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      in Environment

      Using seismology for groundwater management

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      As climate change increases the number of extreme weather events, such as megadroughts, groundwater management is key for sustaining water supply. But current groundwater monitoring tools are either costly or insufficient for deeper aquifers, limiting our ability to monitor and practice sustainable management in populated areas.

      Now, a new paper published in Nature Communications bridges seismology and hydrology with a pilot application that uses seismometers as a cost-effective way to monitor and map groundwater fluctuations.

      “Our measurements are independent from and complementary to traditional observations,” says Shujuan Mao PhD ’21, lead author on the paper. “It provides a new way to dictate groundwater management and evaluate the impact of human activity on shaping underground hydrologic systems.”

      Mao, currently a Thompson Postdoctoral Fellow in the Geophysics department at Stanford University, conducted most of the research during her PhD in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). Other contributors to the paper include EAPS department chair and Schlumberger Professor of Earth and Planetary Sciences Robert van der Hilst, as well as Michel Campillo and Albanne Lecointre from the Institut des Sciences de la Terre in France.

      While there are a few different methods currently used for measuring groundwater, they all come with notable drawbacks. Hydraulic heads, which drill through the ground and into the aquifers, are expensive and can only give limited information at the specific location they’re placed. Noninvasive techniques based on satellite- or airborne-sensing lack the sensitivity and resolution needed to observe deeper depths.

      Mao proposes using seismometers, which are instruments used to measure ground vibrations such as the waves produced by earthquakes. They can measure seismic velocity, which is the propagation speed of seismic waves. Seismic velocity measurements are unique to the mechanical state of rocks, or the ways rocks respond to their physical environment, and can tell us a lot about them.

      The idea of using seismic velocity to characterize property changes in rocks has long been used in laboratory-scale analysis, but only recently have scientists been able to measure it continuously in realistic-scale geological settings. For aquifer monitoring, Mao and her team associate the seismic velocity with the hydraulic property, or the water content, in the rocks.

      Seismic velocity measurements make use of ambient seismic fields, or background noise, recorded by seismometers. “The Earth’s surface is always vibrating, whether due to ocean waves, winds, or human activities,” she explains. “Most of the time those vibrations are really small and are considered ‘noise’ by traditional seismologists. But in recent years scientists have shown that the continuous noise records in fact contain a wealth of information about the properties and structures of the Earth’s interior.”

      To extract useful information from the noise records, Mao and her team used a technique called seismic interferometry, which analyzes wave interference to calculate the seismic velocity of the medium the waves pass through. For their pilot application, Mao and her team applied this analysis to basins in the Metropolitan Los Angeles region, an area suffering from worsening drought and a growing population.

      By doing this, Mao and her team were able to see how the aquifers changed physically over time at a high resolution. Their seismic velocity measurements verified measurements taken by hydraulic heads over the last 20 years, and the images matched very well with satellite data. They could also see differences in how the storage areas changed between counties in the area that used different water pumping practices, which is important for developing water management protocol.

      Mao also calls using the seismometers a “buy-one get-one free” deal, since seismometers are already in use for earthquake and tectonic studies not just across California, but worldwide, and could help “avoid the expensive cost of drilling and maintaining dedicated groundwater monitoring wells,” she says.

      Mao emphasizes that this study is just the beginning of exploring possible applications of seismic noise interferometry in this way. It can be used to monitor other near-surface systems, such as geothermal or volcanic systems, and Mao is currently applying it to oil and gas fields. But in places like California currently experiencing megadroughts, and who rely on groundwater for a large portion of their water needs, this kind of information is key for sustainable water management.

      “It’s really important, especially now, to characterize these changes in groundwater storage so that we can promote data-informed policymaking to help them thrive under increasing water stress,” she says.

      This study was funded, in part, by the European Research Council, with additional support from the Thompson Fellowship at Stanford University. More

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      in Environment

      Cracking the case of Arctic sea ice breakup

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      Despite its below-freezing temperatures, the Arctic is warming twice as fast as the rest of the planet. As Arctic sea ice melts, fewer bright surfaces are available to reflect sunlight back into space. When fractures open in the ice cover, the water underneath gets exposed. Dark, ice-free water absorbs the sun’s energy, heating the ocean and driving further melting — a vicious cycle. This warming in turn melts glacial ice, contributing to rising sea levels.

      Warming climate and rising sea levels endanger the nearly 40 percent of the U.S. population living in coastal areas, the billions of people who depend on the ocean for food and their livelihoods, and species such as polar bears and Artic foxes. Reduced ice coverage is also making the once-impassable region more accessible, opening up new shipping lanes and ports. Interest in using these emerging trans-Arctic routes for product transit, extraction of natural resources (e.g., oil and gas), and military activity is turning an area traditionally marked by low tension and cooperation into one of global geopolitical competition.

      As the Arctic opens up, predicting when and where the sea ice will fracture becomes increasingly important in strategic decision-making. However, huge gaps exist in our understanding of the physical processes contributing to ice breakup. Researchers at MIT Lincoln Laboratory seek to help close these gaps by turning a data-sparse environment into a data-rich one. They envision deploying a distributed set of unattended sensors across the Arctic that will persistently detect and geolocate ice fracturing events. Concurrently, the network will measure various environmental conditions, including water temperature and salinity, wind speed and direction, and ocean currents at different depths. By correlating these fracturing events and environmental conditions, they hope to discover meaningful insights about what is causing the sea ice to break up. Such insights could help predict the future state of Arctic sea ice to inform climate modeling, climate change planning, and policy decision-making at the highest levels.

