Monitoring melt where Ice Meets Ocean

  Remote Sensing of the Earth in Relation with South Pole Monitoring

A story-driven project post-analysis by Quentin Glaude

 

 

A Society Addicted to Fossil Fuels

 

In its History, human civilization learned to exploit the available energy on Earth.

 

The invention of the steam engine in the early XIX century and the rapid move through the industrial era marks the beginning of the Anthropocene. Coal was found to possess incredible properties. A considerable amount of disposable energy is hidden in this condensed sedimentary rock. Until 2010, coal was the fastest growing energy source, ahead of gas and oil. After the two World Wars, the use of petroleum from military to civil purposes brought Humankind into a new era, where the liquid property of oil made transportation almost free, in comparison to the pre-industrial period.

 

We generally separate energy sources into two categories: fossil and non-fossil fuels. The fossil fuels comprised coal, oil, and gas, while non-fossil fuels include wood, hydropower, nuclear, wind turbines, solar panels, or other synthesized fuels (hydrogen, oil, gas). Even if this latter category occupies the main pages of news and mainstream media distribution, it is always beneficial to remember that fossil fuels encompass more than 80% of the world energy consumption (Coal – for electricity and industry, Oil – for transport, and Gas – for heat and electricity).

Figure 1. Energy Production by sources (IEA, 2021).

The Other Side of the Coin

 Energy brings Humankind into the Anthropocene. Energy allowed us to travel the way we travel, to eat the way we eat, to work the way we work, to consume the way we consume, but also to benefit from limited work hours, tens of paid days off, or even paid retirement. In addition, this general trend occurs with a growing population, whose life expectancy globally never ceased increasing.

 

This energy comes from more than 80% of fossil fuels, emitting in its combustion greenhouse gases. With a population getting closer to 8.000.000.000 inhabitants (still growing) and CO2 annual emission (or equivalent) around 6-7 tons per capita (stable since 1970), Humankind is leaving an important footprint of its presence.

Figure 2. Greenhouse gases emissions per year (GFZ data services, 2016).

 

From Arrhenius in 1898, the effects of greenhouse gases were already known, and discussion about the consequences of the industrial era in terms of global warming emerged. Currently, global warming is not just a theoretical event, but perfectly distinguishable using observations.

Figure 3. Change in global surface temperature as observed and simulated using human and natural VS only natural elements (IPCC, 2021).

 

Figure 3 underlines the undisputable influence of humans on warming the planet. This global warming is amplified in polar regions. Oceans, on the contrary, have the ability to absorb an important amount of this anthropogenic warming.

 

Global warming has important consequences on human society. The warming of the atmosphere increases the rate and length of heat waves. Extreme weather events, in general, are and will become even more frequent. The question about food security is also on the table where we observe a decrease in yield production per surface and a global growing population. The majority of the CO2 increased concentration is absorbed by oceans, which are getting more acid every year.

 

Figure 4. Evaluation of risks related to global warming (IPCC AR5 report, 2014).

 

One of the most visible and direct impacts of global warming is the sea-level rise. In a world where the majority of the biggest cities are located in coastal areas, the problem of increased flood events is critical. Several islands in the Southern Pacific and Indian oceans are subject to disappear in the near future. Finally, reaching critical tipping points can lead to irreversible melt of the largest ice sheets (Greenland and Antarctica), which would cause a sea-level rise of several meters in the next centuries. In the MIMO project, we are addressing the problem of Antarctic Ice Sheet monitoring, in the context of a changing world, with models predicting the ice sheet behavior.

Antarctica, a Dam Ready to Collapse

 

Antarctica is the largest ice mass on Earth, set on a rocky continent. This mass undergoes gravity-driven displacements towards the ocean. In contact with the ocean, the ice starts to float and forms a floating ice shelf. These ice shelves, surrounding 70% of Antarctica, have an important role in keeping the Antarctic Ice Sheet (AIS) stable. Ice shelves can be considered as the seatbelt of the AIS: thin, but crucial for our security. They are acting as regulators of the ice flow by exerting what we call a buttressing effect, because they are locally constrained in embayment or in contact with topographic elements. The thinning or damage of these ice shelves is directly translated in a decrease of buttressing effect, and causes an acceleration of the ice flow and a retreat of the grounding line, i.e. the boundary between floating and grounded ice.

 

Understanding the mechanisms of ice shelves’ behavior is a crucial element when we study the climate change impacts. The MIMO project was born from this perspective.

Fig. 5. 70% of Antarctica is surrounded by ice shelves. Most of them are active regulators of the ice flow by exerting a buttressing effect (Furst, 2016).

 

Nevertheless, human-induced global warming is challenging the stability of our poles. Antarctica is losing mass at an increasing rate, from 40 Gt/a in the 80s to 250 Gt/a in the last decade. Antarctica is the highest potential contributor to sea level rise, with an increased contribution of 14% since 2016, while it has only 7% for the period 1971-2018. Sea-level rise is directly related to a cryosphere imbalance. In addition, contrary to any global-warming-induced undesirable events, sea-level rise has a long-term irreversibility. In this scenario, the geographic distribution of the world population would be completely shifted as the largest cities on Earth are located in coastal areas (example in Figure 5). Cost and maintenance of mitigation infrastructures are expected to subsequently increase too.

Figure 6. Coastal impacts of sea level rise around Venice. In this particularly historical island, 76% of the population would need to move (Owen Mulhern, 2020).

 

SAR Remote Sensing, a Swiss Knife to Monitor the Ice Shelves’ Health

 

Ice shelves are subject to multiple geophysical phenomena that govern their behavior. Field campaigns are difficult to maintain in Antarctica. Though necessary, they suffer from a restricted spatial coverage, often at a punctual resolution, but are also limited to summer periods, due to the cold and dark winter.

