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    MIT-derived algorithm helps forecast the frequency of extreme weather

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    To assess a community’s risk of extreme weather, policymakers rely first on global climate models that can be run decades, and even centuries, forward in time, but only at a coarse resolution. These models might be used to gauge, for instance, future climate conditions for the northeastern U.S., but not specifically for Boston.

    To estimate Boston’s future risk of extreme weather such as flooding, policymakers can combine a coarse model’s large-scale predictions with a finer-resolution model, tuned to estimate how often Boston is likely to experience damaging floods as the climate warms. But this risk analysis is only as accurate as the predictions from that first, coarser climate model.

    “If you get those wrong for large-scale environments, then you miss everything in terms of what extreme events will look like at smaller scales, such as over individual cities,” says Themistoklis Sapsis, the William I. Koch Professor and director of the Center for Ocean Engineering in MIT’s Department of Mechanical Engineering.

    Sapsis and his colleagues have now developed a method to “correct” the predictions from coarse climate models. By combining machine learning with dynamical systems theory, the team’s approach “nudges” a climate model’s simulations into more realistic patterns over large scales. When paired with smaller-scale models to predict specific weather events such as tropical cyclones or floods, the team’s approach produced more accurate predictions for how often specific locations will experience those events over the next few decades, compared to predictions made without the correction scheme.

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    This animation shows the evolution of storms around the northern hemisphere, as a result of a high-resolution storm model, combined with the MIT team’s corrected global climate model. The simulation improves the modeling of extreme values for wind, temperature, and humidity, which typically have significant errors in coarse scale models. Credit: Courtesy of Ruby Leung and Shixuan Zhang, PNNL

    Sapsis says the new correction scheme is general in form and can be applied to any global climate model. Once corrected, the models can help to determine where and how often extreme weather will strike as global temperatures rise over the coming years. 

    “Climate change will have an effect on every aspect of human life, and every type of life on the planet, from biodiversity to food security to the economy,” Sapsis says. “If we have capabilities to know accurately how extreme weather will change, especially over specific locations, it can make a lot of difference in terms of preparation and doing the right engineering to come up with solutions. This is the method that can open the way to do that.”

    The team’s results appear today in the Journal of Advances in Modeling Earth Systems. The study’s MIT co-authors include postdoc Benedikt Barthel Sorensen and Alexis-Tzianni Charalampopoulos SM ’19, PhD ’23, with Shixuan Zhang, Bryce Harrop, and Ruby Leung of the Pacific Northwest National Laboratory in Washington state.

    Over the hood

    Today’s large-scale climate models simulate weather features such as the average temperature, humidity, and precipitation around the world, on a grid-by-grid basis. Running simulations of these models takes enormous computing power, and in order to simulate how weather features will interact and evolve over periods of decades or longer, models average out features every 100 kilometers or so.

    “It’s a very heavy computation requiring supercomputers,” Sapsis notes. “But these models still do not resolve very important processes like clouds or storms, which occur over smaller scales of a kilometer or less.”

    To improve the resolution of these coarse climate models, scientists typically have gone under the hood to try and fix a model’s underlying dynamical equations, which describe how phenomena in the atmosphere and oceans should physically interact.

    “People have tried to dissect into climate model codes that have been developed over the last 20 to 30 years, which is a nightmare, because you can lose a lot of stability in your simulation,” Sapsis explains. “What we’re doing is a completely different approach, in that we’re not trying to correct the equations but instead correct the model’s output.”

    The team’s new approach takes a model’s output, or simulation, and overlays an algorithm that nudges the simulation toward something that more closely represents real-world conditions. The algorithm is based on a machine-learning scheme that takes in data, such as past information for temperature and humidity around the world, and learns associations within the data that represent fundamental dynamics among weather features. The algorithm then uses these learned associations to correct a model’s predictions.

    “What we’re doing is trying to correct dynamics, as in how an extreme weather feature, such as the windspeeds during a Hurricane Sandy event, will look like in the coarse model, versus in reality,” Sapsis says. “The method learns dynamics, and dynamics are universal. Having the correct dynamics eventually leads to correct statistics, for example, frequency of rare extreme events.”

    Climate correction

    As a first test of their new approach, the team used the machine-learning scheme to correct simulations produced by the Energy Exascale Earth System Model (E3SM), a climate model run by the U.S. Department of Energy, that simulates climate patterns around the world at a resolution of 110 kilometers. The researchers used eight years of past data for temperature, humidity, and wind speed to train their new algorithm, which learned dynamical associations between the measured weather features and the E3SM model. They then ran the climate model forward in time for about 36 years and applied the trained algorithm to the model’s simulations. They found that the corrected version produced climate patterns that more closely matched real-world observations from the last 36 years, not used for training.

    “We’re not talking about huge differences in absolute terms,” Sapsis says. “An extreme event in the uncorrected simulation might be 105 degrees Fahrenheit, versus 115 degrees with our corrections. But for humans experiencing this, that is a big difference.”

    When the team then paired the corrected coarse model with a specific, finer-resolution model of tropical cyclones, they found the approach accurately reproduced the frequency of extreme storms in specific locations around the world.

    “We now have a coarse model that can get you the right frequency of events, for the present climate. It’s much more improved,” Sapsis says. “Once we correct the dynamics, this is a relevant correction, even when you have a different average global temperature, and it can be used for understanding how forest fires, flooding events, and heat waves will look in a future climate. Our ongoing work is focusing on analyzing future climate scenarios.”

    “The results are particularly impressive as the method shows promising results on E3SM, a state-of-the-art climate model,” says Pedram Hassanzadeh, an associate professor who leads the Climate Extremes Theory and Data group at the University of Chicago and was not involved with the study. “It would be interesting to see what climate change projections this framework yields once future greenhouse-gas emission scenarios are incorporated.”

    This work was supported, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      Artificial reef designed by MIT engineers could protect marine life, reduce storm damage

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      The beautiful, gnarled, nooked-and-crannied reefs that surround tropical islands serve as a marine refuge and natural buffer against stormy seas. But as the effects of climate change bleach and break down coral reefs around the world, and extreme weather events become more common, coastal communities are left increasingly vulnerable to frequent flooding and erosion.

      An MIT team is now hoping to fortify coastlines with “architected” reefs — sustainable, offshore structures engineered to mimic the wave-buffering effects of natural reefs while also providing pockets for fish and other marine life.

      The team’s reef design centers on a cylindrical structure surrounded by four rudder-like slats. The engineers found that when this structure stands up against a wave, it efficiently breaks the wave into turbulent jets that ultimately dissipate most of the wave’s total energy. The team has calculated that the new design could reduce as much wave energy as existing artificial reefs, using 10 times less material.

