The research team, led by Aditya Khuller, a senior research scientist at the University of Washington’s Applied Physics Laboratory, set out to resolve a stubborn disagreement in the planetary science community. “We know there is water ice in the area surrounding the north pole of Mars, but there has been widespread disagreement as to how dusty that ice is,” Khuller said. The stakes of that disagreement are higher than they might first appear. Dust content determines how dark the ice is, and darkness determines temperature. “If it is dustier, the ice will be darker. Just like a dark T-shirt in the sun makes you warmer, dusty ice gets warmer and vaporizes faster on Mars,” Khuller explained. In the thin Martian atmosphere, where water vapor sublimates directly from ice to gas, even small differences in dust concentration can meaningfully change how quickly polar ice is lost to the atmosphere.

The methodological heart of the study lies in a cross-planetary detective story. For years, the leading technique for estimating the physical properties of Martian ice was an analytical approach originally developed for studying soil on the Moon. Several years ago, Khuller noticed something troubling: when he tested the accuracy of that lunar-derived method against measurements on Earth, the results seemed off. The discrepancy suggested that decades of estimates about Martian ice composition might rest on a shaky foundation. Rather than simply flagging the problem, Khuller and Pari Mohan, who recently graduated from the University of Washington with a degree in geoscience, decided to redo the calculations entirely using a different framework.

That framework came from an unexpected corner of the university. Steve Warren, professor emeritus of Earth and space sciences at the University of Washington, has spent decades perfecting methods for analyzing snow and ice on our own planet. His radiative transfer techniques, refined through years of studying how light interacts with snow crystals and embedded impurities, had been used successfully to study terrestrial snow and ice for decades. “His methods had been used successfully to study snow and ice on Earth for decades. So I thought it would be interesting to adapt these Earth-tested methods to Mars,” Khuller said. The adaptation required accounting for the very different conditions on Mars, including its lower atmospheric pressure, different illumination geometry, and the peculiar way dust grains scatter light within ice matrices.

The data underpinning the new analysis came from a combination of sources spanning half a century of Mars exploration. NASA celebrated its first successful mission to Mars 50 years ago with the Viking program, and in 2008 the Mars Phoenix lander achieved a major milestone by successfully sampling ice near the north pole. That triumph carried particular weight because it followed the loss of the Mars Polar Lander, which went missing near the south pole in 1999. The University of Washington researchers combined the Phoenix mission’s ground-truth measurements with observations from orbiting satellites, allowing them to connect what the lander touched on the surface with what spacecraft see from above. This pairing of surface and orbital data is essential, because orbiters can survey vast swaths of the polar terrain but need calibration against direct measurements.

The results paint a strikingly different picture of the north polar cap. Rather than a uniformly dirty slab of ice, the polar layered deposits are structured, in Khuller’s words, “like an ice-cream sandwich,” with layers of dustier ice interleaved between slabs of much cleaner ice. The team traced the origin of this layering to an annual cycle. A dusty layer of frost forms over the ice cap every Martian winter, and when summer arrives, that seasonal frost sublimates away, exposing the older, cleaner ice beneath. “By looking at how the brightness changed over time, we figured out that there is a frost that forms in the winter and it’s more dusty. In the Martian summer it goes away, exposing cleaner, older ice,” Khuller said. The brightness changes observed from orbit over successive seasons provided the key signature distinguishing seasonal frost from the permanent ice below.

The quantitative correction is substantial. Previous estimates had suggested that the top layer of the polar ice contained as much as 25 percent dust by mass, a figure that would make the ice dark and thermally aggressive under the Martian sun. The new study finds the true value is closer to 3 percent, a nearly tenfold reduction. That difference transforms scientific understanding of the ice cap’s radiative properties: cleaner ice reflects far more sunlight, stays colder, and sublimates more slowly. It also changes how researchers should interpret the layered deposits as climate archives, since the amount of dust locked into each layer is one of the primary proxies for the conditions under which that ice formed.

