CR
Cryospheric Sciences

Cryospheric Sciences

Image of the Week — Quantifying Antarctica’s ice loss

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) .

Antarctica overview map. [Credit: NASA]

Antarctica is losing ice

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…

 

Reference/Further reading

The IMBIE Team, 2018. Mass balance of the Antarctic Ice Sheet from 1992-2017. Nature 558, 219–222.

Edited by Sophie Berger

Image of the Week — Orange is the new white

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…

Марс атакует 🌔 #smurygins_family_trip

A post shared by Alina Smurygina (@sinyaya_ptiza) on


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:

  1. 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.
  2. Sentinel-2 has a high revisit capacity of 5 days which increases the probability to capture cloud-free  images shortly after the dust deposition.
  3. 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).
  4. 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…

Further reading

 Edited by Sophie Berger


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.

What’s on at POLAR18?

What’s on at POLAR18?

Next Tuesday (19th June) the POLAR18 Open Science Conference kicks off in Davos, Switzerland. We have put together a quick guide about events that might be of interest to you during the week! Conferences are about the science, of course, but the social side is just as important 🙂


What is POLAR18?

The eagle-eyed among you will have spotted that the POLAR18 conference is, in fact, a collection of different meetings held between the 15th-26th June, it’s quite confusing at first glance, so here is a summary of what is going on!

  • 15 – 18 June – SCAR and IASC/ASSW Business & Satellite Meetings (i.e. Side meetings and workshops) – details here.
  • 19 – 23 June  – SCAR/IASC Open Science Conference & Open COMNAP Session (i.e. the main event!)
    • Main program here – this will be the most important part for most of you!
    • Side meetings program here
  • 24 – 26 June – SCAR Delegates Meeting & 2018 Arctic Observing Summit – details here.

Venue

The conference and side meetings are held at the Congress Centre Davos which is in the middle of town (see map below). It is easy to walk around Davos, but if you want to use the local buses you get a free “Guest Card” bus ticket included with most hotel, hostel and apartment bookings.

Needless to say, Davos is a great place to be if you like biking, hiking, trail running and just generally being outside – for ideas on what to do, check out the Q&A section of the POLAR18 website.


Events for ECSs

There is a lot going on during the week – below we have listed just some of the social and networking events we think might be of particular interest to ECSs.

APECS World Summit – Sunday 17th and Monday 18th June

The Association for Polar Early Career Scientists (APECS) is excited to invite members and other early career professionals from around the globe to our 2nd APECS World Summit 2018! Hosted directly before POLAR2018 – the theme for this two-day event on 17-18 June will be “Connecting the Poles”. Please check out this link for more information and very important – YOU NEED TO REGISTER!

Southern Ocean Data Hack 2018 – Sunday 17th June, from 8:00 AM – 4:00 PM

Every wished someone had combined all the measurements of this or that for you into one handy dataset? Well….someone has! Pop into the Southern Ocean Data Hack on Sunday 17th June in Room B Strela to see these collected data sets and talk to the creators behind them. The workshop is supported by the NSF-funded SeaView project (www.seaviewdata.org) and the Southern Ocean Observing System (www.soos.aq).

Introduction to and use of the datasets will be on an informal, drop-in basis from 8am – 4pm. Contact: Steve Diggs (sdiggs@ucsd.edu) or Pip Bricher (data@soos.aq ) if you want more info!

Celebrate the Arctic! – Monday, 18th June 2018, from 7:00 PM – 10:00 PM

This is a social networking event to highlight successes of the Arctic research community, organised by ARCUS on Monday 18th June (evening before the official start of the open science conference). It starts at 7pm in the Greenroom at the Hard Rock Hotel Davos. It is a free event with complimentary catering, door prizes, and a cash bar.

 

EGU Cryosphere ECS Team MeetupTuesday 19th June from 7:00PM

A relaxed social meet-up of the EGU Cryosphere ECS (early career scientist) team – that’s the folks that write this blog!

We are always looking for new members to get involved with the blog, our social media team and organising events and courses at the EGU General Assembly. So if you are interested in knowing more about the EGU Cryosphere Team come along to our meet-up to find out more 🙂

Please email Emma (emma.smith@awi.de) for details!

