Three satellite images of May Glacier: optical, infrared, and SAR (see text)
With over 198 000 glaciers in the world, you can always find a glacier that fits your mood or a given occasion. So why not for example celebrate the first Image of the Week of May with a picture of the aptly named May Glacier?
May Glacier is in fact not named after the month, but after Mr May, an officer onboard the Flying Fish during her expedition to the East Antarctic coast in the 1840s. Apart from that, there is not much to say about this 9 x 11 km glacier located in East Antarctica around 130°E, except that it is really hard to find a picture with the keywords “may” and “glacier”… So I let you enjoy the Image of the Week, which combines three satellite images of May Glacier (at the centre) and its surroundings exactly a month ago, when the skies were clear and the sea ice pretty:
A 10km-long, 4-km-wide and 350m-high cavity has recently been discovered under one of the fastest-flowing glaciers in Antarctica using different airborne and satellite techniques (see this press release and this study). This enormous cavity previously contained 14 billion tons of ice and formed between 2011 and 2016. This indicates that the bottom of the big glaciers on Earth can melt faster than expected, with the potential to raise sea level more quickly than we thought. Let’s see in further details how the researchers made this discovery.
Thwaites Glacier is a wide and fast-flowing glacier flowing in West Antarctica. Over the last years, it has undergone major changes. Its grounding line (separation between grounded ice sheet and floating ice shelf) has retreated inland by 0.3 to 1.2 km per year in average since 2011. The glacier has also thinned by 3 to 7 m per year. Several studies suggest that this glacier is already engaged in an unstoppable retreat (e.g. this study), called ‘marine ice sheet instability’, with the potential to raise sea level by about 65 cm.
With the help of airborne and satellite measurement techniques, the researchers that carried out this study have discovered a 10km-long, 4km-wide and 350m-high cavity that formed between 2011 and 2016 more than 1 km below the ice surface. In Figure 2B, you can identify this cavity around km 20 along the T3-T4 profile between the green line (corresponding to the ice bottom in 2011) and the red line (ice bottom in 2016). According to the researchers, the geometry of the bed topography in this region allowed a significant amount of warm water from the ocean to come underneath the glacier and progressively melt its base. This lead to the creation of a huge cavity.
Fig. 2: A) Ice surface and bottom elevations in 2014 (blue) and 2016 (red) retrieved from airborne and satellite remote sensing along the T1-T2 profile identified in Fig. 2C. B) Ice surface and bottom elevations in 2011 (green) and 2016 (red) along the T3-T4 profile. C) Changes in ice surface elevation between 2011 and 2017. The ticks on the T1-T2 and T3-T4 profiles are marked every km [Credit: adapted with permission from Figure 3 of Milillo et al. (2019)].
What does it mean?
In order to make accurate projections of future sea-level rise coming from specific glaciers, such as Thwaites Glacier, ice-sheet models need to compute rates of basal melting in agreement with observations. This implies a correct representation of the bed topography and ice bottom underneath the glacier.
However, the current ice-sheet models usually suffer from a too low spatial resolutionand use a fixed shape to represent cavities. Thus, these models probably underestimate the loss of ice coming from fast-flowing glaciers, such as Thwaites Glacier. By including the results coming from the observations of this studyand further ongoing initiatives (such as the International Thwaites Glacier Collaboration), ice-sheet models would definitely improve and better capture the complexity of glaciers.
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.
The participants to the 5th Snow Science Winter School [Credit: Anna Kontu]
From February 17th to 23rd, 21 graduate students and postdoctorate researchers from around the world made their way to Hailuoto, a small island on the coast of Finland, to spend a week learning about snow on sea-ice for the 5th Snow Science Winter School. The course, jointly organized by the Finnish Meteorological Institute and the Swiss Federal Institute for Forest, Snow and Landscape Research WSL, brought together a wide range of scientists interested in snow: climate modellers, large-scale hydrologists, snow microstructure modellers, sea-ice scientists and remote sensing experts studying the Arctic, Antarctica and various mountain ranges. The week was spent between field sessions out on the sea-ice, daily lectures, and data analysis sessions, punctuated by amazing food and Finnish saunas to finish the day!
Our field sessions focused on learning to use both standard snow measurement techniques and advanced state-of-the-art methods. We first practiced sampling the thin, crusty snowpack with traditional methods: digging snow pits and recording grain size, temperature profile and density. We then moved to advanced techniques, learning about micro-tomography – which generates 3D images of the snow without destroying the way the individual ice crystals are arranged, near-infrared imagery and the measurement of specific surface area of the snow crystals by recording how a laser beam is reflected and modified as it passes through the snow sample. These techniques all give information on how the snow crystals are arranged in the snow pack that are not obtainable with the traditional techniques. They also give important parameters for remote sensing validation and snowpack modelling.
The lecturers had brought with them some of the most advanced instruments, in some cases their own unique prototypes, giving us an amazing opportunity to practice working with these instruments. Amongst them was the SLF SnowMicroPen, which can measure the mechanical resistance of the snowpack, the optical sensors IRIS and SnowCube which use the reflection from a laser beam to calculate the surface area of the snow crystals, and a small radar which relates the conductivity of snow to the amount of liquid water mixed in with the snow and the density. On top of that, we honed our sea-ice drilling and measurement skills. During our field sessions, we were exposed to all the conditions a field researcher might experience, from cloudy skies, over to high winds threatening to blow away all your equipment to crisp, cold blue skies.
