Feed aggregator

body {background-color: #D2D1D5;} Research & Developments is a blog for brief updates that provide context for the flurry of news that impacts science and scientists today.

Human-driven climate change is driving the rise of sea levels, worsening flood conditions and threatening coastal communities around the world. Not only is sea level rising, but it’s rising faster every year. Understanding the degree to which different processes contribute to sea level, known as the sea level budget, can help scientists better predict where and how quickly sea level will rise under potential climate futures.

 
Related

•  Read the paper: Improved closure of the global mean sea level budget from observational advances since 1960
•  The Global Impact of Losing U.S. Sea Level Science
 

But for several decades there has been a “budget gap” between measurements of sea level change and the total estimated contributions from glaciers, polar ice, land storage, and oceans expanding as they heat up (thermospheric expansion). Research published today in Science Advances has helped close that budget gap by incorporating more recent sea level observations, reconciling measurements taken by different instruments, and including recent community estimates of sea level rise and its components.

The new analysis breaks down the drivers of sea level rise from 1960 to 2023. The team found that the largest contributor is heat-driven expansion of seawater, responsible for 43% of sea level rise since 1960. Melting ice contributed the next largest amount of sea level rise: 27% came from mountain glaciers, while 15% came from the Greenland Ice Sheet and 12% from the Antarctic Ice Sheet. Lastly, sea level rose 3% as land reduced its capacity to store water.

Since 1960, 43% of global sea level rise can be attributed to thermal expansion of water, just 3% to a reduction in land water storage, and the remainder from melting ice and glaciers. Credit: Zheng et al., Science Advances (2026)

“For years, there has been a frustrating gap between how much the oceans were observed to be rising and how much we could explain from the individual causes,” John Abraham, an engineer at the University of St. Thomas in St Paul, Minn., and a coauthor on the new research, said in a press release. “This work shows that, with better instruments, processes, and smarter analysis, this knowledge gap can be closed. We can explain sea level rise with greater confidence.”

The researchers also calculated the rate at which sea level has risen since 1960 and how each component factored in. They found that the rate of sea level rise has recently doubled: It was 2 millimeters per year averaged over 1960­–2023 and 4 millimeters per year averaged over just 2005–2023. The strongest driver of that doubling is ocean warming, responsible for 41% of the accelerating rate of sea level rise, followed by reduced land water storage (21%).

In the past, glacial melt was the largest contributor to sea level rise before it was overtaken by thermospheric ocean expansion overtook (left). The rate of sea level rise has been speeding up since about 1980, also driven by thermospheric ocean expansion (right). Credit: Zheng et al., Science Advances (2026)

This research demonstrates the importance of maintaining detailed records of sea level rise, collecting new measurements, and not backing away from global change research. With better data on which processes contribute to sea level rise and its acceleration, policymakers and local communities can create informed mitigation strategies that account for future rise.

—Kimberly M. S. Cartier (@astrokimcartier.bsky.social), Staff Writer

These updates are made possible through information from the scientific community. Do you have a story about science or scientists? Send us a tip at eos@agu.org. Text © 2026. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Sea level rise is a direct consequence of human-induced climate change: global warming. It is relentless and very hard to stop. It arises from human-induced warming and the consequential expansion of the ocean, plus the addition of more and more water from melting glaciers and ice sheets. It will continue long into the future.

Old oil and gas wells may continue to affect the environment long after they have stopped producing, with new field evidence showing that their leakage footprint can be broader and more persistent than surface methane measurements alone reveal. A study led by researchers at The Lyell Centre, Heriot-Watt University, examined persistent methane leakage from a legacy petroleum well in British Columbia, Canada. The team found that while methane emissions at the ground surface were concentrated in a relatively small area and varied through time, the leakage also left a wider detectable signature in the shallow subsurface and surrounding soils.

Roughly the size of Texas, the Karoo Basin of central western South Africa is brutally dry, sparsely populated, and known in part for its potentially “massive” hydrocarbon deposits.

South Africa, which consumes more energy than any other country in sub-Saharan Africa, has shown a growing interest in commercial fracking for shale gas and oil across the Karoo hinterland, with the country moving in late 2025 to lift a 13-year ban on shale gas exploration in the area.

However, a recent study from the University of Cape Town, published in Seismological Research Letters, cautioned that the Karoo might not be as seismologically calm as it appears, meaning fracking efforts could have the potential to induce earthquakes in the region.