      “We’re trying to study the relationship between ice cracking, climate change, and heat flow in the ocean,” says Andrew March, an assistant leader of Lincoln Laboratory’s Advanced Undersea Systems and Technology Group. “Do cracks in the ice cause warm water to rise and more ice to melt? Do undersea currents and waves cause cracking? Does cracking cause undersea waves? These are the types of questions we aim to investigate.”

      Arctic access

      In March 2022, Ben Evans and Dave Whelihan, both researchers in March’s group, traveled for 16 hours across three flights to Prudhoe Bay, located on the North Slope of Alaska. From there, they boarded a small specialized aircraft and flew another 90 minutes to a three-and-a-half-mile-long sheet of ice floating 160 nautical miles offshore in the Arctic Ocean. In the weeks before their arrival, the U.S. Navy’s Arctic Submarine Laboratory had transformed this inhospitable ice floe into a temporary operating base called Ice Camp Queenfish, named after the first Sturgeon-class submarine to operate under the ice and the fourth to reach the North Pole. The ice camp featured a 2,500-foot-long runway, a command center, sleeping quarters to accommodate up to 60 personnel, a dining tent, and an extremely limited internet connection.

      At Queenfish, for the next four days, Evans and Whelihan joined U.S. Navy, Army, Air Force, Marine Corps, and Coast Guard members, and members of the Royal Canadian Air Force and Navy and United Kingdom Royal Navy, who were participating in Ice Exercise (ICEX) 2022. Over the course of about three weeks, more than 200 personnel stationed at Queenfish, Prudhoe Bay, and aboard two U.S. Navy submarines participated in this biennial exercise. The goals of ICEX 2022 were to assess U.S. operational readiness in the Arctic; increase our country’s experience in the region; advance our understanding of the Arctic environment; and continue building relationships with other services, allies, and partner organizations to ensure a free and peaceful Arctic. The infrastructure provided for ICEX concurrently enables scientists to conduct research in an environment — either in person or by sending their research equipment for exercise organizers to deploy on their behalf — that would be otherwise extremely difficult and expensive to access.

      In the Arctic, windchill temperatures can plummet to as low as 60 degrees Fahrenheit below zero, cold enough to freeze exposed skin within minutes. Winds and ocean currents can drift the entire camp beyond the reach of nearby emergency rescue aircraft, and the ice can crack at any moment. To ensure the safety of participants, a team of Navy meteorological specialists continually monitors the ever-changing conditions. The original camp location for ICEX 2022 had to be evacuated and relocated after a massive crack formed in the ice, delaying Evans’ and Whelihan’s trip. Even the newly selected site had a large crack form behind the camp and another crack that necessitated moving a number of tents.

      “Such cracking events are only going to increase as the climate warms, so it’s more critical now than ever to understand the physical processes behind them,” Whelihan says. “Such an understanding will require building technology that can persist in the environment despite these incredibly harsh conditions. So, it’s a challenge not only from a scientific perspective but also an engineering one.”

      “The weather always gets a vote, dictating what you’re able to do out here,” adds Evans. “The Arctic Submarine Laboratory does a lot of work to construct the camp and make it a safe environment where researchers like us can come to do good science. ICEX is really the only opportunity we have to go onto the sea ice in a place this remote to collect data.”

      A legacy of sea ice experiments

      Though this trip was Whelihan’s and Evans’ first to the Arctic region, staff from the laboratory’s Advanced Undersea Systems and Technology Group have been conducting experiments at ICEX since 2018. However, because of the Arctic’s remote location and extreme conditions, data collection has rarely been continuous over long periods of time or widespread across large areas. The team now hopes to change that by building low-cost, expendable sensing platforms consisting of co-located devices that can be left unattended for automated, persistent, near-real-time monitoring. 

      “The laboratory’s extensive expertise in rapid prototyping, seismo-acoustic signal processing, remote sensing, and oceanography make us a natural fit to build this sensor network,” says Evans.

      In the months leading up to the Arctic trip, the team collected seismometer data at Firepond, part of the laboratory’s Haystack Observatory site in Westford, Massachusetts. Through this local data collection, they aimed to gain a sense of what anthropogenic (human-induced) noise would look like so they could begin to anticipate the kinds of signatures they might see in the Arctic. They also collected ice melting/fracturing data during a thaw cycle and correlated these data with the weather conditions (air temperature, humidity, and pressure). Through this analysis, they detected an increase in seismic signals as the temperature rose above 32 F — an indication that air temperature and ice cracking may be related.

      A sensing network

      At ICEX, the team deployed various commercial off-the-shelf sensors and new sensors developed by the laboratory and University of New Hampshire (UNH) to assess their resiliency in the frigid environment and to collect an initial dataset.

      “One aspect that differentiates these experiments from those of the past is that we concurrently collected seismo-acoustic data and environmental parameters,” says Evans.

      The commercial technologies were seismometers to detect the vibrational energy released when sea ice fractures or collides with other ice floes; a hydrophone (underwater microphone) array to record the acoustic energy created by ice-fracturing events; a sound speed profiler to measure the speed of sound through the water column; and a conductivity, temperature, and depth (CTD) profiler to measure the salinity (related to conductivity), temperature, and pressure (related to depth) throughout the water column. The speed of sound in the ocean primarily depends on these three quantities. 

