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      in Security

      System tracks movement of food through global humanitarian supply chain

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      Although more than enough food is produced to feed everyone in the world, as many as 828 million people face hunger today. Poverty, social inequity, climate change, natural disasters, and political conflicts all contribute to inhibiting access to food. For decades, the U.S. Agency for International Development (USAID) Bureau for Humanitarian Assistance (BHA) has been a leader in global food assistance, supplying millions of metric tons of food to recipients worldwide. Alleviating hunger — and the conflict and instability hunger causes — is critical to U.S. national security.

      But BHA is only one player within a large, complex supply chain in which food gets handed off between more than 100 partner organizations before reaching its final destination. Traditionally, the movement of food through the supply chain has been a black-box operation, with stakeholders largely out of the loop about what happens to the food once it leaves their custody. This lack of direct visibility into operations is due to siloed data repositories, insufficient data sharing among stakeholders, and different data formats that operators must manually sort through and standardize. As a result, accurate, real-time information — such as where food shipments are at any given time, which shipments are affected by delays or food recalls, and when shipments have arrived at their final destination — is lacking. A centralized system capable of tracing food along its entire journey, from manufacture through delivery, would enable a more effective humanitarian response to food-aid needs.

      In 2020, a team from MIT Lincoln Laboratory began engaging with BHA to create an intelligent dashboard for their supply-chain operations. This dashboard brings together the expansive food-aid datasets from BHA’s existing systems into a single platform, with tools for visualizing and analyzing the data. When the team started developing the dashboard, they quickly realized the need for considerably more data than BHA had access to.

      “That’s where traceability comes in, with each handoff partner contributing key pieces of information as food moves through the supply chain,” explains Megan Richardson, a researcher in the laboratory’s Humanitarian Assistance and Disaster Relief Systems Group.

      Richardson and the rest of the team have been working with BHA and their partners to scope, build, and implement such an end-to-end traceability system. This system consists of serialized, unique identifiers (IDs) — akin to fingerprints — that are assigned to individual food items at the time they are produced. These individual IDs remain linked to items as they are aggregated along the supply chain, first domestically and then internationally. For example, individually tagged cans of vegetable oil get packaged into cartons; cartons are placed onto pallets and transported via railway and truck to warehouses; pallets are loaded onto shipping containers at U.S. ports; and pallets are unloaded and cartons are unpackaged overseas.

      With a trace

      Today, visibility at the single-item level doesn’t exist. Most suppliers mark pallets with a lot number (a lot is a batch of items produced in the same run), but this is for internal purposes (i.e., to track issues stemming back to their production supply, like over-enriched ingredients or machinery malfunction), not data sharing. So, organizations know which supplier lot a pallet and carton are associated with, but they can’t track the unique history of an individual carton or item within that pallet. As the lots move further downstream toward their final destination, they are often mixed with lots from other productions, and possibly other commodity types altogether, because of space constraints. On the international side, such mixing and the lack of granularity make it difficult to quickly pull commodities out of the supply chain if food safety concerns arise. Current response times can span several months.

      “Commodities are grouped differently at different stages of the supply chain, so it is logical to track them in those groupings where needed,” Richardson says. “Our item-level granularity serves as a form of Rosetta Stone to enable stakeholders to efficiently communicate throughout these stages. We’re trying to enable a way to track not only the movement of commodities, including through their lot information, but also any problems arising independent of lot, like exposure to high humidity levels in a warehouse. Right now, we have no way to associate commodities with histories that may have resulted in an issue.”

      “You can now track your checked luggage across the world and the fish on your dinner plate,” adds Brice MacLaren, also a researcher in the laboratory’s Humanitarian Assistance and Disaster Relief Systems Group. “So, this technology isn’t new, but it’s new to BHA as they evolve their methodology for commodity tracing. The traceability system needs to be versatile, working across a wide variety of operators who take custody of the commodity along the supply chain and fitting into their existing best practices.”

      As food products make their way through the supply chain, operators at each receiving point would be able to scan these IDs via a Lincoln Laboratory-developed mobile application (app) to indicate a product’s current location and transaction status — for example, that it is en route on a particular shipping container or stored in a certain warehouse. This information would get uploaded to a secure traceability server. By scanning a product, operators would also see its history up until that point.   

      Hitting the mark

      At the laboratory, the team tested the feasibility of their traceability technology, exploring different ways to mark and scan items. In their testing, they considered barcodes and radio-frequency identification (RFID) tags and handheld and fixed scanners. Their analysis revealed 2D barcodes (specifically data matrices) and smartphone-based scanners were the most feasible options in terms of how the technology works and how it fits into existing operations and infrastructure.

      “We needed to come up with a solution that would be practical and sustainable in the field,” MacLaren says. “While scanners can automatically read any RFID tags in close proximity as someone is walking by, they can’t discriminate exactly where the tags are coming from. RFID is expensive, and it’s hard to read commodities in bulk. On the other hand, a phone can scan a barcode on a particular box and tell you that code goes with that box. The challenge then becomes figuring out how to present the codes for people to easily scan without significantly interrupting their usual processes for handling and moving commodities.” 

      As the team learned from partner representatives in Kenya and Djibouti, offloading at the ports is a chaotic, fast operation. At manual warehouses, porters fling bags over their shoulders or stack cartons atop their heads any which way they can and run them to a drop point; at bagging terminals, commodities come down a conveyor belt and land this way or that way. With this variability comes several questions: How many barcodes do you need on an item? Where should they be placed? What size should they be? What will they cost? The laboratory team is considering these questions, keeping in mind that the answers will vary depending on the type of commodity; vegetable oil cartons will have different specifications than, say, 50-kilogram bags of wheat or peas.

