CR
Cryospheric Sciences

Sea-ice

Image of the Week – Stuck in the ice: could it have been predicted?

Image of the Week –  Stuck in the ice: could it have been predicted?

Expeditions in the Southern Ocean are invaluable opportunities to learn more about this fascinating but remote region of the world. However, sending vessels to navigate the hostile Antarctic waters is an expensive endeavor, not only financially but also from a human perspective. When vessels are forced to turn back due to hazardous conditions or, even worse, become stuck in the ice (as shown in our Image of the Week), a mission full of expectations can quickly turn into a nightmare. Hence there is an increasing demand for reliable information on the navigability of the Southern Ocean a few weeks to a few months in advance. This information could support the final decision whether to start the journey or not, and would allow minimizing the associated risks.


What’s the problem?

In late February 2018, the British vessel RRS James Clark Ross was heading to the Eastern Antarctic Peninsula to investigate the consequences of the calving of a massive iceberg from the Larsen C ice shelf. Unfortunately the vessel had to turn back before reaching its goal due to the unexpected presence of thick sea ice in the region. This story is not unusual. During Christmas 2013, a Russian ship named the Akademik Shokalskiy also got stuck in several meters of Antarctic sea ice. Ironically, one of the rescuing vessels itself (the Chinese Xuě Lóng) got trapped in the ice as well. To prevent such events from happening again, we need to be able to predict the upcoming sea-ice conditions. Can sea-ice conditions be forecast at seasonal time scales? If so, how?

 

Antarctic sea ice, the Year of Polar Prediction and SIPN South

To prevent accidents and unforeseen problems, one goal of the Year Of Polar Prediction is to enhance environmental forecasting capabilities from operational (hours to days) to tactical (weeks to months) time scales in high latitude regions. Several studies support the notion that Antarctic sea ice may be predictable a few months ahead, at least in certain regions (Holland et al. 2017, Chen and Yuan 2004, Holland et al. 2013, Marchi et al. 2018).

To investigate further the predictability of Antarctic sea ice, the Sea Ice Prediction Network South (SIPN South) was launched in 2017. It is a two-year international project endorsed by the YOPP. SIPN South pursues three strategic objectives:

  • Hosting seasonal outlooks of Antarctic sea ice to better understand the sources of sea-ice predictability and the origins of systematic forecast errors in different types of models.
  • Providing news and information on the current state of Antarctic sea ice, disseminating research to a wider audience and reporting ongoing field campaigns.
  • Coordinating realistic seasonal prediction exercises to investigate the potential use of this information for users and customers, primarily ships navigating in the region.

 

February 2018 seasonal sea-ice forecasts

As a first major milestone, SIPN South provided coordinated forecasts of sea ice for February 2018. February is the month with the smallest sea-ice area in the Antarctic, and therefore most of the shipping traffic in the region happens around that time. Participants were asked to provide an estimation of sea-ice coverage (area, concentration) for each day of February 2018, and were asked to issue their predictions by mid-December 2017. 13 research groups participated in this first forecasting experiment, following different approaches: several groups used fully coupled climate dynamical models, while others applied statistical regression methods to predict future ice conditions.

As we all know, the weather is unpredictable beyond a few days. However, previous research has suggested that the statistics of weather (its mean, its variability) can potentially be predicted from months to decades, due to the coupling of the atmosphere with “slower” components of the climate system like the ocean. To reflect this and to accurately estimate the statistics of weather, groups tend to provide not just one forecast, but several of them. These “ensembles” of forecasts provided by each group therefore represent all possible states of the atmosphere, ocean and ice that may prevail in February 2018 – given the known initial conditions of December.

The results of the coordinated experiment are shown in Figure 2. The February mean sea-ice area is shown for each group (colors), along with two actual observational references (black). Bear in mind that the forecast data were issued two months before the actual target date! Here, the forecasts are expressed as anomalies with respect to a reference climatology. All forecasts tend to overestimate the February sea ice area in the Ross Sea. A reason for this wrong estimation might be a very unusual cyclone, which passed over the Ross Sea around the 20th of January 2018 (i.e., between the time the forecasts were issued and the period for verification). This cyclone brought relatively warm air into the region. Furthermore it fractured the ice, opening more areas of open water and possibly increasing the effect of the ice-albedo feedback. Events like this one are not individually predictable several weeks in advance, but a well-designed forecasting system should at least account for this possibility. Despite running ensembles of forecasts, the sea-ice reduction in the Ross Sea was not captured by most forecasts. This may point towards a common and systematic deficiency in these prediction systems.