The students braving the winds to collect data [Credit: Guillaume Couture]
Our daily lectures covered a range of topics, leaning on the expertise of the instructors of the course. After a short introduction about sea-ice, a well-needed refresher considering the wide range of backgrounds of the participants, we jumped into snow-science. We learned about snow measurements from a field, remote sensing, and modelling perspective. The lectures sparked multiple discussions, from the continual need for more ground-validation for remote sensing data, over spatial representativeness and accuracy of the field samples to modelling approaches and a consideration of the limitations of the observational datasets.
After learning how to use these fancy and expensive instruments and using our newly gained knowledge of snow on sea-ice, we were given a day to plan our own field session, collect data, analyze the results and present our result to the other groups on the final afternoon. Some very ambitious projects were quickly checked by reality in the field and the snow conditions were exceptionally challenging. This meant that our data might not perhaps yield any scientific breakthroughs in the field of snow science, but that we certainly learned how to adapt measurement and analysis designs on the fly and will hopefully all have an all-weather plan for the next expedition out into the snow for our various projects at home.
Calculating specific area with the SnowCube [Credit: Anika Rohde].
More than the science
On our second evening, we braved the elements for the ice breaker held in a tent on the sea ice. Luckily, only the ice between the students and lecturers broke so that everyone appeared again at breakfast the next day. The delicious food kept us warm for the duration of the trip and anyone still feeling cold could enjoy the sauna for a truly Finnish experience. Our knowledge gained over the week was tested on the final evening with a sea-ice themed trivia organized by the instructors.
Being this far north provides a great opportunity to witness some elusive northern lights. During the entire week, we kept a close eye on the aurora borealis forecast, and we finally had a good chance of seeing them on our last night. Needless to say, we put our field gear back on to head outside and were rewarded by a beautiful display of dancing green and pink lights in the skies. A wonderful way to finish a successful week of learning, meeting fellow researchers and sparking new research questions!
The elusive northern lights appearing on our last night in Hailuoto [Credit: Anika Rohde]
The accommodation treated us to some beautiful sunsets! [Credit: Caroline Aubry-Wake]
To finish on a high not, here is a short video summarizing our incredible week in Hailuto! [Credit: Caroline Aubry-Wake]
Edited by Violaine Coulon
Caroline Aubry-Wake is a mountain hydrology PhD candidate at the University of Saskatchewan, Canada. By combining mountain fieldwork in the Canadian Rockies with advanced computer modelling, she aims to further understand how melting glaciers and a changing landscape will impact water resources in the future.
Maren Richter is a PhD student at the Department of Physics of the University of Otago. A physical oceanographer by training, she has turned her focus on the solid state of water to study ice-ocean interactions in Antarctica. Specifically, the effect of platelet ice formed near ice shelf cavities on landfast sea ice thickness evolution and variability on interannual to decadal timescales.
Tabular iceberg, Ross Sea, Antarctica [Credit: Marlo Garnsworthy]
Crew in hardhats and red safety gear bustle about, preparing our ship for departure. A whale spouts nearby in the Straits of Magellan, a fluke waving in brief salute, before it submerges again. Our international team of 29 scientists and 2 science communicators, led by co-Chief Scientists Mike Weber and Maureen Raymo, is boarding the JOIDES Resolution, a scientific drilling ship. We’re about to journey on this impressive research vessel into Antarctic waters known as Iceberg Alley for two months on Expedition 382 of the International Ocean Discovery Program.
Not only are these some of the roughest seas on the planet, it is also where most Antarctic icebergs meet their ultimate fate, melting in the warmer waters of the Antarctic Circumpolar Current (ACC), which races unimpeded around the vast continent. And there, in the Scotia Sea, we will drill deep into the sea floor to learn more about the history of the Antarctic Ice Sheet.
The Drilling Ship
The JOIDES Resolution, our scientific drilling ship [Credit: William Crawford and IODP]
The JOIDES Resolution is a 134-meter-long research vessel topped by a derrick towering 62 meters above the water line. It can drill hundreds of meters into the sea floor to retrieve long cylinders of mud called cores. Analyzing this sediment can tell scientists much about geology and Earth’s history, including the history of Climate Change.
“Sediment cores are like sedimentary tape recorders of Earth’s history,” says Maureen Raymo. “You can see how the climate has changed, how the plants have changed, how the temperatures have changed. Imagine you had a multilayer cake and a big straw, and you just stuck your straw into your cake and pulled it out. And that’s essentially what we do on the ocean floor.”
Our drilling sites in the Scotia Sea. [Figure modified from Weber, et al (2014)]
Our expedition is “going to a place that’s never really been studied before,” adds Maureen Raymo. “In fact, we don’t even know what the age of the sediment at the bottom will be.” Nevertheless, we hope to retrieve a few million years’ worth of sediment, perhaps even more. The sediment cores will provide a nearly continuous history of changes in melting of the Antarctic Ice Sheet.