Those layers contain key details about the climate of Mars thousands of years ago, when the ice is thought to have formed from snowfall. Mars experiences massive ice ages that have deposited shallow ice across roughly one-third of the planet’s surface, and the driver of this dramatic variability lies in planetary mechanics. Earth’s axial tilt is stabilized by the gravitational influence of its relatively large moon, which keeps our seasons within a narrow, predictable range over tens of thousands of years. Mars, possessing only two small moons, lacks that stabilizing hand. Its axial tilt, or obliquity, “oscillates wildly,” Khuller said, swinging through large excursions over geological timescales. Those oscillations redistribute sunlight across the planet’s latitudes, driving the advance and retreat of ice ages and leaving their signature in the alternating layers of the polar caps.

The cleaner ice also reshapes thinking about habitability. In a previous study, Khuller and colleagues proposed that layers of dust and ice could create conditions suitable for life on Mars. Dark, dusty layers absorb sunlight and could warm the surrounding ice enough to form pockets of meltwater within otherwise frozen deposits. These pockets, enriched with nutrients supplied by the dust grains, could potentially host bacteria and other primitive life forms. The analogy comes from Earth, where similar pockets of shallow, dusty meltwater within ice are often teeming with microbial life during summer. In winter, the liquid water freezes and the microbes go dormant, reviving when the next summer thaws their icy refuge. “The fact that Mars and Earth both have these similar layers of water ice and dust is interesting,” Khuller said. “Why does one planet have life and the other doesn’t?”

Answering that question may take years, but the new dust measurements sharpen the picture of where to look and what to expect. Cleaner ice absorbs less sunlight than previously assumed, which alters calculations of where and whether meltwater pockets could form within the polar layered deposits, and it refines models of how the ice cap responds to seasonal and long-term climate cycles. Khuller hopes to build on the work by applying these improved, Earth-tested analytical methods to other regions of the red planet, extending the corrected picture of ice composition beyond the north pole. As missions continue to probe the Martian surface and orbiters keep watch over the polar caps, the layered ice of Mars stands as one of the most promising archives of the planet’s climatic memory, and one that now appears considerably cleaner, and perhaps more revealing, than scientists had believed.

Subject of Research: Dust content of exposed water ice at the north polar cap of Mars

Article Title: The north pole of Mars is less dusty than scientists thought

Article References: The north pole of Mars is less dusty than scientists thought. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Mars, north polar cap, water ice, dust content, Mars Phoenix, climate record, polar layered deposits, radiative transfer, ice ages, axial tilt, astrobiology, University of Washington

The satellite at the center of the discovery is the Surface Water and Ocean Topography mission, known as SWOT, a joint effort between NASA and international partners that has been in orbit since December 2022. SWOT was built to measure the water level of oceans, lakes, rivers and other large bodies of water at least once every three weeks. It does so using interferometric radar, a technique that compares multiple radar scans over time to detect subtle elevation changes on the water surface. Oceans and big lakes are relatively straightforward targets for such an instrument. Irrigation canals, however, are frequently narrower than 20 meters, placing them at the extreme low end of the satellite’s observational power. The mission’s architects assumed that water-level fluctuations inside such small channels would be invisible to the spacecraft.

Faisal Hossain, a professor of civil and environmental engineering at the University of Washington, was not convinced that the canals were beyond reach. In 2025, he and his collaborators published the Global Registry of Agricultural Irrigation Networks, or GRAIN, a global dataset that used open-source mapping data and machine learning to chart 3.8 million kilometers of canal networks worldwide. That registry gave researchers, for the first time, a comprehensive map of where the world’s agricultural canals actually are. What it could not show was what was happening inside them, which is precisely the kind of information farmers and irrigation authorities need to manage water deliveries.

Lead author Mridul Sharma, a graduate research assistant in civil and environmental engineering at the University of Washington, took the logical next step. He overlaid SWOT’s radar data on top of the GRAIN canal map to see whether meaningful elevation changes could be detected where the mapped canals ran. The result surprised even the team. Roughly 800,000 kilometers of canals in Asia showed water levels that the satellite could measure with moderate to high confidence at more than 85 percent of locations. “It was quite the accidental and pleasant discovery to see that SWOT is able to track flow direction and water levels in most of the canals skillfully,” Sharma said. “GRAIN mapped where canals are. SWOT revealed what was happening inside them. They complemented each other beautifully.”

