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Cryospheric Sciences

Regular Author

Image of the Week – ROVing in the deep…

Aggregates of sea ice algae seen from the ocean below by the ROV [Credit: Katlein et al. (2017)].

Robotics has revolutionised ocean observation, allowing for regular high resolution measurements even in remote locations or harsh conditions. But the ice-covered regions remain undersampled, especially the ice-ocean interface, as it is still too risky and complex to pilot instruments in this area. This is why it is exactly the area of interest of the paper from which our Image of the week is taken from!


This is sea ice… seen from the ocean

Traditionally, only divers (and maybe seals, fish, krill, belugas, etc.) have been able to see what is happening just under the sea ice, in the ocean. That is no routine activity – I personally have not been in a fieldwork campaign involving a diver. It is extremely dangerous to dive in such cold waters, and the diver is limited to a small area around the entry hole, which might refreeze really fast. The most common method is to drill small holes from the top of the sea ice to the ice-ocean interface at specific locations instead, and collect the bottom of the resulting ice core. There are obvious problems with this method:

  • drilling takes a lot of time and effort;
  • you cannot drill everywhere, since it becomes unsafe if the ice is too thin (you still have to be standing on the ice to do the drilling);
  • the location of your core has to be representative of what you are sampling.

This is why researchers are trying to more often use sea robots, which can take measurements over a large area while the researchers are safe somewhere else. But most robots that are now used to monitor the ocean are not adapted to ice-covered regions, and the few that are require a lot of specifically trained technicians to operate them and/or can only perform very specific tasks.

Our Image of the Week was taken by a new robot, “The Beast”, whose specificities are described in the recently published Katlein et al. (2017). In brief, it is ice-resistant, small, very manoeuvrable, can be operated by only one or two people from a cosy hut on the ice, and contains any possible sensor you can think of (even a small water bottle for sampling, and a net). It belongs to the family of Remotely Operated Vehicles (ROV), which means that it is connected to the operator by a cable – if anything goes wrong under the ice, just pull on the leash!

And thanks to ROVs, we can see (e.g. on this Image of the Week) that the thickness of the sea ice, hence the amount of light that goes through it and the whole sympagic communities vary a lot over small regions.

What the pilot sees when driving the ROV by a sea ice pressure ridge [Credit: Katlein et al. (2017)].

Why do we need such observations?

  1. Robustness: it will not totally replace the traditional ice coring, for some studies still need to get the actual ice. But it will ensure that the choice of locations make sense, or help extrapolate the localised coring results to a larger region.
  2. Validation: for basin-wide studies, we need satellites. But satellite retrievals, especially those for sea ice thickness, still need in-situ measurements for validation. ROVs can provide more validation points than traditional point-coring for the same mission duration, hence ultimately improving algorithms.
  3. Seeing is believing: for anything from outreach to future fieldwork preparation, videos captured by an ROV are an unvaluable tool. Ecologists can even see which species live there (or discover new ones).

 

Further reading

Edited by Clara Burgard

Image of the week – Micro-organisms on Ice!

Image of the week – Micro-organisms on Ice!

The cold icy surface of a glacier doesn’t seem like an environment where life should exist, but if you look closely you may be surprised! Glaciers are not only locations studied by glaciologists and physical scientists, but are also of great interest to microbiologists and ecologists. In fact, understanding the interaction between ice and microbiology is essential to fully understand the glacier system!


Why study micro-organisms on glaciers?

Micro-plants, micro-animals and bacteria live and reproduce in cryoconite ecosystems on the surface of glaciers. Cryoconite is a dark coloured material (Fig. 2) found at the bottom of cylindrical water-filled melt holes (cryoconite holes) on a glacier surface; it consists of dust and mineral powders transported by the wind, and micro-organisms. Cryoconite holes are formed as the dark coloured material causes localised melting, due to reduced albedo (ability of a surface to reflect solar energy).

Figure 2: Example of a Cryoconite hole filled with dark cryoconite material (markers are 10×10 cm) [Credit: Tommaso Santagata – La Venta Esplorazioni Geografiche]

Because organisms in cryoconite thrive in extreme conditions, they are very unique and interesting to study. Information about their genetic makeup and chemical structure can help to inform, for example, medical and pharmaceutical sciences. Currently, however, information on their community structure is still limited.

Cryoconite ecosystems are very isolated and must work together to survive and thrive. Some micro-organisms (e.g. micro-algae) can photosynthesise and are able to live autonomously inside cryoconite holes using atmospheric carbon dioxide, sunlight, water and chlorophyll. By this same mechanism, they can find all the molecules essential for their vital and structural needs and consequently they generate most of the molecules necessary for all other living things. For example, the waste product of photosynthesis, oxygen, is essential for the survival of all organisms living in aerobiosis in these communities. Due to their key role in the ecosystem, the micro-algae are known as “primary producers”.

