

Van Liefferinge, B. Thermal state uncertainty assessment of glaciers and ice sheets: Detecting promising Oldest Ice sites in Antarctica, PhD thesis, Université libre de Bruxelles, Brussels, 2018.

Edited by Sophie Berger

Brice Van Liefferinge  has just earned his PhD at the Laboratoire de Glaciology, Universite Libre de Bruxelles, Belgium. His research focuses on the basal conditions of the ice sheets. He tweets as @bvlieffe.

Image of the Week – Broccoli on Kilimanjaro!

Image of the Week – Broccoli on Kilimanjaro!

On the plateau of Kilimanjaro, Tanzania, the remnants of a glacier can be found and the ice from that glacier contains a rather interesting feature – Broccoli! Not the vegetable, but bubbles that look a lot like it. Our Image of the Week shows some of these strange “Broccoli Bubbles”. Read on to find out more about where these were found and how we can see them.

Figure 2: Kilimanjaro northern ice field, Tanzania, 5800 m a.s.l. Red arrow indicates where ice samples were collected [Credit: Adapted from a Google Earth image]

There is not much ice left on the mountain plateau of Kilimanjaro (Fig. 2), the highest mountain in Africa (5895 m a.s.l.), which is also a dormant volcano. Very likely the last remnants of glacier ice will have gone soon (Thompson et al., 2009). However, a recent expedition to Kilimanjaro’s Northern Ice Field in 2015 (Bohleber et al., 2017) brought home some ice block samples cut with a chain saw from the accessible southern ice cliff 5800 m a.s.l. (red arrow, Fig. 2) . These block were then studied in  ice laboratory at AWI in Germany and an interesting observation was made…Broccoli bubbles!

These irregularly shaped bubbles, which look like broccoli, were seen in the polished ice slabs using close-up photography and an LASM (Large Area Scan Macroscope). This type of bubble intrigued scientists as it is certainly not a common one! When looking from above onto a horizontal section the broccoli bubbles appear to have pointy tips (Fig. 3.), which are all directed towards the glacier face.

Figure 3: “Broccoli” bubbles seen from above. RHS: A horizontal section of ice, area in image is approx. 2 cm high, image is a close-up photograph with a metal plate in the background. The pointed tips of the bubbles (up in this photo) are directed towards the ice cliff face (from which the samples were taken). LHS: Large Area Scan Macroscope (LASM) cross-section through the sample (LHS). The black pore spaces are the Broccoli bubbles [Credit: Johanna Kerch].

Another type of bubble makes also an appearance: the disk- or bowl-shaped bubble (Fig. 1). It is rather regular but not rounded. Instead it is flattened on one or both sides and a little angular, maybe even leaning towards a hexagonal shape. Disk bubbles found close together are oriented in the same direction, one explanation for this could be that the crystal orientation of the ice (the way the ice crystal align during ice flow) plays a role in the bubble formation.

How do the broccoli and disk bubbles evolve? Although we suspect it has something to do with the temperate ice and some temperature gradient at the ice cliff, we do not know for certain. Nonetheless, it is a marvellous thing to discover – before the Kilimanjaro glacier ice is gone for good!

Edited by Emma Smith

Johanna Kerch is a postdoctoral researcher at Alfred-Wegener-Institute in Bremerhaven. Her research focus is on crystal-preferred orientation and microstructure of glacier ice and how it links to other physical properties in ice and the deformation mechanisms in glacier ice. She has studied cold and temperate glacier ice from various sites in the Alps and has recently been involved in making measurements of the physical properties of the EGRIP ice core. She tweets as @JohannaKerch.