      Leaving a mark

      Leveraging results from their testing and insights from international partners, the team has been running a traceability pilot evaluating how their proposed system meshes with real-world domestic and international operations. The current pilot features a domestic component in Houston, Texas, and an international component in Ethiopia, and focuses on tracking individual cartons of vegetable oil and identifying damaged cans. The Ethiopian team with Catholic Relief Services recently received a container filled with pallets of uniquely barcoded cartons of vegetable oil cans (in the next pilot, the cans will be barcoded, too). They are now scanning items and collecting data on product damage by using smartphones with the laboratory-developed mobile traceability app on which they were trained. 

      “The partners in Ethiopia are comparing a couple lid types to determine whether some are more resilient than others,” Richardson says. “With the app — which is designed to scan commodities, collect transaction data, and keep history — the partners can take pictures of damaged cans and see if a trend with the lid type emerges.”

      Next, the team will run a series of pilots with the World Food Program (WFP), the world’s largest humanitarian organization. The first pilot will focus on data connectivity and interoperability, and the team will engage with suppliers to directly print barcodes on individual commodities instead of applying barcode labels to packaging, as they did in the initial feasibility testing. The WFP will provide input on which of their operations are best suited for testing the traceability system, considering factors like the network bandwidth of WFP staff and local partners, the commodity types being distributed, and the country context for scanning. The BHA will likely also prioritize locations for system testing.

      “Our goal is to provide an infrastructure to enable as close to real-time data exchange as possible between all parties, given intermittent power and connectivity in these environments,” MacLaren says.

      In subsequent pilots, the team will try to integrate their approach with existing systems that partners rely on for tracking procurements, inventory, and movement of commodities under their custody so that this information is automatically pushed to the traceability server. The team also hopes to add a capability for real-time alerting of statuses, like the departure and arrival of commodities at a port or the exposure of unclaimed commodities to the elements. Real-time alerts would enable stakeholders to more efficiently respond to food-safety events. Currently, partners are forced to take a conservative approach, pulling out more commodities from the supply chain than are actually suspect, to reduce risk of harm. Both BHA and WHP are interested in testing out a food-safety event during one of the pilots to see how the traceability system works in enabling rapid communication response.

      To implement this technology at scale will require some standardization for marking different commodity types as well as give and take among the partners on best practices for handling commodities. It will also require an understanding of country regulations and partner interactions with subcontractors, government entities, and other stakeholders.

      “Within several years, I think it’s possible for BHA to use our system to mark and trace all their food procured in the United States and sent internationally,” MacLaren says.

      Once collected, the trove of traceability data could be harnessed for other purposes, among them analyzing historical trends, predicting future demand, and assessing the carbon footprint of commodity transport. In the future, a similar traceability system could scale for nonfood items, including medical supplies distributed to disaster victims, resources like generators and water trucks localized in emergency-response scenarios, and vaccines administered during pandemics. Several groups at the laboratory are also interested in such a system to track items such as tools deployed in space or equipment people carry through different operational environments.

      “When we first started this program, colleagues were asking why the laboratory was involved in simple tasks like making a dashboard, marking items with barcodes, and using hand scanners,” MacLaren says. “Our impact here isn’t about the technology; it’s about providing a strategy for coordinated food-aid response and successfully implementing that strategy. Most importantly, it’s about people getting fed.” More

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      in Environment

      Preparing Colombia’s cities for life amid changing forests

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      It was an uncharacteristically sunny morning as Marcela Angel MCP ’18, flanked by a drone pilot from the Boston engineering firm AirWorks and a data collection team from the Colombian regional environmental agency Corpoamazonia, climbed a hill in the Andes Mountains of southwest Colombia. The area’s usual mountain cloud cover — one of the major challenges to working with satellite imagery or flying UAVs (unpiloted aerial vehicles, or drones) in the Pacific highlands of the Amazon — would roll through in the hours to come. But for now, her team had chosen a good day to hike out for their first flight. Angel is used to long travel for her research. Raised in Bogotá, she maintained strong ties to Colombia throughout her master’s program in the MIT Department of Urban Studies and Planning (DUSP). Her graduate thesis, examining Bogotá’s management of its public green space, took her regularly back to her hometown, exploring how the city could offer residents more equal access to the clean air, flood protection and day-to-day health and social benefits provided by parks and trees. But the hill she was hiking this morning, outside the remote city of Mocoa, had taken an especially long time to climb: five years building relationships with the community of Mocoa and the Colombian government, recruiting project partners, and navigating the bureaucracy of bringing UAVs into the country. Now, her team finally unwrapped their first, knee-high drone from its tarp and set it carefully in the grass. Under the gathering gray clouds, the buzz of its rotors joined the hum of insects in the trees, and the machine at last took to the skies.

      From Colombia to Cambridge

      “I actually grew up on the last street before the eastern mountains reserve,” Angel says of her childhood in Bogotá. “I’ve always been at that border between city and nature.” This idea, that urban areas are married to the ecosystems around them, would inform Angel’s whole education and career. Before coming to MIT, she studied architecture at Bogotá’s Los Andes University; for her graduation project she proposed a plan to resettle an informal neighborhood on Bogotá’s outskirts to minimize environmental risks to its residents. Among her projects at MIT was an initiative to spatially analyze Bogotá’s tree canopy, providing data for the city to plan a tree-planting program as a strategy to give vulnerable populations in the city more access to nature. And she was naturally intrigued when Colombia’s former minister of environment and sustainable development came to MIT in 2017 to give a guest presentation to the DUSP master’s program. The minister, Luis Gilberto Murillo (now the Colombian ambassador to the United States), introduced the students to the challenges triggered by a recent disaster in the city of Mocoa, on the border between the lowland Amazon and the Andes Mountains. Unprecedented rainstorms had destabilized the surrounding forests, and that April a devastating flood and landslide had killed hundreds of people and destroyed entire neighborhoods. And as climate change contributed to growing rainfall in the region, the risks of more landslide events were rising. Murillo provided useful insights into how city planning decisions had contributed to the crisis. But he also asked for MIT’s support addressing future landslide risks in the area. Angel and Juan Camilo Osorio, a PhD candidate at DUSP, decided to take up the challenge, and in January 2018 and 2019, a research delegation from MIT traveled to Colombia for a newly-created graduate course. Returning once again to Bogotá, Angel interviewed government agencies and nonprofits to understand the state of landslide monitoring and public policy. In Mocoa, further interviews and a series of workshops helped clarify what locals needed most and what MIT could provide: better information on where and when landslides might strike, and a process to increase risk awareness and involve traditionally marginalized groups in decision-making processes around that risk. Over the coming year, a core team formed to put the insights from this trip into action, including Angel, Osorio, postdoc Norhan Bayomi of the MIT Environmental Solutions Initiative (ESI) and MIT Professor John Fernández, director of the ESI and one of Angel’s mentors at DUSP. After a second visit to Mocoa that brought into the fold Indigenous groups, environmental agencies, and the national army, a plan was formed: MIT would partner with Corpoamazonia and build a network of community researchers to deploy and test drone technology and machine learning models to monitor the mountain forests for both landslide risks and signs of forest health, while implementing a participatory planning process with residents. “What our projects aim to do is give the communities new tools to continue protecting and restoring the forest,” says Angel, “and support new and inclusive development models, even in the face of new challenges.”

