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

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

REMARK: If you’ve enjoyed reading this post, please make sure you’ve voted for it in EGU blog competition (2nd choice in the list)!

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


Why does the Weddell Polynya form?

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

 

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

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

 

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

 

Why do we care about the Weddell Polynya?

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

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

How often does the Weddell Polynya form?

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

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

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

 

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

 

Further reading

Edited by Clara Burgard


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

Image of the week – How hard can it be to melt a pile of ice?!

Image of the week – How hard can it be to melt a pile of ice?!

Snow, sub-zero temperatures for several days, and then back to long grey days of near-constant rain. A normal winter week in Gothenburg, south-west Sweden. Yet as I walk home in the evening, I can’t help but notice that piles of ice have survived. Using the equations that I normally need to investigate the demise of Greenland glaciers, I want to know: how hard can it be to melt this pile of ice by my door? In the image of this week, we will do the simplified maths to calculate this.


Why should the ice melt faster when it rains?

The icy piles of snow are made of frozen freshwater. They will melt if they are in contact with a medium that is above their freezing temperature (0°C); in this case either the ambient air or the liquid rainwater.

How fast they will melt depends on the heat content of this medium. Bear with me now – maths is coming! The heat content of the medium per area of ice, , is a function of the density and specific heat capacity of the medium. Put it simply, the heat capacity is a measure of by how much something will warm when a certain amount of energy is added to it. also depends on the temperature of the medium over the thickness of the boundary layer i.e. the thickness of the rain or air layer that directly impacts the ice.

Assuming that I have not scared you away yet, here comes the equation:

For liquid water (in this article, the rain): , . For the ambient air: , . So we can plug those values into our equation to obtain the heat content of the rain and of the air. We can consider the same temperature over the same (e.g. Byers et al., 1949), and hence we get .

Stepping away from the maths for a moment, this result means that the heat contained in the rain is more than 3000 times that of the ambient air. Reformulating, on a rainy day, the ice is exposed to 3000 times more heat than on a dry day!

The calculations have obviously been simplified. The thickness of the boundary layer is larger for the atmosphere than for the rain, i.e. larger than just a rain drop. At the same time, the rain does not act on the ice solely by bringing heat to it (this is the thermic energy), but also acts mechanically (kinematic energy): the rain falls on the ice and digs through it. For the sake of this blogpost however, we will keep it simple and concentrate on the thermic energy of the rain.

How long will it take for the rain to melt this pile of ice then?

Promise, this will be the last equation of this blogpost! Reformulating the question, what is the melt rate of that ice? Be it for a high latitude glacier or a sad pile of snow on the side of a road, the melt rate is the ratio of the heat flux from the rain (or any other medium) over the heat needed to melt the ice. It indicates whether the rain brings enough heat to the ice surface to melt it, or whether the ice hardly feels it:

More parameters are involved

  • the density of the ice;
  • the latent heat of fusion, defined as how much energy is needed to turn one kilogram of solid water into liquid water;
  • the heat capacity of the ice (see previous paragraph);
  • the difference between the freezing temperature (0°C) and that of the interior of the ice (usually taken as -20°C).

But what is  I am glad you ask! This heat flux , i.e. , is crucial: it not only indicates how much heat your medium has, but also how fast it brings it to the ice. After all, it does not matter whether you are really hot if you stay away from your target. I actually lied to you, here comes the final equation, defining the heat flux:

We can consider that . We already gave and earlier. As for , this is our precipitation, or how much water is falling on a surface over a certain time (given in mm/hour usually during weather bulletins). On 24th January 2018, as I was pondering why the ice had still not melted, my favourite weather forecast website indicated that (278.15 K) and .

Eventually putting all the numbers together, we obtain . So that big pile on the picture that is about 1 m high will require constant rain for nearly 14 days – assuming that the temperature and precipitation do not change, and neglecting a lot of effects as already explained above. Or it would take just over one hour of the Wikipedia record rainfall of 300 mm/hour – but then ice would be the least of my worries.