A Swarm of Earthquakes

The researchers observed 66 earthquakes in this cluster between 2007 and 2022, ranging from 0.7 to 4.8 in magnitude.

The researchers investigated what they call a sudden swarm of earthquakes that occurred in the Leeu Gamka cluster, a region of the Karoo that was previously considered seismically stable. They observed 66 earthquakes in this cluster between 2007 and 2022, ranging from 0.7 to 4.8 in magnitude.

“The individual earthquakes here are very small,” said Alastair Sloan, a tectonics and structural geologist at the University of Cape Town.

Using ambient noise tomography, previous geophysical surveys, and information about the locations of past earthquakes, the researchers identified a critically stressed fault underlying the region. The fault appears to extend for at least 30 kilometers roughly west-northwest to east-northeast.

Looking at South Africa more generally, there are other places where there have been “fairly large” earthquakes with a similar orientation, Sloan said. He cited a series of large earthquakes in the early 20th century in a place called Koffiefontein, north of the study area, and the disastrous 1969 Tulbagh earthquake, west of the team’s study area.

Both of those earthquakes occurred in regions that are geologically similar to the Karoo, though they’re outside of the area being considered for shale gas exploration, Sloan said.

Fracking Risks?

In other parts of the globe, such as Oklahoma in the United States, processes related to oil and gas extraction have led to “induced earthquakes.” Most of these earthquakes have been triggered by wastewater disposal associated with oil production, not by fracking directly.

Researchers are unsure if industrial fluid injection in the Karoo, as is applied in shale gas fracking processes, could trigger significant seismic action in the region’s existing faults.

“Some locations which undergo shale gas development don’t see very much seismicity, and there is a catalog of things which need to be present for [seismicity] to be something that you would particularly worry about,” Sloan said.

For instance, if faults are only within the crystalline basement and therefore separated from the sedimentary layers where the fracking occurs, then it’s not likely they’ll be reactivated, because there’s no way for the fracking fluid to get down to the fault zone itself. Another factor, Sloan added, is that for significant earthquakes to occur, large faults that are already critically stressed need to be present in the region undergoing fracking.

The new study showed that both of these conditions may be met in the Karoo: Microseismicity does extend to the depths at which the carbonaceous shale is present. And this microseismicity is occurring on a reasonably extensive structure with a similar orientation to larger earthquakes that have already occurred in the region.

However, Sloan stressed, this isn’t a cause for immediate panic.

“I don’t want to be too alarmist; the size of the structure revealed by the microseismicity is not huge, and so we do not have evidence to expect an earthquake much larger than the damaging historical earthquakes that we have already seen in the wider region,” he said. “Globally, large earthquakes triggered by fracking (rather than associated deep wastewater exposure) are very rare, but the study suggests the necessary preconditions are present. And so the possibility needs to be considered and monitored carefully.”

Not Unique

Raymond Durrheim, a geoscientist and the South African Research Chair in Exploration, Earthquake and Mining Seismology at the University of the Witwatersrand, and who also examined the Ph.D. thesis on which the new study is based, said no area is perfectly seismically quiet.

“We know the way seismicity works in this whole area of southern Africa is that swarms occur,” he said. “They’ll last for years or even decades, and then they’ll die away. This is not a unique occurrence.”

This study was “useful,” though, Durrheim added, especially with the possibility of shale gas development in the Karoo. “It’s very important that we understand this because we know that when you inject fluid under high pressure, there’s always a chance you could trigger an earthquake,” he said, noting examples of fluid injection triggering earthquakes in places such as Canada. “It’s always a risk.”

To mitigate risks, Sloan suggested it would be useful to have a much denser network of seismometers within this region of South Africa.

—Ray Mwareya (@RMwareya), Science Writer

Citation: Mwareya, R. (2026), A swarm of earthquakes in South Africa’s Karoo Basin poses questions for oil and gas development, Eos, 107, https://doi.org/10.1029/2026EO260159. Published on 20 May 2026. Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Source: Water Resources Research

Evapotranspiration is a critical link between water, energy, and carbon. Scientists need to understand it well to accurately predict weather, droughts, streamflows, and even carbon emissions.

Eddy covariance towers, which measure changes in the atmosphere, are one of the primary ways that scientists measure evapotranspiration in an ecosystem. But these measurements often have a problem with energy imbalance, in which the measured fluxes of sensible heat and latent heat add up to less than they should. (Sensible heat refers to measurable temperature changes occurring via conduction or convection, whereas latent heat refers to water in the atmosphere changing phases.) There’s something missing—up to 30% of the system’s energy—in the math, and that can cause problems for later uses of the measurements, from forecasts to climate policies.

