Arctic ice sets speed limit for major ocean current

The Beaufort Gyre is an enormous, 600-mile-wide pool of swirling cold, fresh water in the Arctic Ocean, just north of Alaska and Canada. In the winter, this current is covered by a thick cap of ice. Each summer, as the ice melts away, the exposed gyre gathers up sea ice and river runoff, and draws it down to create a huge reservoir of frigid fresh water, equal to the volume of all the Great Lakes combined.

Scientists at MIT have now identified a key mechanism, which they call the “ice-ocean governor,” that controls how fast the Beaufort Gyre spins and how much fresh water it stores. In a paper published today in Geophysical Research Letters, the researchers report that the Arctic’s ice cover essentially sets a speed limit on the gyre’s spin.

In the past two decades, as temperatures have risen globally, the Arctic’s summer ice has progressively shrunk in size. The team has observed that, with less ice available to control the Beaufort Gyre’s spin, the current has sped up in recent years, gathering up more sea ice and expanding in both volume and depth.

If global temperatures continue to climb, the researchers expect that the mechanism governing the gyre’s spin will diminish. With no governor to limit its speed, the researchers say the gyre will likely transition into “a new regime” and eventually spill over, like an overflowing bathtub, releasing huge volumes of cold, fresh water into the North Atlantic, which could affect the global climate and ocean circulation.

“This changing ice cover in the Arctic is changing the system which is driving the Beaufort Gyre, and changing its stability and intensity,” says Gianluca Meneghello, a research scientist in MIT’s Department of Earth, Atmospheric and Planetary Sciences. “If all this fresh water is released, it will affect the circulation of the Atlantic.”

Meneghello is a co-author of the paper, along with John Marshall, the Cecil and Ida Green Professor of Oceanography, Jean-Michel Campin and Edward Doddridge of MIT, and Mary-Louise Timmermans of Yale University.

A “new Arctic ocean”

There have been a handful of times in the recorded past when the Beaufort Gyre has spilled over, beginning with the Great Salinity Anomaly in the late 1960s, when the gyre sent a surge of cold, fresh water southward. Fresh water has the potential to dampen the ocean’s overturning circulation, affecting surface temperatures and perhaps storminess and climate.

Similar events could transpire if the Arctic ice controlling the Beaufort Gyre’s spin continues to recede each year.

“If this ice-ocean governor goes away, then we will end up with basically a new Arctic ocean,” Marshall says.

“Nature has a natural governor”

The researchers began looking into the dynamics of the Beaufort Gyre several years ago. At that time, they used measurements taken by satellites between 2003 and 2014, to track the movement of the Arctic ice cover, along with the speed of the Arctic wind. They used these measurements of ice and wind speed to estimate how fast the Beaufort Gyre must be downwelling, or spinning down beneath the ice. But the number they came up with was much smaller than what they expected.

“We thought there was a coding error,” Marshall recalls. “But it turns out there was something else kicking back.” In other words, there must be some other mechanism that was limiting, or slowing down, the gyre’s spin.

The team recalculated the gyre’s speed, this time by including estimates of ocean current activity in and around the gyre, which they inferred from satellite measurements of sea surface heights. The new estimate, Meneghello says, was “much more reasonable.”

In this new paper, the researchers studied the interplay of ice, wind, and ocean currents in more depth, using a high-resolution, idealized representation of ocean circulation based on the MIT General Circulation Model, built by Marshall’s group. They used this model to simulate the seasonal activity of the Beaufort Gyre as the Arctic ice expands and recedes each year.

They found that in the spring, as the Arctic ice melts away, the gyre is exposed to the wind, which acts to whip up the ocean current, causing it to spin faster and draw down more fresh water from the Arctic’s river runoff and melting ice. In the winter, as the Arctic ice sheet expands, the ice acts as a lid, shielding the gyre from the fast-moving winds. As a result, the gyre spins against the underside of the ice and eventually slows down.

“The ice moves much slower than wind, and when the gyre reaches the velocity of the ice, at this point, there is no friction — they’re rotating together, and there’s nothing applying a stress [to speed up the gyre],” Meneghello says. “This is the mechanism that governs the gyre’s speed.”