As around 70% of the earth is covered in water, which is colonised by micro-algae, studying the way they survive in extreme conditions and how they contribute to the ecosystem is of global importance – especially at this time of climate change.

The diversity of highly active bacterial communities in cryoconite holes makes them the most biologically active habitats within glacial ecosystems.

Data collections – Six days on THE glacier

The Perito Moreno glacier (Fig. 3) is known as one of the most important tourist attraction in Argentinian Patagonia (see our previous IOW post). Each day, hundreds of people observe the impressive front of this glacier and wait to see ice detachments and hear the loud sound of it’s impacts in the water of Lake Argentino. The glacier takes it’s name from the explorer Francisco Moreno, who studied the Patagonian region in the 19th century. The glacier is more than 30 km in length and an area of about 250 km2, Perito Moreno is one of the main outlet glaciers of Hielo Patagonico Sur (southern Patagonia icefield).

Figure 3: Aerial view of the Perito Moreno
[Credit : Tommaso Santagata – La Venta Esplorazioni Geografiche]

In April 2017, after several missions to the Greenland Ice Sheet to study extremophilic micro-organisms (organism that thrive in extreme environments) of ice, a team of Italian and French scientists organised a scientific expedition to study the microbiology of Perito Moreno. The expedition was organised by La Venta and Spélé’Ice and included researchers from several French and Italian Universities (see below for full list)

Perito Moreno is very well known, especially to the La Venta team, who have been organising scientific expeditions in Patagonia since 1991. The microbiological research objectives of this mission were to study the micro-organisms that live on the surface of Perito Moreno and compare them to results obtained in the other polar, sub-polar and alpine regions. The multi-disciplinary research team were able to set up a complex field laboratory, which included a microscope and an innovative small tool size capable of DNA sequencing. This meant that samples could be analysed immediately after their extraction from the ice (Fig. 1).

Getting all the equipment and personnel to achieve this expedition onto the ice was not an easy task. The team and their equipment were transported by boat to a site near the front of the glacier. Equipment then needed to be transported to the Buscaini Refugee, a shelter used as a base-camp by the team (Fig. 4). This took two trips, on foot, of about 7 hours (12 km of trail along the lateral moraine and the ice of the glacier with very heavy backpacks) – not an easy start! Luckily this hardship was somewhat mitigated by the absence of extreme cold, in fact, abnormally hot weather tallowed the team to move and work in t-shirts – not bad!

Figure 4: Walking into the field site along the ice of Perito Moreno – part of the 12km of trail to the Buscaini Refugee shelter
[Credit: Alessio Romeo – La Venta Esplorazioni Geografiche]

Thanks to these favourable weather conditions, all the goals were achieved in the short amount of time the team were allowed to camp on the glacier (special permission is needed from the national park to do this). During the five days of activity, many samples were taken and sequenced directly at the camp by the researches. Other important goals, such as morphological comparisons and measurements of the velocity of the glacier through the use of GPS, laser scanning and unmanned aerial vehicles were achieved by another team of researchers (stay tuned for another blog post about this!).

Universities and research institutes involved: University Bicocca of Milan – Italy, University of Milano – Italy, Sciences of the Earth A.Desio – Italy, Natural History Museum of Paris – France, University Diderot of Paris – France, University of Florence – Sciences of the Earth – Italy, University of Bologna – Italy.

Further Reading

Edited by Emma Smith


Tommaso 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

Image of the Week – A new way to compute ice dynamic changes

Fig. 1: Map of ice velocity from the NASA MEaSUREs Program showing the region of Enderby Land in East Antarctica [Credit: Fig. 1 from Kallenberg et al. (2017) ].

Up to now, ice sheet mass changes due to ice dynamics have been computed from satellite observations that suffer from sparse coverage in time and space. A new method allows us to compute these changes on much wider temporal and spatial scales. But how does this method work? Let us discover the different steps by having a look at Enderby Land in East Antarctica, for which ice velocities are shown in our Image of the Week…


Mass balance of ice sheets

The mass balance of an ice sheet is the difference between the mass gain of ice, primarily through snowfall, and the mass loss of ice, primarily via meltwater runoff and ice dynamic processes (e.g. iceberg calving, melting below ice shelves). When the mass gain is equal to the mass loss, the ice sheet is in balance. However, if one exceeds the other, the ice sheet either gains or loses mass.

Measuring mass balance changes of ice sheets is crucial due to their potential contribution to sea level rise (see previous post). You can have a look at this nice review for further details about the recent changes in the mass balance of the two biggest ice sheets on Earth, i.e. Antarctica and Greenland.

