hayksenekerimyan posted a photo:
Some moments don't need color to feel alive. Just you, the water, and a mountain watching over it all.

hayksenekerimyan posted a photo:
Some moments don't need color to feel alive. Just you, the water, and a mountain watching over it all.


A Colorado judge has granted a preliminary injunction to the University Corporation for Atmospheric Research (UCAR). The move temporarily blocks the federal government from moving forward with one part of its effort to dismantle UCAR’s National Center for Atmospheric Research (NCAR) by transferring stewardship of a state-of-the-art supercomputing facility.
Together, UCAR—a nonprofit consortium of universities and colleges—and the National Science Foundation (NSF) operate and maintain the NCAR-Wyoming Supercomputing Center (NWSC) in Cheyenne, Wyo. The facility provides scientists with enormous computational power necessary to run sophisticated analyses of weather, climate, and other Earth systems.
In February, as another step in a chain of actions taken to dismantle NCAR, the NSF informed UCAR and NCAR that it would transfer management and operations of NWSC to a third-party operator.
In turn, UCAR filed a lawsuit alleging that the action violated federal law under the Administrative Procedure Act (APA). To halt NSF’s action under the act, the agency’s attempt to remove UCAR’s stewardship of the facility must be shown to be “arbitrary, capricious, an abuse of discretion, or otherwise not in accordance with law.”
Judge Richard Brooke Jackson of the U.S. District Court for the District of Colorado wrote in a 1 June court order that the action was both arbitrary and capricious “for at least two reasons.” First, NSF didn’t offer an explanation for its decision, and second, it didn’t follow an outlined process to consider public feedback.
The decision means that UCAR will temporarily retain its stewardship of NWSC.
“NSF’s failure to provide any explanation for its decision—let alone a reasonable one—thwarts meaningful judicial review and renders the challenged action arbitrary and capricious,” Jackson wrote.
He went on to note that efforts to transfer stewardship of UCAR assets, including the supercomputing center, to other institutions, pose the risk of “irreparable harm” to UCAR. One of the chief harms would be brain drain, the judge noted multiple times, writing that “UCAR cannot easily replace employees with the level of education, specialized training, and institutional knowledge necessary to operate and maintain the NWSC’s ‘highly integrated, high-performance supercomputing system.'”
In addition to brain drain, Jackson cited financial injuries to UCAR that would be “difficult, if not impossible” to quantify, as well as an overall threat to the consortium’s mission.
“Any degradation in forecasting, modeling, or related scientific capabilities carries real-world consequences, including potential harm to property and human life. Given those stakes, the public interest strongly favors maintaining the status quo unless and until NSF demonstrates that its transfer decision complies with the APA,” he concluded.
In a statement posted to the UCAR website, the consortium’s interim president, Eric Barron, said UCAR was pleased that Judge Jackson recognized how harmful the proposed transfer would be for the the nation’s scientific enterprise.
“UCAR’s top priority is to advance Earth system science in service to society,” he wrote. “Today’s decision ensures that the NWSC will be able to continue its vital work on behalf of the United States and its stakeholders without interruption.”
—Grace van Deelen (@gvd.bsky.social), Staff Writer, and Emily Gardner, (@emfurd.bsky.social), Associate Editor

Manuel Gual posted a photo:
The Forgotten Archive of a Spanish Spy Agency. MORTADELO Y FILEMON
Description:
A cinematic retro espionage collection set in a fictional 1970s Spanish intelligence world, filled with dusty archives, classified files, typewriters, surveillance rooms, laboratories, old telephones, secret maps, dim offices, deserted streets, vintage storefronts, and mysterious objects that suggest abandoned missions, bureaucratic conspiracies, and forgotten undercover operations.
These images were generated by Artificial Intelligence.


Atmospheric rivers act like “rivers in the sky,” shuttling intense bands of warm, heavy moisture from lower to higher latitudes. When an atmospheric river encounters cold air or mountainous terrain, the moisture it carries condenses and falls as heavy rain or snow. In Antarctica, the arrival of an atmospheric river can help build surface ice mass. Much of Antarctica is very dry; an atmospheric river can bring the moisture needed to potentially offset some ice loss.