What can these cores tell us?
As icebergs melt, the dust, dirt, and rocks they carry—known as “iceberg rafted debris”—fall down through the ocean and are deposited as sediment on the seafloor. Analyzing this sediment can tell us when the icebergs that deposited it calved from the ice sheet, and even where they came from. At times when more debris was deposited, we know more icebergs were breaking away from the Antarctic Ice Sheet, which tells us the ice sheet was less stable.
Much shorter cores previously collected at our drilling sites reveal high sedimentation rates, allowing us to observe changes in the ice sheet and the climate on short timescales (from just tens to hundreds of years).
We now know that rapid discharge of icebergs—caused by rapid melting of Antarctic ice shelves and glaciers—occurred in the past, and that episodes of massive iceberg discharge can happen abruptly, within decades. This has huge implications for how the Antarctic Ice Sheet may behave in the future as our world warms.
Where do icebergs come from?
Ok, let’s back up a little—back to where these icebergs were born. Icebergs break off or “calve” from the margins (edges) of ice shelves and glaciers. Ice shelves are floating sheets of ice around the edges of the land. They are important because they have a “buttressing” effect—that is, they act as a wall, holding back the ice behind them. Glaciers are great flowing rivers of ice that grind their way across the land, picking up the rocks and dirt that become iceberg-rafted debris.
As our planet warms due to our greenhouse gas emissions, warmer ocean currents are melting Antarctica’s massive glaciers from below, thinning, weakening, and destabilizing them. In fact, the rate of Antarctic ice mass loss has tripled over the last decade alone.
Polar researchers predict that global sea level will rise up to one meter (around 3.2 feet) by the end of this century, and most of this will be due to melting in Antarctica. And if vulnerable glaciers melt, the West Antarctic Ice Sheet is more likely to collapse, raising sea level even further.
Blue is old ice, Mc Murdo Sound, Antarctica [Credit: Marlo Garnsworthy]
A Hazardous Voyage
We face several hazards on this journey. We are hoping we won’t encounter sea ice, as our vessel is not ice-class, but it’s something we must watch for, especially later in the cruise as winter draws nearer. It is certain that, at times, we’ll experience a sea state not conducive to coring—or to doing much but swallowing sea-sickness medication and retiring to one’s bunk. In heave greater than 4–6 meters, operations must stop for the safety of the crew and equipment.
Of course, our highly experienced ice observer will be ever on the lookout for our greatest hazard—icebergs, of course! We are likely to encounter everything from very small “growlers” to larger “bergy bits” to massive tabular bergs. In fact, it is the smaller icebergs that present the most danger to the ship, as large icebergs are both visible to the eye and are tracked by radar, while smaller ones can be more difficult to detect, especially at night. Nevertheless, we are intentionally sailing into the area of highest iceberg concentration and melt.
“My hope,” says Mike Weber, “is that our expedition will unravel the mysteries of Antarctic ice-sheet dynamics for the past, and this may tell is something about its course in the near future.”
“Bergy bit”, Ross Sea, Antarctica [Credit: Marlo Garnsworthy]
Edited by Sophie Berger
The JOIDES Resolution is part of the International Ocean Discovery Program and is funded by the US National Science Foundation.
Marlo Garnsworthy is an author/illustrator, editor, science communicator, and Education and Outreach Officer for JOIDES Resolution Expedition 382 and previously NBP 17-02. She and Kevin Pluck are co-founders of science communication venture PixelMoversAndMakers.com, creator of the animations in this article.
Thin, ponded sea ice floes in Nares Strait [Credit: Christopher Horvat and Enduring Ice]
Perhaps the most enduring and important signal of a warming climate has been that the minimum Arctic sea ice extent, occurring each year in September, has declined precipitously. Over the last 40 years, most of the Arctic sea ice has thus been transformed to first-year ice that freezes in the winter and melts in the summer.
Concern about sea ice extent and area is valid: since sea ice is a highly reflective surface, a reduction of its area has a significant effect on the energy budget of Earth’s climate. Yet it is well-documented that, in the summertime, when sunlight is strongest, the biggest changes to sea ice volume are coming from effects not associated with changes to ice area, but with changes to sea ice thickness, like increased melt ponding. The change from thick, reflective multi-year summer sea ice to thin, ponded, less-reflective first-year ice are seen throughout the Arctic. In places like Nares Strait, the region of the Canadian Arctic that separates Canada from Greenland (seen above), commonly referred to as the “last ice area”, this is true as well.
The “Enduring Ice” Expedition
In the summer of 2016 and 2017, 4 filmmakers and a scientist (that’s me!) set out to examine Nares Strait, the area that separates Ellesmere Island in Canada from Northern Greenland (see map below). The Strait has been designated the “last ice area” by the World Wildlife Fund, a region which is expected to remain fully covered in thick sea ice even as the rest of the Arctic sea ice cover melts.