      The researchers plan to fabricate each cylindrical structure from sustainable cement, which they would mold in a pattern of “voxels” that could be automatically assembled, and would provide pockets for fish to explore and other marine life to settle in. The cylinders could be connected to form a long, semipermeable wall, which the engineers could erect along a coastline, about half a mile from shore. Based on the team’s initial experiments with lab-scale prototypes, the architected reef could reduce the energy of incoming waves by more than 95 percent.

      “This would be like a long wave-breaker,” says Michael Triantafyllou, the Henry L. and Grace Doherty Professor in Ocean Science and Engineering in the Department of Mechanical Engineering. “If waves are 6 meters high coming toward this reef structure, they would be ultimately less than a meter high on the other side. So, this kills the impact of the waves, which could prevent erosion and flooding.”

      Details of the architected reef design are reported today in a study appearing in the open-access journal PNAS Nexus. Triantafyllou’s MIT co-authors are Edvard Ronglan SM ’23; graduate students Alfonso Parra Rubio, Jose del Auila Ferrandis, and Erik Strand; research scientists Patricia Maria Stathatou and Carolina Bastidas; and Professor Neil Gershenfeld, director of the Center for Bits and Atoms; along with Alexis Oliveira Da Silva at the Polytechnic Institute of Paris, Dixia Fan of Westlake University, and Jeffrey Gair Jr. of Scinetics, Inc.

      Leveraging turbulence

      Some regions have already erected artificial reefs to protect their coastlines from encroaching storms. These structures are typically sunken ships, retired oil and gas platforms, and even assembled configurations of concrete, metal, tires, and stones. However, there’s variability in the types of artificial reefs that are currently in place, and no standard for engineering such structures. What’s more, the designs that are deployed tend to have a low wave dissipation per unit volume of material used. That is, it takes a huge amount of material to break enough wave energy to adequately protect coastal communities.

      The MIT team instead looked for ways to engineer an artificial reef that would efficiently dissipate wave energy with less material, while also providing a refuge for fish living along any vulnerable coast.

      “Remember, natural coral reefs are only found in tropical waters,” says Triantafyllou, who is director of the MIT Sea Grant. “We cannot have these reefs, for instance, in Massachusetts. But architected reefs don’t depend on temperature, so they can be placed in any water, to protect more coastal areas.”

      MIT researchers test the wave-breaking performance of two artificial reef structures in the MIT Towing Tank.Credit: Courtesy of the researchers

      The new effort is the result of a collaboration between researchers in MIT Sea Grant, who developed the reef structure’s hydrodynamic design, and researchers at the Center for Bits and Atoms (CBA), who worked to make the structure modular and easy to fabricate on location. The team’s architected reef design grew out of two seemingly unrelated problems. CBA researchers were developing ultralight cellular structures for the aerospace industry, while Sea Grant researchers were assessing the performance of blowout preventers in offshore oil structures — cylindrical valves that are used to seal off oil and gas wells and prevent them from leaking.

      The team’s tests showed that the structure’s cylindrical arrangement generated a high amount of drag. In other words, the structure appeared to be especially efficient in dissipating high-force flows of oil and gas. They wondered: Could the same arrangement dissipate another type of flow, in ocean waves?

      The researchers began to play with the general structure in simulations of water flow, tweaking its dimensions and adding certain elements to see whether and how waves changed as they crashed against each simulated design. This iterative process ultimately landed on an optimized geometry: a vertical cylinder flanked by four long slats, each attached to the cylinder in a way that leaves space for water to flow through the resulting structure. They found this setup essentially breaks up any incoming wave energy, causing parts of the wave-induced flow to spiral to the sides rather than crashing ahead.

      “We’re leveraging this turbulence and these powerful jets to ultimately dissipate wave energy,” Ferrandis says.

      Standing up to storms

      Once the researchers identified an optimal wave-dissipating structure, they fabricated a laboratory-scale version of an architected reef made from a series of the cylindrical structures, which they 3D-printed from plastic. Each test cylinder measured about 1 foot wide and 4 feet tall. They assembled a number of cylinders, each spaced about a foot apart, to form a fence-like structure, which they then lowered into a wave tank at MIT. They then generated waves of various heights and measured them before and after passing through the architected reef.

      “We saw the waves reduce substantially, as the reef destroyed their energy,” Triantafyllou says.

      The team has also looked into making the structures more porous, and friendly to fish. They found that, rather than making each structure from a solid slab of plastic, they could use a more affordable and sustainable type of cement.

      “We’ve worked with biologists to test the cement we intend to use, and it’s benign to fish, and ready to go,” he adds.

      They identified an ideal pattern of “voxels,” or microstructures, that cement could be molded into, in order to fabricate the reefs while creating pockets in which fish could live. This voxel geometry resembles individual egg cartons, stacked end to end, and appears to not affect the structure’s overall wave-dissipating power.

      “These voxels still maintain a big drag while allowing fish to move inside,” Ferrandis says.

      The team is currently fabricating cement voxel structures and assembling them into a lab-scale architected reef, which they will test under various wave conditions. They envision that the voxel design could be modular, and scalable to any desired size, and easy to transport and install in various offshore locations. “Now we’re simulating actual sea patterns, and testing how these models will perform when we eventually have to deploy them,” says Anjali Sinha, a graduate student at MIT who recently joined the group.

      Going forward, the team hopes to work with beach towns in Massachusetts to test the structures on a pilot scale.

      “These test structures would not be small,” Triantafyllou emphasizes. “They would be about a mile long, and about 5 meters tall, and would cost something like 6 million dollars per mile. So it’s not cheap. But it could prevent billions of dollars in storm damage. And with climate change, protecting the coasts will become a big issue.”

      This work was funded, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      New tool predicts flood risk from hurricanes in a warming climate

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      Coastal cities and communities will face more frequent major hurricanes with climate change in the coming years. To help prepare coastal cities against future storms, MIT scientists have developed a method to predict how much flooding a coastal community is likely to experience as hurricanes evolve over the next decades.

      When hurricanes make landfall, strong winds whip up salty ocean waters that generate storm surge in coastal regions. As the storms move over land, torrential rainfall can induce further flooding inland. When multiple flood sources such as storm surge and rainfall interact, they can compound a hurricane’s hazards, leading to significantly more flooding than would result from any one source alone. The new study introduces a physics-based method for predicting how the risk of such complex, compound flooding may evolve under a warming climate in coastal cities.