Scientists can adjust evapotranspiration measurements to try to correct for this problem, but a commonly used method to do so assumes that the Bowen ratio, or the ratio between sensible and latent heat, remains constant. However, this assumption may be flawed.

Raghav and Kumar present a new way of tackling this old problem without making assumptions about the Bowen ratio. It’s based on water use efficiency, which is how effectively plants use water to produce biomass.

The method first uses a suite of data from an eddy covariance tower to estimate evapotranspiration and energy balance through time. Then it derives the underlying water use efficiency potential while accounting for the influence of atmospheric dryness. In general, for a given vegetation type, this potential underlying efficiency is considered to be relatively stable over a growing season. The statistically smoothed potential underlying water use efficiencies is then compared to reference values derived during periods when the energy balance is well constrained. The ratio of the two is then used to correct evapotranspiration.

The new method is more consistent and more tied to the physics of plant physiology than current methods when results from each are compared, the authors found.

The new method is appropriate for use with any eddy covariance tower location or dataset because the authors used data from more than 250 towers around the world, in a range of ecosystem and climate types, to build their approach. However, they add, it may be less reliable in environments where evaporation dominates transpiration, such as wetlands. Nevertheless, the authors say, this work marks an important advance in measuring evapotranspiration, with broad implications for water management, agriculture, and adapting to climate extremes and drought. (Water Resources Research, https://doi.org/10.1029/2025WR042766, 2026)

—Rebecca Dzombak (@rdzombak.bsky.social), Science Writer

Citation: Dzombak, R. (2026), Improving eddy tower evapotranspiration estimates, Eos, 107, https://doi.org/10.1029/2026EO260163. Published on 20 May 2026. Text © 2026. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Tiny saltwater channels have a big influence on sea ice.

Sea ice typically includes pockets or channels of brine that allow salt water to flow vertically through the ice. When those channels align neatly, they need to make up only about 5% of the ice volume before the water can flow. But in more disordered, granular ice, salt water starts to flow only when the brine channels take up more space—roughly 10% of the ice volume, according to a new study published in Scientific Reports.

“If we’re trying to find predictive models about how these ice cores are responding under climate change, it’s going to be necessary to take into account these structural and microstructural conditions.”

This higher threshold could slow the drainage of surface melt ponds, as well as the transport of nutrients to microbial communities inside the ice.

“If we’re trying to find predictive models about how these ice cores are responding under climate change, it’s going to be necessary to take into account these structural and microstructural conditions,” said Stephen Ackley, a sea ice researcher at the University of Texas at San Antonio who was not involved in the study.

Disorderly Constructs

As seawater freezes, it forms a mixture of ice crystals and brine. In calm conditions, the ice slowly grows into long, parallel crystals separated by orderly brine channels. This columnar sea ice is common in the Arctic, and its properties have been widely used in sea ice models.

But in choppy waves or when the ice’s snow-covered surface floods and refreezes, new ice can’t grow into these ordered columns. Instead, it forms small, randomly oriented grains separated by more complex pores containing brine and gases. Called granular ice, this form is more common in Antarctica but is becoming increasingly prevalent in the Arctic as temperatures rise and ice cover thins.

“It’s the sequel we’ve been waiting decades for.”

In 1998, University of Utah mathematician Kenneth Golden established the first estimate of the point at which the brine channels are connected enough to allow water to flow in columnar ice, called the percolation threshold. The new work, also led by Golden, extends a similar analysis to granular sea ice.

“It’s the sequel we’ve been waiting decades for,” said Don Perovich, a sea ice researcher at Dartmouth who was not involved in the new work.

To quantify the percolation threshold for granular ice, Golden and his colleagues collected sea ice samples during two expeditions off the eastern coast of Antarctica in 2007 and 2012. They measured how quickly water moved through the brine channels in the ice. After the 2012 expedition, they also mapped the arrangement of ice crystals within the ice blocks to correlate those permeability measurements with the microscale structure of the ice.

Most climate models are based on the assumption that the microstructure of sea ice is organized into columns, like those in the image on the left. But new research shows that granular ice, as seen on the right, is growing more common in the Arctic, which could affect climate modeling. Credit: Golden et al., 2026, https://doi.org/10.1038/s41598-026-41706-w, CC BY-NC-ND 4.0

The finding that in granular ice, about twice as much of the ice volume needs to be brine for water to flow compared to columnar ice suggests that brine channels within granular ice are much less interconnected.