Figure 2: February 2018 mean regional sea-ice area anomaly (compared to 1979-2014 observed climatology) by longitude, for the 13 submissions, with observed estimates given in black. Solid lines show the ensemble mean for each contribution, with transparent shading indicating the ensemble range (min-max) [Credit: F. Massonnet].

Communicating climate information

Sea-ice area, as shown in Fig. 2, is a primary parameter used by scientists to quantify ice presence in a given region. It is also a useful number to diagnose model-data mismatch. However, sea-ice area is of little use for those who actually need climate information. For someone operating a vessel, the important information is how likely that vessel is to encounter sea ice in a given region for a given day in February. Information from Fig. 2, while certainly useful to scientists, is meaningless to those willing to extract practical information for navigation.

Alongside the work to understand fundamental drivers of sea-ice predictability in order to eventually improve the predictions, it is necessary to consider how potential users will interact with the forecasts. As explained above, climate forecasts are probabilistic in nature. Communicating probabilistic information to a non-trained audience is always a challenging task: for example, how would you interpret a forecast saying that there is a 50% chance of rain for tomorrow?

To reflect the irreducible uncertainty of climate forecasts (see previous section), sea-ice forecasts are generally expressed in terms of sea-ice probability, i.e. the probability that a given region of the Southern Ocean has sea-ice concentration larger than 15%. This probability is derived for each day and each grid cell from the ensemble forecasts contributed by each group (Fig. 3). If well calibrated, this type of information can be useful to those planning operations weeks in advance. For example, all but one model had forecast a high (>80%) probability of ice presence in the Larsen C area (eastern tip of the Antarctic Peninsula) where the RRS James Clark Ross got stuck five months ago. That is, there was a high risk, according to those forecasts, that ice would be present in that area in February. Of course, this does not mean that navigation would have been impossible (ice breakers can still operate in icy waters, provided the ice is thin), but these forecasts provided a first-order warning that there was a significant risk of encountering hazardous ice conditions there.

Figure 3: Probability of sea-ice presence for 15th February 2018, as forecasted by the five groups that submitted daily sea-ice concentration information. The sea-ice edge as observed by two products is shown in white. The probability of presence for a given day corresponds to the fraction of ensemble members that simulate sea-ice concentration larger than 15% in a given grid cell for that day. A dynamic animation of the figure showing all 28 days of February is available on the SIPN South website. [Credit: F. Massonnet]

Forecasting February 2019

The core phase of the Year of Polar Prediction entails “Special Observing Periods”, that is, intensive efforts to monitor the Arctic and Antarctic regions but also to enhance modeling activities (see this previous post). The (unique) Special Observing Period in the Southern Ocean will take place between mid-November 2018 and mid-February 2019. A new call for contributions will be launched by SIPN South to collect sea-ice forecasts for austral summer 2019, hoping that the first exercise in 2018 will raise the interest of even more research groups. A key question will be to assess whether the systems will be able to forecast better the sea-ice conditions in the challenging Ross Sea area, where most forecasts failed. Better insights will hopefully be gained in tracing the origin of systematic model error and lead to an improvement of Antarctic sea ice predictions within the next decade. As reliable climate information is crucially needed in this remote but important region of the world, future efforts to predict Antarctic sea ice will be very welcome!

 

Further reading

Edited by Adam Bateson and Clara Burgard

 


François Massonnet is a F.R.S.-FNRS Post-Doctoral Researcher at the Université catholique de Louvain and scientific collaborator at the Barcelona Supercomputing Center (Spain). He is assessing climate models as tools to understand (retrospectively and prospectively) polar climate variability and beyond. He tweets as @FMassonnet. Contact Email: francois.massonnet@uclouvain.be

 

 

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 — 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.