Nares Strait [Credit: Enduring Ice, LLC]
Yet when we arrived, what we found was anything but the promised land of thick, multi-year ice. Instead, all of the ice we encountered was thin, heavily ponded, and fragmented. In decades past, the presence of multi-year floes would dam Nares Strait, allowing ice-free passage for kayakers. Instead, the fractured ice poured through the strait, making passage impossible. Faced with an impassable strait, we resorted to pulling the kayaks over the land, moving a total of 100 km in 45 days.
The “Enduring Ice” Expedition [Credit: Christopher Horvat and Enduring Ice]
Most projections have the Arctic totally ice-free in September by 2050, meaning there will truly be no multi-year ice left at all. Yet as the Arctic still cools dramatically in winter, during the summer months (from May to July) when solar radiation is highest, the total area of the Arctic covered in sea ice is still high, but now covered by thin first-year ice. At the same time, the ongoing warming has thinned the Arctic sea ice by more than half (Kwok, 2008).
The albedo of first year ice can be half or less that of multi-year thicker ice (Light, 2008). Since the Arctic has thinned substantially over the last 40 years, the consequences of this thinning on the Arctic and Earth climate system are dramatic.
More and more solar radiation is absorbed by thinner ice. Excess solar absorption leads to ocean and atmospheric warming, and to more sea ice melting, a process known as the ice-albedo feedback. It was previously thought that regions covered by sea ice where inhospitable to photosynthetic life. However, thinning sea ice is likely responsible for the increase in phytoplankton blooms in the Arctic, as more light is transmitted through the thinner ice.
The Arctic sea ice cover is rapidly transitioning from thick, multi-year ice to thin, ponded, first-year sea ice. As we can see, this thinning is resulting in a totally new Arctic climate system.
Communicating scientific findings toward non-experts is a vital part of cryosphere science. However, when it comes to climate change and its impact, the gap between scientific knowledge and human action has never been so evident (see for instance, the publication of the latest IPCC special report). Today, our image of the week features an interview with Cryo Connect, a new initiative for more efficient flow of information between cryosphere scientists and information seekers.
Why have you decided to come up with an initiative like Cryo Connect?
Currently, information seekers such as journalists, policy makers, teachers and stakeholders often resort to internet search engines to find experts for answering specific questions about the cryosphere. Or they return to the same expert they have interacted with in the past. Either way, it is unlikely that they end up receiving information from the expert that knows most about the topic, or even in the preferred language. Some organizations have their own science outreach portals, but a truly global and inclusive network of cryosphere experts willing to provide insights to those seeking information has been lacking. For this reason, we established Cryo Connect.
Number of Cryo Connect experts for each cryospheric component. [Credit: Cryo connect]
Number of Cryo Connect experts for each cryosphere region. [Credit: Cryo connect]
How has Cryo Connect been doing so far?
Although still in our first year, by October 2018 Cryo Connect has already grown to a community of 98 experts based in 22 countries across the planet. Together, they can provide information on all components of all cryospheric regions in the world – in 19 different languages! Researchers make up about two-fifths of the expert database, while PhD students, senior researchers and professors each constitute a ⅕ part. Lots of knowledge to go around.
Career stage of Cryo Connect experts. [Credit: Cryo connect]
What’s the take-home message for scientists?
That all cryosphere scientists around the globe are invited to sign up as a Cryo Connect expert to increase their visibility to the media and other information seekers. The platform works best, and attracts more information seekers with an even larger expert population from all corners of the planet. And don’t forget to tweet about your latest peer-reviewed publication using the @CryoConnect Twitter handle for increased media exposure!
Edited by Sophie Berger
Cryo-connect is an initiative run by Dirk van As, Faezeh Nick, William Colgan and Inka Koch
Figure 1: Annual evolution of the sea ice area with two different floe shape parameters of 0.44 (red) and 0.88 (blue). The model is spun-up between 2000 – 2006 and then evaluated for a further ten years between 2007 – 2016 and the mean values over this period displayed by the thick lines. Thin lines show the results for individual years. [Credit: Adam Bateson]
Polar sea ice exists as isolated units of ice that we describe as floes. These floes do not have a constant shape (see here for instance); they can vary from almost circular to being jagged and rectangular. However, sea ice models currently assume that all floes have the same shape. Much focus has been paid to the size of floes recently, but do we also need to reconsider how floe shape is treated in models?
Why might floe shape matter?
In recent years, sea ice models have started to examine more and more how individual floes influence the overall evolution of sea ice.
A particular focus has been the size of floes (see here and here) and the parameterisation of processes which influence floe size (see here for example). However less attention has been given to the shape of the floe. The shape of the floe is important for several reasons:
Lateral melt rate: the lateral melt rate describes how quickly a floe melts from its sides. Two floes with the same area but different shape can have a different perimeter; the lateral melt rate is proportional to the floe perimeter.
Wave propagation: a straight floe edge will impact propagating waves differently to a curved or jagged floe edge. The distance waves travel under the sea ice and hence the extent of sea ice that waves can fragment will be dependent on these wave-floe edge interactions.
Floe mechanics: an elongated floe (i.e. much longer in one direction than another) will be more likely to break from incoming waves if its longer edge is aligned with the direction the waves are travelling.
How do models currently treat floe shape?