Antarctica’s varied topography and dry conditions have made detecting atmospheric rivers over the continent challenging. Previous efforts to do so have suggested that atmospheric rivers contribute up to 30% of Antarctica’s total annual precipitation, but these methods may not be capturing the full picture of atmospheric river activity.
Takahashi et al. developed a new 3D atmospheric river detection algorithm to better capture how atmospheric rivers affect Antarctica’s complex terrain. Previous methods have mostly been 2D, meaning they do not accurately account for the vertical variations within an atmospheric river.
To evaluate the algorithm, the researchers applied it to two datasets: (1) daily snowfall totals measured during the 44th Japanese Antarctic Research Expedition (JARE44) at Dome Fuji from February 2003 to January 2004 and (2) the ERA5 (European Centre for Medium-Range Weather Forecasts atmospheric reanalysis) dataset of daily weather patterns and conditions in Antarctica from 1979 to 2023.
The results of the study’s new algorithm showed 16 significant snowfall events during the JARE44 expedition, all of which were not detected by the older 2D method. The new 3D method identified 17 days of atmospheric river activity, which corresponded with 10 heavy snowfall events and accounted for approximately 40% of the total precipitation. Between 1979 and 2023, atmospheric rivers occurred about 10% of the time yet contributed 30%–60% of total precipitation in the Antarctic interior.
The 3D method in the new study suggests that atmospheric river events contribute a greater proportion of total snowfall than previously thought—between 30% and 90%, depending on the Antarctic region. The researchers also suggest that long-term changes in Antarctic snowfall are closely linked with the changes in atmospheric river activity. This connection is especially apparent in East Antarctica, where the link between snowfall increases and atmospheric rivers had not yet been clearly identified in previous studies. (Geophysical Research Letters, https://doi.org/10.1029/2025GL120986, 2026)
—Rebecca Owen (@beccapox.bsky.social), Science Writer


Ensuring the sustainability of water resources and ecosystems in a changing world requires a thorough understanding of how water moves through Earth’s Critical Zone, a dynamic interface where air, water, soil, plants, and rocks interact. Researchers can track and model this movement of water using naturally occurring markers or “tracers.”
A recent article in Reviews of Geophysics explores the latest advancements in tracer-aided mixing models and how they can help us to better understand the Critical Zone. Here, we asked the authors to give an overview of the Critical Zone, how tracer-aided mixing modeling works, and future directions for research.
What is the Critical Zone (CZ)?
The Critical Zone is Earth’s “living skin”—the dynamic layer where the atmosphere, hydrosphere, biosphere, and lithosphere interact. It stretches from the top of the vegetation canopy and, in cold regions, from the surface of snowpacks and glaciers, down through soils and into the deeper aquifers. It encompasses lakes, streams, and wetlands at the surface, and extends beyond the soil layer to underlying groundwater aquifers. It is where rainfall, snowmelt and glacier melt become soil moisture, where plants take up water and return it to the atmosphere, where aquifers get recharged, and where streamflow is generated. In short, the Critical Zone is where most processes that sustain terrestrial life and freshwater resources unfold.
Why is it important to understand how water moves through the Critical Zone?
Virtually every freshwater resource we rely on (e.g., drinking water, irrigation) passes through the Critical Zone.
Virtually every freshwater resource we rely on (e.g., drinking water, irrigation) passes through the Critical Zone at some point. Global warming, land-use changes, and intensifying water demand emerging from rapid urbanization and changes in agriculture are reshaping how water is stored and released within the Critical Zone, often in ways we cannot yet predict. Understanding how much water is stored within the Critical Zone, how this water is both recharged from rainfall and snowmelt and eventually discharged into streams, and the timescale of these dynamic processes is essential for protecting ecosystems, safeguarding water supplies, and adapting to a changing climate.
How would you explain a tracer-aided mixing model to a non-specialist?