Image of the Week — Seasonal and regional considerations for Arctic sea ice changes

Monthly trends in sea ice extent for the Northern Hemisphere’s regional seas, 1979–2016. [Credit: adapted from Onarheim et al (2018), Fig. 7]

The Arctic sea ice is disappearing. There is no debate anymore. The problem is, we have so far been unable to model this disappearance correctly. And without correct simulations, we cannot project when the Arctic will become ice free. In this blog post, we explain why we want to know this in the first place, and present a fresh early-online release paper by Ingrid Onarheim and colleagues in Bergen, Norway, which highlights (one of) the reason(s) why our modelling attempts have failed so far… 


Why do we want to know when the Arctic will become ice free anyway? 

As we already mentioned on this blog, whether you see the disappearance of the Arctic sea ice as an opportunity or a catastrophe honestly depends on your scientific and economic interests.  

It is an opportunity because the Arctic Ocean will finally be accessible to, for example: 

  • tourism; 
  • fisheries; 
  • fast and safe transport of goods between Europe and Asia; 
  • scientific exploration. 

All those activities would no longer need to rely on heavy ice breakers, hence becoming more economically viable. In fact, the Arctic industry has already started: in summer 2016, the 1700-passenger Crystal Serenity became the first large cruise ship to safely navigate the North-West passage, from Alaska to New York. Then in summer 2017, the Christophe de Margerie became the first tanker to sail through the North-East passage, carrying liquefied gas from Norway to South Korea without an ice breaker escort, while the Eduard Toll became the first tanker to do so in winter just two months ago. 

On the other hand, the disappearance of the Arctic sea ice could be catastrophic as having more ships in the area increases the risk of an accident. But not only. The loss of Arctic sea ice has societal and ecological impacts, causing coastal erosion, disappearance of a traditional way of life, and threatening the whole Arctic food chain that we do not fully understand yet. Not to mention all of the risks on the other components of the climate system. (See our list of further readings at the end of this post for excellent reviews on this topic). 

Either way, we need to plan for the disappearance of the sea ice, and hence need to know when it will disappear. 

Arctic sea ice decrease varies with region and season 

In a nutshell, the new paper published by Onarheim and colleagues says that talking about “the Arctic sea ice extent” is an over simplification. They instead separated the Arctic into its 13 distinct basins, and calculated the trends in sea ice extent for each basin and each month of the year. They found a totally different behaviour between the peripheral seas (in blue on this image of the week) and the Arctic proper, i.e. north of Fram and Bering Straits (in red). As is shown by all the little boxes on the image, the peripheral seas have experienced their largest long term sea ice loss in winter, whereas those in the Arctic proper have been losing their ice in summer only. In practice, what is happening to the Arctic proper is that the melt season starts earlier (note how the distribution is not symmetric, with largest values on the top half of the image).  

Talking about Arctic sea ice extent is an over simplification

Moreover, Onarheim and colleagues performed a simple linear extrapolation of the observed trends shown on this image, and found that the Arctic proper may become ice-free in summer from the 2020s. As they point out, some seas of the Arctic proper have in fact already been ice free in recent summers. The trends are less strong in the peripheral seas, and the authors write that they will probably have sea ice in winter until at least the 2050s. 

So, although Arctic navigation should become possible fairly soon, in summer, you may need to choose a different holiday destination for the next 30 winters. 

Melting summer ice. [Credit: Mikhail Varentsov (distributed via imaggeo.egu.eu)]

But why should WE consider the regions separately? 

The same way that you would not plan for the risk of winter flood in New York based on yearly average of the whole US, you should not base your plan for winter navigation from Arkhangelsk to South Korea on the yearly Arctic-wide average of sea-ice behaviour. 

Scientifically, this paper is exciting because different trends at different locations and seasons will also have different consequences on the rest of the climate system. If you have less sea ice in autumn or winter, you will lose more heat from the ocean to the atmosphere, and hence impact both components’ heat and humidity budget. If you have less sea ice in spring, you may trigger an earlier algae bloom. 

As often, this paper highlights that the Earth system behaves in a more complex fashion that it first appears. Just like global warming does not prevent the occurrence of unpleasantly cold days, the disappearance of Arctic sea ice is not as simple as ice cubes melting in your beverage on a sunny day.  

Reference/Further reading

Bhatt, U. S., et al. (2014), Implications of Arctic sea ice decline for the Earth system. Ann. Rev. Environ. Res., 39, 57-89 

Meier, W. N., et al. (2014), Arctic sea ice in transformation: A review of recent observed changes and impacts on biology and human activity. Reviews of Geophysics, 52(3), 185-217. 