With the higher threshold, “you have to reassess all these models, anything that relies on fluid flow through sea ice,” if granular ice is present, said Golden. Granular ice will require warmer or saltier conditions to leave enough brine in the ice structure to meet the percolation threshold and allow water to flow vertically.

Researchers extracted blocks of ice in Antarctica with a chainsaw and poured dyed salt water on top. In this way, they observed how quickly the fluid descended through the ice. Credit: Kenneth Golden

For example, the new value could influence models of how meltwater ponds behave atop an underlying ice sheet. If meltwater ponds form above a base of granular sea ice, those ponds will require warmer temperatures before they start draining than melt ponds on columnar ice will.

If these melt ponds remain on the surface longer waiting for those warmer temperatures, they could lower the albedo, or reflectivity, of the ice sheet. That could cause the ice sheet to absorb more heat, leading to a feedback loop that could accelerate melting.

The higher percolation threshold could also affect algae that lives within the ice. Ice algae make up an important food source for krill and crustaceans, which in turn become food for fish, penguins, and whales. Algae rely on water flowing through the ice to deliver nutrients. Because granular ice requires warmer temperatures for that flow to start, it could affect the depth at which algae can live inside the ice, Golden said.

Percolation Consideration

Still, experts say more data are needed to establish percolation thresholds across both Arctic and Antarctic ice. The size of the grains in granular ice can vary substantially at different temperatures, under different formation conditions, and between the poles. Larger grains could lower the percolation threshold, allowing water to flow even when the ice contains much less than 10% brine by volume, said Sønke Maus, a scientist studying ice microstructure at the Norwegian University of Science and Technology who was not involved in the study.

“The data that we have at the moment for the granular sea ice is sparse,” Maus said. “You need a big campaign to collect such data.”

Golden said that in future work he also plans to develop models to compute the electromagnetic properties of both columnar and granular sea ice. Knowing these properties can help scientists determine the thickness and age of an ice sheet from satellite data.

—Skyler Ware (@skylerdware), Science Writer

Citation: Ware, S. (2026), Changes in sea ice microstructure could affect climate models, Eos, 107, https://doi.org/10.1029/2026EO260164. Published on 20 May 2026. Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Author(s): Chubin Lin, Jiandong Chen, Huihui Wang, and Yangyang Fu

This Letter uncovers five distinct charge transport modes and their transitions in dual-energy electron beam diodes. We via first-principle particle-in-cell (PIC) simulations establish that the specific mode (e.g., space-charge oscillations) and the current transmitted characteristics are essentiall…

[Phys. Rev. E 113, L053203] Published Wed May 20, 2026

In British Columbia a CAN$115 million project is almost complete to mitigate the risk posed by debris flows to the town of Squamish.

Upstream of the town of Squamish in British Columbia, Canada, an extraordinary project is underway to mitigate the risk of debris flows. Known as the Cheekeye Debris Barrier Project, the scheme involves the construction of a concrete barrier that is 24 metres high across the Cheekeye Fan, designed to catch debris flows with a volume up to 2.4 million cubic metres of debris.

The project is almost complete, with hand-over expected in the summer of this year. There is an excellent article about the project on The Tyee website, which includes some very interesting images of the structure. The estimated cost of the project is around CAN$115 million. The location of the Cheekeye Debris Barrier Project is [49.79417, 1123.10878]. This is a render of the final form of the barrier (but take a look at the images of the almost completed structure too):

A render of the completed Cheekeye Debris Barrier. Image via the District of Squamish.

This is a fascinating project that makes a great case study for teaching, not least because both the detailed design considerations and the regulatory process for approving the programme are available in detail.

In terms of the detailed design considerations, there is an excellent open access paper in the Canadian Geotechnical Journal (Lesueur et al. 2025) that provides a very comprehensive analysis of the estimation of the potential volume and mobility of the debris flows on the Cheekeye Fan, and of the considerations that went into the final deisign of the structure.

In terms of the approval process, the District of Squamish has an online archive of documents and Council minutes that extends back to 2003.

I would highlight the challenges around determining the optimal size of a barrier of this type. The team has been balancing risk against cost, following the principle as outlined in Lesueur et al. (2025):-

“The local government specifies that tolerable debris-flow risks be reduced “as low as reasonably practicable” (ALARP), defined in this project as the point where the cost of additional mitigation measures is grossly disproportionate to the benefits gained.”