Figure 7. Examples of geophysical processes of ice shelves. Among others, we can cite: calving, hydrofracturing, crevassing, precipitation, surface/basal melting, circumpolar deep-water upwelling, katabatic wind, tidal mixing, grounding line migration and so on. Figure from Mariel Dirscher (2020).

 

In that sense, Remote Sensing comes at point to study areas that are difficult to access. In particular, SAR remote sensing, using active sensors in radar wavelengths, proved to be very useful in polar regions. Using its own generated signal, SAR remote sensing gets rid of the absence of solar illumination at high latitudes.

 

Moreover, the European Space Agency, through its Copernicus project, is pushing forward the open-access policy of remote sensing products. The Copernicus program consists of a constellation of satellites’ families orbiting the Earth with a short revisit time. Each family of satellites, called Sentinels, has a designated mission. Sentinel-1 is the radar branch of the Copernicus program. Composed of 2 satellites (S1A and S1B), they can observe any region with a revisit time of 6 days if coupled.

 

Though limited in its range of applications, SAR remote sensing is capable of studying many geophysical processes occurring over (and below) ice shelves.

 

The most obvious parameter is the determination of surface displacements. SAR has two families of methods to determine surface displacements based on a pair of two SAR images taken at two different times. The first one is speckle tracking, which includes the more particular coherence tracking, developed in the MIMO project. The goal of coherence tracking is to find where objects moved by locally performing a fine image matching technique using coherence maximization criteria. Tracking these objects on moving areas enables us to derive bi-dimensional displacement maps (Figure 6).

 

Figure 8. Surface velocities from an ensemble of SAR images. Using SAR Coherence Tracking, bidimensional displacements between two dates are determined by complex image matching algorithms.

 

The second family of techniques to infer surface displacements belongs to SAR Interferometry. In a SAR image, each pixel is composed of two information; amplitude information, which is related to the reflectivity of the ground, but also phase information, that is related to the distance from the satellite to the ground. By subtracting the phase of two SAR images taken from different dates, we make an interferogram. A displacement will cause a phase shift in the interferogram. Many components are influencing the interferogram; Differential SAR Interferometry consists in retrieving the phase term related to displacements.

 

One may be cautious that ice shelves are sensitive to variations of the sea level, mostly due to tides and changes in the atmosphere, inducing an undesirable additive signal in our interferogram (Figure 7). Using tides and climate models, we developed algorithms to remove vertical biases from Differential SAR Interferometry to retrieve unbiased horizontal displacements.

Figure 9. As ice shelves are afloat, they are subject to high frequency vertical variations due to tides and inverse barometer effects (due to changes in the atmospheric pressure). These short-term displacements induce a pattern in interferograms (right side of the figure). If not accounted for, these fringes are biasing the estimation of long-term displacements.

 

These vertical displacements are not completely wasteful, as they are the witness of the location where the ice shelf starts to float, i.e. the grounding line. Studying the grounding line migration is a key element to study the ice shelf stability. In the MIMO project, we monitored the short-term variation of the grounding line location (Figure 9).

 

Figure 10. Submonthly Monitoring of the Roi Baudouin Ice Shelf Grounding Line Location Using Sentinel-1 Double Differential SAR Interferometry. In this specific region and this specific time period, we noticed no particular retreat of the ice shelf.

 

An additional property of radar signals is their specific interaction with humidity. Surface melt can be observed using SAR, through changes of the ground properties. In the case of melting events, the echoes of the radar signal are extremely low (Figure 9).

Figure 11. SAR signal amplitude variations due to strong melt event. Surface melt is observed by an important decrease of the radar intensity.

 

The Regional Climate Model (MAR) is able to reconstruct surface melt in Antarctica. Preliminary results show a strong correlation between the radar signal and MAR model. Using time-series analyses at a given location, figure 10 shows an important melt event concordance between SAR observations and melt determined by MAR.

Figure 12. Preliminary results show a strong negative correlation between the scattering mechanisms and the predicted surface melt from a regional climate model (MAR).

 

The last product SAR can observe is the crevasse propagation and the calving front location, i.e. the boundary between an ice shelf and an iceberg. These processes are important as they can participate in the destabilization of ice shelves. It is possible to apply computer vision techniques to SAR images to extract a precise delineation of damaged structures over ice shelves. In the MIMO project, we employed the Sato filtering techniques. Originally, the Sato filter was designed to determine neurons on 3D medical images. The idea of the Sato filter is to compute for each pixel the conditional probability to belong to an edge, i.e. being a damaged structure. In the project, we developed automatic crack propagation and front location monitoring (Figure 11).

Figure 13. Using medical imaging techniques, we can emphasize the crack propagation of ice-shelves cracks in Antarctica.

 

To conclude, SAR is an invaluable tool that helps researchers in the cryosphere understand the dynamics of ice shelves. The paradigm shift in the last decade, and the planning for the near future of Earth Observation positively impact the research in Earth Science.

 

In the wish of better understand climate change, a precise understanding of key climate factors happening in Antarctica is crucial. Ice motion change, grounding migration, elevation change, calving events, surface melt, SAR remote sensing is able to bring important added-values to ice-sheet and climate modelers.

 

In the end, the MIMO project contributed to understanding the impacts of climate factors in the Ice Sheet monitoring. The recent advances in SAR and remote sensing in general, helps in studying small-scale (spatially and temporally) changes over ice shelves.  Together with other scientists, we hope that the published results will participate in the global comprehension of the physical science of climate change. In the end, these papers will find their place in official documents, such as the recent IPCC AR6 report, required for the redaction of technical documents, and thus helping policy-makers make the right decisions with regards to the Paris Agreement.