“In mechanical systems, the governor, or limiter, kicks in when things are going too fast,” Marshall adds. “We found nature has a natural governor in the Arctic.”

The evolution of sea ice over the Beaufort Gyre: In springtime, as ice thaws and melts into the sea, the gyre is exposed to the Arctic winds. Courtesy of the researchers

“In a warming world”

Marshall and Meneghello note that, as Arctic temperatures have risen in the last two decades, and summertime ice has shrunk with each year, the speed of the Beaufort Gyre has increased. Its currents have become more variable and unpredictable, and are only slightly slowed by the return of ice in the winter.

“At some point, if this trend continues, the gyre can’t swallow all this fresh water that it’s drawing down,” Marshall says. Eventually, the levee will likely break and the gyre will burst, releasing hundreds of billions of gallons of cold, fresh water into the North Atlantic.

An increasingly unstable Beaufort Gyre could also disrupt the Arctic’s halocline — the layer of ocean water underlying the gyre’s cold freshwater, that insulates it from much deeper, warmer, and saltier water. If the halocline is somehow weakened by a more instable gyre, this could encourage warmer waters to rise up, further melting the Arctic ice.

“This is part of what we’re seeing in a warming world,” Marshall says. “We know the global mean temperatures are going up, but the Arctic tempertures are going up even more. So the Arctic is very vulnerable to climate change. And we’re going to live through a period where the governor goes away, essentially.”

This research was supported, in part, by the National Science Foundation.

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Technique quickly identifies extreme event statistics

Seafaring vessels and offshore platforms endure a constant battery of waves and currents. Over decades of operation, these structures can, without warning, meet head-on with a rogue wave, freak storm, or some other extreme event, with potentially damaging consequences.

Now engineers at MIT have developed an algorithm that quickly pinpoints the types of extreme events that are likely to occur in a complex system, such as an ocean environment, where waves of varying magnitudes, lengths, and heights can create stress and pressure on a ship or offshore platform. The researchers can simulate the forces and stresses that extreme events — in the form of waves — may generate on a particular structure.

Compared with traditional methods, the team’s technique provides a much faster, more accurate risk assessment for systems that are likely to endure an extreme event at some point during their expected lifetime, by taking into account not only the statistical nature of the phenomenon but also the underlying dynamics.

“With our approach, you can assess, from the preliminary design phase, how a structure will behave not to one wave but to the overall collection or family of waves that can hit this structure,” says Themistoklis Sapsis, associate professor of mechanical and ocean engineering at MIT. “You can better design your structure so that you don’t have structural problems or stresses that surpass a certain limit.”

Sapsis says that the technique is not limited to ships and ocean platforms, but can be applied to any complex system that is vulnerable to extreme events. For instance, the method may be used to identify the type of storms that can generate severe flooding in a city, and where that flooding may occur. It could also be used to estimate the types of electrical overloads that could cause blackouts, and where those blackouts would occur throughout a city’s power grid.

Sapsis and Mustafa Mohamad, a former graduate student in Sapsis’ group, currently assistant research scientist at Courant Institute of Mathematical Sciences at New York University, are publishing their results this week in the Proceedings of the National Academy of Sciences.

Bypassing a shortcut

Engineers typically gauge a structure’s endurance to extreme events by using computationally intensive simulations to model a structure’s response to, for instance, a wave coming from a particular direction, with a certain height, length, and speed. These simulations are highly complex, as they model not just the wave of interest but also its interaction with the structure. By simulating the entire “wave field” as a particular wave rolls in, engineers can then estimate how a structure might be rocked and pushed by a particular wave, and what resulting forces and stresses may cause damage.

These risk assessment simulations are incredibly precise and in an ideal situation might predict how a structure would react to every single possible wave type, whether extreme or not. But such precision would require engineers to simulate millions of waves, with different parameters such as height and length scale — a process that could take months to compute. 

“That’s an insanely expensive problem,” Sapsis says. “To simulate one possible wave that can occur over 100 seconds, it takes a modern graphic processor unit, which is very fast, about 24 hours. We’re interested to understand what is the probability of an extreme event over 100 years.”