      One example of compound flooding’s impact is the aftermath from Hurricane Sandy in 2012. The storm made landfall on the East Coast of the United States as heavy winds whipped up a towering storm surge that combined with rainfall-driven flooding in some areas to cause historic and devastating floods across New York and New Jersey.

      In their study, the MIT team applied the new compound flood-modeling method to New York City to predict how climate change may influence the risk of compound flooding from Sandy-like hurricanes over the next decades.  

      They found that, in today’s climate, a Sandy-level compound flooding event will likely hit New York City every 150 years. By midcentury, a warmer climate will drive up the frequency of such flooding, to every 60 years. At the end of the century, destructive Sandy-like floods will deluge the city every 30 years — a fivefold increase compared to the present climate.

      “Long-term average damages from weather hazards are usually dominated by the rare, intense events like Hurricane Sandy,” says study co-author Kerry Emanuel, professor emeritus of atmospheric science at MIT. “It is important to get these right.”

      While these are sobering projections, the researchers hope the flood forecasts can help city planners prepare and protect against future disasters. “Our methodology equips coastal city authorities and policymakers with essential tools to conduct compound flooding risk assessments from hurricanes in coastal cities at a detailed, granular level, extending to each street or building, in both current and future decades,” says study author Ali Sarhadi, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences.

      The team’s open-access study appears online today in the Bulletin of the American Meteorological Society. Co-authors include Raphaël Rousseau-Rizzi at MIT’s Lorenz Center, Kyle Mandli at Columbia University, Jeffrey Neal at the University of Bristol, Michael Wiper at the Charles III University of Madrid, and Monika Feldmann at the Swiss Federal Institute of Technology Lausanne.

      The seeds of floods

      To forecast a region’s flood risk, weather modelers typically look to the past. Historical records contain measurements of previous hurricanes’ wind speeds, rainfall, and spatial extent, which scientists use to predict where and how much flooding may occur with coming storms. But Sarhadi believes that the limitations and brevity of these historical records are insufficient for predicting future hurricanes’ risks.

      “Even if we had lengthy historical records, they wouldn’t be a good guide for future risks because of climate change,” he says. “Climate change is changing the structural characteristics, frequency, intensity, and movement of hurricanes, and we cannot rely on the past.”

      Sarhadi and his colleagues instead looked to predict a region’s risk of hurricane flooding in a changing climate using a physics-based risk assessment methodology. They first paired simulations of hurricane activity with coupled ocean and atmospheric models over time. With the hurricane simulations, developed originally by Emanuel, the researchers virtually scatter tens of thousands of “seeds” of hurricanes into a simulated climate. Most seeds dissipate, while a few grow into category-level storms, depending on the conditions of the ocean and atmosphere.

      When the team drives these hurricane simulations with climate models of ocean and atmospheric conditions under certain global temperature projections, they can see how hurricanes change, for instance in terms of intensity, frequency, and size, under past, current, and future climate conditions.

      The team then sought to precisely predict the level and degree of compound flooding from future hurricanes in coastal cities. The researchers first used rainfall models to simulate rain intensity for a large number of simulated hurricanes, then applied numerical models to hydraulically translate that rainfall intensity into flooding on the ground during landfalling of hurricanes, given information about a region such as its surface and topography characteristics. They also simulated the same hurricanes’ storm surges, using hydrodynamic models to translate hurricanes’ maximum wind speed and sea level pressure into surge height in coastal areas. The simulation further assessed the propagation of ocean waters into coastal areas, causing coastal flooding.

      Then, the team developed a numerical hydrodynamic model to predict how two sources of hurricane-induced flooding, such as storm surge and rain-driven flooding, would simultaneously interact through time and space, as simulated hurricanes make landfall in coastal regions such as New York City, in both current and future climates.  

      “There’s a complex, nonlinear hydrodynamic interaction between saltwater surge-driven flooding and freshwater rainfall-driven flooding, that forms compound flooding that a lot of existing methods ignore,” Sarhadi says. “As a result, they underestimate the risk of compound flooding.”

      Amplified risk

      With their flood-forecasting method in place, the team applied it to a specific test case: New York City. They used the multipronged method to predict the city’s risk of compound flooding from hurricanes, and more specifically from Sandy-like hurricanes, in present and future climates. Their simulations showed that the city’s odds of experiencing Sandy-like flooding will increase significantly over the next decades as the climate warms, from once every 150 years in the current climate, to every 60 years by 2050, and every 30 years by 2099.

      Interestingly, they found that much of this increase in risk has less to do with how hurricanes themselves will change with warming climates, but with how sea levels will increase around the world.

      “In future decades, we will experience sea level rise in coastal areas, and we also incorporated that effect into our models to see how much that would increase the risk of compound flooding,” Sarhadi explains. “And in fact, we see sea level rise is playing a major role in amplifying the risk of compound flooding from hurricanes in New York City.”

      The team’s methodology can be applied to any coastal city to assess the risk of compound flooding from hurricanes and extratropical storms. With this approach, Sarhadi hopes decision-makers can make informed decisions regarding the implementation of adaptive measures, such as reinforcing coastal defenses to enhance infrastructure and community resilience.

      “Another aspect highlighting the urgency of our research is the projected 25 percent increase in coastal populations by midcentury, leading to heightened exposure to damaging storms,” Sarhadi says. “Additionally, we have trillions of dollars in assets situated in coastal flood-prone areas, necessitating proactive strategies to reduce damages from compound flooding from hurricanes under a warming climate.”

      This research was supported, in part, by Homesite Insurance. More

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      in Environment

      Studying rivers from worlds away

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      Rivers have flowed on two other worlds in the solar system besides Earth: Mars, where dry tracks and craters are all that’s left of ancient rivers and lakes, and Titan, Saturn’s largest moon, where rivers of liquid methane still flow today.

      A new technique developed by MIT geologists allows scientists to see how intensely rivers used to flow on Mars, and how they currently flow on Titan. The method uses satellite observations to estimate the rate at which rivers move fluid and sediment downstream.

      Applying their new technique, the MIT team calculated how fast and deep rivers were in certain regions on Mars more than 1 billion years ago. They also made similar estimates for currently active rivers on Titan, even though the moon’s thick atmosphere and distance from Earth make it harder to explore, with far fewer available images of its surface than those of Mars.

      “What’s exciting about Titan is that it’s active. With this technique, we have a method to make real predictions for a place where we won’t get more data for a long time,” says Taylor Perron, the Cecil and Ida Green Professor in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “And on Mars, it gives us a time machine, to take the rivers that are dead now and get a sense of what they were like when they were actively flowing.”