The exact same equations apply to this small icy island, melted by the air and ocean [Credit: Monika Dragosics (distributed via imaggeo.egu.eu)]

In conclusion, liquid water contains a lot more heat than the air, but ice is very resilient. The mechanisms involved in melting ice are more complex than this simple calculation from only three equations, yet they are the same whether you are on fieldwork on an Antarctic ice shelf or just daydreaming on your way home.

Other blogposts where ice melts…

Edited by Adam Bateson and Clara Burgard

Image of the Week – Ice caps on Mars?!

Image of the Week – Ice caps on Mars?!

Much like our Planet Earth, Mars has polar ice caps too, one for each pole: the Martian North Polar Ice Cap (shown on our image of the week) and the Southern Polar Ice Cap. Yet, their composition and structure reveals these ice caps are quite different from those of Planet Earth…


Mars refresher

 

Planet Earth and planet Mars [Credit : NASA]

As a refresher, here are some Mars facts:

  • Mars is the 4th planet from the sun.
  • Its equatorial diameter is half the size of the Earth’s, but is bigger than our moon’s.
  • Its mean surface temperature is -63°C (the Earth’s surface is around 14°C)
  • Mars’ atmosphere is 96% carbon dioxide, less than 2% argon, less than 2% nitrogen and less than 1% other gases.
  • Mars’ rotational axis has a tilt similar to Earth’s giving it four seasons as well .

For more detailed pictures and facts about Mars, go have a look on the NASA website here.

What are these Martian ice caps like?

Like Earth, both of Mars’ poles are frozen. It is the only place in the solar system besides Earth where you can find permanent ice caps. These two Martian ice caps are primarily made of frozen water… but not only! During the winter season, the poles permanent bulk of “water ice” are covered by a seasonal layer of frozen carbon dioxide (commonly known as dry ice).

How come? Similar to Earth, during each pole’s respective winter, these ice caps experience continuous darkness for several months. The temperature becomes so cold (freezing point is -126°C !) that carbon dioxide in its atmosphere freezes and falls onto the ground, forming layers of dry ice. In the summer when the sun returns and temperatures warm, the dry ice begins sublimating back into the atmosphere. At the North pole almost all the dry ice turns back into gas and the ice caps shows its water ice, while a layer of frozen carbon dioxide always remains at the South pole. Seasonal variations can thus be observed like those on Earth.

Martian North (left) et South (right) poles [Credit: NASA ]

The northern ice cap on Mars is much bigger than the southern one. It is about 1,000 kilometers wide (roughly the width of Greenland at its widest point) while the South pole is only 350 kilometers in diameter. Yet… they both contain the same amount of ice! If all of this ice was to melt, Mars’ surface would be covered by an ocean that was 18 meters deep. They are thus the currently largest known water reservoirs on the planet.

But… what are these spiral forms on Mars’ ice caps?!

The ice caps at both Martian poles show spiral throughs. According to the ESA, these unique features are the result of strong winds that spiral at the surface of the ice caps due to the same Coriolis effect that exists on Earth. This makes every fluid rotate to the right in the North Hemisphere and to the left in the South Hemisphere.

In the North Pole, one of these throughs, called Chasma Boreale, is particularly big. This 100-kilometer-wide and 2-kilometer-deep canyon roughly cuts the Northern Martian ice cap in half.

Chasma Boreale on the Northern ice cap [Credit: NASA ]

Drilling ice cores on Mars?

The seasonal melting and accumulation of ice occurs while dust deposits, which explain why both Martian polar caps exhibit layered features. They are thus composed of layers of ice mixed with dust (in the scientific jargon, Mars ice caps are called “Polar Layered Deposits”). As for ice cores on Earth, information about the past climate of Mars might be “trapped” in these dust layers. These are essential if we want to find proof of a time when liquid water existed on Mars! Unfortunately, ice cores have not been drilled… yet!

Layers in North Martian Ice Cap (The more dust, the darker the surface) [Credit: NASA/JPL/University of Arizona ]

Further Reading

Edited by David Rounce


Violaine Coulon is a PhD student of the glaciology unit, at the Université Libre de Bruxelles (ULB), Brussels, Belgium. She is using a numerical ice sheet model to investigate the dynamics and stability of the Antarctic Ice Sheet for the past 1.5 million years.