As a more practical shortcut, engineers use these simulators to run just a few scenarios, choosing to simulate several random wave types that they think might cause maximum damage. If a structural design survives these extreme, randomly generated waves, engineers assume the design will stand up against similar extreme events in the ocean.

But in choosing random waves to simulate, Sapsis says, engineers may miss other less obvious scenarios, such as combinations of medium-sized waves, or a wave with a certain slope that could develop into a damaging extreme event.

“What we have managed to do is to abandon this random sampling logic,” Sapsis says.

A fast learner

Instead of running millions of waves or even several randomly chosen waves through a computationally intensive simulation, Sapsis and Mohamad developed a machine-learning algorithm to first quickly identify the “most important” or “most informative” wave to run through such a simulation.

The algorithm is based on the idea that each wave has a certain probability of contributing to an extreme event on the structure. The probability itself has some uncertainty, or error, since it represents the effect of a complex dynamical system. Moreover, some waves are more certain to contribute to an extreme event over others.

The researchers designed the algorithm so that they can quickly feed in various types of waves and their physical properties, along with their known effects on a theoretical offshore platform. From the known waves that the researchers plug into the algorithm, it can essentially “learn” and make a rough estimate of how the platform will behave in response to any unknown wave. Through this machine-learning step, the algorithm learns how the offshore structure behaves over all possible waves. It then identifies a particular wave that maximally reduces the error of the probability for extreme events. This wave has a high probability of occuring and leads to an extreme event. In this way the algorithm goes beyond a purely statistical approach and takes into account the dynamical behavior of the system under consideration.

The researchers tested the algorithm on a theoretical scenario involving a simplified offshore platform subjected to incoming waves. The team started out by plugging four typical waves into the machine-learning algorithm, including the waves’ known effects on an offshore platform. From this, the algorithm quickly identified the dimensions of a new wave that has a high probability of occurring, and it maximally reduces the error for the probability of an extreme event.

The team then plugged this wave into a more computationally intensive, open-source simulation to model the response of a simplified offshore platform. They fed the results of this first simulation back into their algorithm to identify the next best wave to simulate, and repeated the entire process. In total, the group ran 16 simulations over several days to model a platform’s behavior under various extreme events. In comparison, the researchers carried out simulations using a more conventional method, in which they blindly simulated as many waves as possible, and were able to generate similar statistical results only after running thousands of scenarios over several months.

MIT researchers simulated the behavior of a simplified offshore platform in response to the waves that are most likely to contribute to an extreme event. Courtesy of the researchers

Sapsis says the results demonstrate that the team’s method quickly hones in on the waves that are most certain to be involved in an extreme event, and provides designers with more informed, realistic scenarios to simulate, in order to test the endurance of not just offshore platforms, but also power grids and flood-prone regions.

“This method paves the way to perform risk assessment, design, and optimization of complex systems based on extreme events statistics, which is something that has not been considered or done before without severe simplifications,” Sapsis says. “We’re now in a position where we can say, using ideas like this, you can understand and optimize your system, according to risk criteria to extreme events.”

This research was supported, in part, by the Office of Naval Research, Army Research Office, and Air Force Office of Scientific Research, and was initiated through a grant from the American Bureau of Shipping.

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Five from MIT earn Simons Foundation Postdoctoral Fellowships in Marine Microbial Ecology

Four current and former MIT-Woods Hole Oceanographic Institution Joint Program students (MIT-WHOI) and one postdoc from the Department of Civil and Environmental Engineering (CEE) have been awarded Simons Foundation Postdoctoral Fellowships in Marine Microbial Ecology, bringing the total of MIT awardees to five out of the nine fellowships granted nationally in 2018.

The Simons Foundation exists to advance the frontiers of research in mathematics and the basic sciences. Its Life Sciences division supports basic research on fundamental questions in biology, and is currently focused on origins of life, microbial oceanography, microbial ecology and evolution, and support of early career scientists. For the postdoctoral fellowships in marine microbial ecology, the foundation encourages applicants outside of strictly ocean research, seeking researchers interested in using cross-disciplinary experience, modeling, and theory development to explore the interrelationship of microorganisms and ocean processes.