Imagine mixing a glass of orange juice with a glass of apple juice, and trying afterwards to work out how much of each went into the glass. If the juices had distinctive “fingerprints” (imagine its color, sugar content, or a specific chemical) and these fingerprints primarily changed because of the mixing of these two juices, you can then measure the fingerprint in the final mixture and back-calculate the proportion of its distinct sources.
Tracer-aided mixing models work in a similar way but can track the entire water cycle. Different water sources (e.g., rainfall, snowmelt, glacier melt, soil water, groundwater) can have distinct “fingerprints” in a naturally occurring tracer, such as stable isotopes of water or specific dissolved elements. By measuring these fingerprints in the streamwater or groundwater and in its potential sources for example, hydrologists can estimate how much each source contributed to the streamwater or groundwater.

What are some of the most significant and exciting recent advances in tracer-aided mixing models?
Classical mixing models relied on demanding assumptions: that all water sources can be identified and sampled, and that their signatures were distinct and constant in time. Much of the recent progress has been about relaxing these assumptions.
Bayesian approaches now estimate full probability distributions and provide a more realistic picture of uncertainty. Methods like Convex Hull End-Member Mixing Analysis (CHEMMA) use machine learning to infer the distinct sources directly from data, while ensemble hydrograph separation exploits tracer fluctuations over time, thereby making un-mixing feasible even when multiple sources have overlapping signatures. Perhaps the most conceptually novel advance is end-member splitting, which flips the question from “where does streamflow come from?” to “where does precipitation go?”
Alongside these modeling advances, there have been immense advances in how tracers are measured. Portable laser and mass spectrometers now enable high-frequency, in-situ tracer measurements which allows us to capture critical hydrological events such as storms and snowmelt in near-real time.
What are stable water isotope tracers and what are their advantages?
Stable water isotopes are naturally occurring non-radioactive atoms of hydrogen and oxygen that make up a water molecule but have slightly different molecular masses. The two stable isotopes widely used in hydrology are 2H (deuterium) and 18O (oxygen-18). Because these isotopes are part of the water molecule itself, they directly travel with the water molecule. Their key advantages are: (1) they are conservative, meaning they do not react chemically as water moves through soils and aquifers, and (2) they carry distinct signatures resulting from climatic variables such as air temperature.
These properties make stable water isotopes the most versatile and widely used tracer in Critical Zone hydrology.
Consequently, in the European Alps, winter precipitation has a different isotopic signature than summer precipitation because winters are cooler than summers. Other hydrological processes such as evaporation and sublimation leave a recognizable fingerprint on the remaining water, thereby allowing us to estimate how much evaporation or sublimation occurred. Stable water isotopes can be measured in essentially every water compartment, from atmospheric vapor and precipitation to snowpack, plant xylem, soil water, streams, and groundwater. Together, these properties make stable water isotopes the most versatile and widely used tracer in Critical Zone hydrology.
What are the current limitations of tracer-aided mixing models?
Despite their power, mixing models still face many constraints. End-member signatures vary in space and time, are sometimes too similar to distinguish, and some sources may be overlooked entirely. Non-conservative tracers such as nitrate or sulfate can react with their environment along their journey, thereby biasing results if these reactions are not explicitly accounted for.
Sampling is another major bottleneck. Capturing the spatial heterogeneity of soils, snowpacks, and groundwater requires a lot of measurements that are often logistically or financially prohibitive, especially in remote regions. Many of the newer, more powerful tracers such as noble gases or stable isotopes of trace elements, can only be analyzed by a handful of specialized laboratories. As a result, global coverage remains highly uneven, with key regions such as the Arctic and the global South still under-sampled.
What are some of the major unsolved questions and where is more research needed?
There are several fronts where more research is needed. Source signatures are not static, and methods that explicitly capture their variability in time are still underdeveloped. Embedding tracers within global Earth System Models would, in theory, enable more accurate assessment of hydrological partitioning e.g., how rainfall, snowmelt, and glacier melt are split between sublimation, evapotranspiration, groundwater, and streamflow. These will directly inform more robust climate projections, but this remains technically demanding.
