Cryospheric Sciences


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Quantarctica: Mapping Antarctica has never been so easy!

Quantarctica: Mapping Antarctica has never been so easy!

One of the most time-consuming and stressful parts of any Antarctic research project is simply making a map. Whether it’s plotting your own data points, lines, or images; making the perfect “Figure 1” for your next paper, or replying to a collaborator who says “Just show me a map!,” it seems that quick and effective map-making is a skill that we take for granted. However, finding good map data and tools for Earth’s most sparsely-populated and poorly-mapped continent can be exhausting. The Quantarctica project aims to provide a package of pre-prepared scientific and geographic datasets, combined with easy-to-use mapping software for the entire Antarctic community. This post will introduce you to Quantarctica, but please note that the project is organizing a Quantarctica User Workshop at the 2017 EGU General Assembly (see below for more details).

[Credit: Quantarctica Project]

What is Quantarctica?

Quantarctica is a collection of Antarctic geographic datasets which works with the free, open-source mapping software QGIS. Thanks to this Geographic Information System package, it’s now easier than ever for anyone to create their own Antarctic maps – for any topic and at any spatial scale. Users can add and plot their own scientific data, browse satellite imagery, make professional-quality maps and figures, and much, much more. Read on to learn how researchers are using Quantarctica, and find out how to use it to start making your own (Qu-)Antarctic maps!

Project Origins

When you make a sandwich, you start with bread, not flour. So why would you start with ‘flour’ to do your science?” — Kenny Matsuoka, Norwegian Polar Institute

Deception Island isn’t so deceptive anymore, thanks to Quantarctica’s included basemap layers, customized layer styles, and easy-to-use cartography tools. [Credit: Quantarctica Project]

Necessity is the mother of invention, and people who work in Antarctica are nothing if not inventive. When Kenny Matsuoka found himself spending too much time and effort just locating other Antarctic datasets and struggling with an expired license key for his commercial Geographic Information System (GIS) software in the field, he decided that there had to be a better way – and that many of his Antarctic colleagues were probably facing the same problems. In 2010, he approached Anders Skoglund, a topographer at the Norwegian Polar Institute, and they decided to collaborate and combine some of the critical scientific and basemap data for Antarctica with the open-source, cross-platform (Windows, Mac, and Linux) mapping software QGIS. Quantarctica was born, and was quickly made public for the entire Antarctic community.

Since then, maps and figures made with Quantarctica have appeared in at least 25 peer-reviewed journal articles (that we can find!). We’ve identified hundreds of Quantarctica users, spread among every country participating in Antarctic research, with especially high usage in countries with smaller Antarctic programs. We’ve been actively incorporating even more datasets into the project, teaching user workshops at popular Antarctic conferences – such as EGU 2017 – and building educational materials on Antarctic mapping for anyone to use.

A great example of a Quantarctica-made figure published in a paper. Elevation, imagery , ice flow speeds, latitude/longitude graticules, custom text and drawing annotations… it’s all there and ready for you to use! [Credit: Figs 1 and 2 from Winter et al (2015)].

What data can I find in Quantarctica?

  • Continent-wide satellite imagery (Landsat, MODIS, RADARSAT)
  • Digital elevation models and/or contour lines of bed and ice-surface topography and seafloor bathymetry
  • Locations of all Antarctic research stations and every named location in Antarctica (the SCAR Composite Gazetteer of Antarctica)
  • Antarctic and sub-Antarctic coastlines and outlines for exposed rock, ice shelf, and subglacial lakes
  • Magnetic and gravity anomalies
  • Ice flow velocities, catchment areas, mass balance, and firn thickness grids
  • Ancient UFO crash sites

…just to name a few!

Four examples of included datasets. From left to right: Ice flow speed, drainage basins, and subglacial lakes; bed topography; geoid height; modeled snow accumulation and surface blue ice areas [Credit: Quantarctica Project]

All of these datasets have been converted, imported, projected to a standard Antarctic coordinate system, and hand-styled for maximum visibility and compatibility with other layers. All you have to do is select which layers you want to show! The entire data package is presented in a single QGIS project file that you can quickly open, modify, save, and redistribute as your own. We also include QGIS installers for Windows and Mac, so everything you need to get started is all in one place. And finally, all of the data and software operates entirely offline, with no need to connect to a license server, so whether you’re in a tent in Antarctica or in a coffee shop with bad wi-fi, you can still work on your maps!

Quantarctica was used in traverse planning for the MADICE Project, a collaboration between India’s National Centre for Antarctic and Ocean Research (NCAOR) and the Norwegian Polar Institute (NPI), investigating mass balance, ice dynamics, and climate in central Dronning Maud Land. Check out pictures from their recently-completed field campaign on Facebook and Twitter! Base image: RADARSAT Mosaic; Ice Rises: Moholdt and Matsuoka (2015); Mapping satellite features on ice: Ian Lee, University of Washington; Traverse track: NCAOR/NPI. [Credit: Quantarctica Project]

Every dataset in Quantarctica is free for non-commercial use, modification, and redistribution – we get explicit permission from the data authors before their datasets are included in Quantarctica, always include any README or extra license/disclaimer files, and never include a dataset if it has any stricter terms than that. We always provide all metadata and citation information, and require that any Quantarctica-made maps or figures printed online or in any publication include citations for the original datasets.

How do I start using Quantarctica?

Quantarctica is available for download at It’s a 6 GB package, so if your internet connection is struggling with the download, just contact us and we can send it to you on physical media. You can use the bundled QGIS installers for your operating system, or download the latest version of QGIS at and simply open the Quantarctica project file, Quantarctica.qgs, after installation.

We’re actively developing Version 3 of Quantarctica, for release in Late 2017. Do you know of a pan-Antarctic dataset that you think should be included in the new version? Just email the Quantarctica project team at

Quantarctica makes it easy to start using QGIS, but if you’ve never used mapping software before or need to brush up on a few topics, we recommend QGIS Tutorials and Tips and the official QGIS Training Manual. There are also a lot of great YouTube tutorial videos out there!


Nobody said you could only use Quantarctica for work – you can use it to make cool desktop backgrounds, too! Foggy day in the Ross Island / McMurdo Dry Valleys area? Though it often is, the fog effects image was created using only the LIMA 15m Landsat Imagery Mosaic and RAMP2 DEM in Quantarctica, with the help of this tutorial. [Credit: Quantarctica Project]

Quantarctica Short Course at EGU 2017

Are you attending EGU 2017 and want to learn how to analyze your Antarctic data and create maps using Quantarctica? The Quantarctica team will be teaching a short course (SC32/CR6.15) on Monday, 24 April at 13:30-15:00 in room -2.31. Some basic GIS/QGIS experience is encouraged, but not required. If you’re interested, fill out the registration survey here: and feel free to send any questions or comments to We’ll see you in Vienna!

Edited by Kenny Matsuoka and Sophie Berger

Reference/Further Reading

Data sources

[Read More]

Image of the Week – Icelandic glaciers monitored from space!

Image of the Week – Icelandic glaciers monitored from space!

Located in the North Atlantic Ocean, just south of the polar circle, Iceland is a highly fascinating land. Covered by some of the largest glaciers in Europe and hosting active volcanoes, geothermal sites and subglacial lakes, it is extremely dynamic in nature and ever changing. With this Image of the Week we will tell you a bit about the changing ice caps of Iceland and how we can monitor them from space!

Icelandic ice caps since the mid-1990s

Iceland enjoys a mild and moist climate because of the relatively warm and saline Irminger current transporting heat to its southern coast, although the cold East Greenland and East Icelandic currents may cause sea ice to form to the north. Iceland’s ice caps, which receive abundant precipitation from North Atlantic cyclones, cover about 11% of the land, and contain ~3600 km2 of ice. If they completely melted they would contribute 1 cm to Sea Level Rise (SLR).

In the period 1995-2010, Icelandic glaciers shrank every year and lost mass at an average rate of 9.5±1.5 Gton a-1 – generally reflecting higher summer temperatures and longer melting seasons than in the early 1990s (Björnsson et al., 2013). Importantly, in recent decades Iceland has been the second largest source of glacier meltwater to the North Atlantic after Greenland and its peripheral glaciers. Furthermore, surge-type outlet glaciers – which have unpredictable dynamics – are present in all Icelandic ice caps and represent as much as 75% of the area of Vatnajökull (Bjornsson et al., 2003), the largest ice cap in Europe by volume. Therefore, it is important to continuously monitor Icelandic ice caps (>90% of the whole glaciated area) at high spatial resolution. Glaciological field surveys can yield accurate measurements and are routinely performed in Iceland on all ice caps and most glaciers. However, it is not always feasible to use field methods, depending on the remoteness and size of the glacier (e.g. several glaciers and ice caps in the Arctic). Continuous monitoring of such hardly accessible areas can be achieved from space at high spatial resolution.