Thus, the barrier is not designed to stop the maximum credible debris flow, which is 5.5 million cubic metres (more than double the design event). This is pragmatic engineering at its best, and the Cheekeye Debris Barrier Project provides the level of detail that allows the decision-making process to be fully understood.

Reference

LeSueur, P. et al. 2026. Risk-informed design of debris-flow mitigation at Cheekeye Fan. Canadian Geotechnical Journal. 62: 1-16. https://doi.org/10.1139/cgj-2023-0008

Return to The Landslide Blog homepage Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

SummarySolving wave equations using machine learning methods, such as physics-informed neural networks (PINNs) and neural operator approaches, has become an active area of research in the computational seismology community. However, a significant challenge associated with these methods is the degradation of long-term prediction accuracy, which arises from the inherently nonlinear dynamics of wavefields governed by partial differential equations (PDEs). Koopman theory provides a promising framework by enabling the transformation of nonlinear dynamical systems into linear ones, thus allowing linear analysis tools to be applied to complex, nonlinear problems. In this study, we introduce a data-driven operator learning method, the Koopman Neural Operator (KNO), for solving the two-dimensional acoustic wave equation in the time domain. Within the KNO framework, the time-domain wavefield is treated as the state variables, while the velocity model acts as the control variables. These form a nonlinear dynamical system, which is mapped into a linear latent space using a convolutional encoder. The Koopman operator is then approximated by parameterizing the integral kernel in the wavenumber domain, facilitating linear time evolution of the encoded variables. A convolutional decoder subsequently transforms the evolved latent variables back into the original wavefield domain to obtain the predicted time-domain wavefields. To evaluate the performance of KNO, we first conducted numerical experiments on the three most complex datasets from the OpenFWI benchmark and compared the results with those of the current state-of-the-art Fourier Neural Operator (FNO). The results demonstrate that KNO outperforms FNO in terms of prediction accuracy, computational efficiency, memory consumption, and convergence speed. Additionally, KNO exhibits notably strong stability in seismic wavefield extrapolation on the Marmousi model. Finally, we comprehensively evaluate the parallel scalability of the proposed KNO model, and compared KNO with the finite difference method (FDM) (based on both CPU and GPU) in terms of computational speed. Collectively, these experiments indicate that KNO provides a promising new approach for long-term and relatively high-precision wavefield extrapolation in seismic modeling.

SummarySpectral Induced Polarization (SIP) has gained recognition as an advanced geophysical method for monitoring soil water content. SIP’s ability to simultaneously assess soil texture and water content makes it particularly valuable for studying soil dynamics under varying environmental conditions. However, its application in complex field environments has been hindered by issues such as capacitive and inductive coupling, which affect the quality of measurements. In this study, we combined water monitoring in soil and plant (field and lab SIP measurements, sap flow and soil moisture monitoring) to characterize soil heterogeneity and evaluate vine water availability in a Médoc vineyard during the summer drought of 2023. Different SIP field acquisition strategies relying on multiwire cables, fully coaxial cables array or hybrid coaxial/multiwire were tested. The acquisition setup was shown to strongly affect data quality depending on soil moisture conditions. Lab and field SIP measurements confirmed a strong correlation between the quadrature conductivity at 0.25 Hz and soil volumetric water content (VWC) as well as a linear relationship between phase shift at 0.25 Hz and VWC. The real and imaginary parts of the conductivity was used to infer VWC dynamics based on empirical petrophysical relationships established in situ. A mechanistic model based on the Dynamic Stern Layer model was also applied to high-quality SIP data for the same purpose. We found that imaginary conductivity was much less sensitive to soil water conductivity than real conductivity. Thus, in vineyard soils subject to soil amendments and resulting variations in soil water salinity, we hypothesized that SIP monitoring provide more reliable estimates of changes in soil moisture content than standard electrical resistivity tomography. We showed that SIP monitoring effectively captured soil drying dynamics down to a depth of 1 m during the growing season. The SIP method combined with soil moisture probes could thus provide simultaneous access to both soil moisture dynamics and the spatial distribution of soil texture, opening up new perspectives for mapping soil moisture dynamics in the field, even in case of potentially large soil water salinity fluctuations. In our case, SIP indicated a decrease in soil water storage from 150 to 50 mmH20 during the summer drought of 2023. By combining SIP and vine sapflow monitoring, Vine water availability, defined as total transpirable soil water could also be estimated at 98±8 mm H20 for the vines equipped with sapflow sensor, which is of great interest for culture water management. Finally, the distinct responses of the real and imaginary conductivity components underscore the value of SIP for soil moisture assessment in viticultural environments subject to variable salinity inputs. This work is the first to attempt a quantitative estimation of soil water storage in commercial vineyards using SIP methods. It extends previous applications limited to other agricultural settings and broaden the applicability of mechanistic models (Dynamic Stern Layer model) for predicting volumetric water content based on multi-frequency complex conductivity measurements under field conditions.