      Lifelines for the climate

      The goal of tropical forest conservation is an urgent one. As forests are cut down, their trees and soils release carbon they have stored over millennia, adding huge amounts of heat-trapping carbon dioxide to the atmosphere. Deforestation, mainly in the tropics, is now estimated to contribute more to climate change than any country besides the United States and China — and once lost, tropical forests are exceptionally hard to restore. “Tropical forests should be a natural way to slow and reverse climate change,” says Angel. “And they can be. But today, we are reaching critical tipping points where it is just the opposite.” This became the motivating force for Angel’s career after her graduation. In 2019, Fernández invited her to join the ESI and lead a new Natural Climate Solutions Program, with the Mocoa project as its first centerpiece. She quickly mobilized the partners to raise funding for the project from the Global Environmental Facility and the CAF Development Bank of Latin America and the Caribbean, and recruited additional partners including MIT Lincoln Laboratories, AirWorks, and the Pratt Institute, where Osorio had become an assistant professor. She hired machine learning specialists from MIT to begin design on UAVs’ data processing, and helped assemble a local research network in Mocoa to increase risk awareness, promote community participation, and better understand what information city officials and community groups needed for city planning and conservation. “This is the amazing thing about MIT,” she says. “When you study a problem here, you’re not just playing in a sandbox. Everyone I’ve worked with is motivated by the complexity of the technical challenge and the opportunity for meaningful engagement in Mocoa, and hopefully in many more places besides.” At the same time, Angel created opportunities for the next generation of MIT graduate students to follow in her footsteps. With Fernández and Bayomi, she created a new course, 4.S23 (Biodiversity and Cities), in which students traveled to Colombia to develop urban planning strategies for the cities of Quidbó and Leticia, located in carbon-rich and biodiverse areas. The course has been taught twice, with Professor Gabriella Carolini joining the teaching team for spring 2023, and has already led to a student report to city officials in Quidbó recommending ways to enhance biodiversity and adapt to climate change as the city grows, a multi-stakeholder partnership to train local youth and implement a citizen-led biodiversity survey, and a seed grant from the MIT Climate and Sustainability Consortium to begin providing both cities detailed data on their tree cover derived from satellite images. “These regions face serious threats, especially on a warming planet, but many of the solutions for climate change, biodiversity conservation, and environmental equity in the region go hand-in-hand,” Angel says. “When you design a city to use fewer resources, to contribute less to climate change, it also causes less pressure on the environment around it. When you design a city for equity and quality of life, you’re giving attention to its green spaces and what they can provide for people and as habitat for other species. When you protect and restore forests, you’re protecting local bioeconomies.”

      Bringing the data home

      Meanwhile, in Mocoa, Angel’s original vision is taking flight. With the team’s test flights behind them, they can now begin creating digital models of the surrounding area. Regular drone flights and soil samples will fill in changing information about trees, water, and local geology, allowing the project’s machine learning specialists to identify warning signs for future landslides and extreme weather events. More importantly, there is now an established network of local community researchers and leaders ready to make use of this information. With feedback from their Mocoan partners, Angel’s team has built a prototype of the online platform they will use to share their UAV data; they’re now letting Mocoa residents take it for a test drive and suggest how it can be made more user-friendly. Her visit this January also paved the way for new projects that will tie the Environmental Solutions Initiative more tightly to Mocoa. With her project partners, Angel is exploring developing a course to teach local students how to use UAVs like the ones her team is flying. She is also considering expanded efforts to collect the kind of informal knowledge of Mocoa, on the local ecology and culture, that people everywhere use in making their city planning and emergency response decisions, but that is rarely codified and included in scientific risk analyses. It’s a great deal of work to offer this one community the tools to adapt successfully to climate change. But even with all the robotics and machine learning models in the world, this close, slow-unfolding engagement, grounded in trust and community inclusion, is what it takes to truly prepare people to confront profound changes in their city and environment. “Protecting natural carbon sinks is a global socio-environmental challenge, and one where it is not enough for MIT to just contribute to the knowledge base or develop a new technology,” says Angel. “But we can help mobilize decision-makers and nontraditional actors, and design more inclusive and technology-enhanced processes, to make this easier for the people who have lifelong stakes in these ecosystems. That is the vision.” More

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      in Environment

      Detailed images from space offer clearer picture of drought effects on plants

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      “MIT is a place where dreams come true,” says César Terrer, an assistant professor in the Department of Civil and Environmental Engineering. Here at MIT, Terrer says he’s given the resources needed to explore ideas he finds most exciting, and at the top of his list is climate science. In particular, he is interested in plant-soil interactions, and how the two can mitigate impacts of climate change. In 2022, Terrer received seed grant funding from the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) to produce drought monitoring systems for farmers. The project is leveraging a new generation of remote sensing devices to provide high-resolution plant water stress at regional to global scales.