As a proof of concept, the researchers concentrated on canals in 22 countries across Asia, a region where irrigation plays a critical role in feeding roughly 3 billion people. They examined the satellite’s data along 800,000 kilometers of canals within that region and assigned a confidence score to each kilometer. The scoring was based on two criteria: how closely the satellite’s view of the canal water matched the known contours of the surrounding land, and how strong the radar signal was relative to the noise in the data. Where the observed water surface tracked the terrain smoothly and the signal stood out clearly from background noise, confidence was high. Where the two diverged or the signal was weak, confidence dropped.

The team also validated the approach against ground truth. They compared the satellite’s data to real canal measurements in the United States and found that the confidence levels produced by their scoring system matched the system’s actual abilities. This cross-continental check matters because it suggests the confidence scores are not merely statistical artifacts but reliable indicators of where SWOT’s canal observations can be trusted. Of all the kilometers studied, the team designated 37.5 percent as highly observable, 46.9 percent as moderately observable and 15.6 percent as poorly observable. In other words, more than eight in every ten kilometers of canal in the study region could be monitored with at least moderate confidence by a satellite that was never designed to see them.

The patterns behind those numbers are instructive. The highest-confidence areas corresponded to well-organized, wider canals with smooth slopes and open surroundings, conditions that give the radar a clean view of the water surface and a stable signal to track. Dense vegetation around canals proved to be the satellite’s biggest obstacle, since foliage scatters and absorbs radar energy and obscures the narrow ribbon of water beneath. That limitation is likely to matter most in tropical and subtropical regions where canal banks are heavily vegetated. Encouragingly, the researchers expect performance to improve over time as Hossain and other scientists working with SWOT data build better algorithms and analysis methods tailored to small water bodies.

The study, published September 30 in Geophysical Research Letters, points toward a fundamentally new way of managing the conveyance systems that sustain modern agriculture. “What we are seeing is not simply a new satellite capability,” Hossain said. “It may represent a fundamentally new way of managing the water conveyance systems that sustain modern agriculture.” The next step for the research team is to turn the discovery into practical tools. Hossain and collaborators at the University of Washington are already building systems that use SWOT data to monitor and improve water delivery in South Asia and to aid canal management in the western United States, where aging irrigation infrastructure faces growing pressure from drought and competing demands.

The practical implications for farmers could be far-reaching. In time, growers around the world could use SWOT-powered tools to monitor which canals are carrying sufficient water, see where water levels drop unexpectedly, identify stretches where canal flow might be stagnant, and understand how water delivery evolves across an entire growing season. The researchers offer a concrete example: a farmer preparing to plant rice, one of the most water-intensive staple crops, might see through SWOT-based monitoring that there will not be enough water arriving to the field to support the crop, and switch instead to a less water-intensive option such as corn or wheat. Such decisions, made with timely and objective information rather than guesswork, could reduce crop losses and stretch scarce water supplies further.

Beyond individual farms, the new view of agriculture’s circulatory system could improve drought preparedness, strengthen food security and help researchers map humanity’s transformation of the global freshwater cycle. Irrigation is one of the largest human uses of freshwater on the planet, and canal networks are the arteries through which most of that water moves. Measuring them systematically from space adds a missing piece to the global water balance. “Some of the most important scientific discoveries happen when a tool designed for one purpose unexpectedly reveals something else,” Hossain said. “SWOT may be offering a similar surprise. A mission built to study oceans and rivers has begun revealing the hidden dynamics of the canals that sustain agricultural production around the globe. What was once invisible is becoming measurable.” Co-authors on the study include Sanchit Minocha and Shahzaib Khan, graduate research assistants at the University of Washington; Sarath Suresh, a postdoctoral researcher at Virginia Tech who completed the research as a UW doctoral student; and Tamlin Pavelsky of the University of North Carolina at Chapel Hill. The research was funded by NASA.