Onarheim, I., et al. (2018), Seasonal and regional manifestation of Arctic sea ice loss. Journal of Climate, EOR.  

Post, E., et al. (2013), Ecological consequences of sea-ice decline. Science, 341, 519-524 

Edited by Sophie Berger

Image of the Week – The colors of sea ice

Image of the Week – The colors of sea ice

The Oscars 2018 might be over, but we have something for you that is just as cool or even cooler (often cooler than -20°C)! Our Image of the Week shows thin sections of sea ice photographed under polarized light, highlighting individual ice crystals in different colors, and is taken from a short video that we made. Read more about what this picture shows and watch the movie about how we got these colorful pictures…


Sea ice can vary in salinity

Sea ice forms differently than fresh water ice due to its salt content. When sea water begins to freeze, the ice crystals aren’t able to incorporate salt into their structure and hence reject salt into the surrounding water. This increases the density of the remaining sea water which sinks (see this previous post). Some salty water gets trapped between the crystals though. This water will also slowly freeze, always rejecting the salts into the remaining water. The saltier the water, the lower its freezing point. This means the remnant very salty water, which we call brine, remains liquid even at temperatures below -20oC!

Sea ice crystals can vary in shape

The first layer of sea ice is typically granular – the crystals are small and round, with a diameter around one centimeter. This is because this layer is formed in open seas, where the crystals which go on to form this layer are spun and broken up by surface waves. This granular structure includes lots of ‘pockets’ of trapped brine. Under this surface ice layer, which is typically 10-30 cm thick, ice starts growing in more sheltered conditions. Such sea ice is columnar. The crystals are flat and elongated – like layers in a vertical cake. The brine is trapped between these layers in brine channels. When ice is relatively warm, for example shortly after freezing or before it starts melting, such channels are wide and can be connected. Brine can then escape from them at the lower end into the ocean. The channels also allow small, hardy microscopic plants and animals to travel through the ice. Often air bubbles are trapped in them too.

Sea ice can vary in how it looks too!

The size and form of sea ice crystals – sea ice texture – impacts various properties of the sea ice including its salt content, density and suitability as a habitat. It also influences the optical properties of ice, however. While pure water ice is transparent (see this previous post), sea ice appears milky. That is because of brine channels and bubbles between the crystals.

When looking at large regions of sea ice from space by sensors mounted on satellites, sea ice texture will be important too. Visible light has a short wavelength and this means it only penetrates into the top millimeter of ice. Images collected in the visible light range (see this previous post) will show features dominated by the surface properties of the ice. In comparison, microwaves have a longer wavelength and can penetrate deeper into the ice. Hence imagery of the sea ice cover collected in the microwave spectrum of light (see this previous post) will display features influenced by the internal structure of the sea ice in addition to the surface features.

 

The video below shows how the sea ice samples are analyzed for texture and how we got the colorful pictures for our Image of the Week…

 

Further reading

Edited by Adam Bateson and Clara Burgard


Polona Itkin is a Post-doctoral Researcher at the Norwegian Polar Institute, Tromsø. She investigates the sea ice dynamics of the Arctic Ocean and its connection to the sea ice thickness. In her work she combines the information from in-site observations, remote sensing and numerical modeling. Polona is part of the social media project ‘oceanseaiceNPI’ – a group of scientists that communicates their knowledge through social media channels: Instagram.com/OceanSeaIceNPI, Twitter.com/OceanSeaIceNPI, Facebook.com/OceanSeaIceNPI, contact Email: polona.itkin@npolar.no

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

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 – The Gap, the Bridge, and the Game-changer

The Gap, the Bridge, and the Game-changer, together with many of the passive microwave satellite missions relevant for sea ice concentration mapping for the period 1980s to 2030s [Credit: T. Lavergne].

The Gap, the Bridge, and the Game-changer are three series of satellites. They carry instruments that measure the microwave radiation emitted by the Earth (called passive microwave instruments), while flying 800 km above our heads at 7,5 km/s. Since the late 1970s, most sea ice properties (concentration, extent, area, velocity, age and more!) have been measured with such passive microwave instruments.
So who are the Gap, the Bridge, and the Game-changer? Their story is what this Image of the Week is about…


The Gap

Since 1978, the U.S. equipped 11 satellites with passive microwave instruments to observe global sea ice. These instruments are called SMMR, SSM/I and SSMIS. Their measurements have produced a continuous, almost 40 year long climate data record of sea ice (see how satellite observations are converted into sea ice properties in this previous post). However, as described late last year in a Nature article, the remaining three of these instruments are ageing, already beyond their expected lifetime, and with no planned continuation from the U.S (see SSMIS F16-18 on our Image of the Week).