      Growing up in Granada, Spain, Terrer always had an aptitude and passion for science. He studied environmental science at the University of Murcia, where he interned in the Department of Ecology. Using computational analysis tools, he worked on modeling species distribution in response to human development. Early on in his undergraduate experience, Terrer says he regarded his professors as “superheroes” with a kind of scholarly prowess. He knew he wanted to follow in their footsteps by one day working as a faculty member in academia. Of course, there would be many steps along the way before achieving that dream. 

      Upon completing his undergraduate studies, Terrer set his sights on exciting and adventurous research roles. He thought perhaps he would conduct field work in the Amazon, engaging with native communities. But when the opportunity arose to work in Australia on a state-of-the-art climate change experiment that simulates future levels of carbon dioxide, he headed south to study how plants react to CO2 in a biome of native Australian eucalyptus trees. It was during this experience that Terrer started to take a keen interest in the carbon cycle and the capacity of ecosystems to buffer rising levels of CO2 caused by human activity.

      Around 2014, he began to delve deeper into the carbon cycle as he began his doctoral studies at Imperial College London. The primary question Terrer sought to answer during his PhD was “will plants be able to absorb predicted future levels of CO2 in the atmosphere?” To answer the question, Terrer became an early adopter of artificial intelligence, machine learning, and remote sensing to analyze data from real-life, global climate change experiments. His findings from these “ground truth” values and observations resulted in a paper in the journal Science. In it, he claimed that climate models most likely overestimated how much carbon plants will be able to absorb by the end of the century, by a factor of three. 

      After postdoctoral positions at Stanford University and the Universitat Autonoma de Barcelona, followed by a prestigious Lawrence Fellowship, Terrer says he had “too many ideas and not enough time to accomplish all those ideas.” He knew it was time to lead his own group. Not long after applying for faculty positions, he landed at MIT. 

      New ways to monitor drought

      Terrer is employing similar methods to those he used during his PhD to analyze data from all over the world for his J-WAFS project. He and postdoc Wenzhe Jiao collect data from remote sensing satellites and field experiments and use machine learning to come up with new ways to monitor drought. Terrer says Jiao is a “remote sensing wizard,” who fuses data from different satellite products to understand the water cycle. With Jiao’s hydrology expertise and Terrer’s knowledge of plants, soil, and the carbon cycle, the duo is a formidable team to tackle this project.

      According to the U.N. World Meteorological Organization, the number and duration of droughts has increased by 29 percent since 2000, as compared to the two previous decades. From the Horn of Africa to the Western United States, drought is devastating vegetation and severely stressing water supplies, compromising food production and spiking food insecurity. Drought monitoring can offer fundamental information on drought location, frequency, and severity, but assessing the impact of drought on vegetation is extremely challenging. This is because plants’ sensitivity to water deficits varies across species and ecosystems. 

      Terrer and Jiao are able to obtain a clearer picture of how drought is affecting plants by employing the latest generation of remote sensing observations, which offer images of the planet with incredible spatial and temporal resolution. Satellite products such as Sentinel, Landsat, and Planet can provide daily images from space with such high resolution that individual trees can be discerned. Along with the images and datasets from satellites, the team is using ground-based observations from meteorological data. They are also using the MIT SuperCloud at MIT Lincoln Laboratory to process and analyze all of the data sets. The J-WAFS project is among one of the first to leverage high-resolution data to quantitatively measure plant drought impacts in the United States with the hopes of expanding to a global assessment in the future.

      Assisting farmers and resource managers 

      Every week, the U.S. Drought Monitor provides a map of drought conditions in the United States. The map has zero resolution and is more of a drought recap or summary, unable to predict future drought scenarios. The lack of a comprehensive spatiotemporal evaluation of historic and future drought impacts on global vegetation productivity is detrimental to farmers both in the United States and worldwide.  

      Terrer and Jiao plan to generate metrics for plant water stress at an unprecedented resolution of 10-30 meters. This means that they will be able to provide drought monitoring maps at the scale of a typical U.S. farm, giving farmers more precise, useful data every one to two days. The team will use the information from the satellites to monitor plant growth and soil moisture, as well as the time lag of plant growth response to soil moisture. In this way, Terrer and Jiao say they will eventually be able to create a kind of “plant water stress forecast” that may be able to predict adverse impacts of drought four weeks in advance. “According to the current soil moisture and lagged response time, we hope to predict plant water stress in the future,” says Jiao. 

      The expected outcomes of this project will give farmers, land and water resource managers, and decision-makers more accurate data at the farm-specific level, allowing for better drought preparation, mitigation, and adaptation. “We expect to make our data open-access online, after we finish the project, so that farmers and other stakeholders can use the maps as tools,” says Jiao. 

      Terrer adds that the project “has the potential to help us better understand the future states of climate systems, and also identify the regional hot spots more likely to experience water crises at the national, state, local, and tribal government scales.” He also expects the project will enhance our understanding of global carbon-water-energy cycle responses to drought, with applications in determining climate change impacts on natural ecosystems as a whole. More

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      in Environment

      New nanosatellite tests autonomy in space

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      In May 2022, a SpaceX Falcon 9 rocket launched the Transporter-5 mission into orbit. The mission contained a collection of micro and nanosatellites from both industry and government, including one from MIT Lincoln Laboratory called the Agile MicroSat (AMS).

      AMS’s primary mission is to test automated maneuvering capabilities in the tumultuous very low-Earth orbit (VLEO) environment, starting at 525 kilometers above the surface and lowering down. VLEO is a challenging location for satellites because the higher air density, coupled with variable space weather, causes increased and unpredictable drag that requires frequent maneuvers to maintain position. Using a commercial off-the-shelf electric-ion propulsion system and custom algorithms, AMS is testing how well it can execute automated navigation and control over an initial mission period of six months.