One approach used within sea ice models to define floe shape is the use is the use of a parameter, α. The smaller the floe shape parameter, the longer the floe perimeter (and hence, the higher the lateral melt rate). A standard value used for the parameter is 0.66 (Steele, 1992). Figure 2 shows how this floe shape parameter varies for some common shapes.
Figure 2: The floe shape parameters for some common shapes are given for comparison to the standard value of 0.66. [Credit: Adam Bateson]
The standard value of the floe shape parameter, 0.66, was obtained from taking the mean floe shape parameter measured over all floes greater than 1 km from a singular study area of 110 km x 95 km at one snapshot in time. Despite the limited data set used to estimate this shape parameter, it is being used for all sea ice throughout the year for all floe sizes. However, this would only be a concern to the accuracy of modelling if it turns out that sea ice evolution in models is sensitive to the floe shape parameter.
Model sensitivity to floe shape
To investigate the model sensitivity to the floe shape parameter two simulations have been run: one uses a floe shape parameter of 0.88 and the other uses 0.44, chosen to represent likely extremes. The two simulations are run from 2000 – 2016, with 2000 – 2006 used as a spin-up period. Figure 1 displays the mean total ice area throughout the year and results of individual years for each simulation. Figure 3 is an equivalent plot to show the annual evolution of total ice volume for each simulation.
The results show that the perturbation from reducing the floe shape parameter is smaller than the variation between years within the same simulation. However, the model does show a permanent reduction in volume throughout the year and a 10 – 20 % reduction in the September sea ice minimum. The impact of the floe shape is hence small but significant, particularly for predicting the annual minimum sea ice extent and volume.
Figure 3: Annual evolution of the sea ice volume with two different floe shape parameters of 0.44 (red) and 0.88 (blue). The model is spun-up between 2000 – 2006 and then evaluated for a further ten years between 2007 – 2016 and the mean values over this period displayed by the thick lines. Thin lines show the results for individual years.
More recent studies on floe shape
In 2015, Gherardi and Lagomarsino analysed the floe shape behaviour from four separate samples of satellite imagery from both the Arctic and Antarctic. The study found different distributions of floe shapes in different locations, however there was no correlation between floe shape and size. This property would allow models to treat floe shape and size as independent properties. More recently, in 2018, Herman et al. analysed the results of laboratory experiments of ice breaking by waves. It was found that wave break-up influenced the shape of the floes, tending to produce straight edges and sharp angles. These features are associated with a smaller floe parameter i.e. would produce an increased lateral melt rate.
More observations are needed to identify whether the use of a constant floe shape parameter is justified. The following questions are important:
Do further observations support the finding that floe size and shape are uncorrelated?
What range of values for the floe shape parameter can be observed in reality?
Do we see significant variations in the floe shape parameter between locations?
Do these variations occur over a large enough scale that they can be represented within existing model resolutions?
Adam Bateson is a PhD student at the University of Reading (United Kingdom), working with Danny Feltham. His project involves investigating the fragmentation and melting of the Arctic seasonal sea-ice cover, specifically improving the representation of relevant processes within sea-ice models. In particular he is looking at lateral melting and wave induced fragmentation of sea-ice as drivers of break up, as well as the role of the ocean mixed layer as either an amplifier or dampener to the impacts of particular processes. Contact: email@example.com or @a_w_bateson on twitter.
Fig. 1: Deriving the bathymetry and temperature of a large supraglacial pond on Khumbu Glacier, Everest region of Nepal. The sonar-equipped unmanned surface vessel nicknamed ‘BathyBot’ (left), and kayak retrieval of temperature loggers (right) [Credit: Scott Watson].
A creeping flux of ice descends Everest, creating the dynamic environment of Khumbu Glacier. Ice and snow tumble, debris slumps, ice cliffs melt, englacial cavities collapse, ponds form and drain, all responding to a variable energy balance. Indeed, Khumbu Glacier is a debris-covered glacier, meaning it features a layer of sediment, rocks and house-sized boulders that covers the ice beneath. Recent advances in understanding debris-covered glacier hydrology come from combining in situ surveys with remotely sensed satellite data.
The dramatic beauty of Nepal’s Everest region attracts a mix of trekkers, climbers, and scientists. Flowing down from the slopes of Mount Everest, the debris-covered Khumbu Glacier has drawn scientists from the mid-1900s, and offers temporary residence for research teams and a myriad of climbers. In some locations, Khumbu Glacier has thinned by up to 80 m in the last three decades, leading to moraines overlooking the glacier with impressive topographic relief and providing an instant visualisation of glacier mass loss for trekkers heading to Everest Base Camp.
Melt at the surface of this glacier is moderated by an undulating debris layer, which insulates the ice beneath, and enhanced locally by dynamic surface features such as supraglacial ponds and ice cliffs thinly veiled by debris. These features contribute disproportionately to melt and lead to the development of hummocky, pitted surface topography. The resulting variable surface topography and melt rates complicate meltwater runoff and flow routing across the glacier. To better understand them, in situ surveying (Fig. 1) is increasingly combined with fine spatial-temporal resolution satellite imagery to reveal the hydrological evolution of debris-covered glaciers, which is closely linked to their mass loss.