Europe will be operating a series of similar instruments (the MicroWave Imagers, MWI) on their 2nd Generation Polar System from 2023. A (looming future) gap is feared if the last U.S. instruments fail before the European ones are fully operating.

The decline of summer sea ice extent in the Arctic is an iconic indicator of climate change and U.S. satellites have enabled and sustained its monitoring for all these years (see this earlier post). More than a news magnet, the satellite time series is a back-bone for our understanding of the evolution of global sea ice. It is a key asset for developing and evaluating our climate models. The possibility of a data gap understandably caught the attention of the scientific community and the general public. This (looming future) «Gap» is the first character in our story.

The Bridge

The «Bridge» is known under the code name Feng Yun 3 (FY3) MWRI and is Chinese. The FY3 programme, operated by the Chinese Meteorological Administration (CMA), is a series of satellites with passive microwave instruments very similar to the ones on the American and European satellites. FY3D -the 4th satellite in the FY3 series- was successfully launched in late 2017, bridging the data gap that was feared to happen, even if the remaining U.S. SSMIS satellites would fail next month.

Over the past few months, scientists at the EUMETSAT OSI SAF (the European Organization for the Exploitation of Meteorological Satellites – Ocean and Sea Ice Satellite Application Facility) have been investigating the quality of FY3 passive microwave data. They adapted their algorithms to retrieve sea ice concentration from raw satellite measurements, so that they yield very similar accuracy to the sea ice concentration data they obtain from the SSMIS. An example sea ice concentration map using the OSI SAF algorithm on raw FY3 data is shown below. Such maps can extend the climate data record released in early 2017, should the last SSMIS fail.

Sea Ice Concentration maps for February 6th 2018 (left: Northern Hemisphere, right: Southern Hemisphere). These are computed by the OSI SAF algorithms applied on raw FY3 MWRI data [Credit: A. Sørensen].

Access to the FY3 data was facilitated by bi-lateral agreements between EUMETSAT and CMA. National and international space agencies coordinate their activities in a variety of forums such as CEOS (Comittee on Earth Observation Satellites), CGMS (Coordination Group for Meteorological Satellites) or WMO PSTG (the World Meteorological Organization Polar Space Task Group) to cite a few. This global-scale coordination goes mostly unnoticed to the public and the scientific community. It is, however, a great aid for our ability to continuously monitor and predict the global environment.

You might think that, now that the Gap is Bridged, I have nothing more to tell you about passive microwave satellites for sea ice observations? Well, think again. There is a third character to our story: the «game-changer».

The Game-changer

Without further teasing you, our «game-changer» is CIMR. CIMR stands for the «Copernicus Imaging Microwave Radiometer». It might get selected for joining the family of Copernicus satellites some time in the late 2020s.

Before I tell you what makes CIMR so special, we need a short introduction on what passive microwave instruments are, why we like them for observing sea ice, and how they work:

T. Lavergne (2018) Passive Microwave Remote Sensing of Sea Ice : a crash-course in just four list items, Int. J. of Short Lists

  1. The best satellite instruments for measuring sea ice use the microwave part of the electromagnetic spectrum (from ~1 to ~100 GHz). This type of radiation does not depend on Sun light, and is not blocked by clouds.

  2. Passive microwave instruments record a tiny amount of radiation naturally emitted at the surface of the Earth and in the atmosphere. Aboard the satellite, the radiation is reflected by an antenna towards a recording instrument: the radiometer.

  3. Radiometers can measure at several frequencies. Once the images are back at the processing centers on Earth, algorithms are applied to compute geophysical products such as sea ice concentration.

  4. Radiometers with low frequencies (e.g. 6 GHz) yield best accuracy for sea ice concentration products. The bigger the antenna, the better the final resolution of the product.