      “AMS integrates electric propulsion and autonomous navigation and guidance control algorithms that push a lot of the operation of the thruster onto the spacecraft — somewhat like a self-driving car,” says Andrew Stimac, who is the principal investigator for the AMS program and the leader of the laboratory’s Integrated Systems and Concepts Group.

      Stimac sees AMS as a kind of pathfinder mission for the field of small satellite autonomy. Autonomy is essential to support the growing number of small satellite launches for industry and science because it can reduce the cost and labor needed to maintain them, enable missions that call for quick and impromptu responses, and help to avoid collisions in an already-crowded sky.

      AMS is the first-ever test of a nanosatellite with this type of automated maneuvering capability.

      AMS uses an electric propulsion thruster that was selected to meet the size and power constraints of a nanosatellite while providing enough thrust and endurance to enable multiyear missions that operate in VLEO. The flight software, called the Bus Hosted Onboard Software Suite, was designed to autonomously operate the thruster to change the spacecraft’s orbit. Operators on the ground can give AMS a high-level command, such as to descend to and maintain a 300-kilometer orbit, and the software will schedule thruster burns to achieve that command autonomously, using measurements from the onboard GPS receiver as feedback. This experimental software is separate from the bus flight software, which allows AMS to safely test its novel algorithms without endangering the spacecraft.

      “One of the enablers for AMS is the way in which we’ve created this software sandbox onboard the spacecraft,” says Robert Legge, who is another member of the AMS team. “We have our own hosted software that’s running on the primary flight computer, but it’s separate from the critical health and safety avionics software. Basically, you can view this as being a little development environment on the spacecraft where we can test out different algorithms.”

      AMS has two secondary missions called Camera and Beacon. Camera’s mission is to take photos and short video clips of the Earth’s surface while AMS is in different low-Earth orbit positions.

      “One of the things we’re hoping to demonstrate is the ability to respond to current events,” says Rebecca Keenan, who helped to prepare the Camera payload. “We could hear about something that happened, like a fire or flood, and then respond pretty quickly to maneuver the satellite to image it.”

      Keenan and the rest of the AMS team are collaborating with the laboratory’s DisasterSat program, which aims to improve satellite image processing pipelines to help relief agencies respond to disasters more quickly. Small satellites that could schedule operations on-demand, rather than planning them months in advance before launch, could be a great asset to disaster response efforts.

      The other payload, Beacon, is testing new adaptive optics capabilities for tracking fast-moving targets by sending laser light from the moving satellite to a ground station at the laboratory’s Haystack Observatory in Westford, Massachusetts. Enabling precise laser pointing from an agile satellite could aid many different types of space missions, such as communications and tracking space debris. It could also be used for emerging programs such as Breakthrough Starshot, which is developing a satellite that can accelerate to high speeds using a laser-propelled lightsail.

      “As far as we know, this is the first on-orbit artificial guide star that has launched for a dedicated adaptive optics purpose,” says Lulu Liu, who worked on the Beacon payload. “Theoretically, the laser it carries can be maneuvered into position on other spacecraft to support a large number of science missions in different regions of the sky.”

      The team developed Beacon with a strict budget and timeline and hope that its success will shorten the design and test loop of next-generation laser transmitter systems. “The idea is that we could have a number of these flying in the sky at once, and a ground system can point to one of them and get near-real-time feedback on its performance,” says Liu.

      AMS weighs under 12 kilograms with 6U dimensions (23 x 11 x 36 centimeters). The bus was designed by Blue Canyon Technologies and the thruster was designed by Enpulsion GmbH.

      Legge says that the AMS program was approached as an opportunity for Lincoln Laboratory to showcase its ability to conduct work in the space domain quickly and flexibly. Some major roadblocks to rapid development of new space technology have been long timelines, high costs, and the extremely low risk tolerance associated with traditional space programs. “We wanted to show that we can really do rapid prototyping and testing of space hardware and software on orbit at an affordable cost,” Legge says.

      “AMS shows the value and fast time-to-orbit afforded by teaming with rapid space commercial partners for spacecraft core bus technologies and launch and ground segment operations, while allowing the laboratory to focus on innovative mission concepts, advanced components and payloads, and algorithms and processing software,” says Dan Cousins, who is the program manager for AMS. “The AMS team appreciates the support from the laboratory’s Technology Office for allowing us to showcase an effective operating model for rapid space programs.”

      AMS took its first image on June 1, completed its thruster commissioning in July, and has begun to descend toward its target VLEO position. More

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      in Energy

      New materials could enable longer-lasting implantable batteries

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      For the last few decades, battery research has largely focused on rechargeable lithium-ion batteries, which are used in everything from electric cars to portable electronics and have improved dramatically in terms of affordability and capacity. But nonrechargeable batteries have seen little improvement during that time, despite their crucial role in many important uses such as implantable medical devices like pacemakers.

      Now, researchers at MIT have come up with a way to improve the energy density of these nonrechargeable, or “primary,” batteries. They say it could enable up to a 50 percent increase in useful lifetime, or a corresponding decrease in size and weight for a given amount of power or energy capacity, while also improving safety, with little or no increase in cost.

      The new findings, which involve substituting the conventionally inactive battery electrolyte with a material that is active for energy delivery, are reported today in the journal Proceedings of the National Academy of Sciences, in a paper by MIT Kavanaugh Postdoctoral Fellow Haining Gao, graduate student Alejandro Sevilla, associate professor of mechanical engineering Betar Gallant, and four others at MIT and Caltech.

      Replacing the battery in a pacemaker or other medical implant requires a surgical procedure, so any increase in the longevity of their batteries could have a significant impact on the patient’s quality of life, Gallant says. Primary batteries are used for such essential applications because they can provide about three times as much energy for a given size and weight as rechargeable batteries.