“Postdoctoral fellows bring new ideas and energy to a field, so support for postdocs not only helps launch their careers but also pushes the field forward,” says Marian Carlson, director of life sciences at the foundation.

The awards are for three years and include an annual stipend and $25,000 towards research support.

B.B. Cael

MIT-WHOI Joint Program graduate student B.B. Cael — currently working with Professor Mick Follows of the Department of Earth, Atmospheric and Planetary Sciences at MIT — successfully sought Simons Foundation support for a postdoctoral fellowship to build upon his thesis research on the export of biogenic carbon out of the surface ocean and attenuation of sinking particulate matter (SPM) through the ocean’s interior.

“Phytoplankton living in the sunlit surface ocean mediate the transformation of energy, carbon, and inorganic nutrients within the global marine biosphere,” Cael explains. “In the open ocean, the fraction of SPM that is not ‘remineralized’ or degraded by microbes in the photosynthetic zone becomes sequestered well below the permanent thermocline and is effectively removed from exchange with the atmosphere for decades to millennia. This process is one of many ways in which ocean ecology plays a role in our planet’s climate.”

As a postdoc with Angelique E. White in the Department of Oceanography at the University of Hawai’i, Cael will collect measurements to develop and test plausible and mechanistic theories for SPM flux that might provide an improved understanding for climate and ocean models.

Cael holds a BA in mathematics, human biology, and philosophy, and an MS in applied mathematics, both from Brown University.

Matti Gralka

MIT CEE postdoc Matti Gralka studies microscopic interactions in complex microbial communities on chitin particles in the lab of Otto Cordero, the Doherty Assistant Professor in Ocean Utilization and assistant professor of civil and environmental engineering at MIT. He plans to use the Simons award to investigate the resistance and resilience of marine microbial communities to perturbations.

“I am a physicist broadly interested in applying quantitative experiments and models towards understanding fundamental principles about biological systems and processes,” says Gralka. “At MIT, I will study the interplay of ecology and evolution, i.e., can we predict the assembly and function of microbial communities, their adaptation and response to perturbations, without a full knowledge of all microscopic details?”

Prior to MIT, Gralka completed his PhD in physics at the University of California at Berkeley working with Professor Oskar Hallatschek to study evolutionary dynamics in microbial colonies, investigating how spatial structure affects the action of selection.

Bennett Lambert

With this award from the Simons Foundation, graduate student Bennett Lambert of CEE and the MIT-WHOI Joint Program will be pursuing his postdoctoral fellowship at the University of Washington, working with E. Virginia Armbrust on the behavior of marine microbes and the role diversity plays in survival.

Lambert’s current research in CEE Visiting Associate Professor Roman Stocker’s lab investigates the interactions of individual microbes and how those interactions scale up to affect biogeochemistry in the oceans. Traditional oceanographic techniques cannot be used to investigate the microorganisms, causing Lambert and his colleagues to engineer an in situ chemotaxis assay (ISCA). This allows the investigation of microbial behavior in their natural environment.

“To examine the interactions, I've been working to develop microfluidic techniques that can be applied in both the field and the lab. In the Armbrust Lab, I'll be continuing in the same vein and applying microfluidic techniques to study phenotypic heterogeneity in marine picoeukaryotes,” says Lambert.

Prior to MIT, Lambert completed his BS in civil and environmental engineering at the University of Alberta.

Also receiving 2018 Simons Foundation fellowships in marine microbial ecology are two alumni of the MIT-WHOI Joint Program: Emily Zakem PhD ’17 and Nicholas Hawko PhD ’17. Zakem, herself a former member of the Follows Group at MIT, will explore, “what controls the transition from aerobic to anaerobic microbial activity in the ocean,” in the laboratory of Professor Naomi Levine at the University of Southern California. Also at the University of Southern California, Hawko will be working on, “regional versus phylogenetic inheritance of iron metabolic traits in Prochlorococcus,” with Professor Seth John.

A complete list of the award recipients and their projects is available at the Simons Foundation website.

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