      Perron and his colleagues have published their results today in the Proceedings of the National Academy of Sciences. Perron’s MIT co-authors are first author Samuel Birch, Paul Corlies, and Jason Soderblom, with Rose Palermo and Andrew Ashton of the Woods Hole Oceanographic Institution (WHOI), Gary Parker of the University of Illinois at Urbana-Champaign, and collaborators from the University of California at Los Angeles, Yale University, and Cornell University.

      River math

      The team’s study grew out of Perron and Birch’s puzzlement over Titan’s rivers. The images taken by NASA’s Cassini spacecraft have shown a curious lack of fan-shaped deltas at the mouths of most of the moon’s rivers, contrary to many rivers on Earth. Could it be that Titan’s rivers don’t carry enough flow or sediment to build deltas?

      The group built on the work of co-author Gary Parker, who in the 2000s developed a series of mathematical equations to describe river flow on Earth. Parker had studied measurements of rivers taken directly in the field by others. From these data, he found there were certain universal relationships between a river’s physical dimensions — its width, depth, and slope — and the rate at which it flowed. He drew up equations to describe these relationships mathematically, accounting for other variables such as the gravitational field acting on the river, and the size and density of the sediment being pushed along a river’s bed.

      “This means that rivers with different gravity and materials should follow similar relationships,” Perron says. “That opened up a possibility to apply this to other planets too.”

      Getting a glimpse

      On Earth, geologists can make field measurements of a river’s width, slope, and average sediment size, all of which can be fed into Parker’s equations to accurately predict a river’s flow rate, or how much water and sediment it can move downstream. But for rivers on other planets, measurements are more limited, and largely based on images and elevation measurements collected by remote satellites. For Mars, multiple orbiters have taken high-resolution images of the planet. For Titan, views are few and far between.

      Birch realized that any estimate of river flow on Mars or Titan would have to be based on the few characteristics that can be measured from remote images and topography — namely, a river’s width and slope. With some algebraic tinkering, he adapted Parker’s equations to work only with width and slope inputs. He then assembled data from 491 rivers on Earth, tested the modified equations on these rivers, and found that the predictions based solely on each river’s width and slope were accurate.

      Then, he applied the equations to Mars, and specifically, to the ancient rivers leading into Gale and Jezero Craters, both of which are thought to have been water-filled lakes billions of years ago. To predict the flow rate of each river, he plugged into the equations Mars’ gravity, and estimates of each river’s width and slope, based on images and elevation measurements taken by orbiting satellites.

      From their predictions of flow rate, the team found that rivers likely flowed for at least 100,000 years at Gale Crater and at least 1 million years at Jezero Crater — long enough to have possibly supported life. They were also able to compare their predictions of the average size of sediment on each river’s bed with actual field measurements of Martian grains near each river, taken by NASA’s Curiosity and Perseverance rovers. These few field measurements allowed the team to check that their equations, applied on Mars, were accurate.

      The team then took their approach to Titan. They zeroed in on two locations where river slopes can be measured, including a river that flows into a lake the size of Lake Ontario. This river appears to form a delta as it feeds into the lake. However, the delta is one of only a few thought to exist on the moon — nearly every viewable river flowing into a lake mysteriously lacks a delta. The team also applied their method to one of these other delta-less rivers.

      They calculated both rivers’ flow and found that they may be comparable to some of the biggest rivers on Earth, with deltas estimated to have a flow rate as large as the Mississippi. Both rivers should move enough sediment to build up deltas. Yet, most rivers on Titan lack the fan-shaped deposits. Something else must be at work to explain this lack of river deposits.

      In another finding, the team calculated that rivers on Titan should be wider and have a gentler slope than rivers carrying the same flow on Earth or Mars. “Titan is the most Earth-like place,” Birch says. ”We’ve only gotten a glimpse of it. There’s so much more that we know is down there, and this remote technique is pushing us a little closer.”

      This research was supported, in part, by NASA and the Heising-Simons Foundation. More

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      in Environment

      Megawatt electrical motor designed by MIT engineers could help electrify aviation

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      Aviation’s huge carbon footprint could shrink significantly with electrification. To date, however, only small all-electric planes have gotten off the ground. Their electric motors generate hundreds of kilowatts of power. To electrify larger, heavier jets, such as commercial airliners, megawatt-scale motors are required. These would be propelled by hybrid or turbo-electric propulsion systems where an electrical machine is coupled with a gas turbine aero-engine.

      To meet this need, a team of MIT engineers is now creating a 1-megawatt motor that could be a key stepping stone toward electrifying larger aircraft. The team has designed and tested the major components of the motor, and shown through detailed computations that the coupled components can work as a whole to generate one megawatt of power, at a weight and size competitive with current small aero-engines.

      For all-electric applications, the team envisions the motor could be paired with a source of electricity such as a battery or a fuel cell. The motor could then turn the electrical energy into mechanical work to power a plane’s propellers. The electrical machine could also be paired with a traditional turbofan jet engine to run as a hybrid propulsion system, providing electric propulsion during certain phases of a flight.

      “No matter what we use as an energy carrier — batteries, hydrogen, ammonia, or sustainable aviation fuel — independent of all that, megawatt-class motors will be a key enabler for greening aviation,” says Zoltan Spakovszky, the T. Wilson Professor in Aeronautics and the Director of the Gas Turbine Laboratory (GTL) at MIT, who leads the project.

      Spakovszky and members of his team, along with industry collaborators, will present their work at a special session of the American Institute of Aeronautics and Astronautics – Electric Aircraft Technologies Symposium (EATS) at the Aviation conference in June.

      The MIT team is composed of faculty, students, and research staff from GTL and the MIT Laboratory for Electromagnetic and Electronic Systems: Henry Andersen Yuankang Chen, Zachary Cordero, David Cuadrado,  Edward Greitzer, Charlotte Gump, James Kirtley, Jr., Jeffrey Lang, David Otten, David Perreault, and Mohammad Qasim,  along with Marc Amato of Innova-Logic LLC. The project is sponsored by Mitsubishi Heavy Industries (MHI).

      Heavy stuff

      To prevent the worst impacts from human-induced climate change, scientists have determined that global emissions of carbon dioxide must reach net zero by 2050. Meeting this target for aviation, Spakovszky says, will require “step-change achievements” in the design of unconventional aircraft, smart and flexible fuel systems, advanced materials, and safe and efficient electrified propulsion. Multiple aerospace companies are focused on electrified propulsion and the design of megawatt-scale electric machines that are powerful and light enough to propel passenger aircraft.