      To precisely measure the temperature across the entire water column at one location, they deployed an array of transistor-based temperature sensors developed by the laboratory’s Advanced Materials and Microsystems Group in collaboration with the Advanced Functional Fabrics of America Manufacturing Innovation Institute. The small temperature sensors run along the length of a thread-like polymer fiber embedded with multiple conductors. This fiber platform, which can support a broad range of sensors, can be unspooled hundreds of feet below the water’s surface to concurrently measure temperature or other water properties — the fiber deployed in the Arctic also contained accelerometers to measure depth — at many points in the water column. Traditionally, temperature profiling has required moving a device up and down through the water column.

      The team also deployed a high-frequency echosounder supplied by Anthony Lyons and Larry Mayer, collaborators at UNH’s Center for Coastal and Ocean Mapping. This active sonar uses acoustic energy to detect internal waves, or waves occurring beneath the ocean’s surface.

      “You may think of the ocean as a homogenous body of water, but it’s not,” Evans explains. “Different currents can exist as you go down in depth, much like how you can get different winds when you go up in altitude. The UNH echosounder allows us to see the different currents in the water column, as well as ice roughness when we turn the sensor to look upward.”

      “The reason we care about currents is that we believe they will tell us something about how warmer water from the Atlantic Ocean is coming into contact with sea ice,” adds Whelihan. “Not only is that water melting ice but it also has lower salt content, resulting in oceanic layers and affecting how long ice lasts and where it lasts.”

      Back home, the team has begun analyzing their data. For the seismic data, this analysis involves distinguishing any ice events from various sources of anthropogenic noise, including generators, snowmobiles, footsteps, and aircraft. Similarly, the researchers know their hydrophone array acoustic data are contaminated by energy from a sound source that another research team participating in ICEX placed in the water. Based on their physics, icequakes — the seismic events that occur when ice cracks — have characteristic signatures that can be used to identify them. One approach is to manually find an icequake and use that signature as a guide for finding other icequakes in the dataset.

      From their water column profiling sensors, they identified an interesting evolution in the sound speed profile 30 to 40 meters below the ocean surface, related to a mass of colder water moving in later in the day. The group’s physical oceanographer believes this change in the profile is due to water coming up from the Bering Sea, water that initially comes from the Atlantic Ocean. The UNH-supplied echosounder also generated an interesting signal at a similar depth.

      “Our supposition is that this result has something to do with the large sound speed variation we detected, either directly because of reflections off that layer or because of plankton, which tend to rise on top of that layer,” explains Evans.  

      A future predictive capability

      Going forward, the team will continue mining their collected data and use these data to begin building algorithms capable of automatically detecting and localizing — and ultimately predicting — ice events correlated with changes in environmental conditions. To complement their experimental data, they have initiated conversations with organizations that model the physical behavior of sea ice, including the National Oceanic and Atmospheric Administration and the National Ice Center. Merging the laboratory’s expertise in sensor design and signal processing with their expertise in ice physics would provide a more complete understanding of how the Arctic is changing.

      The laboratory team will also start exploring cost-effective engineering approaches for integrating the sensors into packages hardened for deployment in the harsh environment of the Arctic.

      “Until these sensors are truly unattended, the human factor of usability is front and center,” says Whelihan. “Because it’s so cold, equipment can break accidentally. For example, at ICEX 2022, our waterproof enclosure for the seismometers survived, but the enclosure for its power supply, which was made out of a cheaper plastic, shattered in my hand when I went to pick it up.”

      The sensor packages will not only need to withstand the frigid environment but also be able to “phone home” over some sort of satellite data link and sustain their power. The team plans to investigate whether waste heat from processing can keep the instruments warm and how energy could be harvested from the Arctic environment.

      Before the next ICEX scheduled for 2024, they hope to perform preliminary testing of their sensor packages and concepts in Arctic-like environments. While attending ICEX 2022, they engaged with several other attendees — including the U.S. Navy, Arctic Submarine Laboratory, National Ice Center, and University of Alaska Fairbanks (UAF) — and identified cold room experimentation as one area of potential collaboration. Testing can also be performed at outdoor locations a bit closer to home and more easily accessible, such as the Great Lakes in Michigan and a UAF-maintained site in Barrow, Alaska. In the future, the laboratory team may have an opportunity to accompany U.S. Coast Guard personnel on ice-breaking vessels traveling from Alaska to Greenland. The team is also thinking about possible venues for collecting data far removed from human noise sources.

      “Since I’ve told colleagues, friends, and family I was going to the Arctic, I’ve had a lot of interesting conversations about climate change and what we’re doing there and why we’re doing it,” Whelihan says. “People don’t have an intrinsic, automatic understanding of this environment and its impact because it’s so far removed from us. But the Arctic plays a crucial role in helping to keep the global climate in balance, so it’s imperative we understand the processes leading to sea ice fractures.”

      This work is funded through Lincoln Laboratory’s internally administered R&D portfolio on climate. More

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      in Environment

      Ocean vital signs

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      Without the ocean, the climate crisis would be even worse than it is. Each year, the ocean absorbs billions of tons of carbon from the atmosphere, preventing warming that greenhouse gas would otherwise cause. Scientists estimate about 25 to 30 percent of all carbon released into the atmosphere by both human and natural sources is absorbed by the ocean.