      That difference in capacity, Gao says, makes primary batteries “critical for applications where charging is not possible or is impractical.” The new materials work at human body temperature, so would be suitable for medical implants. In addition to implantable devices, with further development to make the batteries operate efficiently at cooler temperatures, applications could also include sensors in tracking devices for shipments, for example to ensure that temperature and humidity requirements for food or drug shipments are properly maintained throughout the shipping process. Or, they might be used in remotely operated aerial or underwater vehicles that need to remain ready for deployment over long periods.

      Pacemaker batteries typically last from five to 10 years, and even less if they require high-voltage functions such as defibrillation. Yet for such batteries, Gao says, the technology is considered mature, and “there haven’t been any major innovations in fundamental cell chemistries in the past 40 years.”

      The key to the team’s innovation is a new kind of electrolyte — the material that lies between the two electrical poles of the battery, the cathode and the anode, and allows charge carriers to pass through from one side to the other. Using a new liquid fluorinated compound, the team found that they could combine some of the functions of the cathode and the electrolyte in one compound, called a catholyte. This allows for saving much of the weight of typical primary batteries, Gao says.

      While there are other materials besides this new compound that could theoretically function in a similar catholyte role in a high-capacity battery, Gallant explains, those materials have lower inherent voltages that do not match those of the remainder of the material in a conventional pacemaker battery, a type known as CFx. Because the overall output from the battery can’t be more than that of the lesser of the two electrode materials,  the extra capacity would go to waste because of the voltage mismatch. But with the new material, “one of the key merits of our fluorinated liquids is that their voltage aligns very well with that of CFx,” Gallant says.

      In a conventional  CFx battery, the liquid electrolyte is essential because it allows charged particles to pass through from one electrode to the other. But “those electrolytes are actually chemically inactive, so they’re basically dead weight,” Gao says. This means about 50 percent of the battery’s key components, mainly the electrolyte, is inactive material. But in the new design with the fluorinated catholyte material, the amount of dead weight can be reduced to about 20 percent, she says.

      The new cells also provide safety improvements over other kinds of proposed chemistries that would use toxic and corrosive catholyte materials, which their formula does not, Gallant says. And preliminary tests have demonstrated a stable shelf life over more than a year, an important characteristic for primary batteries, she says.

      So far, the team has not yet experimentally achieved the full 50 percent improvement in energy density predicted by their analysis. They have demonstrated a 20 percent improvement, which in itself would be an important gain for some applications, Gallant says. The design of the cell itself has not yet been fully optimized, but the researchers can project the cell performance based on the performance of the active material itself. “We can see the projected cell-level performance when it’s scaled up can reach around 50 percent higher than the CFx cell,” she says. Achieving that level experimentally is the team’s next goal.

      Sevilla, a doctoral student in the mechanical engineering department, will be focusing on that work in the coming year. “I was brought into this project to try to understand some of the limitations of why we haven’t been able to attain the full energy density possible,” he says. “My role has been trying to fill in the gaps in terms of understanding the underlying reaction.”

      One big advantage of the new material, Gao says, is that it can easily be integrated into existing battery manufacturing processes, as a simple substitution of one material for another. Preliminary discussions with manufacturers confirm this potentially easy substitution, Gao says. The basic starting material, used for other purposes, has already been scaled up for production, she says, and its price is comparable to that of the materials currently used in CFx batteries. The cost of batteries using the new material is likely to be comparable to the existing batteries as well, she says. The team has already applied for a patent on the catholyte, and they expect that the medical applications are likely to be the first to be commercialized, perhaps with a full-scale prototype ready for testing in real devices within about a year.

      Further down the road, other applications could likely take advantage of the new materials as well, such as smart water or gas meters that can be read out remotely, or devices like EZPass transponders, increasing their usable lifetime, the researchers say. Power for drone aircraft or undersea vehicles would require higher power and so may take longer to be developed. Other uses could include batteries for equipment used at remote sites, such as drilling rigs for oil and gas, including devices sent down into the wells to monitor conditions.

      The team also included Gustavo Hobold, Aaron Melemed, and Rui Guo at MIT and Simon Jones at Caltech. The work was supported by MIT Lincoln Laboratory and the Army Research Office. More

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      in Energy

      Taking a magnifying glass to data center operations

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      When the MIT Lincoln Laboratory Supercomputing Center (LLSC) unveiled its TX-GAIA supercomputer in 2019, it provided the MIT community a powerful new resource for applying artificial intelligence to their research. Anyone at MIT can submit a job to the system, which churns through trillions of operations per second to train models for diverse applications, such as spotting tumors in medical images, discovering new drugs, or modeling climate effects. But with this great power comes the great responsibility of managing and operating it in a sustainable manner — and the team is looking for ways to improve.

      “We have these powerful computational tools that let researchers build intricate models to solve problems, but they can essentially be used as black boxes. What gets lost in there is whether we are actually using the hardware as effectively as we can,” says Siddharth Samsi, a research scientist in the LLSC. 

      To gain insight into this challenge, the LLSC has been collecting detailed data on TX-GAIA usage over the past year. More than a million user jobs later, the team has released the dataset open source to the computing community.

      Their goal is to empower computer scientists and data center operators to better understand avenues for data center optimization — an important task as processing needs continue to grow. They also see potential for leveraging AI in the data center itself, by using the data to develop models for predicting failure points, optimizing job scheduling, and improving energy efficiency. While cloud providers are actively working on optimizing their data centers, they do not often make their data or models available for the broader high-performance computing (HPC) community to leverage. The release of this dataset and associated code seeks to fill this space.

      “Data centers are changing. We have an explosion of hardware platforms, the types of workloads are evolving, and the types of people who are using data centers is changing,” says Vijay Gadepally, a senior researcher at the LLSC. “Until now, there hasn’t been a great way to analyze the impact to data centers. We see this research and dataset as a big step toward coming up with a principled approach to understanding how these variables interact with each other and then applying AI for insights and improvements.”