Continuous health check from space

Since 2010, the ESA CryoSat-2 (CS2) mission has been fundamental in retrieving ice elevation data over glacial terrain characterised by complex topography and steep slopes – notoriously hard to monitor via satellite. CS2’s radar altimeter provides the elevation of the Point-Of-Closest-Approach (POCA) – the point at the surface closest to the satellite on a straight line – every ~400 m along the flight track. The main novelty of this mission is the use of a second antenna, which allows the use of interferometry across-track to accurately infer the location of a surface reflection in presence of a slope (read more about it here). Additionally, a new and exciting application of CS2 interferometric capabilities is that we can exploit the echos after the POCA, i.e. the reflections coming from the sloping surface moments after the first one. This approach generates a swath of elevations every ~400 m and provides up to two orders of magnitude more elevation data than with conventional POCA processing (Fig. 2; Gray et al., 2013, Foresta et al., 2016).

Since 2010, the ESA CryoSat-2 (CS2) mission has been fundamental in retrieving ice elevation data

Figure 2: Example of the improved elevation data using CS2 swath-processing. CS2 swath data (colors) and conventional (circles) heights over the Austfonna ice cap (Svalbard) for two satellite passes. Swath processing delivers up to two orders of magnitude more elevation data. [Credit: Dr. N. Gourmelen,University of Edinburgh, School of GeoSciences]

This rich dataset can be used to generate maps of surface elevation change rates at sub-kilometer resolution (Figs. 1 and 3). These maps show extensive thinning of up to -10 m a-1 in marginal areas of Iceland’s ice caps, while patterns of change are more variable in their interior. Fig. 3 shows the difference in spatial coverage between the POCA and Swath approaches, with the former sampling preferentially along topographic highs (see for example the Langjökull ice cap in Fig. 3). Using these high resolution maps, it is possible to independently infer the mass balance of each ice cap purely from satellite altimetry data. Based on CS2 swath-processed elevations, between glaciological years 2010/11 and 2014/15 Iceland has lost mass at an average rate of 5.8±0.7 Gton a-1 contributing 0.016±0.002 mm a-1 to SLR (Foresta et al., 2016). The rate of mass loss is ~40% less than during the preceding 15 years, partly caused by Vatnajökull (63% of the total mass loss) having had positive mass balance during the glaciological year 2014/15 due to anomalously high precipitation. Langjökull, with widespread thinning up to the ice divide (Figs. 1 and 3), is the fastest changing ice cap in terms of mass loss per unit area.

between glaciological years 2010/11 and 2014/15 Iceland has lost mass at an average rate of 5.8±0.7 Gton a-1 contributing 0.016±0.002 mm a-1 to SLR

Beside estimating mass change at the ice cap scale, the novel swath approach demonstrates the capability to observe glaciological processes at a sub-catchment scale. Different accumulation and thinning patterns over Vatnajökull and Langjökull, for example, are directly related to past surges or subglacial volcanic eruptions, some of which happened decades ago. Their long term lingering effects on the ice cap topography are now visible from space and as the satellite data record extends we will be able to gain an increased understanding of how these effects evolve over time.

Figure 3 – Comparison between swath-processed (Swath) and conventional (POCA) surface elevation change rates over the six largest ice caps in Iceland, representing 90% of the glaciated area. V (Vatnajökull), L (Langjökull),H(Hofsjökull),M(Mýrdalsjökull), D (Drangajökull), and E (Eyjafjallajökull). The inset shows the location of individual elevation measurements by using Swath and POCA approaches over Langjökull. [Credit: After Foresta et al. (2016).]

Edited by Emma Smith

Luca Foresta is a PhD student in the Glaciology and Cryosphere Research Group at the University of Edinburgh (@EdinGlaciology), and his research focuses on improving CryoSat-2 processing as well as exploiting swath-processed CryoSat-2 data to quantify surface, volume and mass changes over ice caps.


Image of the Week – Apocalypse snow? … No, it’s sea ice!

Image of the Week – Apocalypse snow? … No, it’s sea ice!

Sea ice brine sampling is always great fun, but sometimes somewhat challenging !

As sea water freezes to form sea ice, salts in the water are rejected from the ice and concentrate in pockets of very salty water, which are entrapped within the sea ice. These pockets are known as “brines”.

Scientists sample these brines to measure the physical and bio-geochemical properties, such as: temperature, salinity, nutrient, water stable isotopes, Chlorophyll A, algal species, bacterial number and DNA, partial pressure of CO2, dissolved and particulate Carbon and Nitrogen, sulphur compounds, and trace metals.  All of this helps to better understand how sea ice impacts the atmosphere-ocean exchanges of climate relevant gases.

In theory, sampling such brines is very simple: you just have to drill several holes in the sea-ice ensuring that the holes don’t reach the bottom of ice and wait for half an hour. During this time, the brine pockets which are trapped in the surrounding sea ice drain under gravity into the hole. After that, you just need to sample the salty water that has appeared in the hole. Simple…

…at least it would be if they didn’t have to deal with the darkness of the Antarctic winter, blowing snow, handling water at -30°C and all while wearing trace metal clean suits on top of polar gear…hence the faces!

This photo won the jury prize of the Antarctic photo competition, organised by APECS Belgium and Netherlands as part of Antarctica Day celebrations (1st of December).

All the photos of the contest can be seen here.

Edited by Sophie Berger and Emma Smith

Jean-Louis Tison is a professor at the Université libre de Bruxelles. His activities are focused on the study of physico-chemical properties of « interface ice », be it the « ice-bedrock » (continental basal ice) , « ice-ocean » (marine ice) or « ice-atmosphere » (sea ice) interface. His work is based on numerous field expeditions and laboratory experiments, and on the development of equipments and analytical techniques dedicated to the multi-parametric study of ice: textures and fabrics, stable isotopes of oxygen and hydrogen, total gas content and gas composition, bulk salinity, major elements chemistry…


Image of the Week – Supraglacial debris variations in space and time!

Image of the Week – Supraglacial debris variations in space and time!

There is still a huge amount we don’t know about how glaciers respond to climate change. One of the most challenging areas is determining the response of debris-covered glaciers. Previously, we have reported on a number of fieldwork expeditions to debris-covered glaciers but with this Image of The Week we want to show you another way to investigate these complex glaciers – numerical modelling!

Debris-covered glaciers

Debris-covered glaciers occur globally, with a great many being found in the Himalaya-Karakoram mountain range. For example, in the Everest Region of Nepal 33% of glacier area is debris covered (Thakuri et al., 2014). The response of debris-covered glaciers to future climate change in such regions has huge implications for water resources, with one fifth of the world’s population relying on water from the Himalayan region for their survival (Immerzeel et al., 2010).

Debris-covered glaciers respond to climate change differently to debris-free glaciers as the supraglacial debris layer acts as a barrier between the atmosphere and glacier (Reznichenko et al., 2010). The supraglacial debris layer has several key influences on the glacier dynamics:

  • Glacier ablation (loss of mass from the ice surface) is enhanced or inhibited depending on debris layer thickness and properties – see our previous post.
  • Supraglacial debris causes glaciers to reduce in volume through surface lowering rather than terminus retreat (typical of debris free mountain glaciers).

Understanding the influence of a supraglacial debris layer on mass loss or gain is, therefore, key in determining the future of these glaciers. The properties of supraglacial debris layers can vary in time and space both in debris layer thickness and distribution, as well as properties of the rocks which make up the debris (e.g. albedo, surface roughness, porosity, size and moisture content). It is these characteristics of the debris-cover which control the heat transfer through the debris and therefore the amount of thermal energy that reaches the underlying ice causing melting (Nicholson and Benn, 2006). In order to better predict the future of debris-covered glaciers we needs to be able to numerically model their behaviour. This means we need a better understanding of the variations in debris cover and how this affects the ice dynamics.

How does a supraglacial debris layer vary in time and space?

Our Image of the Week (Fig. 1) shows a schematic of how debris distribution can vary spatially across a glacier surface and also this can change through time. The main inputs of debris are:

  • Upper regions: snow and ice avalanches in the upper reaches of the glacier.
  • Mid and Lower regions: rock avalanches and rock falls (Mihalcea et al., 2006).

These irregular mass movement events vary in frequency and magnitude, and therefore affect debris distribution across the glacier surface but also through time. The irregularity of them makes it really hard to predict and simulate! Luckily, debris transport is a little more predictable.

Figure 2: An ice cliff emerging out of the supraglacial debris layer on Khumbu Glacier, Nepal, with Nuptse in the background. [Credit: M. Gibson]

Debris is initially transported along medial moraines (glacially transported debris)  in the upper and mid-sections of the glacier, this is known as entrained debris. The various sources of entrained debris combine to form a continuous debris cover in the lower reaches of the glacier (Fig. 1). As a supraglacial debris layer is forming, such as for Baltoro glacier (Fig. 1), the boundary between the continuous debris layer and entrained debris sections progresses further upglacier over time.