Ice mass changes from snowfall and meltwater runoff (what we call ‘surface mass balance’ changes) are reasonably well simulated by regional climate models, which give good agreement with observations (see this study for Antarctica and this one for Greenland). Mass changes from ice dynamics are more complex to obtain. They are commonly estimated by combining ice velocity and ice thickness. Ice velocity is measured via satellite radar interferometry, while ice thickness is obtained thanks to airborne radar. Unfortunately, these measurements have sparse temporal and spatial coverage, especially in Antarctica, which makes the computation of mass changes from ice dynamics challenging.

A new method to estimate ice dynamic changes

Kallenberg et al. (2017) conducted a study focussing on Enderby Land in East Antarctica (see our Image of the Week) in which they use a novel approach to estimate ice dynamic changes. This region of Antarctica has experienced a slightly positive mass balance in past years, meaning that the ice sheet has slightly thickened in this region.

Kallenberg et al. (2017) first used satellite observations to compute the total changes in ice sheet mass. They took advantage of two high-technology datasets. The first one, “Gravity Recovery And Climate Experiment” (GRACE), measures changes in the Earth’s gravity field, from which ice mass changes can be derived. A summary explaining how GRACE works can be found in this previous post. The second satellite dataset, “Ice, Cloud, and land Elevation Satellite” (ICESat), measures changes in ice surface elevation, from which changes in ice mass can be computed by using ice density.

However, Kallenberg et al. (2017) were not interested in the total ice mass changes, as obtained from GRACE and ICESat satellites, but rather in ice dynamic changes. They subtracted two quantities from the total mass changes in order to obtain the remaining dynamic changes:

  1. Surface mass balance changes: changes from processes happening at the surface of the ice sheet (e.g. snow accumulation, meltwater runoff). These changes were obtained from model simulations using the Regional Atmospheric Climate Model (RACMO2), for which details can be found in this previous post.
  2. Glacial Isostatic Adjustment: changes in land topography due to ice loading and unloading. These changes were computed from Glacial Isostatic Adjustment models.

What does this study tell us?

The results of this study show that it is possible to compute changes in ice mass resulting from ice dynamics with higher spatial and temporal coverage than before, using a combination of satellite observations and models.

Also, the use of two different satellite datasets (GRACE and ICESat) shows that they agree quite well with each other in the region of Enderby Land (see Fig. 2). This means that using one or the other dataset does not make a big difference.

Finally, this new method also shows that differences between GRACE and ICESat reduce when using the newer version of RACMO2 for computing surface mass balance changes. This tells us that comparing results of ice dynamics from both satellites with different models is a good way to identify which models correctly simulate surface processes and which models do not.

Fig. 2: Ice dynamic changes (dH/dt, where H is ice thickness and t is time) computed from (a) GRACE and (b) ICESat and expressed in meters per year [Credit: Fig. 5 from Kallenberg et al. (2017) ].

Further reading

Edited by Clara Burgard and Emma Smith


David 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.

Image of the Week – The birth of a sea-ice dragon!

Image of the Week – The birth of a sea-ice dragon!

Dragon-skin ice may sound like the name of an episode of the Game of Thrones fantasy franchise. However, this fantasy name hides a rare and bizarre type of ice formation that you can see in our Image of the Week. It has been recently observed by the “Polynyas, ice production and seasonal evolution in the Ross Sea” (PIPERS) research team in Antarctica. This bizarre phenomenon caused by strong wind conditions has not been observed in Antarctica since 2007.


PIPERS expedition observed dragon-skin ice

In early April, the Nathan B Palmer icebreaker (see Fig. 2) began its 65-day voyage to Antarctica to study sea ice in the Ross Sea during the autumn period. This expedition, named PIPERS, was carried out by a team of 26 scientists from 9 countries. Its goal was to investigate polynyas, ice production, and seasonal evolution with a particular focus on the Terra Nova Bay and Ross Sea Polynyas (see Fig. 3).

Fig.2 : The Nathan B Palmer icebreaker caught in sea ice [Credit: IMAS ].

A polynya is an area of open water or thin sea ice surrounded by thicker sea ice and is generally located in coastal areas [Stringer and Groves, 1991]. Ice formation in polynyas is strongly influenced by wind conditions whose action can lead to astonishing spatial patterns in sea ice appearance. Special wind conditions probably also lead to what the members of the PIPERS expedition had the opportunity to observe: ice patterns that resemble dragon scales, therefore called dragon-skin ice. Such a sighting is quite remarkable as the last one dates back from a decade. However, the sparsity of observations of dragon-skin ice phenomena is probably a consequence of the relatively small number of expeditions in Antarctica during the autumn and winter seasons…

Fig. 3: The Terra Nova Bay Polynya and Ross Sea Polynya explored by the PIPERS expedition. [Credit: PIPERS ].