Queers + Allies Meetup – Friday, 22nd June 2018 at 18:30 PM

There will be a Queer/LGBT + Allies meetup at POLAR18 in the Rinerhorn/Strela room at the Congress Centre Davos (conference venue) on Friday, 22 June at 18:30 (after the poster session). The meeting is designed as a meet-up to discuss community goals and get to know people – after the meeting the evening will move to a social location downtown! 

Image of the Week – Icy expedition in the Far North

Image of the Week – Icy expedition in the Far North

Many polar scientists who have traveled to Svalbard have heard several times how most of the stuff there is the “northernmost” stuff, e.g. the northernmost university, the northernmost brewery, etc. Despite hosting the four northernmost cities and towns, Svalbard is however accessible easily by “usual-sized” planes at least once per day from Oslo and Tromsø. This is not the case for the fifth northernmost town: Qaanaaq (previously called Thule) in Northwest Greenland. Only one small plane per week reaches the very isolated town, and this only if the weather permits it. And, coming from Europe, you have to change plane at least twice within Greenland! It is near Qaanaaq, during a measurement campaign, that our Image of the Week was taken…


Who, When and Where?

In January 2017, a few German and Danish sea-ice scientists traveled to Qaanaaq to set up different measurement instruments on, in and below the sea ice covering the fjord near Qaanaaq. While in town, they stayed in the station ran by the Danish Meteorological Institute. After a few weeks installation they traveled back to Europe, leaving the instruments to measure the sea-ice evolution during end of winter and spring.

 

What and How?

The goal of the measurement campaign was to measure in a novel way the evolution of the vertical salinity and the temperature profiles inside the sea ice, and the evolution of the snow covering the ice. These variables are not measured often in a combined way but are important to understand better how the internal properties of the sea ice evolve and how it affects or is affected by its direct neighbors, the atmosphere and the ocean. The team had to find a place remote enough from human influence, and with good ice conditions. As there are only few paved roads in Qaanaaq, cars are not the best mode of transport. The team therefore traveled a couple of hours on dog sleds (in the dark and at around -30°C!), with the help of local guides and their well-trained dogs (see Fig. 2 and 3).

 

Fig. 2: While the humans were working, the dogs could take a well-deserved break [Credit: Measurement campaign team].

Once on the spot, the sea-ice measurement device was introduced into the ice by digging a hole of 1m x 1m in the ice, placing the measurement device in it, and waiting until the ice refroze around it. Additionally, a meteorological mast and a few moorings were installed nearby (see Image of the Week and Fig. 3) to provide measurements of the atmospheric and oceanic conditions during the measurements. Further, a small mast was installed to enable the data to be transferred through the IRIDIUM satellite network.

 

Fig. 3: Small meteorological mast with dog sleds in the background [Credit: Measurement campaign team].

Finally, the small instrument family was left alone to measure the atmosphere-ice-ocean evolution for around four months. After this monitoring period, in May, the team had to do this trip all over again to get all the measurement devices back. Studying Greenlandic sea ice is quite an adventure!

 

Further reading

Edited by Violaine Coulon

Image of the Week – Polar Prediction School 2018

Image of the Week – Polar Prediction School 2018

Early career scientists studying polar climate are one lucky group! The 29 young scientists who took part in the 10 day Polar Prediction School this year were no exception. They travelled to Arctic Sweden to learn and discuss the challenges of polar prediction and to gain a better understanding of the physical aspects of polar research.


The Year of Polar Prediction

The Year of Polar Prediction (YOPP) was launched on May 15th 2017; a large 2 year project that ‘aims to close gaps in polar forecasting capacity’ and ’lead to better forecasts of weather and sea-ice conditions to improve future environmental safety at both poles’. With these aims in mind, and with the support of the related APPLICATE project and the Association for Polar Early Career Scientists (APECS), a ten day Polar Prediction School took place in Abisko, Sweden in mid-April.

Abisko is a little town of 85 inhabitants, located north of the Arctic Circle (68°N) next to a National Park and a large lake. Due to the interesting habitats found in the region it is an excellent place to undertake polar research. Consequently, a scientific research station is located in the town, where research mainly focuses on biology, ecology, and meteorology.

Heading back to the research station (seen at the back of the picture) after a long hike [Credit: C. Burgard].

The 29 school participants were made up of Master students, PhD students, and PostDocs, with some studying the Arctic and some the Antarctic. The participants had diverse research backgrounds, with research that focused on atmospheric sciences, oceanic sciences, glaciers, sea ice and hydrology of polar regions, and used a range of techniques, from weather or climate models to in-situ or satellite observations. However, in the end, we were all linked together by our interest in the polar regions. Both this diversity and this link in our research helped us to exchange ideas about the common issues and the differences in all our disciplines.