Subject of Research: Satellite-based monitoring of irrigation canal water levels using the NASA SWOT mission

Article Title: NASA satellite can monitor most of world’s irrigation canals, study finds

Article References: NASA satellite can monitor most of world’s irrigation canals, study finds. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: SWOT satellite, irrigation canals, water monitoring, NASA, University of Washington, remote sensing, interferometric radar, food security, drought preparedness, agriculture, freshwater, Geophysical Research Letters

The study was led by Mattea Sim, an assistant research professor at the Massive Data Institute in Georgetown’s McCourt School of Public Policy. Her co-authors were Yoshi Kohno, the McDevitt Chair in Computer Science, Ethics, and Society and professor at Georgetown’s Department of Computer Science and Center for Digital Ethics, and Yael Eiger, a Ph.D. candidate at the University of Washington whose research focuses on technology in the carceral system. Kohno framed the work as part of a broader institutional effort, saying the study is part of a growing effort at Georgetown focused on exploring the impact and relationship between AIs and humans, grounded in both psychology and computer science.

The researchers adopted two distinct approaches to understand how AI summaries interact with human memory. In the first phase, they analyzed summary outputs produced by OpenAI’s ChatGPT and Google’s Gemini to quantify how frequently errors appeared and what categories those errors fell into. The results were sobering. The AI summaries frequently omitted critical details, misconstrued information and hallucinated inaccurate details that were not present in the underlying material at all. The source material was an animated video depicting a car and pedestrian accident, and the summaries were measured against the actual contents of that video to determine how faithfully the models reproduced what happened.

The most common category of error was omission, meaning the failure to mention the primary events of the animated video. Across all prompts and models, the summaries omitted 51.6 percent of central details on average. Even more striking, all but one of the summaries — 95 percent of them — omitted the single most central detail of the event: the fact that a car collided with a pedestrian. Eiger said she was struck by how bad the summaries were, even at this stage in AI development, and noted that it worries her that police departments may be using video summarization technologies without rigorous testing and without an awareness of how incorrect AI-generated summaries could be.

The second phase of the study examined what those errors do to the people who read them. Participants were first asked to watch one of two animated videos, which were created in a recent replication study that modernized materials from a classic human memory experiment. The researchers were careful about the nature of the footage. Kohno emphasized that they did not use actual police body camera footage. Instead, the videos depicted a red car approaching an intersection with either a stop or a yield sign, with participants randomly assigned to see one of the two traffic signs. In the videos, the car turns right at the intersection and collides with a pedestrian walking into the road. After being knocked down, the pedestrian stands up, the driver exits the car and the two meet.

Between 24 and 48 hours later, participants returned for the second portion of the experiment. Each was randomly assigned to read either an AI-generated summary that was accurate or one that contained an inaccurate detail changed by the researchers. Before reading, participants were also told that the summary had been written by either an AI system or a human transcriber. In reality, all of the summary text was generated by ChatGPT, and in some cases separate parts of the model’s answers were stitched together to ensure that the experimental conditions remained uniform across participants. In total, 331 people completed both parts of the experiment, providing a substantial sample for measuring how the summaries shaped recall.

The memory effects were dramatic. When participants were asked whether the car in the video had approached a stop sign or a yield sign, 83.6 percent of those who read a summary with accurate information answered correctly. Among those who read a misleading summary, only 44.8 percent were correct — a gap of nearly 39 percentage points. Participants who read a misleading AI summary were significantly less likely to accurately recall the original event compared to people who read an accurate summary. Crucially, the manipulation worked even when people knew the summary came from a machine. The impact of misleading AI summaries on memory did not depend on participants’ trust in AI or their familiarity with it, suggesting that susceptibility to this form of misinformation is broad and not easily guarded against by skepticism about the technology.