Expanding data coverage in under-sampled regions is critical, and citizen science and low-cost sensors may help. Machine learning is a promising approach for uncovering non-linear relationships and gap-filling sparse datasets, but requires training data that often do not yet exist. Greater interdisciplinary integration, e.g., combining tracers with remote sensing, ecological indicators, and biogeochemical data, could yield a more holistic view of the Critical Zone. Finally, the field would benefit from shared protocols and open data practices to enhance progress.
—Andrea L. Popp (andrea.popp@smhi.se;
0000-0003-3911-8105), Swedish Meteorological and Hydrological Institute, Sweden; Harsh Beria (hberia@ethz.ch;
0000-0003-2597-9449), ETH Zurich, Switzerland
Editor’s Note: It is the policy of AGU Publications to invite the authors of articles published in Reviews of Geophysics to write a summary for Eos Editors’ Vox.

The key word here is could. Experts including Ken Graham, the director of NOAA’s National Weather Service, all emphasize that no two El Niños are alike.
“Each one is unique with its own imprint on our weather,” Graham said in a NOAA press release. However, scientists have learned a few things from watching the ways that this warm phase of a natural climate cycle over the tropical Pacific has affected our weather patterns in the past.
“Advanced monitoring and an improved understanding of El Niño patterns allow the NWS to better predict and better prepare the public and our core partners for what is to come,” Graham said.
This morning, NOAA released an El Niño Advisory, announcing that the climate phenomenon (the warm phase of the El Niño–Southern Oscillation) has officially arrived in the tropical Pacific. The agency forecasts a 63% chance of a “very strong” El Niño from November 2026 to January 2027 that “would rank among the largest El Niño events in the historical record.”
NOAA defines a “very strong” El Niño as when the Pacific’s surface waters are more than 2°C warmer than average. The agency doesn’t use the phrase “Super El Niño,” but there have only been three such “super” or “very strong” El Niño events since 1980. The last one was in 2015.
What does this mean for climate, for humans, and marine species? Here’s a roundup of some potential forecasted effects—some good, some bad—of the weather pattern that’s been making headlines over the past few months.
In a typical year, a warm pool of water in the equatorial Pacific would be transported westward—away from the western coast of the Americas—by trade winds. But during an El Niño event, those trade winds weaken, and the warm pool of water extends east, explained Ariel Cohen, the meteorologist in charge of the National Weather Service’s Los Angeles and Oxnard Office in a press briefing at the Aquarium of the Pacific in Long Beach, Calif.
This warm water “causes jet energy in the atmosphere to bring disturbed weather southward across the southern United States, which can bring wetter than normal conditions to our area with drier conditions farther to the north,” Cohen said.
The southward shift of the storm track could also lead to drier conditions over the northern Rockies and as far east as the Ohio and Tennessee Valleys.
In the past, strong El Niños have led to decreased amounts of plankton in the Pacific, particularly the open ocean, forcing species that rely on plankton (and the species that rely on the species that rely on plankton, and so forth) to widen their net when searching for food.
“[Plankton] is important because that’s the base of the food web,” explained Andrew Leising, a research oceanographer at NOAA, at the Aquarium of the Pacific. “Marine mammals and other migratory species end up being closer to shore, because they’re going to where their food is.”
Whales in particular rely on the upwelling of cold water to bring them krill to eat. As they are driven nearer to the coast in search of food, they also grow more likely to become entangled in fishing nets.
Warm water is a key ingredient in a hurricane, so it might seem, at first thought, that the Pacific’s unusually warm waters might augur a more extreme hurricane season. But another effect of El Niño is that it strengthens vertical wind shear over the Atlantic. When winds are too strong, they can tear a storm apart before it picks up the momentum to become a hurricane.
“Wind shear is good for us, bad for the hurricanes,” Phil Klotzbach, a hurricane forecaster at Colorado State University and lead author of the university’s 2026 Atlantic Hurricane Forecast, told Eos.