Eventually transported debris will reach the terminus of the glacier and be deposited (Fig. 1), mainly due to a decrease in surface velocity of the glacier towards the terminus. However, once debris is deposited it doesn’t just sit there; debris is constantly being shifted around as ablation (surface melting) occurs. As ablation occurs the debris surface ablates unevenly, as the thickness of the debris layer is spatially variable. Uneven ablation, otherwise known as differential surface lowering, causes the glacier surface to be made up of topographic highs and lows, the latter of which sometimes become filled with water, forming supraglacial ponds (Fig. 1) . Another product of debris shifting is that ice cliffs, such as the one seen in Fig. 2, are exposed. These features are initially formed when englacial channels collapse  or debris layers slide (Kirkbride, 1993). All this movement and shifting means that not only do glacier models have to consider variation in debris layers across the glacier and through time, but also the presence of ice cliffs and supraglacial ponds. They are important as they have a very different surface energy balance to debris-covered ice. To complicate things further the frequency and area of ice cliffs and supraglacial ponds also vary through time! You see the complexity of the problem…

Modelling spatially and temporally varying debris layers

Numerical modelling is key to understanding how supraglacial debris layers affect glacier mass balance. However, current numerical modelling often either omits the presence of a supraglacial debris layer entirely, or a debris layer that is static in time and/or space (e.g. Collier et al., 2013; Rowan et al., 2015; Shea et al., 2014). However, as outlined earlier, these supraglacial debris layers are not static in time or space. Understanding the extent to which spatiotemporal variations in supraglacial debris distribution occur could aid identification of when glaciers became debris-covered, glaciers that will become debris-covered glaciers in the future, and the timescales over which supraglacial debris layers vary. The latter is particularly relevant to numerical modelling as it would result in total glacier ablation being calculated more precisely throughout the modelling time period. Understanding the interaction between glacier dynamics and debris distribution is therefore key to reconstructing debris-covered glacier systems as accurately as possible.

Edited by Emma Smith

Morgan Gibson is a PhD student at Aberystwyth University, UK, and is researching the role of supraglacial debris in ablation of Himalaya-Karakoram debris-covered glaciers. Morgan’s work focuses on: the extent to which supraglacial debris properties vary spatially; how glacier dynamics control supraglacial debris distribution; and the importance of spatial and temporal variations in debris properties on ablation of Himalaya-Karakoram debris-covered glaciers. Morgan tweets at @morgan_gibson, contact email address:

Katabatic winds – A load of hot (or cold) air?

Katabatic winds – A load of hot (or cold) air?

It might seem obvious that a warming world will lead to a reduction in glacial ice cover, but predicting the response of glaciers to climatic change is no simple task (even within the short term). One way to approach this problem is to come up with relationships which describe how glaciers interact with the world around them, for example, how the ice interacts with the air above it. Our post today delves into the world of ice-air interaction and describes some of the problems encountered by those who are investigating it, in particular the problem of modelling katabatic winds! Not sure what we are talking about…then read on to find out more! 

What are katabatic winds?

Anyone who has stood on, or in front of a glacier on a clear, sunny day has no doubt felt the bitter chill of a katabatic wind, forcing them to don a warm jacket and lose their chance at that lovely “glacier tan”. Katabatic winds (derived from the Greek word katabasis, meaning ‘downhill’) develop over snow and ice surfaces because the 0°C ice surface cools the air just above it. This cold, dense air then flows downhill under the force of gravity (Fig. 1 and Fig. 2). This is not recent news and such wind chill has no doubt punished glaciologists and explorers for the last century or more –  Mawson’s Description of the 1911-1914 Australian Antarctica Expedition is aptly named “The Home of the Blizzard“. However, despite being well known, this phenomenon still causes much uncertainty when it comes to modelling the melting of glacier ice surfaces around the world.

Soon gusts swept the tops of the rocky ridges, gradually descending to throw up the snow at a lower level. Then a volley raked the Hut, and within a few minutes we were once more enveloped in a sea of drifting snow, and the wind blew stronger than ever. – Mawson, 1915, The Home of the Blizzard

Figure 2: The view from the upper reaches of Tsanteleina Glacier in the western Italian Alps (Val d’Rhemes, Aosta). Katabatic winds generally flow in a down-glacier direction – here, from right to left [Credit: T Shaw].

Challenges for modelling

Air temperature is really important in determining how much a glacier melts and we need to know as much about it as possible to provide accurate predictions now and into the future. This is particularly relevant because the warmer it gets, the more energy is available to melt ice and seasonal snow. Unfortunately though, we don’t have an infinite supply of meteorological observations (e.g. air temperature, wind speed etc) at many locations we are interested in. As a result, we have to make simple assumptions about what the weather is doing at a remote, far away glacier. One such simple assumption is based upon the fact that air temperature typically decreases with increasing elevation, and so if we know the elevation of a location we are interested in, we can assume a ‘likely’ temperature. The rate of change in temperature with elevation is known as a ‘lapse rate’.

Air temperature is really important in determining how much a glacier melts…the warmer it gets, the more energy is available to melt ice and seasonal snow.

When predicting glacier melt, it is common practice to use a lapse rate which stays constant in time and space. This is convenient as we often don’t know the actual lapse rate at a given location, but this often ignores things happening at the surface of the Earth. An important example of this is when we have katabatic winds over glaciers!

When conditions are warm, and skies are clear, the cooling of the air above the ice surface, means that the application of a lapse rate is fairly useless, or close to it [Greuell and Böhm, 1998]! That is because the cooling from the surface continues as air flows down the glacier, typically creating colder temperatures at lower elevations, the opposite of the typical lapse rate assumption that models will apply.

‘Bow-shaped’ temperature vs. elevation relationships

To complicate matters for people trying to model the air temperature over glaciers, the effect of surface cooling is not just dependent on the amount of time an air parcel is in contact with the ice surface but also the characteristics of the ice surface it has been in contact with. In fact, after cooling on their descent down-glacier, air parcels have been documented to warm again, leaving interesting slightly “bow-shaped” curves to the temperature-elevation relationship. This effect has been found for the Swiss Haut Glacier d’Arolla and the Italian Tsanteleina Glacier (Fig. 3c,d). A new model approach to tackling this bow-shaped problem has been presented by recent research [Ayala et al., 2015] and offers a means of accounting for katabatic winds in glacier models. Nevertheless, more data and more work are still needed to generalise these models [Shaw et al., in review].

Figure 3: Relationship between elevation and air temperature on three different glaciers in the western Alps. Miage (Italy), Tsanteleina (Italy) and Arolla (Switzerland). Glaciers are represented using the mean of all data available (green), the top 10% of off-glacier temperatures (P90 – red) and the bottom 10% of off-glacier temperatures (P10 – blue), plus one standard deviation. The debris-covered Miage Glacier does not demonstrate a classic katabatic flow regime and therefore temperature corresponds well to elevation even under warm conditions [Credit: T Shaw, unpublished].

after cooling on their descent down-glacier, air parcels have been documented to warm again, leaving interesting slightly “bow-shaped” curves to the temperature-elevation relationship.

Air temperatures across debris-covered glaciers

As you may have read in our previous post on the topic, debris-covered glaciers behave in a different way to those with a clean ice surface. Detailed observations of air temperature across a debris-covered glacier show that the glacier responds to the heating of surface debris in the sunlight and a consequent warming of the lower atmosphere [Shaw et al., 2016]. Because of this, air temperature conforms very strongly to the elevation dependency that is assumed when using a lapse rate. Although very local variations of air temperature on other debris-covered glaciers cannot be well estimated by a lapse rate [Steiner and Pellicciotti, 2016], the insulating effect of thick debris cover means that the current approach to using simple lapse rates for estimating air temperature over debris-covered glaciers could be suitable.

Nevertheless, challenges for accurately representing air temperature above glaciers without debris cover remain. The fact that globally averaged temperatures are expected to rise over the current century (areas at high latitudes have shown a stronger warming trend) [Collins et al, 2013], the applicability of using lapse rates could further diminish. Recent patterns of warmer-than-average temperatures also suggest a difficulty of accurately estimating on-glacier temperatures in the short-term. For example, for the period of May 2015 – August 2016, every month beat the previously held record for warmest globally average temperature (GISTEMP). Imagine the bow-shaped problem to that!

Edited by Matt Westoby and Emma Smith

Thomas Shaw is a PhD student in the Department of Geography at Northumbria University, UK. His research is focused on the spatial and temporal variance in near-surface air temperature across debris-covered and debris-free glaciers in the western Italian Alps. As well as conducting research in the Alps, he is also very interested in glaciers and their processes on Svalbard (Norwegian Arctic) and has spent plenty of time studying above, or within (!), ice at high latitudes. Contact e-mail:

Image of the Week – For each tonne of CO2 emitted, Arctic sea ice shrinks by 3m² in summer

Image of the Week – For each tonne of CO2 emitted, Arctic sea ice shrinks by 3m² in summer

Declining sea ice in the Arctic is definitely one of the most iconic consequences of climate change. In a study recently published in Science, Dirk Notz and Julienne Stroeve find a linear relationship between carbon dioxide (CO2) emissions and loss of Arctic sea-ice area in summer. Our image of this week is based on these results and shows the area of September Arctic sea ice lost per inhabitant due to CO2 emissions in 2013.