      “There is no silver bullet to make this happen, and the devil is in the details,” Spakovszky says. “This is hard engineering, in terms of co-optimizing individual components and making them compatible with each other while maximizing overall performance. To do this means we have to push the boundaries in materials, manufacturing, thermal management, structures and rotordynamics, and power electronics”

      Broadly speaking, an electric motor uses electromagnetic force to generate motion. Electric motors, such as those that power the fan in your laptop, use electrical energy — from a battery or power supply — to generate a magnetic field, typically through copper coils. In response, a magnet, set near the coils, then spins in the direction of the generated field and can then drive a fan or propeller.

      Electric machines have been around for over 150 years, with the understanding that, the bigger the appliance or vehicle, the larger the copper coils  and the magnetic rotor, making the machine heavier. The more power the electrical machine generates, the more heat it produces, which requires additional elements to keep the components cool — all of which can take up space and add significant weight to the system, making it challenging for airplane applications.

      “Heavy stuff doesn’t go on airplanes,” Spakovszky says. “So we had to come up with a compact, lightweight, and powerful architecture.”

      Good trajectory

      As designed, the MIT electric motor and power electronics are each about the size of a checked suitcase weighing less than an adult passenger.

      The motor’s main components are: a high-speed rotor, lined with an array of magnets with varying orientation of polarity; a compact low-loss stator that fits inside the rotor and contains an intricate array of copper windings; an advanced heat exchanger that keeps the components cool while transmitting the torque of the machine; and a distributed power electronics system, made from 30 custom-built circuit boards, that precisely change the currents running through each of the stator’s copper windings, at high frequency.

      “I believe this is the first truly co-optimized integrated design,” Spakovszky says. “Which means we did a very extensive design space exploration where all considerations from thermal management, to rotor dynamics, to power electronics and electrical machine architecture were assessed in an integrated way to find out what is the best possible combination to get the required specific power at one megawatt.”

      As a whole system, the motor is designed such that the distributed circuit boards are close coupled with the electrical machine to minimize transmission loss and to allow effective air cooling through the integrated heat exchanger.

      “This is a high-speed machine, and to keep it rotating while creating torque, the magnetic fields have to be traveling very quickly, which we can do through our circuit boards switching at high frequency,” Spakovszky says.

      To mitigate risk, the team has built and tested each of the major components individually, and shown that they can operate as designed and at conditions exceeding normal operational demands. The researchers plan to assemble the first fully working electric motor, and start testing it in the fall.

      “The electrification of aircraft has been on a steady rise,” says Phillip Ansell, director of the Center for Sustainable Aviation at the University of Illinois Urbana-Champaign, who was not involved in the project. “This group’s design uses a wonderful combination of conventional and cutting-edge methods for electric machine development, allowing it to offer both robustness and efficiency to meet the practical needs of aircraft of the future.”

      Once the MIT team can demonstrate the electric motor as a whole, they say the design could power regional aircraft and could also be a companion to conventional jet engines, to enable hybrid-electric propulsion systems. The team also envision that multiple one-megawatt motors could power multiple fans distributed along the wing on future aircraft configurations. Looking ahead, the foundations of the one-megawatt electrical machine design could potentially be scaled up to multi-megawatt motors, to power larger passenger planes.

      “I think we’re on a good trajectory,” says Spakovszky, whose group and research have focused on more than just gas turbines. “We are not electrical engineers by training, but addressing the 2050 climate grand challenge is of utmost importance; working with electrical engineering faculty, staff and students for this goal can draw on MIT’s breadth of technologies so the whole is greater than the sum of the parts. So we are reinventing ourselves in new areas. And MIT gives you the opportunity to do that.” More

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      in Environment

      River erosion can shape fish evolution, study suggests

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      If we could rewind the tape of species evolution around the world and play it forward over hundreds of millions of years to the present day, we would see biodiversity clustering around regions of tectonic turmoil. Tectonically active regions such as the Himalayan and Andean mountains are especially rich in flora and fauna due to their shifting landscapes, which act to divide and diversify species over time.

      But biodiversity can also flourish in some geologically quieter regions, where tectonics hasn’t shaken up the land for millennia. The Appalachian Mountains are a prime example: The range has not seen much tectonic activity in hundreds of millions of years, and yet the region is a notable hotspot of freshwater biodiversity.

      Now, an MIT study identifies a geological process that may shape the diversity of species in tectonically inactive regions. In a paper appearing today in Science, the researchers report that river erosion can be a driver of biodiversity in these older, quieter environments.

      They make their case in the southern Appalachians, and specifically the Tennessee River Basin, a region known for its huge diversity of freshwater fishes. The team found that as rivers eroded through different rock types in the region, the changing landscape pushed a species of fish known as the greenfin darter into different tributaries of the river network. Over time, these separated populations developed into their own distinct lineages.

      The team speculates that erosion likely drove the greenfin darter to diversify. Although the separated populations appear outwardly similar, with the greenfin darter’s characteristic green-tinged fins, they differ substantially in their genetic makeup. For now, the separated populations are classified as one single species. 

      “Give this process of erosion more time, and I think these separate lineages will become different species,” says Maya Stokes PhD ’21, who carried out part of the work as a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS).

      The greenfin darter may not be the only species to diversify as a consequence of river erosion. The researchers suspect that erosion may have driven many other species to diversify throughout the basin, and possibly other tectonically inactive regions around the world.

      “If we can understand the geologic factors that contribute to biodiversity, we can do a better job of conserving it,” says Taylor Perron, the Cecil and Ida Green Professor of Earth, Atmospheric, and Planetary Sciences at MIT.

      The study’s co-authors include collaborators at Yale University, Colorado State University, the University of Tennessee, the University of Massachusetts at Amherst, and the Tennessee Valley Authority (TVA). Stokes is currently an assistant professor at Florida State University.

      Fish in trees

      The new study grew out of Stokes’ PhD work at MIT, where she and Perron were exploring connections between geomorphology (the study of how landscapes evolve) and biology. They came across work at Yale by Thomas Near, who studies lineages of North American freshwater fishes. Near uses DNA sequence data collected from freshwater fishes across various regions of North America to show how and when certain species evolved and diverged in relation to each other.

      Near brought a curious observation to the team: a habitat distribution map of the greenfin darter showing that the fish was found in the Tennessee River Basin — but only in the southern half. What’s more, Near had mitochondrial DNA sequence data showing that the fish’s populations appeared to be different in their genetic makeup depending on the tributary in which they were found.

      To investigate the reasons for this pattern, Stokes gathered greenfin darter tissue samples from Near’s extensive collection at Yale, as well as from the field with help from TVA colleagues. She then analyzed DNA sequences from across the entire genome, and compared the genes of each individual fish to every other fish in the dataset. The team then created a phylogenetic tree of the greenfin darter, based on the genetic similarity between fish.