Chaotic ice formation caused by strong winds

Dragon-skin ice is a chaotic result of the complex interplay between the ocean and the atmosphere. Coastal polynyas in Antarctica are kept open by the action of strong and cold offshore winds (see Fig. 4) known as katabatic winds, which blow downwards as fast as 100 km/h for several hours [McKnight and Hess, 2000]. Sea ice forming at the cold sea surface gets blown away by these strong winds, preventing a closed sea-ice cover in this area. As the ice is blown away, an area of open water gets in direct contact with the atmosphere, leading to strong cooling and new formation of ice, that gets blown away again, and so on… Therefore, in general, sea ice in polynyas consists of thin pancake ice (see Fig. 5) i.e. round pieces of ice from 0.3 to 3 meters in diameter, which results from the aggregation of ice crystals caused by the wave action. Due to the wind action, the pieces of ice are pushed out by the wind action to the edges of the polynya.  As these pieces push strongly against each other, dragon-like scales appear on sea ice giving birth to the so-called dragon-skin ice.

Fig.4: Formation of coastal polynyas due to the action of katabatic winds [Credit: Wikimedia Commons ].

Figure 5: Sea ice in polynyas takes the form of pancake ice due to the action of water waves [Credit: PIPERS ].

The importance of polynyas for ocean-atmosphere interactions

Besides providing us with dazzling pictures of the cryosphere, investigating sea-ice production and evolution in polynyas is essential to better understand the complex interactions between the ocean and the atmosphere.
As sea water freezes into sea ice, salt is expelled into the ocean, raising its local salinity. The incessant production of sea ice in polynyas leads to water masses with very high salinity inside the polynyas. As sea water cools down, it releases energy in the atmosphere, leading to a warming of the atmosphere in polar regions. Moreover, due to their high density, these masses of cold and salty water sink and mix with lower ocean layers.
First results from the PIPERS mission show that when sea ice is forming, polynyas release greenhouse gases to atmosphere, instead of capturing it, as it was previously assumed! But fully understanding what’s happening there will necessitate more time and analyses….

Further reading

 

Edited by Scott Watson and Clara Burgard
Modified by Sophie Berger on 3 July 2017 to account for remarks of Célia Sapart (Member of the PIPER expedition)


Kevin Bulthuis is a F.R.S.-FNRS Research Fellow at the Université de Liège and the Université Libre de Bruxelles. He investigates the influence of uncertainties and instabilities in ice-sheet models as a limitation for accurate predictions of future sea-level rise. Contact Email:kevin.bulthuis@ulg.ac.be.

Image of the Week – Ice lollies falling from the sky

Lolly in the sky. [Credit: Darwin Bell via flickr]

You have more than probably eaten many lollipops as a kid (and you might still enjoy them). The good thing is that you do not necessarily need to go to the candy shop to get them but you can simply wait for them to fall from the sky and eat them for free. Disclaimer: this kind of lollies might be slightly different from what you expect…


Are lollies really falling from the sky?

Eight years ago (in January 2009), a low-pressure weather system coming from the North Atlantic Ocean reached the UK and brought several rain events to the country. Nothing is really special about this phenomenon in Western Europe in the winter. However, a research flight started sampling the clouds in the warm front (transition zone where warm air replaces cold air) ahead of the low-pressure system and discovered hydrometeors (precipitation products, such as rain and snow) of an unusual kind. Researchers named them ‘ice lollies’ due to their characteristic shape and maybe due to their gluttony. The microphysical probes onboard the aircraft, combined with a radar system located in Southern England, allowed them to measure a wide range of hydrometeors, including these ice lollies that were observed for the first time with such concentration levels.

How do ice lollies form?

A recent study (Keppas et al, 2017) explains that ice lollies form when water droplets (size of 0.1 to 0.7 mm) collide with ice crystals with the form of a column (size of 0.25 to 1.4 mm) and freeze on top of them (see Fig. 2).

Fig 2: Formation of an ice lolly: water droplet (the circle) collides with an ice crystal (the column) [Credit: Fig. 1a from Keppas et al., (2017)].

Such ice lollies form in ‘mixed-phase clouds’, i.e. clouds made of water droplets and ice crystals and whose temperature is below the freezing point (0°C). At these temperatures, water droplets can be supercooled, meaning that they stay liquid below the freezing point.

Figure 3 below shows the processes and particles involved in the formation of ice lollies. Ice lollies are mainly found at temperatures between 0 and -6°C, in the vicinity of the warm conveyor belt, which represents the main source of warm moist air that feeds the low-pressure system. This warm conveyor belt brings water vapour that participates in the formation and growth of supercooled water droplets. Ice crystals formed near the cloud tops fall through the warm conveyor belt and collide with the water droplets to form ice lollies.

Fig 3: Processes involved with the formation of ice lollies, which mainly form under the warm conveyor belt [Credit: Fig 4 from Keppas et al., (2017)].

