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Geosciences Column: Scientists pinpoint where seawater could be leaking into Antarctic ice shelves

Geosciences Column: Scientists pinpoint where seawater could be leaking into Antarctic ice shelves

Over the last few decades, Antarctic ice shelves have been disintegrating at a rapid rate, likely due to warming atmospheric and ocean temperatures, according to scientists. New research reveals that one type of threat to ice shelf stability might be more widespread that previously thought.

A study recently published in EGU’s open access journal The Cryosphere identified several regions in Antarctica were liquid seawater could be leaking into vulnerable layers of an ice shelf.

Scientists have known for some time now that seawater can seep into an ice shelf’s firn layer, the region of compacted snow that is on its way to becoming ice. This seawater infiltration presents an issue to the ice shelf’s stability, since as the seawater spreads throughout the firn layer, the water can create fractures and help expand crevasses already present in the frozen material. Past research has shown that the presence of liquid brine from seawater within an ice shelf is correlated to increased fracturing and calving.

While ice shelf collapse doesn’t directly contribute to sea level rise, since the ice is already floating, stable ice shelves often push back on land-based ice sheets and glaciers, slowing down ice flow into the ocean. Past research has suggested that once an ice shelf collapses, the rate of ice flow from unsupported glaciers can greatly accelerate.

To better understand Antarctic ice shelves’ risk of collapse, the researchers involved with this new study sought to identify where ice shelf firn layers are vulnerable to seawater infiltration. Using Antarctic geometry data, they mapped out the potential ‘brine zones’ within the continent’s ice shelves. These are regions of the ice shelf where the firn layer is both below the sea level and permeable enough to let seawater percolate through.

The results of their analysis revealed that almost all ice shelves in Antarctica have spots where seawater can potentially leak through their layers, with about 10-40 percent of the continent’s total ice shelf area possibly at risk of infiltration.

Map of potential brine zones areas around Antarctica. Map shows areas where permeable firn lies below sea level (the brine zone), with the threshold for firn permeability defined as 750 kg m−3 (red), 800 kg m−3 (yellow) and 830 kg m−3 (blue) calculated using Bedmap2 surface elevation. Bar charts show the mean percentage area of selected ice shelves covered by the brine zone. (Credit: S. Cook et al. 2018)

The researchers compared their estimated points to a map of previously confirmed brine zones, observed through ice cores or radar surveys. After reviewing these records, they identified only one record of brine presence that hadn’t been highlighted by their developed model.

The study found many areas in Antarctica where seawater infiltration could be possible, but has not been previously observed. The findings suggest that this firn layer vulnerability to seawater might be more widespread than previously believed.

The researchers suggest that the most likely new regions where brine from seawater may be present includes the Abbot Ice Shelf, Nickerson Ice Shelf, Sulzberger Ice Shelf, Rennick Ice Shelf, and slower-moving areas of Shackleton Ice Shelf. The regions all contain large swathes of permeable firn below sea level while also subject to relatively warm air temperatures and low flow speeds, the ideal conditions for maintaining liquid brine.

The study points out that there are still many uncertainties in this research, considering the unknowns still present in the data used for mapping and the factors that may influence seawater infiltration. For example, some areas that have large predicted brine zones have an unusually think layer of firn from heavy snowfall. This is the case for the Edward VIII Bay in eastern Antarctica. “Our results indicate the total ice shelf area where permeable firn lies below sea level, but this does not necessarily imply that the firn contains brine,” the authors of the study noted in their article.

Given their findings, the researchers involved recommend that this potentially widespread influence on ice shelves should be further examined and assessed by future studies.

By Olivia Trani, EGU Communications Officer

References

Cook, S., Galton-Fenzi, B. K., Ligtenberg, S. R. M. and Coleman, R.: Brief communication: widespread potential for seawater infiltration on Antarctic ice shelves, The Cryosphere, 12(12), 3853–3859, doi:10.5194/tc-12-3853-2018, 2018.

Hoegh-Guldberg, O., D. Jacob, M. Taylor, M. Bindi, S. Brown, I. Camilloni, A. Diedhiou, R. Djalante, K.L. Ebi, F. Engelbrecht, J.Guiot, Y. Hijioka, S. Mehrotra, A. Payne, S.I. Seneviratne, A. Thomas, R. Warren, and G. Zhou, 2018: Impacts of 1.5ºC Global Warming on Natural and Human Systems. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I.Gomis, E. Lonnoy, T.Maycock, M.Tignor, and T. Waterfield (eds.)]. In Press

Scambos, T. A.: Glacier acceleration and thinning after ice shelf collapse in the Larsen B embayment, Antarctica, Geophysical Research Letters, 31(18), doi:10.1029/2004gl020670, 2004.