What did we know about the Arctic sea ice before this study?

Since the late 1970s, sea ice has been dramatically shrinking in the Arctic, losing 3.8% of its area per decade. Sea-ice area is at its minimum in September, at the end of the melting season.

The main cause of this loss is the increase in surface temperature over the recent years (Mahlstein and Knutti, 2012), which has been more pronounced in the Arctic compared to other regions on Earth (Cohen et al., 2014). The use of statistical methods involving both observations and climate models shows that the recent warming in the Arctic can be attributed to human activity, i.e. mainly greenhouse gas emissions (Gillett et al., 2008). This suggests a direct link between human activity and Arctic sea-ice loss, which is confirmed in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC).

How exactly is sea-ice loss related to CO2 emissions ?

Notz and Stroeve (2016) relate the Arctic sea-ice decline to cumulative CO2 emissions since 1850 (i.e. the total amount of CO2 that has been emitted since 1850) for both observations and climate models. Cumulative CO2 emissions constitute a robust indicator of the recent man-made global warming (IPCC, 2014).

The two quantities are clearly linearly related (see Figure 2). From 1953 to 2015, about 3.5 million km² of Arctic sea ice have been lost in September while 1200 gigatonnes (1 Gt = 10e9 tonnes) of CO2 have been emitted to the atmosphere. This means that for each tonne of CO2 released into the atmosphere, the Arctic loses 3 m² of sea ice.

Fig 2: Monthly mean September Arctic sea-ice area against cumulative CO2 emissions since 1850 for the period 1953-2015. Grey circles and diamonds show the results from in-situ (1953-1978) and satellite (1979-2015) observations, respectively. The thick red line shows the 30-year running mean and the dotted red line represents the trend of 3 m² sea-ice area loss per tonne of CO2 emitted. [Credit: D. Notz, National Snow and Ice Data Center ]

Starting from the relationship between cumulative CO2 emissions and sea-ice area, it is then easy to attribute to each country in the world their own contribution to sea-ice loss based on their CO2 emissions per capita. The countries that stand out in the map are thus the countries emitting the most in relation to their population.

Could the Arctic be ice-free in the future?

If this relationship holds in the future (in other words, if we extend the red dotted line to zero sea-ice area in Figure 2), adding 1000 Gt of CO2 in the atmosphere would free the Arctic of sea ice in September. Since we are currently emitting about 35 Gt CO2 per year, it would take less than 30 years to have the Arctic free of sea ice in the summer (which confirms previous model studies (e.g. Massonnet et al., 2012)).

Edited by Clara Burgard and Sophie Berger

Further reading

DavidDavid Docquier is a post-doctoral researcher at the Earth and Life Institute of Université catholique de Louvain (UCL) in Belgium. He works on the development of processed-based sea-ice metrics in order to improve the evaluation of global climate models (GCMs). His study is embedded within the EU Horizon 2020 PRIMAVERA project, which aims at developing a new generation of high-resolution GCMs to better represent the climate.

Ice Cores “For Dummies”

Ice Cores “For Dummies”

Ice cores are important tools for investigating past climate as they are effectively a continuous record of snowfall, which preserves historical information about climate conditions and atmospheric gas composition. In this new “For Dummies” post, we discuss the history and importance of ice-core science, and look at the way we can use ice core chemistry to reconstruct past climate.

Ice sheets, archives of our past

When snow falls on the surface of an ice sheet it begins to compact the snow beneath it – eventually it will be compacted enough to be transformed into ice. Simultaneously, atmospheric air held between the snowflakes is slowly trapped in the ice – forming small air bubbles. In areas where mean annual temperatures at the ice surface remain below 0C, such as Greenland and Antarctica, there is little surface melting, so this snow builds up to form thick ice sheets – up to 3000 metres in some part of East Antarctica! Low surface melt means that the snow that is compressed into ice each year forms a continuous record of the annual snowfall and atmospheric gas concentrations at the time of deposition, but how do we access this record..?

Snow that is compressed into ice each year forms a continuous record of the annual snowfall and atmospheric gas concentrations at the time of deposition

…We drill ice cores – of course!

An ice core is a cylinder of ice that is retrieved from the ice sheet by drilling vertically downwards. The core is drilled in sections from the surface, deep into the ice sheet (Fig. 1) using a rotating drill. Each section of the core is processed at the drill site and often cut further into shorter sections of ~55 cm for more practical transport and analysis in labs. A great deal of equipment is needed to achieve this and drilling is a slow and careful process often taking several field seasons to drill a deep core. An example of a drilling camp is shown in Fig. 2, housing scientists and engineers involved in drilling an ice core on the Fletcher Promontory, West Antarctica.

Figure 1: a) Ice core drill being lowered into the ice on Pine Island Glacier [Credit: Alex P. Taylor] b) Dr Rob Mulvaney processing the Berkner Island ice core, Weddell Sea, Antarctica [Credit: R. Mulvaney]

Figure 2: The layout of the Fletcher Promontory ice-drilling project, Weddell Sea, Antarctica. In the background the large Weatherhaven tent houses the drill rig, the central Weatherhaven tent is used for storage and equipment and a simple shower, the nearest Polarhaven tent is the mess tent, and the Polarhaven tent to the left houses the main generator. The pyramid tents in the foreground are the sleeping tents, and the two to the right are used for toilet facilities [Credit: Mulvaney et al., 2014]

Where to drill an ice core for the best record?

To get a good record of climate we want to find an area of ice that has many annual layers (good temporal resolution) that has not been disturbed by high ice flow velocities, usually these conditions can be found at an ice dome or divide. An ice sheet is a large plateau with a relatively stable rate of annual snowfall; the dome (or ice divide) is the point in the ice sheet where there is only vertical flow (compression) of ice (Fig. 3). Horizontal flow of ice is greater with the greater distance from the dome. Therefore, domes are the ideal site on the ice sheet or ice cap to drill for an ice core to ensure no interference with the snowfall history at the site. It is reasonable to assume that the ice-core record taken from a site with high annual snowfall will not extend the furthest back in time; similarly, a low annual snowfall and a large ice-sheet thickness will offer a record spanning much further back in time.

Figure 3: Ice flow within the ice sheet showing the zero flow at the ice divide – the ideal site for an ice core [Credit: Snowball Earth]

For Antarctica, the amount of snowfall across the ice sheet depends on the distance from the coast and sources of moisture; the highest mean annual snowfall is found at West Antarctic ice sheet sites whilst the lowest values are inland on the East Antarctic ice sheet, one of the driest deserts on Earth. In addition to the West and East Antarctic ice sheets, the Antarctic Peninsula is the third and final sector of the continent with high mean annual snowfall comparable to West Antarctica. In comparison to Antarctica, the Greenland ice sheet has a relatively high present-day mean annual snowfall, varying across the ice sheet between 10 and 30 cm per year. Therefore, if your aim is to find the oldest ice on Earth, East Antarctica is a good place to start looking, see our post on the quest to drill an ice core that contains ice which is over a million years old. Additionally, for the longest records it is paramount to find a drilling location with no (or at least very low) annual melting at the bedrock.

If your aim is to find the oldest ice on Earth, East Antarctica is a good place to start looking

What does an ice core actually record?

Once an ice core has been drilled and cut into sections, some of the sections are analysed and others are preserved. This is particularly important as some of the analysis is destructive (e.g. melting of the ice to extract water and gas). Therefore an archive of the ice core itself is needed. So, what information can we obtain from analysing the core and how is it done?

Annual layers, past snowfall and past temperatures!

Reconstructing the past surface temperature and snowfall is incredibly useful for understanding climate processes and changes through time in order to assess any present-day local and regional changes in climate. We can do this by:

          • Measuring the thickness of the annual layers: This is done by counting layers in the core, either by visual identification of the peaks in deposition or use of a computer algorithm. The thickness of a specific year depends on how much snow fell at the site and on how much the snowfalls of the following years compacted this specific layer. We can estimate the strain caused by compaction which allows us to extract historical annual snowfall.
          • Past air temperatures (Stable Water Isotope Record): An additional method to reconstruct past snowfall is from the ratios of the stable water isotopes from the water that forms snow and precipitation. The ratio of stable water isotopes has a linear relationship with surface temperature (see box below). Mathematical reconstructions of accumulation using the temperature reconstructions from stable water isotopes are employed in ice core profiles where the compaction of annual snowfall results in an annual layer thickness beyond standard laboratory resolution, such as Antarctic sites. Following the accumulation reconstruction, the rate of compaction of the annual snowfall to ice and subsequent ‘thinning’ of the deposited snowfall layer must be estimated by glaciological modelling.
          • Trace-element analysis: For the upper depths of a deep ice core, or an ice core with an easily-resolvable annual layer thickness, the continuous analysis of an ice core for stable water isotopes offers a sub-annual view of the climate record.