      “But there’s a lot of uncertainty in that number,” says Ryan Woosley, a marine chemist and a principal research scientist in the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at MIT. Different parts of the ocean take in different amounts of carbon depending on many factors, such as the season and the amount of mixing from storms. Current models of the carbon cycle don’t adequately capture this variation.

      To close the gap, Woosley and a team of other MIT scientists developed a research proposal for the MIT Climate Grand Challenges competition — an Institute-wide campaign to catalyze and fund innovative research addressing the climate crisis. The team’s proposal, “Ocean Vital Signs,” involves sending a fleet of sailing drones to cruise the oceans taking detailed measurements of how much carbon the ocean is really absorbing. Those data would be used to improve the precision of global carbon cycle models and improve researchers’ ability to verify emissions reductions claimed by countries.

      “If we start to enact mitigation strategies—either through removing CO2 from the atmosphere or reducing emissions — we need to know where CO2 is going in order to know how effective they are,” says Woosley. Without more precise models there’s no way to confirm whether observed carbon reductions were thanks to policy and people, or thanks to the ocean.

      “So that’s the trillion-dollar question,” says Woosley. “If countries are spending all this money to reduce emissions, is it enough to matter?”

      In February, the team’s Climate Grand Challenges proposal was named one of 27 finalists out of the almost 100 entries submitted. From among this list of finalists, MIT will announce in April the selection of five flagship projects to receive further funding and support.

      Woosley is leading the team along with Christopher Hill, a principal research engineer in EAPS. The team includes physical and chemical oceanographers, marine microbiologists, biogeochemists, and experts in computational modeling from across the department, in addition to collaborators from the Media Lab and the departments of Mathematics, Aeronautics and Astronautics, and Electrical Engineering and Computer Science.

      Today, data on the flux of carbon dioxide between the air and the oceans are collected in a piecemeal way. Research ships intermittently cruise out to gather data. Some commercial ships are also fitted with sensors. But these present a limited view of the entire ocean, and include biases. For instance, commercial ships usually avoid storms, which can increase the turnover of water exposed to the atmosphere and cause a substantial increase in the amount of carbon absorbed by the ocean.

      “It’s very difficult for us to get to it and measure that,” says Woosley. “But these drones can.”

      If funded, the team’s project would begin by deploying a few drones in a small area to test the technology. The wind-powered drones — made by a California-based company called Saildrone — would autonomously navigate through an area, collecting data on air-sea carbon dioxide flux continuously with solar-powered sensors. This would then scale up to more than 5,000 drone-days’ worth of observations, spread over five years, and in all five ocean basins.

      Those data would be used to feed neural networks to create more precise maps of how much carbon is absorbed by the oceans, shrinking the uncertainties involved in the models. These models would continue to be verified and improved by new data. “The better the models are, the more we can rely on them,” says Woosley. “But we will always need measurements to verify the models.”

      Improved carbon cycle models are relevant beyond climate warming as well. “CO2 is involved in so much of how the world works,” says Woosley. “We’re made of carbon, and all the other organisms and ecosystems are as well. What does the perturbation to the carbon cycle do to these ecosystems?”

      One of the best understood impacts is ocean acidification. Carbon absorbed by the ocean reacts to form an acid. A more acidic ocean can have dire impacts on marine organisms like coral and oysters, whose calcium carbonate shells and skeletons can dissolve in the lower pH. Since the Industrial Revolution, the ocean has become about 30 percent more acidic on average.

      “So while it’s great for us that the oceans have been taking up the CO2, it’s not great for the oceans,” says Woosley. “Knowing how this uptake affects the health of the ocean is important as well.” More

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      in Environment

      Improving predictions of sea level rise for the next century

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      When we think of climate change, one of the most dramatic images that comes to mind is the loss of glacial ice. As the Earth warms, these enormous rivers of ice become a casualty of the rising temperatures. But, as ice sheets retreat, they also become an important contributor to one the more dangerous outcomes of climate change: sea-level rise. At MIT, an interdisciplinary team of scientists is determined to improve sea level rise predictions for the next century, in part by taking a closer look at the physics of ice sheets.

      Last month, two research proposals on the topic, led by Brent Minchew, the Cecil and Ida Green Career Development Professor in the Department of Earth, Atmospheric and Planetary Sciences (EAPS), were announced as finalists in the MIT Climate Grand Challenges initiative. Launched in July 2020, Climate Grand Challenges fielded almost 100 project proposals from collaborators across the Institute who heeded the bold charge: to develop research and innovations that will deliver game-changing advances in the world’s efforts to address the climate challenge.

      As finalists, Minchew and his collaborators from the departments of Urban Studies and Planning, Economics, Civil and Environmental Engineering, the Haystack Observatory, and external partners, received $100,000 to develop their research plans. A subset of the 27 proposals tapped as finalists will be announced next month, making up a portfolio of multiyear “flagship” projects receiving additional funding and support.

      One goal of both Minchew proposals is to more fully understand the most fundamental processes that govern rapid changes in glacial ice, and to use that understanding to build next-generation models that are more predictive of ice sheet behavior as they respond to, and influence, climate change.

      “We need to develop more accurate and computationally efficient models that provide testable projections of sea-level rise over the coming decades. To do so quickly, we want to make better and more frequent observations and learn the physics of ice sheets from these data,” says Minchew. “For example, how much stress do you have to apply to ice before it breaks?”