Scambos, T., Fricker, H. A., Liu, C.-C., Bohlander, J., Fastook, J., Sargent, A., Massom, R. and Wu, A.-M.: Ice shelf disintegration by plate bending and hydro-fracture: Satellite observations and model results of the 2008 Wilkins ice shelf break-ups, Earth and Planetary Science Letters, 280(1–4), 51–60, doi:10.1016/j.epsl.2008.12.027, 2009.

State of the Cryosphere: Ice Shelves. National Snow & Ice Data Center

GeoTalk: To understand how ice sheets flow, look at the bedrock below

GeoTalk: To understand how ice sheets flow, look at the bedrock below

Geotalk is a regular feature highlighting early career researchers and their work. In this interview we speak to Mathieu Morlighem, an associate professor of Earth System Science at the University of California, Irvine who uses models to better understand ongoing changes in the Cryosphere. At the General Assembly he was the recipient of a 2018 Arne Richter Award for Outstanding Early Career Scientists.  

Could you start by introducing yourself and telling us a little more about your career path so far?

Mathieu Morlighem (Credit: Mathieu Morlighem)

I am an associate professor at the University of California Irvine (UCI), in the department of Earth System Science. My current research focuses on better understanding and explaining ongoing changes in Greenland and Antarctica using numerical modelling.

I actually started glaciology by accident… I was trained as an engineer, at Ecole Centrale Paris in France, and was interested in aeronautics and space research. I contacted someone at the NASA Jet Propulsion Laboratory (JPL) in the US to do a six-month internship at the end of my master’s degree, thinking that I would be designing spacecrafts. This person was actually a famous glaciologist (Eric Rignot), which I did not know. He explained that I was knocking on the wrong door, but that he was looking for students to build a new generation ice sheet model. I decided to accept this offer and worked on developing a new ice sheet model (ISSM) from scratch.

Even though this was not what I was anticipating as a career path, I truly loved this experience. My initial six-month internship became a PhD, and I then moved to UCI as a project scientist, before getting a faculty position two years later. Looking back, I feel incredibly lucky to have seized that opportunity. I came to the right place, at the right time, surrounded by wonderful people.

This year you received an Arne Richter Award for Outstanding Early Career Scientists for your innovative research in ice-sheet modelling. Could you give us a quick summary of your work in this area?

The Earth’s ice sheets are losing mass at an increasing rate, causing sea levels to rise, and we still don’t know how quickly they could change over the coming centuries. It is a big uncertainty in sea level rise projections and the only way to reduce this uncertainty is to improve ice flow models, which would help policy makers in terms of coastal planning or choosing mitigation strategies.

I am interested in understanding the interactions of ice and climate by combining state-of-the-art numerical modelling with data collected by satellite and airplanes (remote sensing) or directly on-site (in situ).  Modelling ice sheet flow at the scale of Greenland and Antarctica remains scientifically and technically challenging. Important processes are still poorly understood or missing in models so we have a lot to do.

I have been developing the UCI/JPL Ice Sheet System Model, a new generation, open source, high-resolution, higher-order physics ice sheet model with two colleagues at the Jet Propulsion Laboratory over the past 10 years. I am still actively developing ISSM and it is the primary tool of my research.

More specifically, I am working on improving our understanding of ice sheet dynamics and the interactions between the ice and the other components of the Earth system, as well as improving current data assimilation capability to correctly initialize ice sheet models and capture current trends. My work also involves improving our knowledge of the topography of Greenland and Antarctica’s bedrock (through the development of new algorithms and datasets). Knowing the shape of the ground beneath the two ice sheets is key for understanding how an ice sheet’s grounding line (the point where floating ice meets bedrock) changes and how quickly chunks of ice will break from the sheet, also known as calving.

Steensby Glacier flows around a sharp bend in a deep canyon. (Credit: NASA/ Michael Studinger)

At the General Assembly, you presented a new, comprehensive map of Greenland’s bedrock topography beneath its ice and the surrounding ocean’s depths. What is the importance of this kind of information for scientists?