One of a kind, the CIMR will focus on the low frequencies (6, 10, and 18 GHz), and fly an antenna big enough to ensure much better resolution than any of the passive microwave instruments we ever used before. This requires the antenna of CIMR to be substantially larger than that of SSMIS (60cm diameter), MWI (75cm) or even AMSR2 (2.1m)! The AMSR-E instrument and its followers were game-changers 15 years ago, and still offer the best resolution today… but future operational models and polar applications will require better sea ice products all too soon.

An exciting time opens for satellite-based observations of polar sea ice, as the pre-studies for CIMR are started by the European Space Agency this spring! Will industry take-up the challenge and build a big enough antenna for CIMR? Will CIMR be selected as EU’s future polar Copernicus mission? If “yes” to both, Europe will have a game-changer: high-resolution all-weather daily global accurate mapping of sea ice concentration.

I will definitely follow the developments with CIMR! Maybe I’ll tell you how it went in a future blog post? 🙂

Note: Were there too many acronyms in this blog? Well, we are sorry about that. Those satellite-people just LOVE their acronyms! A good resource for searching what satellite acronyms mean is the “Space capability” page from the World Meteorological Organization: https://www.wmo-sat.info/oscar/spacecapabilities (enter the acronym in the Quick Search, top-right for the page).

Further reading

Edited by David Docquier and Clara Burgard


Thomas Lavergne is a research scientist at the Norwegian Meteorological Institute. His main interest is in improving algorithms to improve sea ice satellite products, and help towards a better understanding between observation and model communities. He recently worked with EUMETSAT OSI SAF and ESA CCI to produce Climate Data Records for Sea Ice Concentration. He tweets as @lavergnetho.

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 – Understanding Antarctic Sea Ice Expansion

Fig. 1: Average monthly Antarctic sea ice extent time series in black, with the small increasing trend in blue. [Credit: NSIDC]

Sea ice is an extremely sensitive indicator of climate change. Arctic sea ice has been dubbed ‘the canary in the coal mine’, due to the observed steady decline in the summer sea ice extent in response to global warming over recent decades (see this and this previous posts). However, the story has not been mirrored at the other pole. As shown in our image of the week (blue line in Fig. 1), Antarctic sea ice has actually been expanding slightly overall!


The net expansion is the result of opposing regional trends

The small increasing trend in Antarctic sea-ice extent is the sum of opposing regional trends (click here for definitions of area, concentration and extent). Sea ice in the Weddell and Ross seas has expanded whereas in the Amundsen and Bellingshausen (A-B) seas the sea-ice cover has diminished (Holland 2014). The size of these trends varies with the seasons (Fig. 2). There are no significant trends in ice concentration – the fraction of a chosen area/grid box that is sea ice covered — if you look at (Southern hemisphere) winter values, however we do see trends when looking at a time series of summer values. The differences in trends between seasons suggests interactions with atmosphere and ocean (feedbacks) that amplify (in the spring) and dampen (in the autumn) changes in the ice cover, creating this seasonality. Some of this variability can be explained by changes in the winds (Holland and Kwok, 2012). But the complexity of the trends can’t be explained by one single change in forcing (e.g. winds, snowfall or temperature) or a single process (e.g. ice albedo feedback acting in the spring/summer).

 

Fig. 2: Seasonal trend in ice concentration. Maximum trends are seen in summer. Large increases are seen in the Weddell and Ross seas, and decreases in the Amundsen and Bellingshausen (A-B) seas. [Credit: Fig 2 from Holland (2014). , reprinted with permission by Wiley and Sons].

Why hasn’t Antarctic sea ice extent been decreasing?

There is no clear consensus on this. In short, we don’t really know… It is not as intuitive as the ‘warmer climate results in less ice’ narrative for the Arctic. We only have a time series of Antarctic sea ice extent from 1979 (the start of satellite observations). We therefore can’t be sure what role natural variability is having on decadal and longer timescales, i.e. if this is just natural ups and downs or an “unusual” trend related to climate change. Another difficulty is that we don’t have a reliable time series of sea ice volume as we have difficulties in getting reliable sea ice thickness measurements, because of the thick snow covering on sea ice in the Southern Ocean. For example, it could be that the ice is becoming thinner although the sea-ice area has increased.