      Currently, Minchew’s Glacier Dynamics and Remote Sensing group uses satellites to observe the ice sheets on Greenland and Antarctica primarily with interferometric synthetic aperture radar (InSAR). But the data are often collected over long intervals of time, which only gives them “before and after” snapshots of big events. By taking more frequent measurements on shorter time scales, such as hours or days, they can get a more detailed picture of what is happening in the ice.

      “Many of the key unknowns in our projections of what ice sheets are going to look like in the future, and how they’re going to evolve, involve the dynamics of glaciers, or our understanding of how the flow speed and the resistances to flow are related,” says Minchew.

      At the heart of the two proposals is the creation of SACOS, the Stratospheric Airborne Climate Observatory System. The group envisions developing solar-powered drones that can fly in the stratosphere for months at a time, taking more frequent measurements using a new lightweight, low-power radar and other high-resolution instrumentation. They also propose air-dropping sensors directly onto the ice, equipped with seismometers and GPS trackers to measure high-frequency vibrations in the ice and pinpoint the motions of its flow.

      How glaciers contribute to sea level rise

      Current climate models predict an increase in sea levels over the next century, but by just how much is still unclear. Estimates are anywhere from 20 centimeters to two meters, which is a large difference when it comes to enacting policy or mitigation. Minchew points out that response measures will be different, depending on which end of the scale it falls toward. If it’s closer to 20 centimeters, coastal barriers can be built to protect low-level areas. But with higher surges, such measures become too expensive and inefficient to be viable, as entire portions of cities and millions of people would have to be relocated.

      “If we’re looking at a future where we could get more than a meter of sea level rise by the end of the century, then we need to know about that sooner rather than later so that we can start to plan and to do our best to prepare for that scenario,” he says.

      There are two ways glaciers and ice sheets contribute to rising sea levels: direct melting of the ice and accelerated transport of ice to the oceans. In Antarctica, warming waters melt the margins of the ice sheets, which tends to reduce the resistive stresses and allow ice to flow more quickly to the ocean. This thinning can also cause the ice shelves to be more prone to fracture, facilitating the calving of icebergs — events which sometimes cause even further acceleration of ice flow.

      Using data collected by SACOS, Minchew and his group can better understand what material properties in the ice allow for fracturing and calving of icebergs, and build a more complete picture of how ice sheets respond to climate forces. 

      “What I want is to reduce and quantify the uncertainties in projections of sea level rise out to the year 2100,” he says.

      From that more complete picture, the team — which also includes economists, engineers, and urban planning specialists — can work on developing predictive models and methods to help communities and governments estimate the costs associated with sea level rise, develop sound infrastructure strategies, and spur engineering innovation.

      Understanding glacier dynamics

      More frequent radar measurements and the collection of higher-resolution seismic and GPS data will allow Minchew and the team to develop a better understanding of the broad category of glacier dynamics — including calving, an important process in setting the rate of sea level rise which is currently not well understood.  

      “Some of what we’re doing is quite similar to what seismologists do,” he says. “They measure seismic waves following an earthquake, or a volcanic eruption, or things of this nature and use those observations to better understand the mechanisms that govern these phenomena.”

      Air-droppable sensors will help them collect information about ice sheet movement, but this method comes with drawbacks — like installation and maintenance, which is difficult to do out on a massive ice sheet that is moving and melting. Also, the instruments can each only take measurements at a single location. Minchew equates it to a bobber in water: All it can tell you is how the bobber moves as the waves disturb it.

      But by also taking continuous radar measurements from the air, Minchew’s team can collect observations both in space and in time. Instead of just watching the bobber in the water, they can effectively make a movie of the waves propagating out, as well as visualize processes like iceberg calving happening in multiple dimensions.

      Once the bobbers are in place and the movies recorded, the next step is developing machine learning algorithms to help analyze all the new data being collected. While this data-driven kind of discovery has been a hot topic in other fields, this is the first time it has been applied to glacier research.

      “We’ve developed this new methodology to ingest this huge amount of data,” he says, “and from that create an entirely new way of analyzing the system to answer these fundamental and critically important questions.”  More

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      in Environment

      MIT ReACT welcomes first Afghan cohort to its largest-yet certificate program

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      Through the championing support of the faculty and leadership of the MIT Afghan Working Group convened last September by Provost Martin Schmidt and chaired by Associate Provost for International Activities Richard Lester, MIT has come together to support displaced Afghan learners and scholars in a time of crisis. The MIT Refugee Action Hub (ReACT) has opened opportunities for 25 talented Afghan learners to participate in the hub’s certificate program in computer and data science (CDS), now in its fourth year, welcoming its largest and most diverse cohort to date — 136 learners from 29 countries.

      ”Even in the face of extreme disruption, education and scholarship must continue, and MIT is committed to providing resources and safe forums for displaced scholars,” says Lester. “We greatly appreciate MIT ReACT’s work to create learning opportunities for Afghan students whose lives have been upended by the crisis in their homeland.”

      Currently, more than 3.5 million Afghans are internally displaced, while 2.5 million are registered refugees residing in other parts of the world. With millions in Afghanistan facing famine, poverty, and civil unrest in what has become the world’s largest humanitarian crisis, the United Nations predicts the number of Afghans forced to flee their homes will continue to rise. 

      “Forced displacement is on the rise, fueled not only by constant political, economical, and social turmoil worldwide, but also by the ongoing climate change crisis, which threatens costly disruptions to society and has potential to create unprecedented displacement internationally,” says associate professor of civil and environmental engineering and ReACT’s faculty founder Admir Masic. During the orientation for the new CDS cohort in January, Masic emphasized the great need for educational programs like ReACT’s that address the specific challenges refugees and displaced learners face.