I ended up working on developing this new map because we could not make any reliable simulations with the bedrock maps that were available a few years ago: they were missing key features, such as deep fjords that extend 10s of km under the ice sheet, ridges that stabilize the retreat, underwater sills (that act as sea floor barriers) that may block warm ocean waters at depth from interacting with the ice, etc.

Subglacial bed topography is probably the most important input parameter in an ice sheet model and remains challenging to measure. The bed controls the flow of ice and its discharge into the ocean through a set of narrow valleys occupied by outlet glaciers. I am hoping that the new product that I developed, called BedMachine, will help reduce the uncertainty in numerical models, and help explain current trends.

3D view of the bed topography and ocean bathymetry of the Greenland Ice Sheet from BedMachine v3 (Credit: Peter Fretwell, BAS)

How did you and your colleagues create this map, and how does it compare to previous models?

The key ingredient in this map, is that a lot of it is based on physics instead of a simple “blind” interpolation. Bedrock elevation is measured by airborne radars, which send electromagnetic pulses into the Earth’s immediate sub-surface and collect information on how this energy is reflected back. By analyzing the echo of the electromagnetic wave, we can determine the ice thickness along the radar’s flight lines. Unfortunately, we cannot determine the topography away from these lines and the bed needs to be interpolated between these flight lines in order to provide complete maps.

During my PhD, I developed a new method to infer the bed topography beneath the ice sheets at high resolution based on the conservation of mass and optimization algorithms. Instead of relying solely on bedrock measurements, I combine them with data on ice flow speed that we get from satellite observations, how much snow falls onto the ice sheet and how much melts, as well as how quickly the ice is thinning or thickening. I then use the principle of conservation of mass to map the bed between flight lines. This method is not free of error, of course! But it does capture features that could not be detected with other existing mapping techniques.

3D view of the ocean bathymetry and ice sheet speed (yellow/red) of Greenland’s Northwest coast (Credit: Mathieu Morlighem, UCI)

What are some of the largest discoveries that have been made with this model? 

Looking at the bed topography alone, we found that many fjords beneath the ice, all around Greenland, extend for 10s and 100s of kilometers in some cases and remain below sea level. Scientists had previously thought some years ago that the glaciers would not have to retreat much to reach higher ground, subsequently avoiding additional ice melt from exposure to warmer ocean currents. However, with this new description of the bed under the ice sheet, we see that this is not true. Many glaciers will not detach from the ocean any time soon, and so the ice sheet is more vulnerable to ice melt than we thought.

More recently, a team of geologists in Denmark discovered a meteorite impact crater hidden underneath the ice sheet! I initially thought that it was an artifact of the map, but it is actually a very real feature.

More importantly maybe, this map has been developed by an ice sheet modeller, for ice sheet modellers, in order to improve the reliability of numerical simulations. There are still many places where it has to be improved, but the models are now really starting to look promising: we not only understand the variability in changes in ice dynamics and retreat all around the ice sheet thanks to this map, we are now able to model it! We still have a long way to go, but it is an exciting time to be in this field.

Interview by Olivia Trani, EGU Communications Officer

Geosciences Column: Do roads mean landslides are more likely?

Geosciences Column: Do roads mean landslides are more likely?

Landslides have been in the news frequently over the past 12 months or so. It’s not surprising considering their devastating consequences and potential impact on nearby communities. Data collected by Dave Petley in his Landslide Blog shows that from January to July 2014 alone, there were 222 landslides that caused loss of life, resulting in 1466 deaths.

A recent paper, in the journal Natural Hazards and Earth System Sciences investigates, what the potential effects of human denudation can have on the occurrence of landslide events. There is no denying that landslide susceptibility has been increased by human activity. Global warming and greater precipitation are key contributing factors to the rise in the number of landslides which occur globally. On a local scale, the building of infrastructure, particularly roads and felling of trees to make way for agriculture are largely to blame for increased numbers of slides and slumps.

Overview of the study area with mean annual precipitation patterns (top panel), and its location in southern Ecuador (lower left panel). Highways Troncal de la Sierra E35 and Transversal Sur E50 extend in the north–south and east–west direction, respectively. The numbers along the street refer to the corresponding geological unit (1: unconsolidated rocks; 2: sedimentary rocks; 3: volcanic rocks; 4: metamorphic rocks; 5: plutonic rocks). The area of the detailed map (lower right panel) will be used as a sample area for the visualization of a predictive map in Fig. 5. Precipitation data are taken from the study of Rollenbeck and Bendix (2001). From Brenning et al., (2015)

Overview of the study area with mean annual precipitation patterns (top panel), and its location in southern Ecuador (lower left panel). Highways Troncal de la Sierra E35 and Transversal Sur E50 extend in the north–south and east–west direction, respectively. The numbers along the street refer to the corresponding geological unit (1: unconsolidated rocks; 2: sedimentary rocks; 3: volcanic rocks; 4: metamorphic rocks; 5: plutonic rocks). Precipitation data are taken from the study of Rollenbeck and Bendix (2001). From Brenning et al., (2015). Click on the image for a larger version.