            Figure 4: Seasonal deposition of four chemical species in the WAIS Divide ice core. Pink: electrical conductivity measurements; Black: Black Carbon; Red: non-sea salt Sulphur; Blue: Sodium. Each panel, shows the averaged annual record for 2 different periods: the Antarctic Cold Reversal (ACR, 13-14,000 years ago – bold line) and the Holocene, (10-11,000 years ago – thin line) the [Credit: Fig. 2, Sigl et al., 2016 ]

            The deposition of a number of chemical elements increases during the summer season and decreases during the winter.When these elements are measured in the ice core they can be depicted as an almost-sinusoidal record, indicating the historical seasons. High-resolution ice-core profiles can be dated by counting these annual layers, and have been done so across Greenland and at the West Antarctic Ice Sheet (WAIS) Divide ice core site. Fig. 4 shows two annual signals over 24 months for four different chemicals that are deposited in ice cores (Sigl et al., 2016). The peak in seasonal deposition is shown twice for each chemical, at different times in history, but the seasonality of these species remains strong throughout time.
Reconstructing Past Temperatures
We commonly think of water as H2O - a molecule containing two hydrogen atoms and one oxygen atom. However, atoms (i.e. Hydrogen and Oxygen) come in several forms, known as isotopes - atoms with the same number of protons, but differing numbers of neutrons. Those isotopes that don't decay over time and are preserved in the ice core are know as stable water isotopes. It is possible to measure the amount of each different stable water isotope present in an ice core by melting the ice core and using a mass spectrometer to analyse the water produced.

The snow that eventually forms ice cores starts its life as ocean water which is evaporated and transported to the polar regions. Water isotopes with more neutrons are heavier and therefore require more energy to evaporate and transport. The amount of energy available to do this is related to temperature. Therefore heavier isotopes are found in ice cores in higher amounts at warmer periods in the planet's history! Find out more  here!

Atmospheric gas

Ice-core measurements of atmospheric gases correlate well with direct measurements taken from the atmosphere dating back to 1950. As a result of this, ice-core scientists can assume that the atmospheric gas concentrations measured in ice cores reflects the atmospheric conditions at the time the gas was entrapped in the ice core. Hence, ice cores tell us that carbon dioxide concentrations have been relatively stable for the last millennia until around 1800 AD but since then a rise of almost 40% has been measured in both ice cores and direct atmospheric measurements (Fig. 5).

Figure 5: 1000 years of atmospheric CO2 concentrations from various Antarctic ice cores (DML, South Pole, Law Dome and Siple Dome) and the direct measurements in Mauna Loa Observatory [Credit: Ashleigh Massam, compiled from open access data sources]

Carbon dioxide concentrations have been relatively stable for the last millennia until around 1800 AD but since then a rise of almost 40% has been measured

In addition to comparison with present-day measurements, the trapped gases offer a record of direct atmospheric and greenhouse gas concentrations, including methane, carbon dioxide and nitrous oxide (Fig. 6) on a longer timescale – up to 800,000 years (Loulergue et al., 2008). Records show the connection between fluctuations in the atmosphere and long-term global climate variations (e.g. temperature) on a millennial timescale (Kawamura et al., 2007). The long-term trends show a pattern in the gas concentrations that compare well with glacial-interglacial climate. The phasing and timing of the eight glacial cycles covered by this record are dominated by the orbital cycle of the Earth on a 96,000-year periodicity, with a warm, interglacial period between each cold period. However, as we will see later in this blog post, this may not be the case when we look further back in time!

Figure 6: Variations of temperature (from present day mean temperature, black), atmospheric carbon dioxide (in part per million by volume — blue) and methane (in part per billion per volume red) over the past 800,000 years, from the EPICA Dome C ice core in Antarctica. Modern value (of 2009) of carbon dioxide and methane are indicated by arrows. [Credit : Centre for Ice and Climate , University of Copenhagen. Re-used with permission ]

Other climate proxies

Chemistry preserved in the ice also offers a proxy (=a means) to reconstruct other seasonally-deposited tracers:

                        • Information on past sea-ice extent can be obtained from chemicals found in ice cores which are also present in sea salt such as sodium, chlorine and methanesulphonic acid (MSA) (Sommer et al., 2000; Curran et al., 2003; Rothlisberger et al., 2003).
                        • The seasonal deposition of elements such as iron, magnesium and calcium, which are linked to dust from far-afield and the short-term climate variability such as atmospheric circulation (Fuhrer et al., 1999).
                        • Finally, volcanic layers in the ice core such as tephra and sulphate deposit provides a unique timestamp to a specific depth. These layers were deposited at the same time, all over the world and can be pinpointed to a specific volcanic eruption. Deposits of the same layer outside of a glaciated landscape, (e.g. within rock layers ) can often be dated using radiocarbon (Carbon-14) or another radiogenic dating methods. Additional age horizons can be interpreted by events assumed to occur in the world at the same time, such as rapid climate events. Age constraints are beneficial to interpreting deep ice-core records that are not analysed at a sub-annual resolution by offering pinpoint age horizons to an ice-core record.

Current knowledge from ice-core records

As we have seen, ice core are important because they put the current climate variations into the context of a long-term climate history. Additionally, polar ice cores can allow us to looks at variations between the northern and southern hemisphere. Ice cores also extend back much, much further in time than terrestrial weather stations or satellite records:

Figure 7: Deep ice core locations in Greenland and Antarctica [Credit and more details: NSIDC ]

The current past climate record tells us about glacial and inter-glacial periods (Fig. 6) but also allows us to look at finer detail – i.e. the variability within these periods, which were previously assumed stable.  For example, ice cores have led to the discovery of Dansgaard-Oeschger events; which are are rapid climate fluctuation events, characterised by rapid warming followed by gradual cooling to return to glacial conditions, 25 of these events have happened during the last glacial period.

Records from the Northern and Southern hemisphere also allow us to link these small and large scale changes in climate in the two hemispheres. For example, ice cores analysed from both poles show a ‘call and response’ signal between Dansgaard-Oeschger events in the Northern Hemisphere and events in the Antarctic climate record. The southern hemisphere cooled during the warm phases of Dansgaard-Oeschger events in the northern hemisphere (Buizert et al., 2015), and vice versa during northern hemispheric cooling (see our previous blog post on the subject).

There are already over a dozen ice cores taken from Greenland and Antarctica (Fig. 7), offering a clear and detailed history of the climate during the Late Quaternary period (Fig. 6), going back up to 800,000 years (Quaternary = last 2.6 million years). As we mentioned earlier the timing of glacial and inter-galcial cycles in this 800,000 year old record is dominated by the orbital cycle of the Earth (96,000-year periodicity). However, marine records show that frequency of glacial-interglacial cycles was different before this time (Lisiecki and Raymo, 2005). It is in order to better understand these changes that the quest for the oldest was formed – beginning last month the mission aims to drill an ice core of ice older than 800,000 years to gain detailed information about the climate even further back in time.

Detailed records from high-resolution ice cores improves our understanding of the response of the planet to deglaciation events

The continuous and high-resolution of ice-core records, together with marine and terrestrial records, offers a global view of coupled processes from ice sheet calving events, changes to ocean circulation and heat transport and the subsequent cooling events across the Earth. Detailed records from high-resolution ice cores improves our understanding of the response of the planet to deglaciation events from the large ice sheets that once covered much of the northern hemisphere. Melting ice sheets pose a significant threat to the planet from rising sea levels and the freshwater input leading to inevitable changes in climate.

Edited by Emma Smith and Sophie Berger

Ashleigh Massam is a final-year PhD student based in the Ice Dynamics and Palaeoclimate group at the British Antarctic Survey and with the Department of Geography at Durham University. Her project is developing the age-depth profiles of three ice cores drilled at James Ross Island, Fletcher Promontory and Berkner Island, West Antarctica, by a combination of high-resolution trace-element analytical techniques and modelling ice-sheet processes.

Ice-Hot News : The “Oldest Ice” quest has begun

Ice-Hot News : The “Oldest Ice” quest has begun

This is it! The new European horizon 2020 project on Oldest Ice has been launched and the teams are already heading out to the field, but what does “Old Ice” really mean? Where can we find it and why should we even care? This is what we (Marie, Olivier and Brice) will try to explain somewhat.

Why do we care about old ice, ice cores and past climate?

Figure 1: Drilling an ice core [Credit: Brice Van Liefferinge]

Figure 1: Drilling an ice core [Credit: Brice Van Liefferinge]

Unravelling past climate and how it responded to changes in environmental conditions (e.g. radiative forcing) is crucial for our understanding of the current climate and for predicting how climate will likely change in the future.

Ice cores contain unique and quantitative information on the past climate (e.g. atmospheric gas concentration). The caveat is that at the moment, we can “only” go back up to 800,000 years at EPICA Dome C ice core (Parrenin et al, 2007).

Nonetheless, marine records tell us that during the Mid-Pleistocene there was a major climate transition (0.8-1.2 million years ago): a change in the frequency of glacial-interglacial cycles in the Northern Hemisphere. Instead of an ice age every 40,000 year, the climate changed to what is termed a “100,000 year world”. Unfortunately, the time resolution of marine records are too coarse to provide details on the mechanisms behind such climate changes. We must therefore rely on ice cores to obtain a high enough temporal resolution. Furthermore, the ice traps air bubbles and can therefore provide a record of the atmospheric composition that can be used to directly measure the paleo atmosphere through the transition.