Are these ice lollies important?

Ice lollies were observed more recently (September 2016) during another aircraft mission over the northeast Atlantic Ocean but no radar coverage supported the observations. At the moment of writing this article, the lack of observations prevent us from determining the importance of these ice lollies in the climate system. However, future missions would provide more insight. In the meantime, we suggest you to enjoy a lollipop such as the one shown in the image of this week 🙂

This is a joint post, published together with the atmospheric division blog, given the interdisciplinarity of the topic.

Edited by Sophie Berger and Dasaraden Mauree

Reference/Further reading

Keppas, S. Ch., J. Crosier, T. W. Choularton, and K. N. Bower (2017), Ice lollies: An ice particle generated in supercooled conveyor belts, Geophys. Res. Lett., 44, doi:10.1002/2017GL073441

 


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.

Image of the Week – Ice Ice Bergy

Image of the Week – Ice Ice Bergy

They come in all shapes, sizes and textures. They can be white, deep blue or brownish. Sometimes they even have penguins on them. It is time to (briefly) introduce this element of the cryosphere that has not been given much attention in this blog yet: icebergs!


What is an iceberg?

Let’s start with the basics. An iceberg, which literally translates as “ice mountain”, is a bit of fresh ice that broke off a glacier, an ice shelf, or a larger iceberg, and that is now freely drifting in the ocean. As an approximation, you can consider that since an iceberg is already in the water (about 90% under water even), its melting does not contribute to sea-level rise. However, if you remember our Sea Level “For Dummies” post, you know that the melting of fresh ice reduces the ocean’s density and makes it expand. Icebergs are found at both poles, although they tend to be larger in the Southern Ocean. The largest iceberg ever spotted there was 335 by 97 km, which represents an area larger than Belgium !

Modelled trajectories of icebergs around Antarctica. The different colours represent different size classes, ranging from 0-1 km² (class 1) to 100-1000 km² (class 5). [Credit: subset of Fig 2 from Rackow et al (2017)]

Icebergs can drift over thousands of kilometres (Rackow et al., 2017), during several years. A more thorough account of the life of an iceberg will be given in a future post, but be aware that among other things, as it drifts:

  • The iceberg is eroded by the waves and melted by the relatively warm ocean;
  • It can split in several pieces because of this melting and mechanical stress;
  • Sea ice can freeze around it, trapping it in the pack ice.

This means that the iceberg changes shape a lot, and can be tricky to monitor (Mazur et al, 2017).

Why do we want to monitor icebergs?

You may have heard of the Titanic, and hence are aware that icebergs pose a risk for navigation not only in the polar regions but even in the North Atlantic. Icebergs also are large reservoirs of freshwater, and depending on how and where they melt, this inflow of melted freshwater can really affect the ocean; it even dominates the freshwater budget in some Greenland fjords (Enderlin et al., 2016).

Icebergs have traditionally been rather understudied, so we are only now discovering how important they are and how they interact with the rest of the climate system: increasing sea ice production (A. Mazur, PhD thesis, 2017), biological activity (Vernet et al., 2012), and even carbon storage (Smith et al., 2011). And sometimes, they have penguins on them!

All eyes in the CryoTeam are now turned to the Antarctic Peninsula, where a giant iceberg may detach from the Larsen C ice shelf soon. To learn how we know that, check this video made by ESA. And of course, continue reading us – we’ll be reporting about the birth of this monster berg!

An iceberg by Antarctica [Credit: C. Heuzé]

Edited by Sophie Berger

Further reading

  • Enderlin et al. (2012), Iceberg meltwater fluxes dominate the freshwater budget in Greenland’s iceberg-congested glacial fjords, Geophysical Research Letters, doi:10.1002/2016GL070718

  • Mazur et al. (2017), An object-based SAR image iceberg detection algorithm applied to the Amundsen Sea, Remote Sensing of Environment, doi:10.1016/j.rse.2016.11.013

  • Rackow et al. (2017), A simulation of small to giant Antarctic iceberg evolution: Differential impact on climatology estimates, Journal of Geophysical Research: Oceans, doi: 10.1002/2016JC012513
  • Smith et al. (2011), Carbon export associated with free-drifting icebergs in the Southern Ocean, Deep Sea Research, doi: 10.1016/j.dsr2.2010.11.027
  • Vernet et al. (2012), Islands of Ice: Influence of Free-Drifting Antarctic Icebergs on Pelagic Marine Ecosystems, Oceanography, doi:10.5670/oceanog.2012.72

Image of the Week – Antarctica’s Flowing Ice, Year by Year

Fig 1: Map series of annual ice sheet speed from Mouginot et al. (2017). Speeds range from 0 (purple) to 1000+ (dark brown) m/yr. [Credit: George Roth]

Today’s Image of the Week shows annual ice flow velocity mosaics at 1km resolution from 2005 to 2016 for the Antarctic ice sheet. These mosaics, along with similar data for Greenland (see Fig.2), were published by Mouginot et al, (2017) last month as part of NASA’s MEaSUREs (Making Earth System Data Records for Use in Research Environments) program.