There are important processes and/or feedbacks between sea ice and ocean or between sea ice and atmosphere that we are missing from our models

Currently, global climate models are poor at reproducing the observed Antarctic sea ice changes (Turner et al. 2013). Models simulate a decrease in the overall sea ice extent, instead of the observed increase. They also fail to reproduce the correct spatial variations, as shown in Fig. 2. This makes it very hard to make predictions about future changes in Antarctic sea ice from model results, and implies that there are important processes and/or feedbacks between sea ice and ocean or between sea ice and atmosphere that we are missing from our models, and therefore our understanding of the Southern Ocean climate system is incomplete.

 

However, there are some suggestions as to processes that could explain some of the observed Antarctic sea ice variability. The largely fall into two main categories: natural variability and anthropogenic changes.

 

1.Natural Variability

Natural variability refers to the repeating oscillations and patterns we see in the climate system. Some of these repeating patterns can be correlated with increases/decreases in Antarctic sea ice. In particular El Nino Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) have been linked to Antarctic sea ice changes. The SAM is a measure of the difference in pressure between 40°S and 65°S, a positive SAM indicates a stronger difference in pressure, driving stronger westerly winds around Antarctica, increasing the thermal isolation of Antarctica. Stronger westerlies are associated with cooler sea surface temperatures and expansion of the sea ice cover on short  timescales (seasons to years).

The SAM has been in a mostly positive phase since the mid-1990s, so is believed may have something to do with some of the small increase in sea ice extent we have seen. However, variability on longer time scales (decades or longer) could also explain some of the small increase, but this is tricky to assess without a longer observational time series.

 

2. Anthropogenic Changes

The main two human-induced changes on the Antarctic climate system are the ozone hole and increased melting of the Antarctic ice sheet.

  • Ozone hole
    The ozone hole causes the westerly winds to strengthen, making the sea ice cover expand. However it is more complicated than this, as the impact on the sea ice may depend on what timescale we look at. Over longer timescales (years to decades) the initial response may be outweighed by an increase in ocean upwelling (due to the stronger winds). This brings warm water from below the cold surface layer up to the surface, melting the sea ice from below, eventually resulting in a net sea ice area decrease in response to the ozone hole. See Ferreira et al. (2015) for details.
  • Increased melting of the Antarctic ice sheet
    This could also play a role in the observed sea ice expansion, by increasing the ocean stratification. This results in a cooler and fresher surface layer, favouring the growth of sea ice (Bintanja et al. 2015).

 

It is very tricky to distinguish what is natural variability, what is human induced, or a complicated combination of two.

 

It is very tricky to distinguish what is natural variability, what is human induced, or a complicated combination of two. This means we don’t really know whether the observed large decrease in Antarctic sea ice extent seen in 2016/2017 (read more about it here) is just an anomaly or the start of a decreasing trend. So, in summary Antarctic sea ice is confusing, and we still can’t claim to completely understand observed variability. But this makes it interesting and means there is still a wealth of secrets left to be discovered about Antarctic sea ice!

 

Further reading

 

Edited by Clara Burgard et Sophie Berger


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 – Does size really matter? A story of ice floes and power laws

Figure 1: Sea ice extent in 2014 during the melting season. The pink lines mark the inner and outer extent of the marginal ice zone. The data comes from the CPOM setup of the CICE sea-ice model run with 9 years spin up from 2005. [Credit: Adam Bateson]

The retreating Arctic sea ice is one of the most well-known facets of Climate Change. Images of polar bears desperately swimming through polar seas searching for somewhere to rest and feed resonate strongly with the public. Beyond these headlines however, the Arctic Ocean is displaying a rapid transition from having mostly permanent ice cover to a more seasonal cover.


The Marginal Ice Zone

As both atmospheric and ocean average temperatures increase over the 21st century, the region of the Arctic considered either marginal or seasonal i.e. regions where sea ice is present for at least some of the year but with periods of either no or incomplete sea ice cover, is projected to increase significantly. Our image of the Week (Fig. 1) shows how the Marginal Ice Zone (defined here as regions with 15 % – 80 % ice coverage) evolves through the melting season. This means that the thermodynamic (i.e. melting, freezing) and dynamic (i.e. mechanical) processes which dominate the marginal ice zone are likely to become more important in influencing how the sea ice evolves in future.