Image of the Week – Arctic changes in a warming climate

Image of the Week – Arctic changes in a warming climate

The Arctic is changing rapidly and nothing indicates a slowdown of these changes in the current context. The Snow, Water, Ice and Permafrost in the Arctic (SWIPA) report published by the Arctic Monitoring and Assessment Program (AMAP) describes the present situation and the future evolution of the Arctic, the local and global implications, and mitigation and adaptation measures. The report is based on research conducted between 2010 and 2016 by an international group of over 90 scientists, experts, and members of Arctic indigenous communities. As such, the SWIPA report is an IPCC-like assessment focussing on the Arctic. Our Image of the Week summarizes the main changes currently happening in the Arctic regions.


What is happening to Arctic climate currently?

The SWIPA report confirms that the Arctic is warming much faster than the rest of the world, i.e. more than twice the global average for the past 50 years (Fig. 2). For example, Arctic surface air temperature in January 2016 was 5°C higher than the average over 1981-2010. This Arctic amplification is due to a variety of climate feedbacks, which amplify the current warming beyond the effects caused by increasing greenhouse gas concentrations alone (see the SWIPA report, Pithan & Mauritsen (2014) and this previous post for further information).

Fig.2: Anomaly of Arctic and global annual surface air temperatures relative to 1981-2010 [Credit: Fig. 2.2 of AMAP (2017), revised from NOAA (2015)].

This fast Arctic warming has led to the decline of the ice cover over both the Arctic Ocean (sea ice) and land (Greenland Ice Sheet and Arctic glaciers).

For sea ice, not only the extent has dramatically decreased over the past decades (see Stroeve et al. 2012 and Fig. 3), but also the thickness (see Lindsay & Schweiger, 2015). Most Arctic sea ice is now first-year ice, which means that it grows in autumn-winter and melts completely during the following spring-summer. In contrast, the multiyear sea-ice cover, which is ice that has survived several summers, is rapidly disappearing.

Fig. 3: Arctic sea-ice extent in March and September from the National Snow and Ice Data Center (NSIDC) and the Ocean and Sea Ice Satellite Application Facility (OSI SAF) [Credit: Fig. 5.1 of AMAP (2017)].

In terms of land ice, the ice loss from the Greenland Ice Sheet and Arctic glaciers has been accelerating in the recent decades, contributing a third of the observed global sea-level rise. Another third comes from ocean thermal expansion, and the remainder comes from the Antarctic Ice Sheet, other glaciers around the world, and terrestrial storage (Fig. 4, see also this previous post and Chapter 13 of the last IPCC report).

Fig. 4: Global sea-level rise contribution from the Arctic components (left bar), Antarctic Ice Sheet and other glaciers (middle-left bar), terrestrial storage (middle-right bar) and ocean thermal expansion (right bar) [Credit: Fig. 9.3 of AMAP (2017)].

Besides contributing to rising sea levels, land-ice loss releases freshwater into the Arctic Ocean. Compared with the 1980-2000 average, the freshwater volume in the upper layers of the Arctic Ocean has increased by more than 11%. This could potentially affect the ocean circulation in the North Atlantic through changes in salinity (see this previous post).

Other changes currently occurring in the Arctic include the decreasing snow cover, thawing permafrost, and ecosystem modifications (e.g. occurrence of algal blooms, species migrations, changing vegetation, and coastal erosion). You can have a look at the main Arctic changes in our Image of the Week.

 

Where are we going?

The SWIPA report highlights that the warming trends in the Arctic will continue, even if drastic greenhouse gas emission cuts are achieved in the near future. For example, mean Arctic autumn and winter temperatures will increase by about 4°C in 2040 compared to the average over 1981-2005 according to model projections (Fig. 5, right panel). This corresponds to twice the increase in projected temperature for the Northern Hemisphere (Fig. 5, left panel).