The school programme

The course aimed to broaden students’ knowledge around their very specific PhD area. Therefore, the school covered a huge range of topics including polar lows, polar ocean-sea ice forecasting, remote sensing of the cryosphere, boundary layers, clouds and much more! Each day was made up of a mixture of lectures and practical sessions, which included:

  • Computer modelling exercises, for example using a simple 1D sea ice model
  • Observations, which included measuring temperature and wind from a weather station on the frozen lake next to the station, and daily radiosonde launches at lunchtime, in sync with radiosonde launches worldwide. These results were compared to model predictions each day.
  • Data assimilation, which focused on understanding the shortcomings in reanalysis products that we all use, including sources of uncertainty and error in the products and how they may impact our own work.

After dinner each evening a different group gave an informal weather briefing for the next day, which was often condensed down to how cloudy it would be, the amount of snow predicted (very little), and temperature (which averaged 2-3°C). Not quite the harsh, sub-zero temperatures that most of us had packed for! Each day was broken up by two coffee breaks (always accompanied by an obligatory cinnamon roll!) and meals which were taken all together in the main research building. This dragged everyone out of the lecture room to chat and refresh before the next session.

As is usual for any worthwhile meteorological fieldwork, we installed a small weather mast on the lake [Credit: C. Burgard].

Living Arctic weather for real

The usual weather in Abisko during April is fairly dry with temperatures ranging from 2°C to -6°C. In preparation for the cold, most of us had brought an abundance of wooly jumpers, thick thermal layers and numerous pairs of socks. However, on arrival in Abisko, the sun was shining and it was a balmy 7°C for the first two days. Whilst erecting the meteorology mast many of us were wearing T-shirts and sunglasses, after abandoning our warmer gear. The warm weather was not to last! Cloudy, relatively mild (2°C to -2°C) conditions persisted throughout most of the week, and it remained dry, which made it easier to forecast the weather but we were all hoping for a little snow! Finally, on the final day of the summer school, large snowflakes fell, although sadly it all melted quite quickly.

When we arrived, the whole area was coated in a thick layer of white snow and the frozen lake was covered. However, by the end of our visit, the bare earth was visible, and the top of the lake was slushy puddles of water. The changes in weather throughout the summer school made for interesting observation records. The albedo (reflectivity) of the lake surface went from approximately 0.8 for the fresh, white snow, but was reduced to 0.4 for the darker, water covered lake surface. It was great to see some theory in action!

Exploring the region

Luckily, we were also given a free day , in which we could explore the region, go skiing or just relax. One large group went off hiking, whilst a smaller group went cross country skiing and a few had a walk to the nearby frozen waterfall. But don’t worry, the science still continued! A group of 3 people stayed close by to release the lunchtime radiosonde.

Abisko children launching a radiosonde! [Credit: J. Turton]

Our visit to the area coincided with the exciting annual ice fishing contest! Whilst cars and small DIY tools are common place in many cities, in Abisko it is a snow mobile (or skidoo) and an ice drill, so they were well versed in the art of ice fishing! The majority of the town’s occupants arrived at the lake and started drilling small holes to catch some fish. After two hours, a number of prizes were awarded (e.g for the longest fish caught). Unfortunately, some of the holes were a little too close to our meteorology mast, and some cables were pulled out, but thankfully we still collected some good data!

An important aspect of any research is engaging with the local communities and communicating effectively with them. So all of the summer school attendees gathered by the lake to watch the ice fishing contest, and a large number of the children from Abisko gathered to watch us release the radiosonde, even helping launch one. They found our activities just as exciting as we found theirs!

And we did some science communication as well!

A crucial aspect of science is how you communicate it to a variety of audiences. The way you might discuss your thesis to your viva panel should be completely different to the way you describe your science to your Great Aunt Linda or to a group of 10-year olds who are attending your outreach event. As part of the summer school, we learnt a range of tips and tricks for communicating science, thanks to Jessica Rohde. Jess is the communications officer for IARPC (Interagency Arctic Research Policy Committee) Collaborations and has years of science communication experience under her belt. Each evening we had a short lecture by Jess, which focused on a specific area of communication including presentation slide design, knowing your audience, listening to the audience and finding the story behind your science. Once we had learnt the theory we then put what we had learnt into practice. We did a bit of  improv’, which included 1-minute elevator pitches and tailoring your science to taxi drivers, the Queen of England and models (no not computer models, the Kate Moss variety). An important take-home message was that there is no such thing as the ‘general public’. When designing your outreach event, the ‘general public’ could involve children of all ages (and therefore all learning levels), parents, teachers, professors and pensioners. Therefore, you should listen to the needs of your audience and understand what their motivation is.