The new European project ‘Oldest ice’ was set up for this very objective: crack the Mid-Pleistocene Transition climate. It brings together engineers, experimentalists and modellers from 14 Universities around the world.

In this post, we will focus on the first mission of the project: locating areas with million year old ice in Antarctica. The next steps will be to:

  • develop the drilling technology,

  • improve our geophysical knowledge of the identified site,

  • and finally, reach the “holy grail”: recover ice from the very base of the ice sheet with a target age of 1.5 Million years.

The whole project is anticipated to last 10 years!

The new European project ‘Oldest ice’ was set up for this very objective: crack the Mid-Pleistocene Transition climate

The first mission: “Where to find million year old ice?”

Oldest Ice (ice more than 1 mio. years old) can only be recovered in Antarctica, but where exactly? This question has to be answered in a two-step approach:

  1. On a large scale, we must first narrow down places in Antarctica where Oldest Ice might be found. To do that, we rely on models.

  2. Then, we can focus our analysis on those regions by gathering field data in the form of airborne radar surveys. Further ground-based work is currently taking place.

On a larger scale, Oldest Ice in Antarctica requires:

  1. Thick ice and cold bed. We need thick ice to reconstruct past climate variations with sufficient temporal resolution (e.g. is there enough ice to measure air bubbles or other climate markers). However, the thicker the ice, the higher the basal temperature. If the bottom of the ice is too warm, the ice at the base will start to melt, potentially destroying the Oldest Ice of the ice sheet.
    Finding a suitable drill site hence requires a good trade-off between thickness and cold-bed conditions.

  2. Slow-moving ice. This is found mainly at the centre of the ice sheet. Imagine this: if ice were to flow at as little as 1 m per year over a period of 1.5 Million years, it would have travelled 1,500 km over that time interval! However, there is a catch: slow-moving areas are also low-accumulation areas, and low accumulation means warmer ice. This is because the ice is cooled by the addition of cold snow at the surface that then gets transformed to ice and then travels downwards. Indeed, the greater the accumulation, the deeper the “cold snow” can penetrate into the ice sheet!

  3. Undisturbed ice. In order to obtain an interpretable climate record, the ice recovered from the drill needs to be stratigraphically ordered, i.e. no mixing of the ice can have occurred so that we can assume that time increases with depth when we measure ice composition down the core. Variations in the height of the bedrock can induce such ice mixing.

(more information can be found in Van Liefferinge and Pattyn (2013))

Figure 2. Potential locations of cold bed (basal temperatures 2000 m), slow motion (horizontal flow speeds <2m/yr) The colour bar represents the basal temperature. The two insets focus on Dome C and Dome F, two areas highly likely to store million year old ice. [Credit: Brice Van Lieffering, updated from Van Liefferinge, B. and Pattyn, 2013]

Figure 2. Potential locations of cold bed (basal temperatures 2000 m), slow motion (horizontal flow speeds <2m/yr) The colour bar represents the basal temperature. The two insets focus on Dome C and Dome F, two areas highly likely to store million year old ice. [Credit: Brice Van Lieffering, updated from Van Liefferinge, B. and Pattyn, 2013]

While boundary conditions such as ice thickness and accumulation rates are relatively well constrained, the major uncertainty remains in determining thermal conditions at the ice base. The thermal conditions depend on the geothermal heat flow (the flux of “energy” provided by the Earth which conducts heat into the crust) underneath the ice sheet. But to measure the geothermal heat flow, you need to reach the bed.

We need to find the ideal drilling location which would satisfy all these conditions – a bit of a “Goldilocks’ choice”: thick ice but not too much, low accumulation but not too low, low geothermal heat flow but high enough to not get folded basal ice. To do this we use several models: a simple one which calculates the minimum geothermal heat flow needed to reach the pressure melting point that we can then compare to data sets, and a more complex one resolving in three dimensions the temperature field with thermomechanical coupling (i.e. linking the ice-flow component to the heat-flow component). The combination of modelling approaches shows that the most likely oldest ice sites are situated near the ice divide areas (close to existing deep drilling sites, but in areas of smaller ice thickness) (see Figure 2).

Give it a go: Try to find million year old ice yourself using this Matlab© tool:

The combination of modelling approaches shows that the most likely oldest ice sites are situated near the ice divide areas

On finer scales: we need deep radiostratigraphy and age modelling

Radar profiles

Figure 3. Radargram from the new OIA radar survey (Young et al., in review) with isochrones interpreted in red [Credit: Marie Cavitte]

Figure 3. Radargram from the new Oldest Ice A radar survey (Young et al., in review) with isochrones interpreted in red [Credit: Marie Cavitte]

Radargrams (see figure 3) are powerful tools to observe the internal structure of the ice: variations in density, acidity and ice fabric all can create conductivity contrasts, which result in radar visual stratigraphy. Below the firn column (the compacting snow, up to 100 m thick), most returns are related to acidity variations, corresponding to successive depositional events (i.e. snowfall). Radar stratigraphy in this case can be considered isochronal, i.e. every visible line (see figure 3) were formed at the same moment, (Siegert et al., 1999). Such radar isochrones can then be traced for kilometres throughout the ice sheet where radar data has been acquired. When radar lines intersect an ice core site, the radar stratigraphy can then be dated by matching the isochrone-depths to the ice core depths at the site and then transferring the age-depth timescale.

This allows to date entire sub-regions. However, the very bottom of the ice column is often difficult to interpret: radar isochrones cannot always be continuously followed from the ice core.

Radargrams are powerful tools to observe the internal structure of the ice

The newly acquired Oldest Ice A radar survey (Young et al., in review) over the Dome C region (see figure 2 for location) gives very rich stratigraphic information and the proximity of the EPICA Dome C ice core has allowed the dating of the isochrones. The ice sheet in this area could only be dated to ~360,000 years (Cavitte et al., 2016) and not further back in time because deeper isochrones are tricky to tie to the ice core, and other times, there is no clear signal (deep scattering ice, visible near the bedrock, at the bottom of Figure 3). As such, we need an age model to try to describe the age-depth relation below the deepest dated isochrones.

Modelling the ice

Figure 4. More precise analysis of the Dome C Oldest Ice target, with the lines representing the Oldest Ice A airborne survey collected in winter 2015/16 (Young et al., in review). The colours represent the modelled age of the ice 60 meters above the bedrock, in thousands of years. We can see that this whole region has a lot of potential for recovering million year old ice. [Credit: Olivier Passalacqua]

Figure 4. More precise analysis of the Dome C Oldest Ice target, with the lines representing the Oldest Ice A airborne survey collected in winter 2015/16 (Young et al., in review). The colours represent the modelled age of the ice 60 meters above the bedrock, in thousands of years. We can see that this whole region has a lot of potential for recovering million year old ice. [Credit: Olivier Passalacqua]

The age of the ice primarily depends on its vertical velocity, so we can use a simple 1D model to describe the motion of the ice in the vertical direction. We run the model for an ensemble of vertical velocity profiles and basal melt rates, and consider the distribution of the basal ages (i.e. model ages) given by the profiles that reproduce the observations the best (i.e. isochrones ages).

We need an age model to try to describe the age-depth relation below the deepest dated isochrones

After running the model, it appears that many areas of the Oldest Ice A survey region host very old ice (see red and yellow dots on figure 4 which represent ages > 1 million years). A high enough bottom age gradient, provided by the dated isochrones, is required to ensure sufficiently old ice as a drilling target. Following initial calculations, it will probably be a better choice to drill on the flank of the bedrock relief than on its top.

So in the end, where do we find the oldest ice?

We have to find areas which provide a good compromise between thick ice (for the a good temporal resolution in the ice core) but not too thick (to avoid basal melting). The best sites will be the ones close to the surface ridge (to ensure limited displacement of the ice), standing above the surrounding subglacial lakes, and for which a lot of undated isochrones below the last dated isochrone are visible.

To find out more about Beyond EPICA and keep track of progress visit the project  website and follow @OldestIce on twitter!

Edited by Sophie Berger

Brice Van Liefferinge is a PhD student and a teaching assistant at the Laboratoire de Glaciology, Université libre de Bruxelles, Belgium. His research focuses on the basal conditions of the Antarctic ice sheet. He tweets as @bvlieffe.

Marie Cavitte is a PhD student at the Institute for Geophysics at the University of Texas at Austin, Texas. Her research focuses on understanding radar internal stratigraphy and using it as a means to constrain the temporal stability of the East Antarctic Ice Sheet interior.

Olivier Passalacqua is a PhD student at the Laboratoire de Glaciologie et Géophysique de l’Environnement, Grenoble, France.