      From this tree, they observed that fish within a tributary were more related to each other than to fish in other tributaries. What’s more, fish within neighboring tributaries were more similar to each other than fish from more distant tributaries.

      “Our question was, could there have been a geological mechanism that, over time, took this single species, and splintered it into different, genetically distinct groups?” Perron says.

      A changing landscape

      Stokes and Perron started to observe a “tight correlation” between greenfin darter habitats and the type of rock where they are found. In particular, much of the southern half of the Tennessee River Basin, where the species abounds, is made of metamorphic rock, whereas the northern half consists of sedimentary rock, where the fish are not found.

      They also observed that the rivers running through metamorphic rock are steeper and more narrow, which generally creates more turbulence, a characteristic greenfin darters seem to prefer. The team wondered: Could the distribution of greenfin darter habitat have been shaped by a changing landscape of rock type, as rivers eroded into the land over time?

      To check this idea, the researchers developed a model to simulate how a landscape evolves as rivers erode through various rock types. They fed the model information about the rock types in the Tennessee River Basin today, then ran the simulation back to see how the same region may have looked millions of years ago, when more metamorphic rock was exposed.

      They then ran the model forward and observed how the exposure of metamorphic rock shrank over time. They took special note of where and when connections between tributaries crossed into non-metamorphic rock, blocking fish from passing between those tributaries. They drew up a simple timeline of these blocking events and compared this to the phylogenetic tree of diverging greenfin darters. The two were remarkably similar: The fish seemed to form separate lineages in the same order as when their respective tributaries became separated from the others.

      “It means it’s plausible that erosion through different rock layers caused isolation between different populations of the greenfin darter and caused lineages to diversify,” Stokes says.

      “This study is highly compelling because it reveals a much more subtle but powerful mechanism for speciation in passive margins,” says Josh Roering, professor of Earth sciences at the University of Oregon, who was not involved in the study. “Stokes and Perron have revealed some of the intimate connections between aquatic species and geology that may be much more common than we realize.”

      This research was supported, in part, by the mTerra Catalyst Fund and the U.S. National Science Foundation through the AGeS Geochronology Program and the Graduate Research Fellowship Program. While at MIT, Stokes received support through the Martin Fellowship for Sustainability and the Hugh Hampton Young Fellowship. More

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      in Environment

      Moving water and earth

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      As a river cuts through a landscape, it can operate like a conveyer belt, moving truckloads of sediment over time. Knowing how quickly or slowly this sediment flows can help engineers plan for the downstream impact of restoring a river or removing a dam. But the models currently used to estimate sediment flow can be off by a wide margin.

      An MIT team has come up with a better formula to calculate how much sediment a fluid can push across a granular bed — a process known as bed load transport. The key to the new formula comes down to the shape of the sediment grains.

      It may seem intuitive: A smooth, round stone should skip across a river bed faster than an angular pebble. But flowing water also pushes harder on the angular pebble, which could erase the round stone’s advantage. Which effect wins? Existing sediment transport models surprisingly don’t offer an answer, mainly because the problem of measuring grain shape is too unwieldy: How do you quantify a pebble’s contours?

      The MIT researchers found that instead of considering a grain’s exact shape, they could boil the concept of shape down to two related properties: friction and drag. A grain’s drag, or resistance to fluid flow, relative to its internal friction, the resistance to sliding past other grains, can provide an easy way to gauge the effects of a grain’s shape.

      When they incorporated this new mathematical measure of grain shape into a standard model for bed load transport, the new formula made predictions that matched experiments that the team performed in the lab.

      “Sediment transport is a part of life on Earth’s surface, from the impact of storms on beaches to the gravel nests in mountain streams where salmon lay their eggs,” the team writes of their new study, appearing today in Nature. “Damming and sea level rise have already impacted many such terrains and pose ongoing threats. A good understanding of bed load transport is crucial to our ability to maintain these landscapes or restore them to their natural states.”

      The study’s authors are Eric Deal, Santiago Benavides, Qiong Zhang, Ken Kamrin, and Taylor Perron of MIT, and Jeremy Venditti and Ryan Bradley of Simon Fraser University in Canada.

      Figuring flow

      Video of glass spheres (top) and natural river gravel (bottom) undergoing bed load transport in a laboratory flume, slowed down 17x relative to real time. Average grain diameter is about 5 mm. This video shows how rolling and tumbling natural grains interact with one another in a way that is not possible for spheres. What can’t be seen so easily is that natural grains also experience higher drag forces from the flowing water than spheres do.

      Credit: Courtesy of the researchers

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      Bed load transport is the process by which a fluid such as air or water drags grains across a bed of sediment, causing the grains to hop, skip, and roll along the surface as a fluid flows through. This movement of sediment in a current is what drives rocks to migrate down a river and sand grains to skip across a desert.

      Being able to estimate bed load transport can help scientists prepare for situations such as urban flooding and coastal erosion. Since the 1930s, one formula has been the go-to model for calculating bed load transport; it’s based on a quantity known as the Shields parameter, after the American engineer who originally derived it. This formula sets a relationship between the force of a fluid pushing on a bed of sediment, and how fast the sediment moves in response. Albert Shields incorporated certain variables into this formula, including the average size and density of a sediment’s grains — but not their shape.

      “People may have backed away from accounting for shape because it’s one of these very scary degrees of freedom,” says Kamrin, a professor of mechanical engineering at MIT. “Shape is not a single number.”

      And yet, the existing model has been known to be off by a factor of 10 in its predictions of sediment flow. The team wondered whether grain shape could be a missing ingredient, and if so, how the nebulous property could be mathematically represented.

      “The trick was to focus on characterizing the effect that shape has on sediment transport dynamics, rather than on characterizing the shape itself,” says Deal.

      “It took some thinking to figure that out,” says Perron, a professor of geology in MIT’s Department of Earth, Atmospheric and Planetary Sciences. “But we went back to derive the Shields parameter, and when you do the math, this ratio of drag to friction falls out.”

      Drag and drop

      Their work showed that the Shields parameter — which predicts how much sediment is transported — can be modified to include not just size and density, but also grain shape, and furthermore, that a grain’s shape can be simply represented by a measure of the grain’s drag and its internal friction. The math seemed to make sense. But could the new formula predict how sediment actually flows?