How were these images constructed?

The mosaics shown today (Fig 1 and 2) were built by combining optical imagery from the Landsat-8 satellite with radar (SAR) data from the Sentinel-1a/b, RADARSAT-2, ALOS PALSAR, ENVISAT ASAR, RADARSAT-1, TerraSAR-X, and TanDEM-X sensors.

Although the authors used the well-known techniques of feature and speckle tracking to produce their velocities from optical and radar images, respectively, the major novelty of their study lies in the automation and integration of the different datasets.

Fig.2: Mosaics of yearly velocity maps of the Greenland and Antarctic ice sheet for the period 2015-2016.Composite of satellite-derived yearly ice sheet speeds from 2005-2016 for both Greenland and Antarctica. [Credit: cover figure from Mouginot et al. (2017)]

How is this new dataset useful?

Previously, ice sheet modellers have used mosaics composed of satellite data from multiple years to cover the entire ice sheet. However, this new dataset is one of the first to provide an ice-sheet-wide geographic scale, a yearly temporal resolution, and a moderately high spatial resolution (1km). This means that modellers can now better examine how large parts of the Greenland and Antarctic ice sheets evolve over time. By linking the evolution of the ice sheets to the changes in weather and climate over those ice sheets during specific years, modellers can calibrate the response of those ice sheets’ outlet glaciers to different climate conditions. The changes in the speeds of these outlet glaciers have important consequences for the amount of sea level rise expected for a given amount of warming.

How can I start using this data?

The yearly MEaSUREs data is hosted at the NSIDC in NetCDF format. The maps shown in the animated image were made using Quantarctica/QGIS (for more information on Quantarctica, check out our previous post E). QGIS natively supports NetCDF files like these mosaics with no additional import steps. Users can quickly calculate new grids showing speed, changes in velocities between years, and more by using the QGIS Raster Calculator or gdal_calc.

References/ Further Reading

Mouginot, J., Rignot, E., Scheuchl, B., & Millan, R. (2017). Comprehensive Annual Ice Sheet Velocity Mapping Using Landsat-8, Sentinel-1, and RADARSAT-2 Data. Remote Sensing, 9(4), 364. http://dx.doi.org/10.3390/rs9040364

Image of the Week – Quantarctica: Mapping Antarctica has never been so easy!

Image of the Week – A high-resolution picture of Greenland’s surface mass balance

Written with help from Jelte van Oostsveen
Edited by Clara Burgard and Sophie Berger


George Roth is the Quantarctica Project Coordinator in the Glaciology group (@NPIglaciology) at the Norwegian Polar Institute. He has spent the last several years helping researchers with GIS, cartography, and remote sensing in both the Arctic and Antarctic.

Image of the Week – The ups and downs of sea ice!

Image of the Week – The ups and downs of sea ice!

The reduction in Arctic sea-ice cover has been in the news a lot recently (e.g. here) – as record lows have been observed again and again within the last decade. However, it is also a topic which causes a lot of confusion as so many factors come into play. With this Image of the Week we will give you a brief overview of the ups and downs of sea ice!


In general, Arctic sea ice is at its minimum extent at the end of the summer (September), and its maximum extent at the end of the winter (March). Our Image of the Week (Fig. 1) shows the summer and winter sea ice cover over the last year. In September 2016, the Arctic sea-ice minimum covered the second smallest extent since the beginning of satellite observations (38 years). Only 4.14 million square kilometres of the Northern Hemisphere were covered by sea ice on the day of minimum extent (September 10th). The maximum sea-ice extent was observed on March 7th 2017, only 14.42 million square kilometres of sea ice were observed: the lowest maximum since the beginning of satellite observations.

How long do we have until Arctic summer sea-ice cover is completely gone?

The Arctic Ocean is defined as ice-free, when the sea-ice area does not exceed 1 million km². Due to the close relationship between CO2 emissions and the sea-ice area (see one of our previous posts), it is likely that the summer Arctic sea-ice cover will fall below this threshold during the 21st century. Under the highest emission scenario (RCP 8.5 – IPCC, 2015), an almost ice-free Arctic in September is likely to occur before the middle of the century. It is, however, not easy to predict the exact year of an ice-free Arctic summer as the extent of the ice cover depends on many parameters influencing the freezing and melting of the ice.