Members of the consortium

  • Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI, Germany), Coordination
  • Institut Polaire Français Paul Émile Victor (IPEV, France)
  • Agenzia nazionale per le nuove tecnologie, l’energia e lo sviluppo economico sostenibile (ENEA, Italy
  • Centre National de la Recherche Scientifique (CNRS, France)
  • Natural Environment Research Council – British Antarctic Survey (NERC-BAS, Great Britain)
  • Universiteit Utrecht – Institute for Marine and Atmospheric Research (UU-IMAU, Netherlands)
  • Norwegian Polar Institute (NPI, Norway)
  • Stockholms Universitet (SU, Sweden)
  • Universität Bern (UBERN, Switzerland)
  • Università di Bologna (UNIBO, Italy)
  • University of Cambridge (UCAM, Great Britain)
  • Kobenhavns Universitet (UCPH, Denmark)
  • Université Libre de Bruxelles (ULB, Belgium)
  • Lunds Universitet (ULUND, Sweden)

Non-Europan partners

  • Institute for Geophysics, University of Texas at Austin (UTIG, US)
  • Australian Antarctic Division (AAD, Australia)

Image of the Week – Inside a Patagonian Glacier

Image of the Week – Inside a Patagonian Glacier

Chilean Patagonia hosts many of the most inhospitable glaciers on the planet – in areas of extreme rainfall and strong winds. These glaciers are also home to some of the most spectacular glacier caves on Earth, with dazzlingly blue ice and huge vertical shafts (moulins). These caves give us access to the heart of the glaciers and provide an opportunity to study the microbiology and water drainage in these areas; in particular how this is changing in relation to climate variations. Our image of this week shows the entrance to one of these caves on Grey Glacier in the Torres del Paine National Park.

“Glacier karstification”

Glaciers in Patagonia are “temperate”, which means that the ice temperature is close to the melting point. As glacial melt-water runs over the surface of this “warm” ice it can easily carve features into ice, which are similar to those formed by limestone dissolution in karstic landscapes. Hence, this phenomenon is called Glacier karstification. It is this process that forms many of the caves and sinkholes that are typically found on temperate glaciers.

From the morphological (structural) point of view, glaciers actually behave like karstic areas, which is rather interesting for a speleologist (scientific cave explorer). Besides caves and sinkholes one often finds other shapes similar to karstic landscapes. For example, small depressions on the ice surface formed by water gathering in puddles, whose appearance resembles small kartisic basins (depressions). Of all the features formed by glacier karstification glacier caves are the most important from a glaciological perspective.

Glacier caves can be divided in two main categories:

  • Contact caves – formed between the glacier and bed underneath; or at the contact between extremely cold and temperate ice by sublimation processes (Fig. 2a)
  • Englacial caves – form inside the glacier – as shown in our image of the week today. Most of these caves are formed by runoff, where water enters the glacier through a moulin (vertical shaft) and are the most interesting for exploration and research (Fig. 2b)
Figure 2: Two different types of caves explored on the Grey Glacier. A- Contact formed between the glacier bed and overlying ice [Credit: Tommaso Santagata]. B- Entrance to an englacial cave [Credit: Alessio Romeo/La Venta].

Figure 2: Two different types of caves explored on the Grey Glacier. A- Contact formed between the glacier bed and overlying ice [Credit: Tommaso Santagata]. B- Entrance to an englacial cave [Credit: Alessio Romeo/La Venta].

Exploring the moulins of a Patagonian glacier

Located in the Torres del Paine National Park area (see Fig. 3), the Grey glacier was first explored in 2004 by the association La Venta Esplorazioni Geografiche. In April of this year, a team of speleologists went back to the glacier to survey the evolution of the glacier.

Figure 3: Map of Grey Glacier with survey site of 2004 and 2016 indicated by red dot [Adapted from: Instituto Geografico Militar de Chile ]

Figure 3: Map of Grey Glacier with survey site of 2004 and 2016 indicated by red dot [Adapted from: Instituto Geografico Militar de Chile ]

Grey glacier begins in the Andes and flows down to it’s terminus in Grey Lake, where it has three “tongues” which float out into the water (Fig, 3). As with many other glaciers, Grey Glacier is retreating, though mass loss is less catastrophic than some of Patagonia’s other glaciers (such as the Upsala – which is glaciologically very similar to the Grey Glacier). Grey Glacier has retreated by about 6 km over the last 20 years and has thinned by an average of 40 m since 1970.

In 2004 research was concentrated on the tongue at the east of this Grey Glacier (Fig. 3 – red dot), which is characterised by a surface drainage network with small-size surface channels that run into wide moulin shafts, burying into the glacier. In this latest expedition, the same area was re-examined to see how it had changed in the last 12 years.

Several moulins were explored during the 2016 expedition, including a shaft of more than 90 m deep and some horizontal contact caves (Fig 2). The glacier has clearly retreated and the surface has lowered a lot from the 2004 expedition. The extent of the thinning in recent years can be easily measured on the wall of the mountains around the glacier. Interestingly the entrance to the caves which were explored in 2004 and in 2016 was in the same position as 12 years ago, although the reasons for this are not yet clear.

The entrance of two of the main moulins which were explored were also mapped in 3D using photogrammetry techniques (see video below). The 3D models produced help us to better understand the shape and size of these caves and to study their evolution by repeating this mapping in the future. For more information about the outcome of this expedition, please follow the Inside the Glaciers Blog.



Further Reading:

Books on the subject:

  • Caves of the Sky: A Journey in the Heart of Glaciers, 2004, Badino G., De Vivo A., Piccini L.
  • Encyclopaedia of Caves and Karst Science, 2004, Editor: Gunn J.

Edited by Emma Smith and Sophie Berger

tom_picTommaso Santagata is a survey technician and geology student at the University of Modena and Reggio Emilia. As speleologist and member of the Italian association La Venta Esplorazioni Geografiche, he carries out research projects on glaciers using UAV’s, terrestrial laser scanning and 3D photogrammetry techniques to study the ice caves of Patagonia, the in-cave glacier of the Cenote Abyss (Dolomiti Mountains, Italy), the moulins of Gorner Glacier (Switzerland) and other underground environments as the lava tunnels of Mount Etna. He tweets as @tommysgeo

Black Carbon: the dark side of warming in the Arctic

Black Carbon: the dark side of warming in the Arctic

When it comes to global warming, greenhouse gases – and more specifically CO2 – are the most often pointed out. Fewer people know however that tiny atmospheric particles called ‘black carbon’ also contribute to the current warming. This post presents a paper my colleague and I recently published in nature communications. Our study sheds more light into the chemical make-up of black carbon, passing through the Arctic.

Black Carbon warms the climate

 Figure 1: Global radiative forcing of CO2 (green) compared to black carbon (blue). The colored bars show the mean change in radiative forcing due to the concentration of CO2 and BC in the atmosphere. The estimated range for the expected radiative forcing is everything between the white lines, which show the 90% confidence interval. (Data according to Boucher et al. 2013 (IPCC 5th AR) and Bond et al. 2013). [Credit: Patrik Winiger]

Figure 1: Global radiative forcing of CO2 (green) compared to black carbon (blue). The colored bars show the mean change in radiative forcing due to the concentration of CO2 and BC in the atmosphere. The estimated range for the expected radiative forcing is everything between the white lines, which show the 90% confidence interval. (Data according to Boucher et al. 2013 (IPCC 5th AR) and Bond et al. 2013). [Credit: Patrik Winiger]

Black Carbon (BC) originates from incomplete combustion caused by either natural (e.g., wild fires) or human (e.g., diesel car emissions) activities. As the name suggests, BC is a dark particle which absorbs sunlight very efficiently. In scientific terms we call this a strong positive radiative forcing, which means that the presence of BC in the atmosphere is helping to heat the planet. Some estimates put its radiative forcing in second place, only after CO2 (Figure 1). The significant thing about BC is that it has a short atmospheric lifetime (days to weeks), meaning we could quickly avoid some climate warming by getting rid of its emissions. Currently global emissions are increasing year by year and on snow and ice, the dark particles have a longer lasting effect due to the freeze and thaw cycle, where BC can re-surface, before it is washed away. It is important however to note, that our main focus on emission reduction should target (fossil-fuel) CO2 emissions, because they will affect the climate long after (several centuries) they have been emitted.

Arctic amplification: strongest warming in the North Pole

The Arctic is warming faster than the rest of our planet. Back in 1896, the Swede Arrhenius, (better known for his works: in chemistry), calculated, that a change in atmospheric CO2 – which at that time was a good 100 ppm lower than today – would change the temperature at higher latitudes (towards the poles) more than at lower latitudes.

Figure 2: Observation based global surface temperature anomalies for Jan-Mar (2016) in °C with respect to a 1961-1990 base year. Credit: GISTEMP Team, 2016: GISS Surface Temperature Analysis (GISTEMP). NASA Goddard Institute for Space Studies. Dataset accessed 2016-10-15 at [Hansen et al., 2010].

Figure 2: Surface temperature anomalies (in °C) for Jan-Mar (2016) with respect to a 1961-1990 baseline. [ Credit: NASA — GISTEMP (accessed 2016-10-15) and Hansen et al., 2010].