      A former Bosnian refugee, Masic spent his teenage years in Croatia, where educational opportunities were limited for young people with refugee status. His experience motivated him to found ReACT, which launched in 2017. Housed within Open Learning, ReACT is an MIT-wide effort to deliver global education and professional development programs to underserved communities, including refugees and migrants. ReACT’s signature program, CDS is a year-long, online program that combines MITx courses in programming and data science, personal and professional development workshops including MIT Bootcamps, and opportunities for practical experience.

      ReACT’s group of 25 learners from Afghanistan, 52 percent of whom are women, joins the larger CDS cohort in the program. They will receive support from their new colleagues as well as members of ReACT’s mentor and alumni network. While the majority of the group are residing around the world, including in Europe, North America, and neighboring countries, several still remain in Afghanistan. With the support of the Afghan Working Group, ReACT is working to connect with communities from the region to provide safe and inclusive learning environments for the cohort. ​​

      Building community and confidence

      Selected from more than 1,000 applicants, the new CDS cohort reflected on their personal and professional goals during a weeklong orientation.

      “I am here because I want to change my career and learn basics in this field to then obtain networks that I wouldn’t have got if it weren’t for this program,” said Samiullah Ajmal, who is joining the program from Afghanistan.

      Interactive workshops on topics such as leadership development and virtual networking rounded out the week’s events. Members of ReACT’s greater community — which has grown in recent years to include a network of external collaborators including nonprofits, philanthropic supporters, universities, and alumni — helped facilitate these workshops and other orientation activities.

      For instance, Na’amal, a social enterprise that connects refugees to remote work opportunities, introduced the CDS learners to strategies for making career connections remotely. “We build confidence while doing,” says Susan Mulholland, a leadership and development coach with Na’amal who led the networking workshop.

      Along with the CDS program’s cohort-based model, ReACT also uses platforms that encourage regular communication between participants and with the larger ReACT network — making connections a critical component of the program.

      “I not only want to meet new people and make connections for my professional career, but I also want to test my communication and social skills,” says Pablo Andrés Uribe, a learner who lives in Colombia, describing ReACT’s emphasis on community-building. 

      Over the last two years, ReACT has expanded its geographic presence, growing from a hub in Jordan into a robust global community of many hubs, including in Colombia and Uganda. These regional sites connect talented refugees and displaced learners to internships and employment, startup networks and accelerators, and pathways to formal undergraduate and graduate education.

      This expansion is thanks to the generous support internally from the MIT Office of the Provost and Associate Provost Richard Lester and external organizations including the Western Union Foundation. ReACT will build new hubs this year in Greece, Uruguay, and Afghanistan, as a result of gifts from the Hatsopoulos family and the Pfeffer family.

      Holding space to learn from each other

      In addition to establishing new global hubs, ReACT plans to expand its network of internship and experiential learning opportunities, increasing outreach to new collaborators such as nongovernmental organizations (NGOs), companies, and universities. Jointly with Na’amal and Paper Airplanes, a nonprofit that connects conflict-affected individuals with personal language tutors, ReACT will host the first Migration Summit. Scheduled for April 2022, the month-long global convening invites a broad range of participants, including displaced learners, universities, companies, nonprofits and NGOs, social enterprises, foundations, philanthropists, researchers, policymakers, employers, and governments, to address the key challenges and opportunities for refugee and migrant communities. The theme of the summit is “Education and Workforce Development in Displacement.”

      “The MIT Migration Summit offers a platform to discuss how new educational models, such as those employed in ReACT, can help solve emerging challenges in providing quality education and career opportunities to forcibly displaced and marginalized people around the world,” says Masic. 

      A key goal of the convening is to center the voices of those most directly impacted by displacement, such as ReACT’s learners from Afghanistan and elsewhere, in solution-making. More

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      in Environment

      MIT Center for Real Estate launches the Asia Real Estate Initiative

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      To appreciate the explosive urbanization taking place in Asia, consider this analogy: Every 40 days, a city the equivalent size of Boston is built in Asia. Of the $24.7 trillion real estate investment opportunities predicted by 2030 in emerging cities, $17.8 trillion (72 percent) will be in Asia. While this growth is exciting to the real estate industry, it brings with it the attendant social and environmental issues.

      To promote a sustainable and innovative approach to this growth, leadership at the MIT Center for Real Estate (MIT CRE) recently established the Asia Real Estate Initiative (AREI), which aims to become a platform for industry leaders, entrepreneurs, and the academic community to find solutions to the practical concerns of real estate development across these countries.

      “Behind the creation of this initiative is the understanding that Asia is a living lab for the study of future global urban development,” says Hashim Sarkis, dean of the MIT School of Architecture and Planning.

      An investment in cities of the future

      One of the areas in AREI’s scope of focus is connecting sustainability and technology in real estate.

      “We believe the real estate sector should work cooperatively with the energy, science, and technology sectors to solve the climate challenges,” says Richard Lester, the Institute’s associate provost for international activities. “AREI will engage academics and industry leaders, nongovernment organizations, and civic leaders globally and in Asia, to advance sharing knowledge and research.”