Sim described the phenomenon in stark terms, saying that AI is a new method of delivering misinformation and that it has the potential to create false memories for people who are reading that information. She argued that society should be thinking deeply and critically about whether and how AI should be used to summarize information, especially in high-stakes settings. The authors made a similar point in the study itself, writing that the findings have implications for how AI should be used in critical settings. They noted that although humans-in-the-loop are often expected to correct for AI’s mistakes, their work suggests human memory can instead be distorted by those mistakes, and that AI has the potential to generate misinformation even absent any adversarial intent, which can meaningfully impact human memory.

The implications extend well beyond the laboratory. As individuals and institutions grow more reliant on AI, Kohno hopes the findings encourage people to recognize that AI outputs can have a direct impact on how humans perceive the world. That concern carries particular weight in domains such as policing and medicine, where a distorted summary of an event could influence investigations, legal proceedings or clinical decisions. Eiger, whose research examines technologies increasingly implemented by police for surveillance or departmental efficiency, said these tools are often advertised and framed as beneficial, but the trade-offs remain poorly understood. She would like to see more audits of this type of technology and pointed out that, from a public transparency perspective, there is little insight into how the deployed systems work or which exact models are being used in the race to bring AI into every sector.

The authors also acknowledge the limits of the current work and point toward what comes next. The study used the most up-to-date consumer-facing versions of large language models, but the researchers did not have access to enterprise versions of AI designed for organizational use, which may behave differently. For future studies, the team wants to move beyond animated videos and examine real-world examples. Sim asked what happens with AI summaries of police body camera footage and what police reports look like when they are generated by AI, and whether such summaries manipulate people’s memories of police-civilian interactions and consequently their perceptions of what happened in an incident. Those questions, she suggested, would be very interesting to answer — and the answers may determine how safely AI summarization can be entrusted with society’s most consequential records.

Subject of Research: The effect of misleading AI-generated summaries on human memory and perception of truth

Article Title: New research finds that misleading AI-generated summaries can distort human memory

Article References: New research finds that misleading AI-generated summaries can distort human memory. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: artificial intelligence, AI summaries, human memory, misinformation, ChatGPT, Gemini, large language models, memory distortion, police body camera footage, AI ethics, Georgetown University, University of Washington

The research focuses on the so-called carbon majors, a term used by researchers and activists to describe the 178 leading oil, gas, coal and cement companies whose products and operations have released the overwhelming majority of industrial-era greenhouse gases. Together, these entities have emitted more than a trillion tons of carbon dioxide, a staggering quantity whose atmospheric consequences do not simply vanish when the smoke clears. Carbon dioxide is a long-lived gas, and a substantial fraction of every ton released will remain aloft, trapping heat, for millennia. The study’s central insight is that this persistence creates a long tail of responsibility: the warming attributable to carbon majors is largely locked in, calculable, and relatively independent of what humanity chooses to do next.

To quantify that legacy, the research team turned to the Finite Amplitude Impulse Response model, commonly known as FaIR, a reduced-complexity climate model widely used to simulate how emissions translate into atmospheric concentrations, radiative forcing and global temperature change. The researchers ran simulations of the global climate all the way through the year 2500, exploring both low and higher emissions scenarios. Crucially, they ran each scenario twice: once with the historical emissions of the carbon majors included through 2024, and once with those emissions removed. The difference between the paired runs isolates the temperature signal that can be attributed specifically to the top producers, allowing the team to track how that signal evolves across a wide range of possible futures.

The results reveal a striking asymmetry. In a future where greenhouse gas emissions are sharply limited, the carbon majors account for a larger percentage of the total warming above preindustrial levels, because their historical emissions dominate a smaller overall budget. In higher emissions scenarios, where fossil fuel burning continues unabated and the planet becomes dramatically warmer, future emissions cause a much larger share of the total temperature change. Yet the absolute temperature contribution from the carbon majors remains roughly the same across scenarios. Dargan Frierson, a University of Washington associate professor of atmospheric and climate science and the study’s lead author, summarized the implication: the amount of warming attributable to the top emitters is calculable and relatively independent of future emissions, meaning their responsibility persists no matter which path the world takes.