NOAA’s 2026 Atlantic Hurricane Forecast suggests that the 2026 season has a 55% chance of being below normal, and will likely include 8 to 14 named storms with winds of at least 39 miles per hour.
Past El Niño events have shown that warmer Pacific waters can increase the likelihood of harmful algal blooms. Among other effects, these blooms can lead to a lower abundance, and a northward shift, of market squid. Market squid and Dungeness crab bring the most volume and value to California’s commercial fisheries.
In 2014, a large mass of hot water in the Pacific known as the Blob was followed up by an El Niño event. That year, “we had several closures of crab and shellfish fisheries due to harmful algal blooms,” Leising said.
However, Leising also explained that the warm patch of water in the Pacific this year is much smaller and farther from shore than the Blob was in 2014. So, though we may see effect similar those in 2014, they’re likely to be less extreme.
In addition, the same conditions driving sharks and whales toward the coast could also drive tuna toward the coast, leading to increased opportunities for that fishery.
With El Niño shifting the Pacific jet stream south of its usual position, sea levels along the U.S. West Coast may rise, exacerbating the existing sea level rise linked to climate change. On the East Coast, the jet stream shift can lead to more storm surges, which combine with higher-than-typical precipitation levels.
“It usually ends up being a double whammy,” said NOAA oceanographer and high tide flooding expert William Sweet, in a NOAA news story. “The first punch is decades of sea level rise, which has waters close to the brim in many coastal communities. And now with this second punch—a strong El Niño—coastal communities face more frequent, deeper and widespread high tide flooding along both the West and East Coasts.”
El Niño events can have harmful effects on sea lions. Algal blooms can lead to severe illness, or even death, for the pinnipeds. Algal blooms can also kill off fish and cephalopod species (such as market squid) that sea lions rely on for food. During past El Niño events, California sea lions have also experienced lower rates of reproduction and produced smaller pups, Leising said.
“California sea lions are indicator species, meaning they will be one of the first species which may show signs of domoic acid toxicity, respond to changes in their ecosystem, and signal to the public how our oceans and ecosystem are doing,” said Brett Long, vice president of animal care at the Aquarium of the Pacific.
—Emily Gardner (@emfurd.bsky.social), Associate Editor


“I’ve just always felt like art and science are flip sides of the same coin.”
Scientists use tools ranging from models to microscopes to make sense of the world around them. Some might say artists do the same thing using tools such as paintbrushes and musical instruments.
“I’ve just always felt like art and science are flip sides of the same coin, with maybe different outcomes or different processes, but they’re both just getting at the truth of the world,” said Sara Bouchard, a sound artist and composer and adjunct faculty member in the Department of Kinetic Imaging at Virginia Commonwealth University’s (VCU) School of Art.
A recent National Science Foundation–funded collaboration between scientists and artists brought this principle to life.
The scientist-artist pairs worked together in yearlong residencies and produced art pieces—ranging from music compositions and video installations to ceramic works and paintings—that they presented at the Patricia Valian Reser Center for the Creative Arts in Corvalis, Ore., in early 2026.
“Part of the framing of the residency was around flux as this metaphor for connection and belonging and relationships.”
“The metaphor that people use to describe what this science network measures, or does, is that it’s monitoring the breath of the biosphere,” said Maoya Bassiouni, an environmental scientist at the University of California, Berkeley, who directed and developed the residency. “Those fluxes are sort of this giving and receiving between the land and the atmosphere, and it’s exactly what the scientists are doing in the community. So, part of the framing of the residency was around flux as this metaphor for connection and belonging and relationships.”
Bassiouni, who also created artworks in the residency, presented a lecture about the series alongside two other fluxART artists in late May at the National Center for Atmospheric Research’s (NCAR) Mesa Lab in Boulder, Colo.
An installation at NCAR’s Mesa Lab Library featuring all four fluxART projects also opened on 27 May and will be on display through the end of 2026.