      In its effort to understand how trends and new technologies will impact the future of real estate, AREI has received initial support from a prominent alumnus of MIT CRE who wishes to remain anonymous. The gift will support a cohort of researchers working on innovative technologies applicable to advancing real estate sustainability goals, with a special focus on the global and Asia markets. The call for applications is already under way, with AREI seeking to collaborate with scholars who have backgrounds in economics, finance, urban planning, technology, engineering, and other disciplines.

      “The research on real estate sustainability and technology could transform this industry and help invent global real estate of the future,” says Professor Siqi Zheng, faculty director of MIT CRE and AREI faculty chair. “The pairing of real estate and technology often leads to innovative and differential real estate development strategies such as buildings that are green, smart, and healthy.”

      The initiative arrives at a key time to make a significant impact and cement a leadership role in real estate development across Asia. MIT CRE is positioned to help the industry increase its efficiency and social responsibility, with nearly 40 years of pioneering research in the field. Zheng, an established scholar with expertise on urban growth in fast-urbanizing regions, is the former president of the Asia Real Estate Society and sits on the Board of American Real Estate and Urban Economics Association. Her research has been supported by international institutions including the World Bank, the Asian Development Bank, and the Lincoln Institute of Land Policy.

      “The researchers in AREI are now working on three interrelated themes: the future of real estate and live-work-play dynamics; connecting sustainability and technology in real estate; and innovations in real estate finance and business,” says Zheng.

      The first theme has already yielded a book — “Toward Urban Economic Vibrancy: Patterns and Practices in Asia’s New Cities” — recently published by SA+P Press.

      Engaging thought leaders and global stakeholders

      AREI also plans to collaborate with counterparts in Asia to contribute to research, education, and industry dialogue to meet the challenges of sustainable city-making across the continent and identify areas for innovation. Traditionally, real estate has been a very local business with a lengthy value chain, according to Zhengzhen Tan, director of AREI. Most developers focused their career on one particular product type in one particular regional market. AREI is working to change that dynamic.

      “We want to create a cross-border dialogue within Asia and among Asia, North America, and European leaders to exchange knowledge and practices,” says Tan. “The real estate industry’s learning costs are very high compared to other sectors. Collective learning will reduce the cost of failure and have a significant impact on these global issues.”

      The 2021 United Nations Climate Change Conference in Glasgow shed additional light on environmental commitments being made by governments in Asia. With real estate representing 40 percent of global greenhouse gas emissions, the Asian real estate market is undergoing an urgent transformation to deliver on this commitment.

      “One of the most pressing calls is to get to net-zero emissions for real estate development and operation,” says Tan. “Real estate investors and developers are making short- and long-term choices that are locking in environmental footprints for the ‘decisive decade.’ We hope to inspire developers and investors to think differently and get out of their comfort zone.” More

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      in Energy

      Using artificial intelligence to find anomalies hiding in massive datasets

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      Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on electric current, voltage, and other critical information in real time, often taking multiple recordings per second.

      Researchers at the MIT-IBM Watson AI Lab have devised a computationally efficient method that can automatically pinpoint anomalies in those data streams in real time. They demonstrated that their artificial intelligence method, which learns to model the interconnectedness of the power grid, is much better at detecting these glitches than some other popular techniques.

      Because the machine-learning model they developed does not require annotated data on power grid anomalies for training, it would be easier to apply in real-world situations where high-quality, labeled datasets are often hard to come by. The model is also flexible and can be applied to other situations where a vast number of interconnected sensors collect and report data, like traffic monitoring systems. It could, for example, identify traffic bottlenecks or reveal how traffic jams cascade.

      “In the case of a power grid, people have tried to capture the data using statistics and then define detection rules with domain knowledge to say that, for example, if the voltage surges by a certain percentage, then the grid operator should be alerted. Such rule-based systems, even empowered by statistical data analysis, require a lot of labor and expertise. We show that we can automate this process and also learn patterns from the data using advanced machine-learning techniques,” says senior author Jie Chen, a research staff member and manager of the MIT-IBM Watson AI Lab.

      The co-author is Enyan Dai, an MIT-IBM Watson AI Lab intern and graduate student at the Pennsylvania State University. This research will be presented at the International Conference on Learning Representations.

      Probing probabilities

      The researchers began by defining an anomaly as an event that has a low probability of occurring, like a sudden spike in voltage. They treat the power grid data as a probability distribution, so if they can estimate the probability densities, they can identify the low-density values in the dataset. Those data points which are least likely to occur correspond to anomalies.

      Estimating those probabilities is no easy task, especially since each sample captures multiple time series, and each time series is a set of multidimensional data points recorded over time. Plus, the sensors that capture all that data are conditional on one another, meaning they are connected in a certain configuration and one sensor can sometimes impact others.

      To learn the complex conditional probability distribution of the data, the researchers used a special type of deep-learning model called a normalizing flow, which is particularly effective at estimating the probability density of a sample.

      They augmented that normalizing flow model using a type of graph, known as a Bayesian network, which can learn the complex, causal relationship structure between different sensors. This graph structure enables the researchers to see patterns in the data and estimate anomalies more accurately, Chen explains.

      “The sensors are interacting with each other, and they have causal relationships and depend on each other. So, we have to be able to inject this dependency information into the way that we compute the probabilities,” he says.

      This Bayesian network factorizes, or breaks down, the joint probability of the multiple time series data into less complex, conditional probabilities that are much easier to parameterize, learn, and evaluate. This allows the researchers to estimate the likelihood of observing certain sensor readings, and to identify those readings that have a low probability of occurring, meaning they are anomalies.