Hydrology of Khumbu Glacier
As with debris-free glaciers, water may be routed through supraglacial, englacial, and subglacial pathways, which are conceptually distinct but physically link to one another.
At Khumbu Glacier, surface channels collect and rapidly convey meltwater generated in the upper ablation area (Fig. 2), just below the treacherous Khumbu Icefall, incising at a faster rate than the surface melt. In the middle of the debris-covered area, such streams disappear into the glacier’s interior through cut-and-closure and/or hydrofracture.
Fig.2: The upper ablation area of Khumbu is drained by supraglacial channels which enter the glacier’s interior through hydrofracture and cut-and-closure, while the lower portion is characterised by pitted surface depressions and an increasing density of ponds. Right panel looking east to west shows the hummocky topography and ponding on Khumbu Glacier. [Credit: Evan Miles (left), Ann Rowan (right)].
In areas of low surface gradient , and particularly throughout the hummocky lower reaches of the glacier, supraglacial ponds collect water in surface depressions. These features haveregulate the runoff of debris-covered glaciers by seasonally storing meltwater. The annual melt cycle thus leads to pond expansion and contraction, or their disappearance when the protecting debris layer thaws and relict meltwater conduits become avenues for drainage (Fig 3). The areal fluctuation of ponds can be quantified using satellite images at different times, but cloud cover during the summer monsoon season limits useable imagery at a time when the ponds are most dynamic. Therefore, field-instrumented ponds provide valuable insights into their active melt season behaviour.
Fig. 3: A small 4.5 m deep pond that drained over the course of a year [Credit: Watson et al., 2017a].
Turbid ponds associated with debris influx from ice cliffs are often ephemeral but some can grow to hold vast quantities of water (Fig. 1). Stored water absorbs and transmits solar energy to melt adjacent ice, which generates additional meltwater and leads to pond expansion. The ponds also thermally undercut ice cliffs, leading to both subaqueous and subaerial retreat (Fig. 4). Khumbu Glacier has been developing a growing network of ponds in recent years, which means meltwater is increasingly stored on the surface of the glacier before contributing to downstream river discharge. Ponds that coalesce into larger and more persistent lakes behind unstable deposits of sediment can in some cases pose a hazard to downstream communities. Field and satellite-based techniques are therefore used simultaneously to monitor lake development.
Fig. 4. Supraglacial ponds often exist alongside ice cliffs. These ‘hot spots’ of melt can be observed with repeat point cloud differencing [Credit: Watson et al., 2017b]. An interactive view of the drained pond basin (right) is available here.
What lies beneath?
Ephemeral ponds drain into the ‘black box’ glacier interior, where relatively little is known about the internal structure and hydrology. Scientists have occasionally ventured into the subsurfac e realm through networks of englacial conduits that become exposed as the glacier thins (Fig. 5); such conduits often re-emerge at the glacier surface but may also lead to the bed. The conduits carry meltwater through the glacier but can become dormant if blocked by falling debris or creeping ice, or when the meltwater that sustains them finds a route of lesser resistance. Whilst satellite data can be used to infer the presence of conduits, field-based methods are required for hydrological budgeting and quantifying meltwater transit times. For example, dye tracing can detect the subsurface passage of meltwater where strategically placed fluorometers measure the receipt and dilution of the dye upon re-emergence. Such methods are crucial for developing an improved understanding of the links between, for example, flow in the supraglacial channels up-glacier and discharge at the outlet.
Fig. 5: An exposed conduit on Lirung Glacier (left) [Credit: Miles et al., 2017] and researchers inside a conduit on Ngozumpa Glacier (right) [Credit: Benn et al., 2017].
Multiple teams working across the Himalaya are advancing our understanding of debris-covered glacier hydrology, which is essential to forecast their future and quantify their downstream impact. With the ready availability of increasingly high temporal resolution satellite imagery (e.g. Sentinel-2, Planet Labs), the link between field and spacebourne observations will become increasingly complementary. Developing these links is crucial to upscale observations from specific sites more broadly across the Himalaya.
Scott Watson is a Postdoc at the University of Arizona, USA. He studies glaciers in the Everest region and the surface interactions of supraglacial ponds and ice cliffs. He also investigates natural hazards and the implications of glacial lake outburst floods. Tweets @CScottWatson. Website: www.rockyglaciers.co.uk
Evan Miles is a Research Fellow at the University of Leeds, UK, where he is a part of the EverDrill project’s hot-water drilling at Khumbu Glacier. His recent work has examined the seasonal hydrology and dynamics of debris-covered glaciers, with a focus on the melt associated with dynamic surface features such as supraglacial ice cliffs and ponds. Tweets @Miles_of_Ice
Fig. 1 Cumulative Antarctic Ice Sheet mass change since 1992. [Credit: Fig 2. from The IMBIE team (2018), reprinted with permission from Nature]
It is this time of the year, where any news outlet is full of tips on how to lose weight rapidly to become beach-body ready. According to the media avalanche following the publication of the ice sheet mass balance inter-comparison exercise (IMBIE) team’s Nature paper, Antarctica is the biggest loser out there. In this Image of the Week, we explain how the international team managed to weight Antarctica’s ice sheet and what they found.