      Papers describing the dataset and potential applications have been accepted to a number of venues, including the IEEE International Symposium on High-Performance Computer Architecture, the IEEE International Parallel and Distributed Processing Symposium, the Annual Conference of the North American Chapter of the Association for Computational Linguistics, the IEEE High-Performance and Embedded Computing Conference, and International Conference for High Performance Computing, Networking, Storage and Analysis. 

      Workload classification

      Among the world’s TOP500 supercomputers, TX-GAIA combines traditional computing hardware (central processing units, or CPUs) with nearly 900 graphics processing unit (GPU) accelerators. These NVIDIA GPUs are specialized for deep learning, the class of AI that has given rise to speech recognition and computer vision.

      The dataset covers CPU, GPU, and memory usage by job; scheduling logs; and physical monitoring data. Compared to similar datasets, such as those from Google and Microsoft, the LLSC dataset offers “labeled data, a variety of known AI workloads, and more detailed time series data compared with prior datasets. To our knowledge, it’s one of the most comprehensive and fine-grained datasets available,” Gadepally says. 

      Notably, the team collected time-series data at an unprecedented level of detail: 100-millisecond intervals on every GPU and 10-second intervals on every CPU, as the machines processed more than 3,000 known deep-learning jobs. One of the first goals is to use this labeled dataset to characterize the workloads that different types of deep-learning jobs place on the system. This process would extract features that reveal differences in how the hardware processes natural language models versus image classification or materials design models, for example.   

      The team has now launched the MIT Datacenter Challenge to mobilize this research. The challenge invites researchers to use AI techniques to identify with 95 percent accuracy the type of job that was run, using their labeled time-series data as ground truth.

      Such insights could enable data centers to better match a user’s job request with the hardware best suited for it, potentially conserving energy and improving system performance. Classifying workloads could also allow operators to quickly notice discrepancies resulting from hardware failures, inefficient data access patterns, or unauthorized usage.

      Too many choices

      Today, the LLSC offers tools that let users submit their job and select the processors they want to use, “but it’s a lot of guesswork on the part of users,” Samsi says. “Somebody might want to use the latest GPU, but maybe their computation doesn’t actually need it and they could get just as impressive results on CPUs, or lower-powered machines.”

      Professor Devesh Tiwari at Northeastern University is working with the LLSC team to develop techniques that can help users match their workloads to appropriate hardware. Tiwari explains that the emergence of different types of AI accelerators, GPUs, and CPUs has left users suffering from too many choices. Without the right tools to take advantage of this heterogeneity, they are missing out on the benefits: better performance, lower costs, and greater productivity.

      “We are fixing this very capability gap — making users more productive and helping users do science better and faster without worrying about managing heterogeneous hardware,” says Tiwari. “My PhD student, Baolin Li, is building new capabilities and tools to help HPC users leverage heterogeneity near-optimally without user intervention, using techniques grounded in Bayesian optimization and other learning-based optimization methods. But, this is just the beginning. We are looking into ways to introduce heterogeneity in our data centers in a principled approach to help our users achieve the maximum advantage of heterogeneity autonomously and cost-effectively.”

      Workload classification is the first of many problems to be posed through the Datacenter Challenge. Others include developing AI techniques to predict job failures, conserve energy, or create job scheduling approaches that improve data center cooling efficiencies.

      Energy conservation 

      To mobilize research into greener computing, the team is also planning to release an environmental dataset of TX-GAIA operations, containing rack temperature, power consumption, and other relevant data.

      According to the researchers, huge opportunities exist to improve the power efficiency of HPC systems being used for AI processing. As one example, recent work in the LLSC determined that simple hardware tuning, such as limiting the amount of power an individual GPU can draw, could reduce the energy cost of training an AI model by 20 percent, with only modest increases in computing time. “This reduction translates to approximately an entire week’s worth of household energy for a mere three-hour time increase,” Gadepally says.

      They have also been developing techniques to predict model accuracy, so that users can quickly terminate experiments that are unlikely to yield meaningful results, saving energy. The Datacenter Challenge will share relevant data to enable researchers to explore other opportunities to conserve energy.

      The team expects that lessons learned from this research can be applied to the thousands of data centers operated by the U.S. Department of Defense. The U.S. Air Force is a sponsor of this work, which is being conducted under the USAF-MIT AI Accelerator.

      Other collaborators include researchers at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Professor Charles Leiserson’s Supertech Research Group is investigating performance-enhancing techniques for parallel computing, and research scientist Neil Thompson is designing studies on ways to nudge data center users toward climate-friendly behavior.

      Samsi presented this work at the inaugural AI for Datacenter Optimization (ADOPT’22) workshop last spring as part of the IEEE International Parallel and Distributed Processing Symposium. The workshop officially introduced their Datacenter Challenge to the HPC community.

      “We hope this research will allow us and others who run supercomputing centers to be more responsive to user needs while also reducing the energy consumption at the center level,” Samsi says. 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

      Empowering people to adapt on the frontlines of climate change

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      On April 11, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This article is the fifth in a five-part series highlighting the most promising concepts to emerge from the competition and the interdisciplinary research teams behind them.

      In the coastal south of Bangladesh, rice paddies that farmers could once harvest three times a year lie barren. Sea-level rise brings saltwater to the soil, ruining the staple crop. It’s one of many impacts, and inequities, of climate change. Despite producing less than 1 percent of global carbon emissions, Bangladesh is suffering more than most countries. Rising seas, heat waves, flooding, and cyclones threaten 90 million people.

      A platform being developed in a collaboration between MIT and BRAC, a Bangladesh-based global development organization, aims to inform and empower climate-threatened communities to proactively adapt to a changing future. Selected as one of five MIT Climate Grand Challenges flagship projects, the Climate Resilience Early Warning System (CREWSnet) will forecast the local impacts of climate change on people’s lives, homes, and livelihoods. These forecasts will guide BRAC’s development of climate-resiliency programs to help residents prepare for and adapt to life-altering conditions.