      Their method is especially powerful because this complex graph structure does not need to be defined in advance — the model can learn the graph on its own, in an unsupervised manner.

      A powerful technique

      They tested this framework by seeing how well it could identify anomalies in power grid data, traffic data, and water system data. The datasets they used for testing contained anomalies that had been identified by humans, so the researchers were able to compare the anomalies their model identified with real glitches in each system.

      Their model outperformed all the baselines by detecting a higher percentage of true anomalies in each dataset.

      “For the baselines, a lot of them don’t incorporate graph structure. That perfectly corroborates our hypothesis. Figuring out the dependency relationships between the different nodes in the graph is definitely helping us,” Chen says.

      Their methodology is also flexible. Armed with a large, unlabeled dataset, they can tune the model to make effective anomaly predictions in other situations, like traffic patterns.

      Once the model is deployed, it would continue to learn from a steady stream of new sensor data, adapting to possible drift of the data distribution and maintaining accuracy over time, says Chen.

      Though this particular project is close to its end, he looks forward to applying the lessons he learned to other areas of deep-learning research, particularly on graphs.

      Chen and his colleagues could use this approach to develop models that map other complex, conditional relationships. They also want to explore how they can efficiently learn these models when the graphs become enormous, perhaps with millions or billions of interconnected nodes. And rather than finding anomalies, they could also use this approach to improve the accuracy of forecasts based on datasets or streamline other classification techniques.

      This work was funded by the MIT-IBM Watson AI Lab and the U.S. Department of Energy. More

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      in Environment

      3 Questions: What a single car can say about traffic

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      Vehicle traffic has long defied description. Once measured roughly through visual inspection and traffic cameras, new smartphone crowdsourcing tools are now quantifying traffic far more precisely. This popular method, however, also presents a problem: Accurate measurements require a lot of data and users.

      Meshkat Botshekan, an MIT PhD student in civil and environmental engineering and research assistant at the MIT Concrete Sustainability Hub, has sought to expand on crowdsourcing methods by looking into the physics of traffic. During his time as a doctoral candidate, he has helped develop Carbin, a smartphone-based roadway crowdsourcing tool created by MIT CSHub and the University of Massachusetts Dartmouth, and used its data to offer more insight into the physics of traffic — from the formation of traffic jams to the inference of traffic phase and driving behavior. Here, he explains how recent findings can allow smartphones to infer traffic properties from the measurements of a single vehicle.  

      Q: Numerous navigation apps already measure traffic. Why do we need alternatives?

      A: Traffic characteristics have always been tough to measure. In the past, visual inspection and cameras were used to produce traffic metrics. So, there’s no denying that today’s navigation tools apps offer a superior alternative. Yet even these modern tools have gaps.

      Chief among them is their dependence on spatially distributed user counts: Essentially, these apps tally up their users on road segments to estimate the density of traffic. While this approach may seem adequate, it is both vulnerable to manipulation, as demonstrated in some viral videos, and requires immense quantities of data for reliable estimates. Processing these data is so time- and resource-intensive that, despite their availability, they can’t be used to quantify traffic effectively across a whole road network. As a result, this immense quantity of traffic data isn’t actually optimal for traffic management.

      Q: How could new technologies improve how we measure traffic?

      A: New alternatives have the potential to offer two improvements over existing methods: First, they can extrapolate far more about traffic with far fewer data. Second, they can cost a fraction of the price while offering a far simpler method of data collection. Just like Waze and Google Maps, they rely on crowdsourcing data from users. Yet, they are grounded in the incorporation of high-level statistical physics into data analysis.

      For instance, the Carbin app, which we are developing in collaboration with UMass Dartmouth, applies principles of statistical physics to existing traffic models to entirely forgo the need for user counts. Instead, it can infer traffic density and driver behavior using the input of a smartphone mounted in single vehicle.

      The method at the heart of the app, which was published last fall in Physical Review E, treats vehicles like particles in a many-body system. Just as the behavior of a closed many-body system can be understood through observing the behavior of an individual particle relying on the ergodic theorem of statistical physics, we can characterize traffic through the fluctuations in speed and position of a single vehicle across a road. As a result, we can infer the behavior and density of traffic on a segment of a road.

      As far less data is required, this method is more rapid and makes data management more manageable. But most importantly, it also has the potential to make traffic data less expensive and accessible to those that need it.

      Q: Who are some of the parties that would benefit from new technologies?

      A: More accessible and sophisticated traffic data would benefit more than just drivers seeking smoother, faster routes. It would also enable state and city departments of transportation (DOTs) to make local and collective interventions that advance the critical transportation objectives of equity, safety, and sustainability.

      As a safety solution, new data collection technologies could pinpoint dangerous driving conditions on a much finer scale to inform improved traffic calming measures. And since socially vulnerable communities experience traffic violence disproportionately, these interventions would have the added benefit of addressing pressing equity concerns. 

      There would also be an environmental benefit. DOTs could mitigate vehicle emissions by identifying minute deviations in traffic flow. This would present them with more opportunities to mitigate the idling and congestion that generate excess fuel consumption.  

      As we’ve seen, these three challenges have become increasingly acute, especially in urban areas. Yet, the data needed to address them exists already — and is being gathered by smartphones and telematics devices all over the world. So, to ensure a safer, more sustainable road network, it will be crucial to incorporate these data collection methods into our decision-making. More