Fig. 5: Autumn-winter (NDJFM) temperature changes for the Northern Hemisphere (left) and the Arctic only (right) based on 36 global climate models, relative to 1981-2005, for two emission scenarios [Credit: Fig. 2.15 of AMAP (2017)].

This Arctic amplification leads to four main impacts:

  1. The Arctic Ocean could be ice-free in summer by the late 2030s based on extrapolated observation data. This is much earlier than projected by global climate models.

  2. Permafrost extent is projected to decrease substantially during the 21st Century. This would release large amounts of methane in the atmosphere, which is a much more powerful greenhouse gas than carbon dioxide.

  3. Mean precipitation and daily precipitation extremes will increase in a warming Arctic.

  4. Global sea level will continue to rise due to melting from ice sheets and glaciers, ocean thermal expansion, and changes in terrestrial storage. However, uncertainties remain regarding the magnitude of the changes, which is linked to the different emission scenarios and the type of model used.

What are the implications?

A potential economic benefit to the loss of Arctic sea ice, especially in summer, is the creation of new shipping routes and access to untapped oil and gas resources. However, besides this short-term positive aspect of Arctic changes, many socio-economic and environmental drawbacks exist.

The number of hazards has been rising due to Arctic changes, including coastal flooding and erosion, damage to buildings, risks of avalanches and floods from rapid Arctic glacier melting, wildfires, and landslides related to thawing permafrost. Furthermore, Arctic changes (especially sea-ice loss) may also impact the climate at mid-latitudes, although many uncertainties exist regarding these possible links (see Cohen et al., 2014).

What can we do?

The SWIPA report identifies four action steps:

  1. Mitigating climate change by decreasing greenhouse gas emissions. Implementing the Paris Agreement would allow stabilizing the Arctic temperatures at 5-9°C above the 1986-2005 average in the latter half of this century. This would also reduce the associated changes identified on our Image of the Week. However, it is recognized that even if we implement the Paris Agreement, the Arctic environment of 2100 would be substantially different than that of today.

  2. Adapting to impacts caused by Arctic changes.

  3. Advancing our understanding of Arctic changes through international collaboration, exchange of knowledge between scientists and the general public, and engagement with stakeholders.

  4. Raising public awareness by sharing information about Arctic changes.

Further reading

Edited by Scott Watson and Clara Burgard


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

Image of the Week – Of comparing oranges and apples in the sea-ice context

Image of the Week – Of comparing oranges and apples in the sea-ice context

In the last fifty years, models and observations have enabled us to better understand sea-ice processes. On the one hand, global climate models have been developed, accounting for the sea-ice component in the climate system. On the other hand, satellite instruments have been developed to monitor the “real” sea-ice evolution. These satellite observations are often used to evaluate climate models. However, lately, doubts have arisen to whether comparing model output to observations is the most reasonable method. Are we sometimes comparing oranges to apples? To discuss this matter, sea-ice modelers and sea-ice observers met over three days in Hamburg earlier this month at the Workshop on improved satellite retrievals of sea-ice concentration and sea-ice thickness for climate applications.


How do we measure past and current seaice changes?

The great advantage of satellites over in-situ measurements is that they measure changes in sea-ice concentration (fraction of ocean covered by sea ice in a given area) and sea-ice thickness in a continuous way with an almost complete spatial coverage of the polar regions (see this previous post) and with a high temporal resolution.
Of course, satellites do not directly measure sea-ice concentration. Rather, they measure the brightness temperature (left part of Fig. 2), which is a measure of the radiation emitted by the Earth’s surface and atmosphere, with passive microwave sensors (such as SSM/I). From this brightness temperature, it is possible to compute sea-ice concentration (see this article for further information). Microwave sensors are used because they can “see” the surface through clouds and during polar night, which is not possible with visible sensors (such as MODIS).

In a similar way, satellites do not directly measure sea-ice thickness. Rather, they measure sea-ice freeboard (right part of Fig. 2), i.e. the height of the ice above the sea surface, with different kinds of sensors (laser altimetry [e.g. ICESat], radar altimetry [CryoSat]). Sea-ice thickness is then retrieved through appropriate algorithms (see e.g. this article).