      “The communities that CREWSnet will focus on have done little to contribute to the problem of climate change in the first place. However, because of socioeconomic situations, they may be among the most vulnerable. We hope that by providing state-of-the-art projections and sharing them broadly with communities, and working through partners like BRAC, we can help improve the capacity of local communities to adapt to climate change, significantly,” says Elfatih Eltahir, the H.M. King Bhumibol Professor in the Department of Civil and Environmental Engineering.

      Eltahir leads the project with John Aldridge and Deborah Campbell in the Humanitarian Assistance and Disaster Relief Systems Group at Lincoln Laboratory. Additional partners across MIT include the Center for Global Change Science; the Department of Earth, Atmospheric and Planetary Sciences; the Joint Program on the Science and Policy of Global Change; and the Abdul Latif Jameel Poverty Action Lab. 

      Predicting local risks

      CREWSnet’s forecasts rely upon a sophisticated model, developed in Eltahir’s research group over the past 25 years, called the MIT Regional Climate Model. This model zooms in on climate processes at local scales, at a resolution as granular as 6 miles. In Bangladesh’s population-dense cities, a 6-mile area could encompass tens, or even hundreds, of thousands of people. The model takes into account the details of a region’s topography, land use, and coastline to predict changes in local conditions.

      When applying this model over Bangladesh, researchers found that heat waves will get more severe and more frequent over the next 30 years. In particular, wet-bulb temperatures, which indicate the ability for humans to cool down by sweating, will rise to dangerous levels rarely observed today, particularly in western, inland cities.

      Such hot spots exacerbate other challenges predicted to worsen near Bangladesh’s coast. Rising sea levels and powerful cyclones are eroding and flooding coastal communities, causing saltwater to surge into land and freshwater. This salinity intrusion is detrimental to human health, ruins drinking water supplies, and harms crops, livestock, and aquatic life that farmers and fishermen depend on for food and income.

      CREWSnet will fuse climate science with forecasting tools that predict the social and economic impacts to villages and cities. These forecasts — such as how often a crop season may fail, or how far floodwaters will reach — can steer decision-making.

      “What people need to know, whether they’re a governor or head of a household, is ‘What is going to happen in my area, and what decisions should I make for the people I’m responsible for?’ Our role is to integrate this science and technology together into a decision support system,” says Aldridge, whose group at Lincoln Laboratory specializes in this area. Most recently, they transitioned a hurricane-evacuation planning system to the U.S. government. “We know that making decisions based on climate change requires a deep level of trust. That’s why having a powerful partner like BRAC is so important,” he says.

      Testing interventions

      Established 50 years ago, just after Bangladesh’s independence, BRAC works in every district of the nation to provide social services that help people rise from extreme poverty. Today, it is one of the world’s largest nongovernmental organizations, serving 110 million people across 11 countries in Asia and Africa, but its success is cultivated locally.

      “BRAC is thrilled to partner with leading researchers at MIT to increase climate resilience in Bangladesh and provide a model that can be scaled around the globe,” says Donella Rapier, president and CEO of BRAC USA. “Locally led climate adaptation solutions that are developed in partnership with communities are urgently needed, particularly in the most vulnerable regions that are on the frontlines of climate change.”

      CREWSnet will help BRAC identify communities most vulnerable to forecasted impacts. In these areas, they will share knowledge and innovate or bolster programs to improve households’ capacity to adapt.

      Many climate initiatives are already underway. One program equips homes to filter and store rainwater, as salinity intrusion makes safe drinking water hard to access. Another program is building resilient housing, able to withstand 120-mile-per-hour winds, that can double as local shelters during cyclones and flooding. Other services are helping farmers switch to different livestock or crops better suited for wetter or saltier conditions (e.g., ducks instead of chickens, or salt-tolerant rice), providing interest-free loans to enable this change.

      But adapting in place will not always be possible, for example in areas predicted to be submerged or unbearably hot by midcentury. “Bangladesh is working on identifying and developing climate-resilient cities and towns across the country, as closer-by alternative destinations as compared to moving to Dhaka, the overcrowded capital of Bangladesh,” says Campbell. “CREWSnet can help identify regions better suited for migration, and climate-resilient adaptation strategies for those regions.” At the same time, BRAC’s Climate Bridge Fund is helping to prepare cities for climate-induced migration, building up infrastructure and financial services for people who have been displaced.

      Evaluating impact

      While CREWSnet’s goal is to enable action, it can’t quite measure the impact of those actions. The Abdul Latif Jameel Poverty Action Lab (J-PAL), a development economics program in the MIT School of Humanities, Arts, and Social Sciences, will help evaluate the effectiveness of the climate-adaptation programs.

      “We conduct randomized controlled trials, similar to medical trials, that help us understand if a program improved people’s lives,” says Claire Walsh, the project director of the King Climate Action Initiative at J-PAL. “Once CREWSnet helps BRAC implement adaptation programs, we will generate scientific evidence on their impacts, so that BRAC and CREWSnet can make a case to funders and governments to expand effective programs.”

      The team aspires to bring CREWSnet to other nations disproportionately impacted by climate change. “Our vision is to have this be a globally extensible capability,” says Campbell. CREWSnet’s name evokes another early-warning decision-support system, FEWSnet, that helped organizations address famine in eastern Africa in the 1980s. Today it is a pillar of food-security planning around the world.

      CREWSnet hopes for a similar impact in climate change planning. Its selection as an MIT Climate Grand Challenges flagship project will inject the project with more funding and resources, momentum that will also help BRAC’s fundraising. The team plans to deploy CREWSnet to southwestern Bangladesh within five years.

      “The communities that we are aspiring to reach with CREWSnet are deeply aware that their lives are changing — they have been looking climate change in the eye for many years. They are incredibly resilient, creative, and talented,” says Ashley Toombs, the external affairs director for BRAC USA. “As a team, we are excited to bring this system to Bangladesh. And what we learn together, we will apply at potentially even larger scales.” More