One of the main concerns related to climate change is the rise of the sea level. Rising sea levels would affect coastal cities, which host a large proportion of the Earth’s population. Thus, having a good handle on the time frame for rising sea levels is important for humanity to successfully adapt to climate change.
Antarctica has about 90% of the world’s ice, and thus about 70% of the world’s fresh water. This means that what happens to the Antarctic ice sheet will really affect the rate at which sea levels rise.
One of the interesting, and sometimes scary, things about the dynamics of ice loss in Antarctica is feedback loops. For example, we know that ice is very reflective (things that are more reflective are said to have a higher albedo) and so when sunlight hits it a lot of it bounces back. This can help to keep things nice and cool. This leads to ice-albedo feedback — the process that amplifies an initial change in the amount of ice. If the quantity of ice increases, then this increases the albedo, which makes things cooler, and so more ice accumulates, which makes things cooler, and so on. Conversely, if the quantity of ice decreases, then this makes things warmer since the albedo of the Earth decreases, which makes more ice melt, which makes things warmer, and so on. If we want to understand the dynamics of how ice in Antarctica melts, we have to understand these kind of feedback loops.
This is not an abstract, super long-term worry. I took a course in Antarctica a few years ago, in which we sailed down to the Antarctica Peninsula from the Falkland islands on an old Russian research vessel. The ship carried tourists, students, and scientists. Some of the scientists who had been visiting Antarctica for decades, including the incredible Dr. John Dudeney, said to me that they had seen more ice loss in the last 3 years than in the previous decade.
Of course, ice-albedo feedback is only one of many complicated processes that govern the dynamics of ice loss. Any serious attempt to model ice-sheet evolution in Antarctica must incorporate a highly varied constellation of processes, and see how they all interact. Thus it is super encouraging to see scientists working in that direction.
***The original paper can be found here.***
The main contribution of their model was the introduction of solid-Earth feedback. To understand how the solid-Earth can affect rising sea-levels we have to understand two main concepts: grounding lines and pinning points.
Grounding lines are best explained by a picture:
The position of the grounding line affects the stability of the ice sheet. In the grounding line retreats, as in this video, then more warm water can get under the ice sheet, and thus the ice can melt faster. The movement of of the grounding line is called grounding line migration, and is a key factor in determining how fast or slow the ice sheet loses ice. The position of the grounding line is determined both by the ice and the topology of the earth.
Pinning points are similar to grounding lines in that they are determined in part by the topology of the earth, and can help reduce ice loss. Once again, a picture is helpful:
This quote from Still et al. states the effect of pinning points rather nicely:
Pinning points provide resistance to ice shelf flow by modifying the balance of forces within the floating ice. Each pinning point and the grounded ice above it forms, in effect, an obstacle to ice shelf flow. The obstacle generates a reaction force that acts upstream, in opposition to the gravitational driving stress that compels the ice to flow. Because the balance of forces in floating ice is non-local, this reaction force has an effect everywhere in the ice shelf.Still et al, p. 32
We see that both pinning points and ground line location affect the rate at which ice melts in the Antarctic ice sheet.
One of the main challenges of successfully incorporation the effects of pinning points and ground lines is the resolution needed to accurately model them. As Larour et al. put it,
A key aspect of understanding grounding-line dynamics (GLD) is to understand the relationship between the evolving sea level and the exact position of pinning points. As shown through NASA’s Operation IceBridge topographic mapping as well as decades-long efforts to map grounding-line migration, highly resolved pinning points are present in critical areas of the West Antarctic Ice Sheet (WAIS) that can only be captured at kilometer-scale resolutions (17, 18). In parallel, studies have shown that the physical representation of grounding-line migration can only be modeled through meshes that attain 1-km resolution (19).p. 364
Having a fine resolution matters to get the models right. The model has to be sensitive to both geographical and temporal elements:
Our goal was to carry out a sensitivity study of sea level– and ice flow–related processes by incorporating kilometer-scale resolutions and global processes that involve solid-Earth dynamics. The ice-flow model robustly captures GLD at high resolution (1 km) and over very short time scales (2 weeks).p. 364
This is the main contribution of the paper. The resolution can matter because of one particularly interesting feedback loop. Earlier we spoke of the ice-albedo feedback loop, which depended on the relationship between the quantity of ice and the amount of light being reflected. This feedback loop, on the other hand, in related to the mass of the ice and the pressure it exerts on the underlying earth. As more ice melts, the mass of the ice shelf decreases. This means that any upward movement of the Earth’s crust (which can be occurring for all sorts of tectonic reasons — think of how mountains are created) will be able to lift the ice sheet even further out of the water, possibly changing the location and pinning points and ground lines. Often this slows the rate at which ground lines retreat, which means that we would predict the ice to melt slower than if we hadn’t taken into account the increased upwards movement of the ground, and the ice above. Thus, whereas the ice-albedo feedback loop amplifies the initial direction of the change in ice, in this case the loss of ice mass creates a negative feedback loop — it can help to slow and stabilize the melting of the ice sheet.
Now that we have a decent handle on one of the main mechanisms in which the scientists were interested, lets take a look at the results. The scientists found that by incorporating these effects into their model (which required them to have a much higher-resolution model than had been used before) did indeed decrease our prediction of the rate of ice loss, and thus sea level rise:
The delay between UNC and NSM is 12% in terms of normalized mass change [corresponding to roughly 23 years at 2350 (fig. S1)]. This causes a negative feedback for the TG contribution to SLR of 0.12 m. This represents a 28.4% reduction in its SLR contribution. The differential in grounding-line migration evolves through time (figs. S7 and S9). By year 2300, the differential stands at ~50 to 80 km, and by year 2350, it has reached 100 to 120 km and holds above 80 km throughout year 2450. For corresponding TG ice volume change (Table 1), by year 2100 the negative feedback reaches –1.34%; by year 2350, –28.4%; and by year 2500, –9.9%.p. 364
UNC in the preceding quote is referring to the model the scientists used as a control run, the simulation they did that did not take into account some of the more sophisticated effects I described above. NSM is the model that took into account all of the factors. Thus, we see that including information about the relationship between the solid Earth and the mass of the ice matters. The scientists do note that, while interesting and worthy of notice, “This effect will not stop or reverse ice sheet loss, but it could delay the progress of dynamic mass loss of Thwaites Glacier by approximately 20 years” (from the summary here). Furthermore, “For 21st-century projections,the effects we have modeled here remain negligible. However, for the period starting 2250 and after, SLR projections that would not account for such dynamic geodetic effects run the risk of consistently overestimating (by 20 to 40%) relative sea-level estimates” (p. 364).
So one of the main takeaways seems to be that while this effect does not change our short term predictions much, it will change our predictions on a longer time frame. Another takeaway that the scientists emphasize is that in order to make better and better predictions about timelines for sea-level changes, we need to incorporate more factors like the ones introduced in this paper. Indeed, if we want to take sophisticated, successful action to address climate change, we need all of the information we can get.