Image of the Week – The colors of sea ice

Image of the Week – The colors of sea ice

The Oscars 2018 might be over, but we have something for you that is just as cool or even cooler (often cooler than -20°C)! Our Image of the Week shows thin sections of sea ice photographed under polarized light, highlighting individual ice crystals in different colors, and is taken from a short video that we made. Read more about what this picture shows and watch the movie about how we got these colorful pictures…

Sea ice can vary in salinity

Sea ice forms differently than fresh water ice due to its salt content. When sea water begins to freeze, the ice crystals aren’t able to incorporate salt into their structure and hence reject salt into the surrounding water. This increases the density of the remaining sea water which sinks (see this previous post). Some salty water gets trapped between the crystals though. This water will also slowly freeze, always rejecting the salts into the remaining water. The saltier the water, the lower its freezing point. This means the remnant very salty water, which we call brine, remains liquid even at temperatures below -20oC!

Sea ice crystals can vary in shape

The first layer of sea ice is typically granular – the crystals are small and round, with a diameter around one centimeter. This is because this layer is formed in open seas, where the crystals which go on to form this layer are spun and broken up by surface waves. This granular structure includes lots of ‘pockets’ of trapped brine. Under this surface ice layer, which is typically 10-30 cm thick, ice starts growing in more sheltered conditions. Such sea ice is columnar. The crystals are flat and elongated – like layers in a vertical cake. The brine is trapped between these layers in brine channels. When ice is relatively warm, for example shortly after freezing or before it starts melting, such channels are wide and can be connected. Brine can then escape from them at the lower end into the ocean. The channels also allow small, hardy microscopic plants and animals to travel through the ice. Often air bubbles are trapped in them too.

Sea ice can vary in how it looks too!

The size and form of sea ice crystals – sea ice texture – impacts various properties of the sea ice including its salt content, density and suitability as a habitat. It also influences the optical properties of ice, however. While pure water ice is transparent (see this previous post), sea ice appears milky. That is because of brine channels and bubbles between the crystals.

When looking at large regions of sea ice from space by sensors mounted on satellites, sea ice texture will be important too. Visible light has a short wavelength and this means it only penetrates into the top millimeter of ice. Images collected in the visible light range (see this previous post) will show features dominated by the surface properties of the ice. In comparison, microwaves have a longer wavelength and can penetrate deeper into the ice. Hence imagery of the sea ice cover collected in the microwave spectrum of light (see this previous post) will display features influenced by the internal structure of the sea ice in addition to the surface features.


The video below shows how the sea ice samples are analyzed for texture and how we got the colorful pictures for our Image of the Week…


Further reading

Edited by Adam Bateson and Clara Burgard

Polona Itkin is a Post-doctoral Researcher at the Norwegian Polar Institute, Tromsø. She investigates the sea ice dynamics of the Arctic Ocean and its connection to the sea ice thickness. In her work she combines the information from in-site observations, remote sensing and numerical modeling. Polona is part of the social media project ‘oceanseaiceNPI’ – a group of scientists that communicates their knowledge through social media channels:,,, contact Email:

Image of the Week – A Hole-y Occurrence, the reappearance of the Weddell Polynya

Image of the Week – A Hole-y Occurrence, the reappearance of the Weddell Polynya

During both the austral winters of 2016 and 2017, a famous feature of the Antarctic sea-ice cover was observed once again, 40 years after its first observed occurrence: the Weddell Polynya! The sea-ice cover exhibited a huge hole (of around 2600 km2 up to 80,000 km2 at its peak!), as shown on our Image of the Week. What makes this event so unique and special?

Why does the Weddell Polynya form?

The Weddell Polynya is an open ocean polynya (a large hole in the sea ice, see this previous post), observed in the Weddell Sea (see Fig.2). It was first observed in the 1970s but then did not form for a very long time, until 2016 and 2017…


Fig. 2: Map of the sea ice distribution around Antarctica on 25th of September 2017, derived from satellite data. The red circle marks the actual Weddell Polynya [Credit: Modified from]

In the Southern Ocean, warm saline water masses underlie cold, fresh surface water masses. The upper cold fresh layer acts like a lid, insulating the warmer deep waters from the cold atmosphere. While coastal polynyas (see this previous post) are caused by coastal winds, open ocean polynyas are more mysteriously formed as it is not as clear what causes the warm deep water to be mixed upwards. In the case of the Weddell polynya, it forms above an underwater mountain range, the Maud Rise. This ridge is an obstacle to the water flow and can therefore enhance vertical mixing of the deeper warm saline water masses. The warm water that reaches the surface melts any overlying sea ice, and large amounts of heat is lost from the ocean surface to the atmosphere (see Fig. 3).