      To answer this, the researchers ran a series of flume experiments, in which they pumped a current of water through an inclined tank with a floor covered in sediment. They ran tests with sediment of various grain shapes, including beds of round glass beads, smooth glass chips, rectangular prisms, and natural gravel. They measured the amount of sediment that was transported through the tank in a fixed amount of time. They then determined the effect of each sediment type’s grain shape by measuring the grains’ drag and friction.

      For drag, the researchers simply dropped individual grains down through a tank of water and gathered statistics for the time it took the grains of each sediment type to reach the bottom. For instance, a flatter grain type takes a longer time on average, and therefore has greater drag, than a round grain type of the same size and density.

      To measure friction, the team poured grains through a funnel and onto a circular tray, then measured the resulting pile’s angle, or slope — an indication of the grains’ friction, or ability to grip onto each other.

      For each sediment type, they then worked the corresponding shape’s drag and friction into the new formula, and found that it could indeed predict the bedload transport, or the amount of moving sediment that the researchers measured in their experiments.

      The team says the new model more accurately represents sediment flow. Going forward, scientists and engineers can use the model to better gauge how a river bed will respond to scenarios such as sudden flooding from severe weather or the removal of a dam.

      “If you were trying to make a prediction of how fast all that sediment will get evacuated after taking a dam out, and you’re wrong by a factor of three or five, that’s pretty bad,” Perron says. “Now we can do a lot better.”

      This research was supported, in part, by the U.S. Army Research Laboratory. More

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      in Environment

      Keeping indoor humidity levels at a “sweet spot” may reduce spread of Covid-19

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      We know proper indoor ventilation is key to reducing the spread of Covid-19. Now, a study by MIT researchers finds that indoor relative humidity may also influence transmission of the virus.

      Relative humidity is the amount of moisture in the air compared to the total moisture the air can hold at a given temperature before saturating and forming condensation.

      In a study appearing today in the Journal of the Royal Society Interface, the MIT team reports that maintaining an indoor relative humidity between 40 and 60 percent is associated with relatively lower rates of Covid-19 infections and deaths, while indoor conditions outside this range are associated with worse Covid-19 outcomes. To put this into perspective, most people are comfortable between 30 and 50 percent relative humidity, and an airplane cabin is at around 20 percent relative humidity.

      The findings are based on the team’s analysis of Covid-19 data combined with meteorological measurements from 121 countries, from January 2020 through August 2020. Their study suggests a strong connection between regional outbreaks and indoor relative humidity.

      In general, the researchers found that whenever a region experienced a rise in Covid-19 cases and deaths prevaccination, the estimated indoor relative humidity in that region, on average, was either lower than 40 percent or higher than 60 percent regardless of season. Nearly all regions in the study experienced fewer Covid-19 cases and deaths during periods when estimated indoor relative humidity was within a “sweet spot” between 40 and 60 percent.

      “There’s potentially a protective effect of this intermediate indoor relative humidity,” suggests lead author Connor Verheyen, a PhD student in medical engineering and medical physics in the Harvard-MIT Program in Health Sciences and Technology.

      “Indoor ventilation is still critical,” says co-author Lydia Bourouiba, director of the MIT Fluid Dynamics of Disease Transmission Laboratory and associate professor in the departments of Civil and Environmental Engineering and Mechanical Engineering, and at the Institute for Medical Engineering and Science at MIT. “However, we find that maintaining an indoor relative humidity in that sweet spot — of 40 to 60 percent — is associated with reduced Covid-19 cases and deaths.”

      Seasonal swing?

      Since the start of the Covid-19 pandemic, scientists have considered the possibility that the virus’ virulence swings with the seasons. Infections and associated deaths appear to rise in winter and ebb in summer. But studies looking to link the virus’ patterns to seasonal outdoor conditions have yielded mixed results.

      Verheyen and Bourouiba examined whether Covid-19 is influenced instead by indoor — rather than outdoor — conditions, and, specifically, relative humidity. After all, they note that most societies spend more than 90 percent of their time indoors, where the majority of viral transmission has been shown to occur. What’s more, indoor conditions can be quite different from outdoor conditions as a result of climate control systems, such as heaters that significantly dry out indoor air.

      Could indoor relative humidity have affected the spread and severity of Covid-19 around the world? And could it help explain the differences in health outcomes from region to region?

      Tracking humidity

      For answers, the team focused on the early period of the pandemic when vaccines were not yet available, reasoning that vaccinated populations would obscure the influence of any other factor such as indoor humidity. They gathered global Covid-19 data, including case counts and reported deaths, from January 2020 to August 2020,  and identified countries with at least 50 deaths, indicating at least one outbreak had occurred in those countries.

      In all, they focused on 121 countries where Covid-19 outbreaks occurred. For each country, they also tracked the local Covid-19 related policies, such as isolation, quarantine, and testing measures, and their statistical association with Covid-19 outcomes.

      For each day that Covid-19 data was available, they used meteorological data to calculate a country’s outdoor relative humidity. They then estimated the average indoor relative humidity, based on outdoor relative humidity and guidelines on temperature ranges for human comfort. For instance, guidelines report that humans are comfortable between 66 to 77 degrees Fahrenheit indoors. They also assumed that on average, most populations have the means to heat indoor spaces to comfortable temperatures. Finally, they also collected experimental data, which they used to validate their estimation approach.

      For every instance when outdoor temperatures were below the typical human comfort range, they assumed indoor spaces were heated to reach that comfort range. Based on the added heating, they calculated the associated drop in indoor relative humidity.

      In warmer times, both outdoor and indoor relative humidity for each country was about the same, but they quickly diverged in colder times. While outdoor humidity remained around 50 percent throughout the year, indoor relative humidity for countries in the Northern and Southern Hemispheres dropped below 40 percent in their respective colder periods, when Covid-19 cases and deaths also spiked in these regions.

      For countries in the tropics, relative humidity was about the same indoors and outdoors throughout the year, with a gradual rise indoors during the region’s summer season, when high outdoor humidity likely raised the indoor relative humidity over 60 percent. They found this rise mirrored the gradual increase in Covid-19 deaths in the tropics.

      “We saw more reported Covid-19 deaths on the low and high end of indoor relative humidity, and less in this sweet spot of 40 to 60 percent,” Verheyen says. “This intermediate relative humidity window is associated with a better outcome, meaning fewer deaths and a deceleration of the pandemic.”

      “We were very skeptical initially, especially as the Covid-19 data can be noisy and inconsistent,” Bourouiba says. “We thus were very thorough trying to poke holes in our own analysis, using a range of approaches to test the limits and robustness of the findings, including taking into account factors such as government intervention. Despite all our best efforts, we found that even when considering countries with very strong versus very weak Covid-19 mitigation policies, or wildly different outdoor conditions, indoor — rather than outdoor — relative humidity maintains an underlying strong and robust link with Covid-19 outcomes.”