Bouchard, the sound artist, was paired with Chris Gough, a biogeochemist who serves as the executive director of the Rice Rivers Center at VCU.
Gough studies how factors such as climate and disturbances affect ecosystems, particularly forests and wetlands. Bouchard learned more about Gough’s work by spending a year in his lab.
The result was a composition for choir and percussion called En Masse, which explores the connections between communities and ecosystems in a time of climate crisis. The piece’s five movements represent the movement of carbon through the environment: “Air,” “Wood,” “Soil,” “Fire,” and “Breath.”
In addition to vocals and instruments, the composition features birdsong, recordings from a compost pile, sonified data from Gough’s lab, and spoken words gathered from real people sharing their climate anxieties. An excerpt from the “Fire” movement reads,
Future! / Heavy weight on my ribcage / dusty, fragmented
Fire! / Clenched jaw, copper taste in my mouth / stark, shifted
Fire! / I worry about my kids / desperate, unbreathable
Fire! / and their future / squeezed, extreme
Future! Fire! Fire! Fire!
Both Bouchard and Gough said they were moved by the piece as it was performed in Corvalis and by seeing the mix of artists and scientists who attended, many traveling from other states.
“I was struck by how engaged both the scientific and artistic communities were,” Gough said. “We walked out, and it was a full room of people. It was energizing, and I think it felt meaningful in a way that stepping up on a conference stage to deliver the traditional convention talk [isn’t].”
In another pairing, video artist Julia Oldham partnered with Christopher Still, a plant ecophysiologist at Oregon State University.
The partnership started with Oldham visiting a 175-foot-tall (53-meter-tall) FLUXNET tower near Sisters, Ore., that Still and his team monitor.
At the top of the tower, a PhenoCam takes photos of the surrounding Deschutes National Forest every half hour. Still uses data from these images to examine how the greenness of the canopy changes over time because such changes can provide information about fluxes in carbon, water, and energy.
“I learned more about what Chris uses the PhenoCam for and got superexcited about the fact that Chris is using color data to understand forests,” Oldham said. “I thought that that was a really beautiful point of overlap for us as a scientist and an artist, to think about color and forests and what we can learn from color as a scientific tool.”
The pair created two pieces. 18//Flux shows how the colors and light from one PhenoCam site changed from 4 a.m. to 9 p.m. throughout the year for 13 years. Each frame is divided into 13 strips, with each strip representing 1 hour of the monitoring period.
The two had conversations throughout the duration of the project about the growing role of wildfires in the area. In fact, one of the FLUXNET towers they were using in the project burned down.
Their conversations led to September: Orange, a three-channel video showing footage from 24 different PhenoCams in the northwestern United States and Canada. When all of the landscapes are the same shade, the video briefly pauses. In September, when wildfires sweep through Cascadia, orange becomes the dominant color. The piece is accompanied by field recordings from Oregon forests and sonified canopy greenness data.
“I think the installation was a wild success, and I had a lot of people tell me how much they enjoyed it and appreciated it,” Still said. “Most people don’t respond to a 2D graph of data…whereas I think almost everyone responds to images, and photographs are really meaningful to people. So I think that is a really brilliant way to draw people into the science.”
—Emily Gardner (@emfurd.bsky.social), Associate Editor

Explosive volcanic eruptions inject gases and ash into the atmosphere, posing major hazards for human health, infrastructure, and aviation. A new article in Reviews of Geophysics examines recent advances in estimating Eruption Source Parameters (ESPs), the key conditions at the volcanic vent that are a necessity for modeling the behavior of volcanic plumes. Here, we asked the authors to explain what ESPs are, what technologies are used to observe eruptions, and which scientific challenges and future research directions remain for improving volcanic plume monitoring and modeling.
In simple terms, what are Eruption Source Parameters?
Eruption Source Parameters (ESPs) describe the key conditions at the volcanic vent during an eruption.