 

Fig. 2: Satellite measurement techniques that lead to the observed brightness temperatures and sea-ice freeboard [Credit: C. Burgard].

 

Are the satellite retrievals accurate?

Each method of deriving sea-ice concentration or thickness from satellite measurements has its own uncertainties. For example, algorithms to retrieve sea-ice concentration use several assumptions about the state of the atmosphere and surface emissivity. Also, melt ponds and thin ice show up as lower concentration regions. Similarly, different assumptions about snow depth on ice and about sea-ice density impact the retrieved sea-ice thickness. Therefore, the sea-ice variables retrieved from satellite observations may deviate from their actual “real” state.

 

How do we project future sea-ice changes?

In order to project the future sea-ice evolution, different climate models are used (see this article for example). These climate models are usually evaluated against satellite observations in order to assess their performance. While all models present biases compared to observations, it cannot always be concluded that this is necessarily a problem of the models as observations also have uncertainties as previously said. Therefore, the main discussions at the workshop in Hamburg (Fig. 3) were about reducing uncertainties in the comparison between observations and models.

 

How can we better compare satellite observations and models?

The discussion in Hamburg was very lively as modelers and observers exchanged about how they actually reach the results they provide, explaining in detail their models and algorithms. It became rapidly clear that comparing observed sea-ice concentration to modeled sea-ice concentration might be like comparing apples to oranges under certain circumstances.

Thomas Lavergne, a researcher at the Norwegian Meteorological Institute, gave a presentation related to this discussion by presenting the picture that is our Image of the Week. The classical method up to now has always been to transform the measured satellite signal into a “satellite product”, a quantity that is directly computed by models (direction from right to left in the Image of the Week), so that we can compare this quantity to the corresponding model variable. As already mentioned, this can lead to assumptions and introduce errors into the observations, while one would expect observations to be the best representation of the “real” world.

Another possible approach, already well accepted in the community of weather forecasting, is to transform the model variables all the way into simulated brightness temperatures and compare these to satellite data (direction from left to right in the Image of the Week). The algorithms that transform model variables into simulated satellite quantities are observation operators. Although an active field of research, the observation operators for sea ice are not ready, and the comparison of sea-ice simulations to satellite observations will for the foreseeable future rely on satellite “products”.

At the workshop, Lavergne advocated for a middle-ground solution, where satellite products “take a step back” and climate models “take a step forward” using tailored observation operators. This would reduce the need for assumptions in the satellite products but still be manageable for modelers, and would most likely offer the best consensus for the two communities. This way, observed and modeled quantities can still be compared with each other and uncertainties introduced into the comparison can be reduced.

Fig. 3: Happy sea-ice observers and sea-ice modelers in Hamburg [Credit: Julika Doerffer, CEN, Universität Hamburg]

 

Perspectives

The workshop aim was to bring together sea-ice observers and modelers. While no real consensus on the proposed approach was found, the reflection has been launched and probably deserves some more attention in the future in order to better compare sea-ice models and satellite observations. This might move the debate from an apple-to-oranges comparison to a pear-to-pear one. This will hopefully improve sea-ice models and satellite observations and improve future projections of sea-ice evolution.

 

Further reading

With contributions by Thomas Lavergne and Clara Burgard

Edited by Clara Burgard and Sophie Berger


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

Image of the Week — Think ‘tank’: oceanography in a rotating pool

Miniature ocean at the Coriolis facility in Grenoble. [Credit: Mirjam Glessner]

To study how the ocean behaves in the glacial fjords of Antarctica and Greenland, we normally have to go there on big icebreaker campaigns. Or we rely on modelling results, especially so to determine what happens when the wind or ocean properties change. But there is also a third option that we tend to forget about: we can recreate the ocean in a lab. This is exactly what our Bergen-Gothenburg team has been doing these last weeks at the Coriolis facility, in sunny Grenoble.