      It’s still unclear how indoor relative humidity affects Covid-19 outcomes. The team’s follow-up studies suggest that pathogens may survive longer in respiratory droplets in both very dry and very humid conditions.

      “Our ongoing work shows that there are emerging hints of mechanistic links between these factors,” Bourouiba says. “For now however, we can say that indoor relative humidity emerges in a robust manner as another mitigation lever that organizations and individuals can monitor, adjust, and maintain in the optimal 40 to 60 percent range, in addition to proper ventillation.”

      This research was made possible, in part, by an MIT Alumni Class fund, the Richard and Susan Smith Family Foundation, the National Institutes of Health, and the National Science Foundation. More

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      in Environment

      Small eddies play a big role in feeding ocean microbes

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      Subtropical gyres are enormous rotating ocean currents that generate sustained circulations in the Earth’s subtropical regions just to the north and south of the equator. These gyres are slow-moving whirlpools that circulate within massive basins around the world, gathering up nutrients, organisms, and sometimes trash, as the currents rotate from coast to coast.

      For years, oceanographers have puzzled over conflicting observations within subtropical gyres. At the surface, these massive currents appear to host healthy populations of phytoplankton — microbes that feed the rest of the ocean food chain and are responsible for sucking up a significant portion of the atmosphere’s carbon dioxide.

      But judging from what scientists know about the dynamics of gyres, they estimated the currents themselves wouldn’t be able to maintain enough nutrients to sustain the phytoplankton they were seeing. How, then, were the microbes able to thrive?

      Now, MIT researchers have found that phytoplankton may receive deliveries of nutrients from outside the gyres, and that the delivery vehicle is in the form of eddies — much smaller currents that swirl at the edges of a gyre. These eddies pull nutrients in from high-nutrient equatorial regions and push them into the center of a gyre, where the nutrients are then taken up by other currents and pumped to the surface to feed phytoplankton.

      Ocean eddies, the team found, appear to be an important source of nutrients in subtropical gyres. Their replenishing effect, which the researchers call a “nutrient relay,” helps maintain populations of phytoplankton, which play a central role in the ocean’s ability to sequester carbon from the atmosphere. While climate models tend to project a decline in the ocean’s ability to sequester carbon over the coming decades, this “nutrient relay” could help sustain carbon storage over the subtropical oceans.

      “There’s a lot of uncertainty about how the carbon cycle of the ocean will evolve as climate continues to change, ” says Mukund Gupta, a postdoc at Caltech who led the study as a graduate student at MIT. “As our paper shows, getting the carbon distribution right is not straightforward, and depends on understanding the role of eddies and other fine-scale motions in the ocean.”

      Gupta and his colleagues report their findings this week in the Proceedings of the National Academy of Sciences. The study’s co-authors are Jonathan Lauderdale, Oliver Jahn, Christopher Hill, Stephanie Dutkiewicz, and Michael Follows at MIT, and Richard Williams at the University of Liverpool.

      A snowy puzzle

      A cross-section of an ocean gyre resembles a stack of nesting bowls that is stratified by density: Warmer, lighter layers lie at the surface, while colder, denser waters make up deeper layers. Phytoplankton live within the ocean’s top sunlit layers, where the microbes require sunlight, warm temperatures, and nutrients to grow.

      When phytoplankton die, they sink through the ocean’s layers as “marine snow.” Some of this snow releases nutrients back into the current, where they are pumped back up to feed new microbes. The rest of the snow sinks out of the gyre, down to the deepest layers of the ocean. The deeper the snow sinks, the more difficult it is for it to be pumped back to the surface. The snow is then trapped, or sequestered, along with any unreleased carbon and nutrients.

      Oceanographers thought that the main source of nutrients in subtropical gyres came from recirculating marine snow. But as a portion of this snow inevitably sinks to the bottom, there must be another source of nutrients to explain the healthy populations of phytoplankton at the surface. Exactly what that source is “has left the oceanography community a little puzzled for some time,” Gupta says.

      Swirls at the edge

      In their new study, the team sought to simulate a subtropical gyre to see what other dynamics may be at work. They focused on the North Pacific gyre, one of the Earth’s five major gyres, which circulates over most of the North Pacific Ocean, and spans more than 20 million square kilometers. 

      The team started with the MITgcm, a general circulation model that simulates the physical circulation patterns in the atmosphere and oceans. To reproduce the North Pacific gyre’s dynamics as realistically as possible, the team used an MITgcm algorithm, previously developed at NASA and MIT, which tunes the model to match actual observations of the ocean, such as ocean currents recorded by satellites, and temperature and salinity measurements taken by ships and drifters.  

      “We use a simulation of the physical ocean that is as realistic as we can get, given the machinery of the model and the available observations,” Lauderdale says.

      Play video

      An animation of the North Pacific Ocean shows phosphate nutrient concentrations at 500 meters below the ocean surface. The swirls represent small eddies transporting phosphate from the nutrient-rich equator (lighter colors), northward toward the nutrient-depleted subtropics (darker colors). This nutrient relay mechanism helps sustain biological activity and carbon sequestration in the subtropical ocean. Credit: Oliver Jahn

      The realistic model captured finer details, at a resolution of less than 20 kilometers per pixel, compared to other models that have a more limited resolution. The team combined the simulation of the ocean’s physical behavior with the Darwin model — a simulation of microbe communities such as phytoplankton, and how they grow and evolve with ocean conditions.

      The team ran the combined simulation of the North Pacific gyre over a decade, and created animations to visualize the pattern of currents and the nutrients they carried, in and around the gyre. What emerged were small eddies that ran along the edges of the enormous gyre and appeared to be rich in nutrients.

      “We were picking up on little eddy motions, basically like weather systems in the ocean,” Lauderdale says. “These eddies were carrying packets of high-nutrient waters, from the equator, north into the center of the gyre and downwards along the sides of the bowls. We wondered if these eddy transfers made an important delivery mechanism.”

      Surprisingly, the nutrients first move deeper, away from the sunlight, before being returned upwards where the phytoplankton live. The team found that ocean eddies could supply up to 50 percent of the nutrients in subtropical gyres.

      “That is very significant,” Gupta says. “The vertical process that recycles nutrients from marine snow is only half the story. The other half is the replenishing effect of these eddies. As subtropical gyres contribute a significant part of the world’s oceans, we think this nutrient relay is of global importance.”

      This research was supported, in part, by the Simons Foundation and NASA. More