The research presented in the paper focuses on landslides along mountain roads in Ecuador, where drainage systems and stabilisation of hillsides is often inadequate and is known to increase the likelihood of landslides. This problem is not exclusive to Ecuador and is often linked to poorer infrastructure and engineering in developing countries. In addition, the study area is a tropical mountain ecosystem, which is naturally more sensitive and prone to landslides. The key question here being: are more landslides likely to happen close to a road (in this particular case an interurban highways), or does greater distance from them offer some hazard relief?

The geology, and local climate and vegetation are important factors to also take into consideration when carrying out an assessment of this nature. Highways E35 and E50 run along Southern Ecuador and intersect the Cordillera Real, which creates a strong local climate divide and generates a precipitation gradient along the area studied. Páramo ecosystems are dominant towards the east, whilst tropical dry forests are common in the west. The geology is also variable across the area studied: dipping and jointed metamorphic rocks are dominant, but are in contact with horizontally layered sedimentary units of loose conglomerates and sandstones. Additionally, the hill sides running along the highways are often deforested to make way for coffee, sugar cane and banana crops. When they are not, they are commonly handed over to cattle for grazing.

By mapping, in great detail, all landslide occurrences within a 300m corridor along the highways, the researchers were able to digitise 2185 landslide initiation points! In total, 843 landslides were mapped and classified by recording the type of movement experienced, as well as the material type (soil, debris or rock) and whether the slide was still active, inactive or had been reactivated. The detailed data meant it was possible to statistically model the likelihood of landslides occurring in close proximity to the highway (25m) vs. some distance away (200m). The results showed that susceptibility to landslides increases by one order of magnitude closer to the highway when compared to areas between 150-300 m away from the mountain road. Furthermore, slides close to the highway were found to be more likely to be reactivated than those a greater distance away.

The study found that the local topography, geology and climate conditions had a lesser influence on the likelihood of landslides. However, the influence of stretches of mountain road constructed in the sedimentary units seems to enhance the hazard.

Landslides occurring along the investigated highways. (a) Typical landslides of the wet metamorphic part of the study area in the east. (b) Typical landslides of the semi-arid, conglomeratic part of the study area in the west. (c) Highway destroyed by landsliding. (d) A highway is cleared from a recent landslide occurrence. From Brenning et al., (2015).

Landslides occurring along the investigated highways. (a) Typical landslides of the wet metamorphic part of the study area in the
east. (b) Typical landslides of the semi-arid, conglomeratic part of the study area in the west. (c) Highway destroyed by landsliding. (d) A
highway is cleared from a recent landslide occurrence. From Brenning et al., (2015).

In future, the model can be used to predict locations where landslides are more likely to occur along the E35 and E50. Recently, engineering works have been carried out along the studied stretch of highways to stabilise the hillsides. The data collected as part of the research presented in the paper will be useful in the future to monitor the efficacy of the improvements. On a larger scale, further studies of this type could be used by local governments when planning new infrastructure and could lead to incorporation of cost-effective mitigation measures in new developments.

 

By Laura Roberts Artal, EGU Communications Officer

Reference:

Brenning, A., Schwinn, M., Ruiz-Páez, A. P., and Muenchow, J.: Landslide susceptibility near highways is increased by 1 order of magnitude in the Andes of southern Ecuador, Loja province, Nat. Hazards Earth Syst. Sci., 15, 45-57, doi:10.5194/nhess-15-45-2015, 2015.

Geosciences Column: Meshing models with the small-scale ocean

The latest Geosciences Column is brought to you by Nikita Marwaha, who explains how a new generation of marine models is letting scientists open up the oceans. The new technique, described in Ocean Science, reveals what’s happening to ocean chemistry and biology at scales that are often hard to model…

Diving into the depths of the ocean without getting your feet wet is possible through biogeochemical modelling – a method used by scientists in order to study the ocean’s living systems. These simulated oceans are a means of understanding the role of underwater habitats and how they evolve over time. Covering nutrients, chlorophyll concentrations, marine plants, acidification, sea-ice coverage and flows, such modelling is an important tool used to explore the diverse field of marine biogeochemistry.