You can check out the final results of these sessions here!

In summary…

In the end, although the school was quite intense, everyone was sad to part. We are sure we will all remember this exciting time, where we learnt about the many aspects of polar prediction, and what to consider when tackling science communication. We hope that this school will be organized again in the next years to provide this amazing and unforgettable experience to all those who could not join this year’s Polar Prediction School!

Further reading

Edited by Morgan Jones


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

 

 

Jenny Turton is a post doc working at the institute for Geography at the University of Erlangen-Nuernberg, in the climate system research group. Her current research focuses on the interactions between the atmosphere and surface ice of the 79N glacier in northeast Greenland, as part of the GROCE project. 

 

 

 

Clara Burgard is a PhD student at the Max Planck Institute for Meteorology in Hamburg. She investigates the evolution of sea ice in general circulation models (GCMs). There are still biases in the sea-ice representation in GCMs as they tend to underestimate the observed sea-ice retreat. She tries to understand the reasons for these biases.

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

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

  

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


Why do we care about dynamic changes in Antarctica ?!

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

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

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

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

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

What can we learn from Bayesian statistical approach?

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

Amundsen Sea Embayment : a rapidly thinning area

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

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

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

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

 

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

Bellingshausen Sea Sector :  Not as stable as previously thought…

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

Outlook

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

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

References

Christie, Frazer D. W. et al. 2016. “Four-Decade Record of Pervasive Grounding Line Retreat along the Bellingshausen Margin of West Antarctica.” Geophysical Research Letters 43(11): 5741–49. http://doi.wiley.com/10.1002/2016GL068972.

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

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

Martín-Español, Alba et al. 2016. “Spatial and Temporal Antarctic Ice Sheet Mass Trends, Glacio-Isostatic Adjustment, and Surface Processes from a Joint Inversion of Satellite Altimeter, Gravity, and GPS Data.” Journal of Geophysical Research: Earth Surface 121(2): 182–200. http://dx.doi.org/10.1002/2015JF003550.

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

Paolo, Fernando S, Helen A Fricker, and Laurie Padman. 2015. “Volume Loss from Antarctic Ice Shelves Is Accelerating.” Science 348(6232): 327–31. http://www.sciencemag.org/content/early/2015/03/31/science.aaa0940.abstract.

Edited by Violaine Coulon and Sophie Berger


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

Image of the Week — Biscuits in the Permafrost

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

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


Ice-wedge polygons: Nature’s biscuit-cutter

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

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

Shaping Arctic landscapes

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

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

Are ice wedge polygons climate amplifiers?

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

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

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

Outlook

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

Further Reading

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

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

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

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

On polygons in wetlands: Polygon ponds at sunset | Geolog

Edited by Joe Cook and Sophie Berger


Eleanor Jones is a NERC PhD student on the EU-JPI LowPerm project based at the University of Sheffield and the University Centre in Svalbard. She is investigating the biogeochemistry of ice-wedge polygon wetlands in Svalbard. She tweets as @ElouJones. Contact Email: eljones3@sheffield.ac.uk

Image of the Week – Cure from the Cold?

Image of the Week – Cure from the Cold?

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


Discovering drugs in Earth’s coldest places

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

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

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

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

Glacier microbes: all grown up!

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

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

Microbial wars help humanity

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

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

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

Cultivation’s “1% problem”

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

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

In summary…

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

 

Further reading

Edited by Joe Cook and Clara Burgard


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

Image of the Week – Why is ice colourful?

Image of the Week – Why is ice colourful?

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


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

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

Why is ice colourful?

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

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

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

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

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

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

Polarisation Microscopy

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

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

Further Reading

Personal note on outreach:

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

Edited by Emma Smith


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

Image of the week — Making pancakes

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

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

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


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

Sea ice formation

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

Nilas vs pancakes

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

How to make observations?

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

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

Edited by Sophie Berger


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

 

 

 

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