The problem with his calculations – as accurate and impressive they might have been – was, that he ignored the earth’s geography and seemed unaware of the big heat capacity of the oceans. On the southern half of our planet there is a lot more water, which can take up more heat, as compared to the northern half with more land surface. Thus, in reality the latitudes on the southern hemisphere have not heated as much as their northern counterparts and this effect came to be known as Arctic amplification.

Dark particles on bright snow and ice

Figure 3: Welcome to the Greenland Ice Sheet everybody. Probably an extreme case of ice covered in cryoconite, captured in August 2014 [Credit: Jason Box, (LINK:].

Figure 3: Ice covered in cryoconite, Greenland Ice Sheet, in August 2014 [Credit: Jason Box — Dark Snow project].

Greenhouse gases and BC are not the only reasons for the increase in temperature change and earlier onset of the melting season in the Arctic. Besides BC, there are other ‘light absorbing impurities’ such as dust, microorganisms, or a mixture of all of the above, better known as cryoconite. They all absorb solar radiation and thus decrease the albedo – the amount of solar energy reflected back to space – of the underlying white surface. This starts a vicious cycle by which these impurities melt the snow or ice and eventually uncover the usually much darker surface (e.g., rock or open sea water), leading to more solar absorption and the cycle continues. The effect and composition of these impurities are currently intensively studied on the Greenland ice sheet (check out the Black and Bloom, as well as the Dark Snow projects).

 Black Carbon effect on climate is highly uncertain

One of the reasons for the high uncertainty of BC’s climate effects is the big range in effects it has (see white line on Figure 1), when it interacts with snow and ice (or clouds and the atmosphere).

Another source of uncertainty is probably the big estimated range in the global, and especially in the regional emissions of BC in the Arctic. For example, the emission inventory we work with (ECLIPSE), is based on international and national statistics that indicate how much of a certain fuel (diesel, coal, gas, wood, etc.) is used, and in which way it is used (vehicle sizes, machine type and age, operating conditions, etc.). These numbers can vary a lot. If we, for example, line up different emission inventories of man-made emissions (Figure 4), by comparing the two different fractions of BC (fossil fuels vs. biomass burning) at different latitudes, then we see that the closer we get to the North pole, the more these emission inventories disagree. And this is still ignoring atmospheric transport or emissions of natural sources, such as wildfires.

Computer models, necessary to calculate global climate change, are partly based on input from these emission inventories. Models used for the calculation of the transport of these tiny particles have vastly improved in recent years, but still struggle at accurately mimicking the seasonality or extent of the observed BC concentrations. To some extent this is also due to the range of parametrization in the model, mainly the lifetime of BC, including its removal from the atmosphere by wet scavenging (e.g., rain). So to better understand black carbon effects on climate, more model calculations are necessary, for which the emission inventory estimates need to be verified by observations.

Figure 4: Fraction biomass burning of BC (fbb) at different latitudes North, estimated by three different emission inventories. The green line shows the GAINS emission inventory, which was the precursor to the ECLIPSE inventory (Klimont et al. 2016) [Credit: Patrik Winiger]

Figure 4: Fraction biomass burning of BC (fbb) at different latitudes North, from three different emission inventories. The green line shows the GAINS emission inventory, which was the precursor to the ECLIPSE inventory (Klimont et al. 2016) [Credit: Patrik Winiger]

How do we trace the origin of black carbon?

This is where the science of my colleagues and me comes in. By looking at BC’s isotopic ratio of stable-carbon (12C/13C) and its radiocarbon (14C) content we were able to deduce information about the combustion sources (Figure 5).

Plants (trees) take up contemporary radiocarbon, naturally present in the atmosphere, by photosynthesis of atmospheric CO2. All living organisms have thus more or less the same relative amount of radiocarbon atoms, we talk of a similar isotopic fingerprint. BC from biomass (wood) burning thereby has a contemporary radiocarbon fingerprint.

When they die, organisms stop incorporating contemporary carbon and the radiocarbon atoms are left to decay. Radiocarbon atoms have a relative short (at least on geological time-scales) half-life of 5730 years, which means that fossils and consequentially BC from fossil fuels are completely depleted of radiocarbon. This is how the measured radiocarbon content of a BC sample gives us information on the relative contributions of fossil fuels vs. biomass burning.

The stable carbon isotopic ratio gives information on the type of combustion sources (liquid fossil fuels, coal, gas flaring or biomass burning). Depending on how a certain material is formed (e.g., geological formation of coal), it has a specific isotopic ratio (of 12C/13C), like a fingerprint. Sometimes isotopic fingerprints can be altered during transport (because of chemical reactions or physical processes like condensation and evaporation). However, BC particles are very resistant to reactions and change only very little. Hence, we expect to see the same fingerprints at the observation site and at the source, only that the isotopic signal at the observation site will be a mixture of different source fingerprints.

Figure 5/ Carbon isotopic signatures of different BC sources, summarized by E.N. Kirillova (2013).

Figure 5: Carbon isotopic signatures of different BC sources, summarized by E.N. Kirillova (2013). To give information about the isotopic fingerprint, the delta-notation is used (small delta for 12C/13C, and big delta for 12C/14C). The isotopic values show how much a certain sample is different, on a per mil scale, from an international agreed isotopic standard value (or ratio) for carbon isotopes. [Credit: fig 1 from  Kirillova (2013)]

Where does the black carbon in European Arctic come from?

In our study (Winiger et al, 2016), we observed the concentrations and isotopic sources of tiny particles in airborne BC for over a year, in the European Arctic (Abisko, Sweden), and eventually compared these observations to model results, using the freely available atmospheric transport model FLEXPART and emission inventories for natural and man-made BC emissions.

Seeing our results we were first of all surprised at how well the model agreed with our observations. We saw a clear seasonality of the BC concentrations, like it has been reported in the literature before, and the model was able to reproduce this. Elevated concentrations were found in the winter, which is sometimes referred to as Arctic haze. The combustion sources showed a strong seasonality as well. The radiocarbon data showed, that fossil fuel combustion dominated in the winter and (wood) biomass burning during the low BC-burden periods in the summer. With a combination of the stable isotope fingerprints and Bayesian statistics we further concluded, that the major fossil fuel emissions came from liquid fossil fuels (most likely diesel). The model predicted a vast majority of all these BC emissions to be of European origin. Hence, we concluded, that the European emissions in the model had to be well constrained and the model parametrization of BC lifetime and wet-scavenging had to be fairly accurate for the observed region and period. Our hope is now that our work will be implemented in future models of BC effects and taken into account for future BC mitigation scenarios.

Figure 6: This is an example from the model calculations, showing where the (man-made) BC came from in January 2012. Abisko's position is marked as a blue star. The darker (red) spots show sources of higher BC contribution. This winter example was among the three highest observed (in terms of BC concentration) and the sources were ~50% wood burning, ~20% liquid fossil fuels (diesel) and ~30% coal. Some of the darkest spots can clearly be attributed to European cities.

Figure 6: Example from the model calculations, showing where the (man-made) BC came from in January 2012. Abisko’s position is marked as a blue star. The darker (red) spots show sources of higher BC contribution. This winter example was among the three highest observed (in terms of BC concentration) and the sources were ~50% wood burning, ~20% liquid fossil fuels (diesel) and ~30% coal. Some of the darkest spots can clearly be attributed to European cities. [Credit: fig4b from Winiger et al (2016)]


  • Anderson, T. R., E. Hawkins, and P. D. Jones (2016), CO2, the greenhouse effect and global warming: from the pioneering work of Arrhenius and Callendar to today’s Earth System Models, Endeavour, in press, doi:10.1016/j.endeavour.2016.07.002.
  • Arrhenius, S. (1896), On the influence of carbonic acid in the air upon the temperature of the ground., Philos. Mag. J. Sci., 41(August), 239–276, doi:10.1080/14786449608620846.
  • Hansen, J., R. Ruedy, M. Sato, and K. Lo (2010), Global surface temperature change, Rev. Geophys., 48(4), RG4004, doi:10.1029/2010RG000345.
  • Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-880, in review, 2016.
  • Kirillova, Elena N. “Dual isotope (13C-14C) Studies of Water-Soluble Organic Carbon (WSOC) Aerosols in South and East Asia.” (2013). ISBN 978-91-7447-696-5 pp. 1-37
  • Winiger, P., Andersson, A., Eckhardt, S., Stohl, A., & Gustafsson, Ö. (2016). The sources of atmospheric black carbon at a European gateway to the Arctic. Nature Communications, 7.

Edited by Sophie Berger, Dasaraden Mauree and  Emma Smith
This is joint post with the Atmospheric Division , given the interdisciplinarity of the topic featured.

portraitPatrik Winiger is a PhD student at the Department of Environmental Science and Analytical Chemistry and the Bolin Centre for Climate Research, at Stockholm University. His research interest focuses on impact and mitigation of Short Lived Climate Pollutants and anthropogenic CO2 emissions. Currently he investigates the sources of black carbon aerosols in the Arctic. He tweets as @PatrikWiniger



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