Estimating the Antarctic ice sheet’s mass change
There are many ways to quantify Antarctica’s mass and mass change and most of them rely on satellites. In fact, the IMBIE team notes that there are more than 150 papers published on the topic. Their paper that we highlight this week is remarkable in that it combines all the methods in order to produce just one, easy to follow, time series of Antarctica’s mass change. But what are these methods? The IMBIE team used estimates from three types of methods:
altimetry: tracking changes in elevation of the ice sheet, e.g. to detect a thinning;
gravimetry: tracking changes in the gravitational pull caused by a change in mass;
input-output: comparing changes in snow accumulation and solid ice discharge.
To simplify, let’s imagine that you’re trying to keep track of how much weight you’re losing/gaining. Then altimetry would be like looking at yourself in a mirror, gravimetry would be stepping on a scale, and input-output would be counting all the calories you’re taking in and burning out. None of these methods will tell you directly whether you have lost belly fat, but combining them will.
The actual details of each methods are rather complex and cover more pages than the core of the paper, so I invite you to read them by yourself (from page 5 onwards). But long story short, all estimates were turned into one unique time series of ice sheet mass balance (purple line on Fig. 1). Furthermore, to understand how each region of Antarctica contributed to the time series, the scientists also produced one time series per main Antarctic region (Fig. 2): the West Antarctic Ice Sheet (green line), the East Antarctic Ice Sheet (yellow line), and the Antarctic Peninsula (red line) .
The results are clear: the Antarctic ice sheet as a whole is losing mass, and this mass loss is accelerating. Nearly 3000 Giga tonnes since 1992. That is 400 billion elephants in 25 years, or on average 500 elephants per second.
Most of this signal originates from West Antarctica, with a current trend of 159 Gt (22 billion elephants) per year. And most of this West Antarctic signal comes from the Amundsen Sea sector, host notably to the infamous Pine Island and Thwaites Glaciers.
The Antarctic ice sheet has lost “400 billion elephants in 25 years”
But how is the ice disappearing? Rather, is the ice really disappearing, or is there simply less ice added to Antarctica than ice naturally removed, i.e. a change in surface mass balance? The IMBIE team studied this as well. And they found that there is no Antarctic ice sheet wide trend in surface mass balance; in other words Antarctica is shrinking because more and more ice is discharged into the ocean, not because it receives less snow from the atmosphere.
Floating ice shelf in the Halley embayment, East Antarctica [Credit: Céline Heuzé]
What is happening in East Antarctica?
Yet another issue with determining Antarctica’s weight loss is Glacial Isostatic Adjustment. In a nutshell, ice is heavy, and its weight pushes the ground down. When the ice disappears, the ground goes back up, but much more slowly than the rate of ice melting . This process has been ongoing in Scandinavia notably since the end of the last ice age 21 000 years ago, but it is also happening in East Antarctica by about 5 to 7 mm per year (more information here). Except that there are very few on site GPS measurements in Antarctica to determine how much land is rising, and the many estimations of this uplifting disagree.
So as summarised by the IMBIE team, we do not know yet what the change in ice thickness is where glacial isostatic adjustment is strong, because we are unsure how strong this adjustment is there. As a result in East Antarctica, we do not know whether there is ice loss or not, because it is unclear what the ground is doing.
What do we do now?
The IMBIE team concludes their paper with a list of required actions to improve the ice loss time series: more in-situ observations using airborne radars and GPS, and uninterrupted satellite observations (which we already insisted on earlier).
What about sea level rise, you may think. Or worse, looking at our image of the week, you see the tiny +6mm trend in 10 years and think that it is not much. No, it is not. But note that the trend is far from linear and has been actually accelerating in the last decades…
Figure 1. True color composite of a Sentinel-2 image showing the dust plume off the coast of Libya on 22-Mar-2018 (see also on the ESA website) [Credit: processed by S. Gascoin]
On 22 March 2018, large amounts of Saharan dust were blown off the Libyan coast to be further deposited in the Mediterranean, turning the usually white snow-capped Mountains of Turkey, Romania and even Caucasus into Martian landscapes. As many people were struck by this peculiar color of the snow, they started documenting this event on social media using the “#orangesnow hashtag”. Instagram and twitter are fun, but satellite remote sensing is more convenient to use to track the orange snow across mountain ranges. In this new image of the week, we explore dusty snow with the Sentinel-2 satellites…
Sentinel-2: a great tool for observing dust deposition
Sentinel-2 is a satellite mission of the Copernicus programme and consists of two twin satellites (Sentinel-2A and 2B). Although the main application of Sentinel-2 is crop monitoring, it is also particularly well suited for characterizing the effect of dust deposition on the snowy mountains because:
Sentinel-2A and 2B satellites provide high-resolution images with a pixel size of 10 m to 20 m (depending on the spectral band), which enables to detect dust on snow at the scale of hillslopes.
Sentinel-2 has a high revisit capacity of 5 days which increases the probability to capture cloud-free images shortly after the dust deposition.