How to build your own miniature ocean

Take a 13m diameter (circular) swimming pool. Install it on a rotating platform, and start turning to simulate the Coriolis force, i.e. the impact of the Earth rotation on the flow. Fill it so that the water level reaches 90cm. Actually, the exact value does not matter and can be changed; just make sure that your tank width is an order of magnitude larger than your depth, and that you do not overflow everywhere on the lab floor. Congratulations, you have an ocean! But for now it is a bit boring.

Let’s add some stratification and density-driven currents. As we explained in a previous entry, all you need to do for that is change the temperature and/or salinity of your water. The people here at the Coriolis facility say that changing the salinity is easier than the temperature, so ok, put a source somewhere in your tank that will spit out salty water. Make it even more realistic: have some trough, underwater mountains, solid ice shelves etc. Or rather, some Plexiglas of the corresponding shape. Now you have a beautiful part of the ocean with realistic currents!

But how do you observe it? You can lower probes into the water at specific locations, as if you were doing miniature CTD casts in your miniature ocean. Or you can visualise the whole full-depth flow: add tracer particles to the water flowing from the source (in our case, biodegradable plastic), shoot lasers at it at various depth levels, and take high resolution pictures as you do so. Then, you can track the particles from one image to the next to infer their velocity, using a method called PIV.

 

By the way, it looks way neater than on this image – that one is just from our overview camera, for fun. [Credit: Céline Heuzé]

What does it look like when you fire lasers at a large rotating tank?

In a nutshell, it looks like this:

The water flows from the source on the right of the image, towards the ‘ice shelf’ on the left. We are watching the scene from above, from our office that rotates with the tank. The laser successively illuminates several levels from the bottom of the channel to the water surface, revealing the changing structure of the flow with depth. In our real experiment, it took more than 10 minutes for the water to reach the ‘ice shelf’ – here, I have slightly accelerated it.

It is surprisingly peaceful and relaxing to watch. Well, there is tension and suspense regarding what the flow will do since this is, after all, why we are here. But otherwise you are in the dark, with particles shining all around you, in the silence except for the low-squeeking noise of the rotating tank, gently rocked by the vibrations of the platform, and there is not much you can do but wait and enjoy the view. You can also count how many undesired bubbles and dead insects floating at the surface you can see!

Why do we need rotating tank experiments?

As we explained in this blog, the future of the Antarctic ice sheet is unknown due to marine ice sheet instability. We do not know under which conditions the floating ice shelves that block (‘buttress’) the big land-based ice sheet may collapse. In particular, we do not know what controls the flow of comparatively warm waters that melt the ice shelves:

  •  under which conditions do these waters penetrate under the ice?
  •  at which depths do they sit?
  •  what are the impacts of stratification and the shape of the ice shelf itself?

These questions cannot easily be answered by going in the field. We would need access to many ice shelves, year round, and the ability to observe the flow everywhere –including under the ice– synoptically. Instead in the lab, we just need to adjust our flow speed, or the rotation speed of the tank, or the amount of salt in the source, and we are ready to observe!

Further reading:

The blog of the team: https://skolelab.uib.no/blogg/darelius/

Our blog post about the video game Ice Flows!, illustrating the marine ice sheet instability

Edited by Sophie Berger

Image of the Week – ROVing in the deep…

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

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


This is sea ice… seen from the ocean

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

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

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

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

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

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

Why do we need such observations?

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

 

Further reading

Edited by Clara Burgard

Image of the week – Micro-organisms on Ice!

Image of the week – Micro-organisms on Ice!

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


Why study micro-organisms on glaciers?

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

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

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

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

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

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

Data collections – Six days on THE glacier

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

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

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

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

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

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

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

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

Further Reading

Edited by Emma Smith


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

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

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

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


Mass balance of ice sheets

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

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

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

A new method to estimate ice dynamic changes

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

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

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

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

What does this study tell us?

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

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

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

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

Further reading

Edited by Clara Burgard and Emma Smith


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

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

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

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


PIPERS expedition observed dragon-skin ice

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

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

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

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

Chaotic ice formation caused by strong winds

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

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

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

The importance of polynyas for ocean-atmosphere interactions

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

Further reading

 

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


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