The persistence of that warming has profound physical consequences. Even if humanity were to stop emitting greenhouse gases tomorrow, the environment would not revert to its preindustrial state. According to the study’s findings, Earth would remain approximately 1.5 degrees Celsius above preindustrial temperatures, the threshold that international climate policy has identified as a critical guardrail. Frierson put the conclusion bluntly: we expect continued warming of the climate until fossil fuel emissions stop, and the only stable future is one with no fossil fuels burned at all. In other words, there is no gentle landing. Every additional year of production by the world’s largest emitters extends and deepens the warming that future generations will inherit.

Why does past emissions translate into future disasters? The answer lies in the mechanics of attribution science, the field that connects individual extreme weather events to climate change. Over the past decade, attribution researchers have developed increasingly rigorous statistical methods to determine how much more likely, or how much more intense, a given heat wave, drought or downpour has become because of human-caused warming. These findings now form the backbone of a growing list of lawsuits attempting to hold major emitters responsible for deaths and damages incurred during climate disasters. The new study extends that logic forward in time: if persistent warming raises the baseline probability of extreme events, then gases released decades ago by leading producers may also be responsible for disasters that have not yet occurred.

This forward-looking dimension is what makes the research legally and ethically explosive. Efforts to hold emitters accountable have traditionally hinged on allegations that companies knew about climate risks many decades ago and concealed that information from the public, sometimes employing deceptive tactics to spread disinformation, as documented in archives such as the climate deception dossiers compiled by the Union of Concerned Scientists. The new analysis adds a second, quantifiable strand to that case: the gases released by extracting and burning fossil fuels are not merely a historical wrong but an ongoing mechanism of harm, one that will keep elevating the odds of future catastrophes long after the emissions themselves took place. Responsibility, as Frierson noted, is not just now; it will continue for many, many years into the future.

The timing of the study could hardly be more consequential. Courts around the world are weighing claims brought by cities, states and indigenous communities against fossil fuel producers, and the scientific credibility of attribution evidence has become a decisive factor in several of those proceedings. By showing that the warming contribution of the carbon majors is stable across emissions pathways, the research gives plaintiffs a robust number that does not depend on contested assumptions about future policy. It also gives regulators and policymakers a clear warning: future fossil fuel production will exacerbate climate disasters for many decades to come, which means new legal battles over accountability should be expected for years. Frierson emphasized that this is important for current decisions about fossil fuels, since every new extraction project adds to a warming burden that cannot be easily undone.

Underlying the entire analysis is a sober piece of climate physics. Carbon dioxide’s atmospheric lifetime is not measured in years but in centuries to millennia, and the ocean’s enormous heat capacity means that even after concentrations stabilize, the climate system continues to adjust. Reduced-complexity models like FaIR capture these dynamics by linking emissions pulses to temperature responses with well-constrained parameters drawn from the broader body of climate science. When the model runs with and without carbon major emissions diverge by a consistent margin across 500 simulated years, that margin represents real, physical, irreducible warming, heat that has already been committed to the system by past production decisions. No plausible emissions pathway can claw it back.

The study, co-authored by Lauren Henrie, a former student of Environmental Science and Resource Management at the University of Washington, ultimately reframes the climate crisis as a problem of accumulated, durable responsibility. The faucet is still running, in effect, and the water already in the house will keep spreading through the floors for generations. For the top 178 producers of oil, gas, coal and cement, the message is that their past is the planet’s future: the trillion tons of carbon dioxide already released will continue trapping heat, intensifying storms, and raising the odds of disaster long after today’s headlines fade. And for everyone else, the message is equally clear: the only stable future, the only one in which the warming finally stops climbing, is one in which fossil fuels are no longer burned at all.

Subject of Research: Attribution of long-term global warming and future extreme weather risk to historical emissions from the largest fossil fuel and cement producers

Article Title: Past emissions from top polluters will continue warming the planet for decades to come

Article References: Past emissions from top polluters will continue warming the planet for decades to come. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: carbon majors, climate attribution, fossil fuel emissions, PLOS Climate, University of Washington, FaIR model, extreme weather, climate litigation, carbon dioxide lifetime, global warming, emissions scenarios, climate accountability