Barents Sea plankton bloom: sub-mesoscale flows may be responsible for the twisted, turquoise contours of this bloom (Credit: Jeff Schmaltz, MODIS Land Rapid Response Team, NASA GSFC)

Barents Sea plankton bloom: sub-mesoscale flows may be responsible for the twisted, turquoise contours of this bloom (Credit: Jeff Schmaltz, MODIS Land Rapid Response Team, NASA GSFC)

There is one outstanding problem with this technique though, as the very-small scale or sub-mesoscale marine processes are not well represented in global ocean models. Sub-mesoscale interactions take place on a scale so small, that computational models are unable to resolve them. Short for sub-medium (or ‘sub- meso’) length flows – the smaller flows in question are on the scale of 1-10 km. They are difficult to measure and observe, but their effects are seen in satellite imagery as they twist and turn beautiful blooms of marine algae.

Sub-mesoscale phenomena play a significant role in vertical nutrient supply – the vertical transfer of nutrients from nutrient-rich deep waters to light-rich surface waters where plankton photosynthesise. This is a major area of interest since the growth of marine plants is limited by this ‘two-layered ocean’ dilemma. But the ocean is partially able to overcome this, which is where sub-mesoscale flows come in. Sub-mesoscale flows are important in regions with large temperature differences over short distances – when colder, heavier water flows beneath warmer, lighter water. This movement brings nutrient-rich water up to the light-rich surface. Therefore, accurately modelling these important small-scale processes is vital to studying their effect on ocean life.

Global chlorophyll concentration: red and green areas indicate a high level or growth, whereas blue areas have much less phytoplankton. (Credit: University of Washington)

Global chlorophyll concentration: red and green areas indicate a high level or growth, whereas blue areas have much less phytoplankton. (Credit: SeaWiFS Project)

A group of scientists, led by Imperial College’s Jon Hill, probes the technique of biogeochemical ocean modelling and the issue of studying sub-mesoscale processes in a paper recently published in the EGU journal Ocean Science.  Rather than simply increasing the resolution of the models, the team suggests a novel method – utilising recent advances in adaptive mesh computational techniques. This simulates ocean biogeochemical behavior on a vertically adaptive computational mesh – a method of numerically analysing complex processes using a computer simulation.

What makes it adaptive? The mesh changes in response to the biogeochemical and physical state of the system throughout the simulation.

Their model is able to reproduce the general physical and biological behavior seen at three ocean stations (India, Papa and Bermuda), but two case studies really showcase this method’s potential: observing the dynamics of chlorophyll at Bermuda and assessing the sinking detritus at Papa. The team changed the adaptivity metric used to determine the varying mesh sizes and in both instances. The technique suitably determined the mesh sizes required to calculate these sub-mesoscale processes. This suggests that the use of adaptive mesh technology may offer future utility as a technique for simulating seasonal or transient biogeochemical behavior at high vertical resolution – whilst minimising the number of elements in the mesh. Further work will enable this to become a fully 3D simulation.

Comparison of different meshes produced by adaptive simulations: (a) Bermuda, taking the amount of chlorophyll into account (b) the original adaptive simulation at Bermuda, without taking chlorophyll into account (c) adaptive simulation at Papa, taking the amount of detritus into account (d) the original Papa simulation, without taking detritus into account. (Credit: Hill et al, 2014)

Comparison of different meshes produced by adaptive simulations: (a) Bermuda, taking the amount of chlorophyll into account (b) the original adaptive simulation at Bermuda, without taking chlorophyll into account (c) adaptive simulation at Papa, taking the amount of detritus into account (d) the original Papa simulation, without taking detritus into account. (Credit: Hill et al., 2014)

The fruits of this adaptive way of studying the small-scale ocean are already emerging as the secrets of the mysterious, sub-mesoscale ocean processes are probed. The ocean holds answers to questions about our planet, its future and the role of this complex, underwater world in the bigger, ecological picture – adapting to life and how we model it may just be the key we’ve been looking for.

By Nikita Marwaha

Reference:

Hill, J., Popova, E. E., Ham, D. A., Piggott, M. D. and Srokosz, M.: Adapting to life: ocean biogeochemical modelling and adaptive remeshing. Ocean Sci., 10, 323- 343, 2014