On one hand, some parameters and their effect on the sea-ice cover are well understood and their future evolution can be projected quite well through climate models. For example, changes in the sea surface temperature tend to affect the starting date of the freezing period while changes in air temperature tend to affect the starting date of the melting period. As both air temperature and sea surface temperature are projected to increase in the long term, due to climate change, the period where ice can be present will be reduced more and more.

On the other hand, some parameters lead to several concurring effects, which are difficult to separate clearly and not always fully understood. Therefore, their future evolution and influence on sea ice is not totally clear. For example, the sea-ice loss leads to more open ocean areas, which absorb solar radiation, causing warming and therefore leading to faster sea-ice melting – a mechanism called “sea-ice albedo feedback”. At the same time, more open ocean areas also lead to more evaporation and therefore more clouds, which shield the ice from solar radiation and therefore lead to less warming of the ice and ocean surfaces.

Still, even if we knew the effect and long-term evolution of all these parameters, the exact date of ice-free Arctic could not be defined easily in advance. Why? The chaotic nature of the atmosphere leads to very short-term effects that influence the ice cover as well…

Be careful! A record minimum does not always mean a record maximum (and vice versa)!

On shorter time scales, sudden changes in the atmospheric circulation can have a large impact on sea-ice extent. Therefore, it is not guaranteed that a year with a record low maximum will have a record low minimum and vice versa. For example, heat waves and warm air outbreaks or high winds due to the transport of low pressure systems into the Arctic can lead to a more rapid decline of the sea-ice cover. The other way round, if the atmosphere from lower latitudes does not disturb the Arctic region, the sea-ice cover can stabilise again.

What about this year (2016/2017 season)?

Sometimes, it is not clear why sea-ice retreats rapidly. For example, the low 2016 minimum came as a surprise as the cover started with a very low minimum but then did not melt as fast as in previous years, due to average or below average temperatures. Only shortly before the minimum extent, stormy conditions came into play and led to the low extent that was observed (see Fig. 2).

Figure 2: Comparison of Arctic sea-ice extent between different years for summer (left) and winter (right). [Credit: Image courtesy of the National Snow and Ice Data Center]

The reasons for the record low 2017 maximum are better understood. The Arctic Ocean was not covered by much ice to begin. Then, the autumn and winter in the Arctic were very warm with air temperatures from October 2016 to February 2017 being from 2.5 to up to 5 degrees in some regions higher than on average.

From the Arctic to the Antarctic

In the last decades, although it recovered in some years between the record lows, the Arctic sea-ice cover has overall been declining. This is not the case on the other side of the planet, in Antarctica. Note that Antarctica is a complete different setting than the Arctic Ocean. The former being a continent surrounded by ocean and sea ice, the latter being an ocean with sea ice surrounded by continents.

Figure 3: Comparison of Antarctic sea-ice extent between different years for summer (left) and winter (right). [Credit: Image courtesy of the National Snow and Ice Data Center]

In recent decades, Antarctic sea-ice has been increasing very slowly (see Fig.3). Scientists were puzzled as such an evolution was not expected in a global warming framework. Explanations for this behaviour are that this is likely due to changing wind and surface pressure patterns around Antarctica. Contrary to this trend, this year (2016/2017) was a record low maximum and minimum in Antarctic sea-ice cover. This change is puzzling scientists even more. It remains unclear up to now if this is a permanent shift in the tendency of Antarctic sea ice or if this a single event. Be sure that the next months will be full of papers trying to explain this change in behaviour, it is going to be exciting!

Further reading

Edited by Emma Smith

Image of the Week — The ice blue eye of the Arctic

Image of the Week — The ice blue eye of the Arctic

Positive feedback” is a term that regularly pops up when talking about climate change. It does not mean good news, but rather that climate change causes a phenomenon which it turns exacerbates climate change. The image of this week shows a beautiful melt pond in the Arctic sea ice, which is an example of such positive feedback.


What is a melt pond?

The Arctic sea ice is typically non-smooth, and covered in snow. When, after the long polar night, the sun shines again on the sea ice, a series of events happen (e.g. Fetterer and Untersteiner, 1998):

  • the snow layer melts;

  • the melted snow collects in depressions at the surface of the sea ice to form ponds;

  • these ponds of melted water are darker than the surrounding ice, i.e. they have a lower albedo. As a result they absorb more heat from the Sun, which melts more ice and deepens the pond. Melt ponds are typically 5 to 10 m wide and 15 to 50 cm deep (Perovich et al., 2009);

  • eventually, the water from the ponds ends up in the ocean: either by percolation through the whole sea-ice column or because the bottom of the pond reaches the ocean. Sometimes, it can also simply refreeze, as the air temperatures drop again (Polashenski et al., 2012).

Melt ponds cover 50-60% of the Arctic sea ice each summer (Eicken et al., 2004), and up to 90% of the first year ice (Perovich al., 2011). How do we know these percentages? Mostly, thanks to satellites.