Floe size matters

A key parameter to describe the behaviour of this region is the size of the individual ice floes – sheets of floating sea ice – which form the sea ice cover (see also a previous post on this topic). Floe size impacts melt rate, floe mechanical response, atmosphere-ocean momentum exchange and wave-ice interactions (Fig. 2). The sea ice component of climate models usually assumes all floes have the same, constant size; this assumption removes the ability of sea ice models to represent the complexity of the marginal ice zone. As a result processes which influence floe size such as wave induced break up of floes and lateral melting can’t be represented adequately in current climate models.

Figure 2: Video shows significant wave height in 2014 (darker blue colours indicate bigger waves; note also that a white colour indicates no waves, not necessarily sea ice cover). The purple/pink lines mark the inner and outer extent of the Marginal Ice Zone respectively. The data come from the CPOM setup of the CICE sea-ice model run with 9 years spin up from 2005. [Credit: Adam Bateson]

How can we represent different floe sizes in models?

Given the changing Arctic environment, representing floe size as a variable quantity is likely to be important for future accuracy of sea ice modelling. Currently sea ice models tend to divide the Polar Regions into grid cells, with properties defined as an average across the grid cell. However floe sizes can vary significantly over sub kilometre scales. There are four alternative approaches to representing such a non-uniform distribution of floe sizes within a grid cell:

  1. Define floes individually within the model and allow each floe to evolve independently.
  2. Use a categorical floe size distribution i.e. assign floes to size categories of 1 – 10 m, 10 – 20 m etc. (e.g. Horvat et. al, 2015).
  3. Impose a floe size distribution on each grid cell which evolves over time driven by relevant processes such as lateral melting or floe break-up (e.g. Williams et. al, 2013 a & b).
  4. A single floe size for each grid cell is diagnosed from the fractional ice coverage.

 

Option 1 would be the ideal approach from a Physics perspective. It assumes nothing about what form the floe size distribution may take and allows us to properly assess the impact of different processes for floes of different sizes. This approach is computationally expensive however, which means it will take longer for models to run. Option 4 would the simplest option and wouldn’t have negligible impacts on model run times, however it wouldn’t be possible to include in the model any processes which influence floe size. Option 2 and option 3 represent intermediates between these two extremes. In particular option 3 would be a preferred compromise if floes can be represented as a coherent distribution which evolves over time at the grid length scale.

We should now look at whether observations support the use of such a distribution.

The power law distribution

Figure 3: The cumulative number density for floe size can be represented by a power law. Note that both scales are log scales, and that C in the equation is a constant. The blue and green lines show the distribution for smaller and larger exponents respectively. Note the cumulative number density for a given floe diameter, x, is the fraction of floes size x and larger. [Credit: Adam Bateson]

The floe size distribution is most commonly fitted to a power law (Fig. 3). Power law systems have the property of self-similarity, a term attributed to a system which looks the same over different scales (e.g. the metre or kilometre scale). Power law distributions are relatively easily to investigate mathematically, and can easily be incorporated into a model without significant computational expense.

Do observations support the use of a power law?

Many individual experiments to assess the floe size distribution have shown a good fit to the power law. However, a large range of values for the power law exponent have been reported with observations ranging from 0.9 to 4. Other papers have proposed two power laws over different size ranges, with smaller exponents used for the smaller floe range. Herman et. al (2010) proposed that a distribution with a variable exponent would produce a better fit than a power law. There are further questions we need to consider as well. Over what scale are power laws a valid approximation? What determines the exponent of the power law and can it be assumed that this is constant? Is the power law only valid over a certain range of floe sizes and if so what determines this range?

These questions are not trivial, and the available observations are not sufficient to answer them. However, there is still value in testing different distributions and approaches within models. This can provide information about how sensitive the sea ice cover is to different distributions and which processes in particular are important to accurately model winter ice growth and summer ice loss in the marginal ice zone.

References/Further Reading

Edited by Sophie Berger


Adam Bateson is a PhD student at the University of Reading (United Kingdom), working with Danny Feltham. His project involves investigating the fragmentation and melting of the Arctic seasonal sea-ice cover, specifically improving the representation of relevant processes within sea-ice models. In particular he is looking at lateral melting and wave induced fragmentation of sea-ice as drivers of break up, as well as the role of the ocean mixed layer as either an amplifier or dampener to the impacts of particular processes. Contact: a.w.bateson@pgr.reading.ac.uk or @a_w_bateson on twitter.