Fig. 3: Schematic of polynya formation. The Weddell polynya is an open ocean polynya [Credit: National Snow and Ice Data Center].


Why do we care about the Weddell Polynya?

Overturning and mixing of the water column in the Weddell Polynya forms cold, dense Antarctic Bottom Water, releasing heat stored in the ocean to the atmosphere in the process. Antarctic Bottom Water is formed in the Southern Ocean (predominantly in the Ross and Weddell Seas) and flows northwards, forming the lower branch of the overturning circulation which transports heat from the equator to the poles (see Fig. 4). Antarctic Bottom Water also carries oxygen to the rest of the Earth’s deep oceans. The absence of the Weddell polynya could reduce the formation rate of Antarctic Bottom water, which could weaken the lower branch of the overturning circulation.

Fig.4: Schematic of the overturning (thermohaline) circulation. Deep water formation sites are marked by yellow ovals. Modified from: Rahmstorf, 2002 [©Springer Nature. Used with permission.]

How often does the Weddell Polynya form?

The last time the Weddell Polynya was observed was during the austral winters of 1974 to 1976 (see Fig. 5). It was then absent for nearly 40 years (!) up until austral winter 2016. In a modelling study, de Lavergne et al. 2014 suggested that the Weddell Polynya used to be more common before anthropogenic CO2 emissions started rising at a fast pace. The increased surface freshwater input from melting glaciers and ice sheets, and increased precipitation (as climate change increases the hydrological cycle) have freshened the surface ocean. This freshwater acts again as a lid on top of the warm deeper waters, preventing open ocean convection, reducing the production of Antarctic Bottom Water.

Fig. 5: Color-coded sea ice concentration maps derived from passive microwave satellite data in the Weddell Sea region from the 1970s. The Weddell Polynya is the extensive area of open water (in blue) [Credit: Gordon et al., 2007, ©American Meteorological Society. Used with permission.].

The reappearance of the Weddell Polynya over the past two winters despite the increased surface freshwater input suggests that other natural sources of variability may be currently masking this predicted trend towards less open ocean deep convection. Latif et al. 2013 put forward a theory describing centennial scale variability of Weddell Sea open ocean deep convection, as seen in climate models. In this theory, there are two modes of operation, one where there is no open ocean convection and the Weddell Polynya is not present. In this situation, sea surface temperatures are cold and the deep ocean is warm, and there is relatively large amount of sea ice. The heat at depth increases with time, as it is insulated by the sea ice and freshwater lid. Then, eventually, the deep water becomes warm enough that the stratification is decreased sufficiently so that open water convection begins again, forming the Weddell Polynya. This process continues until the heat reservoir depletes and surface freshwater forcing switches off the deep convection. Models show that the timescale of this variability is set by the stratification, and models with stronger stratification tend to vary on longer timescale, as the heat needs to build up more in order to overcome the stratification.


In the end, the Weddell Polynya is still surrounded by some mystery… Only the next decades will bring us more insight into the true reasons for the appearance and disappearance of the Weddell Polynya…


Further reading

Edited by Clara Burgard

Rebecca Frew is a PhD student at the University of Reading (UK). She investigates the importance of feedbacks between the sea ice, atmosphere and ocean for the Antarctic sea ice cover using a hierarchy of climate models. In particular, she is looking at the how the importance of different feedbacks may vary between different regions of the Southern Ocean.