Monitoring melt ponds by satellites

Like most phenomena that we discuss on this blog, continuous in-situ measurements are not feasible at the scale of the whole Arctic, so scientists rely on satellites instead. For melt ponds, spectro-radiometer data are used (Rösel et al., 2012). These measure the surface reflectance of the Earth i.e. the proportion of energy reflected by the surface for wavelengths in the visible and infrared (0.4 to 14.4 μm). The idea is that different types of surfaces reflect the sunlight differently, and we can use these data to then map the types of surfaces over a region.

In particular for the Arctic, sea ice, open ocean and any stage in-between all reflect the sunlight differently (i.e. have different albedos). The way that the albedo changes with the wavelength is also different for each surface, which is why radiometer measurements are taken for a range of wavelengths. With these measurements, not only can we locate the melt ponds in the Arctic, but even assess how mature the pond is (i.e. how long ago it formed) and how deep it extends. These values are key for climate change predictions.

Fig. 2: Melt pond seen by a camera below the sea ice. (The pond is the lighter area) [Credit: NOAA’s climate.gov]

Melt ponds and the climate

Let’s come back to the positive feedback mentioned in the introduction. Solar radiation and warm air temperature create melt ponds. The darker melt ponds have a higher albedo than the white sea ice, so they absorb more heat, and further warm our climate. This extra heat is also transferred to the ocean, so melt pond-covered sea ice melts three times more from below than bare ice (Flocco et al., 2012). This vicious circle heat – less sea ice – more heat absorbed – even less sea ice…, is called the ice-albedo feedback. It is one of the processes responsible for the polar amplification of global warming, i.e. the fact that poles warm way faster than the rest of the world (see also this post for more explanation).

The ice-albedo feedback is one of the processes responsible for the polar amplification of global warming

But it’s not all doom and gloom. For one thing, melt ponds are associated with algae bloom. The sun light can penetrate deeper through the ocean under a melt pond than under bare ice (see Fig. 2), which means that life can develop more easily. And now that we understand better how melt ponds form, and how much area they cover in the Arctic, efforts are being made to include more realistic sea-ice properties and pond parametrisation in climate models (e.g. Holland et al., 2012). That way, we can study more precisely their impact on future climate, and the demise of the Arctic sea ice.

Edited by Sophie Berger

Further reading

Image of the Week – On the tip of Petermann’s (ice) tongue

Image of the Week – On the tip of Petermann’s (ice) tongue

5th August 2015, 10:30 in the morning. The meeting had to be interrupted to take this picture. We were aboard the Swedish icebreaker Oden, and were now closer than anyone before to the terminus of Petermann Glacier in northwestern Greenland. But we had not travelled that far just for pictures…


Petermann’s ice tongue

Petermann is one of Greenland’s largest “marine terminating glaciers”. As the name indicates, this is a glacier, i.e. frozen freshwater, and its terminus floats on the ocean’s surface. Since Petermann is confined within a fjord, the glacier is long and narrow and can be referred to as an “ice tongue”.

Petermann Glacier is famous for its recent calving events. In August 2010, about a quarter of the ice tongue (260 km2) broke off as an iceberg (Fig. 2). In July 2012, Petermann calved again and its ice tongue lost an extra 130 km2.

These are not isolated events. Greenland’s marine terminating glaciers are all thinning and retreating in response to a warming of both air and ocean temperatures (Straneo et al., 2013), and Greenland’s entire ice sheet itself is threatened. Hence, international fieldwork expeditions are needed to understand the dynamics of these glaciers.

Fig. 2: The 2010 calving event of Petermann. Natural-color image from the Advanced Land Imager (ALI) on NASA’s Earth Observing-1 (EO-1) satellite ( August 16, 2010).  [Credit: NASA’s Earth Observatory]

The Petermann 2015 expedition

In summer 2015, a paleoceanography expedition was conducted to study Petermann Fjord and its surroundings, in order to assess how unusual these recent calving events are compared to the glacier’s past. Our small team focused on the present-day ocean, and specifically investigated how much of the glacier is melted from below by the comparatively warm ocean (that process has been described on this blog previously). In fact, this “basal melting” could be responsible for up to 80% of the mass loss of Petermann Glacier (Rignot, 1996). Additionally, we were also the first scientists to take measurements in this region since the calving events.

Our results are now published (Heuzé et al., 2017). We show that the meltwater can be detected and tracked by simply using the temperature and salinity measurements that are routinely taken during expeditions (that, also, has been described on this blog previously). Moreover, we found that the processes happening near the glacier are more complex than we expected and require measurements at a higher temporal resolution, daily to hourly and over several months, than the traditional summer single profiles. Luckily, this is why we deployed new sensors there! And since these have already sent their data, we should report on them soon!

Edited by David Rounce and Sophie Berger

References and further reading