Sentinel-2 has many spectral bands in the visible and near infrared region of the light spectrum, making easy to separate the effect of dust on snow reflectance — i.e. the proportion of light reflected by snow — from other effects due to snow evolution. The dust particles mostly reduce snow reflectance in the visible, while coarsening of the snow by metamorphism (i.e. the change of microstructure due to transport of vapor at the micrometer scale) tends to reduce snow reflectance in the near infrared (Fig. 2).
Sentinel-2 radiometric observations have high dynamic range and are accurate and well calibrated (in contrast to some trendy miniature satellites), hence they can be used to retrieve accurate surface dust concentration, provided that the influence of the atmosphere and the topography on surface reflectance are removed.
Figure 2: Diffuse reflectance for different types of snowpack. These spectra were computed with 10 nm resolution using the TARTES model (Libois et al, 2013) using the following parameters: snowpack density: 300 kg/m3, thickness: 2 m, fine snow specific surface area (SSA): 40 m2/kg, coarse snow SSA: 20 m2/kg, dust content: 100 μg/g. The optical properties of the dust are those of a sample of fine dust particles from Libya with a diameter of 2.5 μm or less (PM2.5) (Caponi et al, 2017). The Sentinel-2 spectral bands are indicated in grey. [Credit: S. Gascoin]
Dust on snow from Turkey to Spain
The region of Mount Artos in the Armenian Highlands (Turkey) was one of the first mountains to be imaged by Sentinel-2 after the dust event. Actually Sentinel-2 even captured the dust aloft on March 23, before its deposition (Fig. 3)
Figure 3: Time series of three Sentinel-2 images near Mount Artos in Turkey (true color composites of level 1C images, i.e. orthorectified products, without atmospheric correction). [Credit: Contains modified Copernicus Sentinel data, processed by S. Gascoin]
Later in April another storm from the Sahara brought large amounts of dust in southwestern Europe.
Figure 4: Sentinel-2 images of the Sierra Nevada in Spain (true color composites of level 1C images). [Credit: Contains modified Copernicus Sentinel data, processed by S. Gascoin]
This example in the spanish Sierra Nevada nicely illustrates the value of the Sentinel-2 mission since both images were captured only 5 days apart. The high resolution of Sentinel-2 is also important given the topographic variability of this mountain range. This is how it looks in MODIS images, having a 250 m resolution.
Figure 5: MODIS Terra (19) and Aqua (24) images of the Sierra Nevada in Spain. True Color composites of MODIS corrected reflectance. [Credit: NASA, processed by S. Gascoin]
Sentinel-2 satellites enable to track the small-scale variability of the dust concentration in surface snow, even at the scale of the ski runs as shown in Fig. 6.
Figure 6: Comparison of a true color Sentinel-2 image and a photograph of the Pradollano ski resort, Sierra Nevada. [Credit: photograph taken by J. Herrero / Contains modified Copernicus Sentinel data, processed by S. Gascoin]
A current limitation of Sentinel-2, however, is the relative shortness of the observation time series. Sentinel-2A was only launched in 2015 and Sentinel-2B in 2017. With three entire snow seasons, we can just start looking at interannual variability. An example in the Prokletije mountains in Albania is shown in Fig. 7.
Figure 7. Sentinel-2 images of the Prokletije mountains in Albania (true color composites of level 1C images) [Credit: Contains modified Copernicus Sentinel data, processed by S. Gascoin]
These images suggest that the dust event of March 2018 was not exceptional in this region, as 2016 also highlights a similar event. The Sentinel-2 archive will keep growing for many years since the EU Commission seems determined to support the continuity and development of Copernicus programme in the next decades. In the meantime to study the interannual variability the best option is to exploit the long-term records from other satellites like MODIS or Landsat.
Beyond the color of snow, the water resource
Dust on snow is important for water resource management since dust increases the amount of solar energy absorbed by the snowpack, thereby accelerating the melt. A recent study showed that dust controls springtime river flow in the Western USA (Painter et al, 2018).
“It almost doesn’t matter how warm the spring is, it really just matters how dark the snow is.”
said snow hydrologist Jeff Deems in an interview about this study in Science Magazine. Little is known about how this applies to Europe…
Simon Gascoin is a CNRS researcher at Centre d’Etudes Spatiales de la Biosphère (CESBIO), in Toulouse. He obtained a PhD in hydrology from Sorbonne University in Paris and did a postdoc on snow and glacier hydrology at the Centro de Estudios Avanzados en Zonas Áridas (CEAZA) in Chile. His research is now focusing on the application of satellite remote sensing to snow hydrology. He tweets here and blog here.
Marie Dumont is a researcher, leading the snow processes, observations and modelling research team at the snow study centre (CNRM/CEN, Grenoble, France). Her research focuses on snow evolution mostly in alpine region using numerical modelling and optical remote sensing.
Ghislain Picard is a lecturer working at the Institute of Geosciences and Environment at the University Grenoble Alpes, in the climate and ice-sheets research group. His research focuses on snow evolution in polar regions in the context of climate change. Optical and microwave remote sensing is one of its main tools.