Eruption Source Parameters (ESPs) describe the key conditions at the volcanic vent during an eruption, such as the mass eruption rate, exit velocity, temperature, and particle size distribution. These parameters define how material is injected into the atmosphere and are essential inputs for models that simulate plume rise and subsequent dispersal of volcanic gases and ash in the atmosphere. In simple terms, ESPs represent the boundary conditions that control the behavior of volcanic plumes. Because they cannot usually be measured during an eruption, they must be estimated from indirect observations and models, which introduces significant uncertainty.
Why is it important to understand how volcanic ash and gases disperse after an eruption?
Volcanic ash and gases can travel long distances and affect aviation safety, human health, infrastructure, and even climate. Fine ash particles are particularly hazardous for aircrafts, while ash fallout can disrupt communities and critical services on the ground. Gas emissions may also impact air quality and alter the atmospheric radiative budget. Understanding volcanic dispersion is therefore essential for forecasting the movement of volcanic clouds and issuing timely warnings. Reliable forecasts support risk mitigation strategies and enable more effective responses by civil protection agencies and aviation authorities.
What technologies are used to observe volcanic plumes?
Volcanic plumes are observed using a combination of satellite, ground-based, and, more rarely, airborne measurements. Satellite observations are crucial for tracking ash and gas clouds over large spatial scales and in near real time. Ground-based instruments, such as radar, cameras, and infrasound sensors, provide detailed information on plume dynamics close to the source. Increasingly, these observations are integrated with numerical models to infer eruption conditions. The combination of multiple data streams is essential for constraining ESPs and improving the reliability of plume simulations.
What are some of the recent advances in estimating Eruption Source Parameters?
Recent advances have focused on combining observations with numerical models to better constrain ESPs. Multi-sensor approaches, data inversion techniques, and improved plume models have significantly enhanced our ability to estimate eruption rates and plume dynamics. At the same time, high-resolution computational fluid dynamics (CFD) simulations provide deeper insights into the complex fluid dynamic processes governing plume behavior. However, these models are computationally expensive and unsuitable for real-time applications, highlighting the need for approaches that bridge the gap between physical realism and operational efficiency.
What strategies do you propose in your review to improve Eruption Source Parameters estimation?
A central contribution of this review is the proposal of a new class of operational models for volcanic plumes.
A central contribution of this review is the proposal of a new class of operational models for volcanic plumes. These models integrate the physical realism of high-fidelity CFD simulations with the efficiency of simplified models used in forecasting. In particular, the review highlights the potential of artificial intelligence and machine learning techniques to “learn” from CFD results and optimally calibrate the key variables controlling plume dynamics. This hybrid approach allows complex physical processes to be represented in a computationally efficient framework, making it suitable for real-time applications while retaining improved accuracy.
How does improved volcanic plume monitoring lead to more effective volcanic hazard assessment?
Improved monitoring leads to more accurate estimates of ESPs, which directly translate into better forecasts of plume rise and ash dispersion. This reduces uncertainty in hazard assessments and supports more reliable decision-making. For example, more accurate forecasts can help aviation authorities minimize disruptions while maintaining safety and enable civil protection agencies to issue targeted warnings. Ultimately, better integration of observations and models enhances the capacity to respond effectively during eruptions and to mitigate their societal and economic impacts.
What are the remaining questions or knowledge gaps where additional research is needed?
Further research is needed to improve the coupling between observations, physics-based models, and data-driven approaches.
Despite progress, significant challenges remain. ESPs are still difficult to constrain in real time, and uncertainties in both observations and models propagate into forecasts. The integration of diverse data sources is not yet fully optimized, and different estimation methods can yield inconsistent results. Further research is needed to improve the coupling between observations, physics-based models, and data-driven approaches. In particular, developing robust hybrid frameworks that combine CFD, simplified models, and machine learning represents a key direction for advancing both scientific understanding and operational forecasting.
—Antonio Costa (antonio.costa@ingv.it,
0000-0002-4987-6471), Istituto Nazionale di Geofisica e Vulcanologia, Italy
Editor’s Note: It is the policy of AGU Publications to invite the authors of articles published in Reviews of Geophysics to write a summary for Eos Editors’ Vox.