A recent study published in Advances in Atmospheric Sciences has uncovered a detailed mechanism through which intense storms over the Himalayas contribute to increasing moisture in the lower stratosphere—a layer of the atmosphere crucial to global climate regulation. The research, led by Ph.D. student Li Ming and Dr. Wu Xue from the Institute of Atmospheric Physics (IAP) at the Chinese Academy of Sciences, highlights the important role of gravity waves generated by deep convection.

A review paper led by researchers from the University of St Andrews highlights the transformative potential in the use of radar in polar research to predict future sea levels.

body {background-color: #D2D1D5;} Research & Developments is a blog for brief updates that provide context for the flurry of news that impacts science and scientists today.

The Intergovernmental Panel on Climate Change (IPCC), the United Nations body whose mission is to “provide governments at all levels with scientific information that they can use to develop climate policies” will likely update the emissions and land use scenarios used in the models it considers in its bellwether assessment reports.

The IPCC has used these scenarios, known as Shared Socioeconomic Pathways (SSPs) or Representative Concentration Pathways (RCPs), in its two most recent assessment reports (AR), AR5 released in 2014 and AR6 released in 2023. The upcoming AR7 will be informed by a new set of scenarios, as described in a paper published last month in Geoscientific Model Development.

The paper is drawing widespread attention—both within the scientific community and in wider discourse—for its statement regarding one current scenario that has become familiar to anyone following climate science and policy. The scientists said the emissions levels associated with the most extreme, worst-case scenario, SSP5-8.5 (and its predecessor, RCP8.5), “have become implausible.”

 
Related

•  On the death of RCP8.5, from The Climate Brink
•  Read the study: The Scenario Model Intercomparison Project for CMIP7
•  Scientists now say this worst-case climate scenario is ‘implausible.’ Here’s what it means.
 

Even President Donald Trump weighed in with a post on Truth Social on 17 May, where he wrote “GOOD RIDDANCE,” and “the United Nations TOP Climate Committee just admitted that its own projections (RCP8.5) were WRONG! WRONG! WRONG!”

But as scientists have pointed out for years, RCP8.5 was never meant to represent a likely emissions scenario or a forecast of humanity’s future. Some scientists questioned whether it’s even possible for RCP8.5 to play out in real life. 

RCP8.5 is one of four hypothetical emissions scenarios developed in 2011 for climate modeling experiments. When RCP8.5 was created, it was meant to represent a “very high baseline emission scenario” that would warm the world nearly 5°C (9°F) compared with preindustrial temperatures by 2100. Parallel scenarios (SSPs) were presented in 2017. SSP5-8.5 is the worst-case scenario in that framework, representing a world in which fossil fuels are widely exploited and more of the world adopts energy-intensive lifestyles alongside the warming projected by RCP8.5. 

“The scenarios we create today are different than the scenarios we created 15 years ago, because the world is different today than 15 years ago.”

The authors of the new paper wrote that “trends in the costs of renewables, the emergence of climate policy and recent emissions trends” justify the implausibility of the highest-emissions scenarios such as RCP8.5 and SSP5-8.5. 

For scientists, the idea of dropping these scenarios is neither new nor controversial. As three climate scientists (Zeke Hausfather of Berkeley Earth, Glen Peters of the CICERO Center for International Climate Research, and Piers Forster at the University of Leeds) wrote in a blog post: “[RCP8.5] was never a likely outcome even in a world that did not address climate change; rather it was always intended to represent a worst case scenario that pushed fossil fuel expansion to the max.”

The new scenarios presented in Geoscientific Model Development include a high-emissions scenario in which clean energy policy is rolled back, and the world warms about 3.5°C (6.3°F) by 2100—still a level at which humanity can expect very severe impacts, from worsening weather extremes to rapidly rising sea levels.

The IPCC’s likely elimination of RCP8.5, even if it was never a plausible scenario, is a small sign of improvement in global climate change mitigation efforts, Hausfather, Peters, and Forster wrote: “Rapid declines in clean energy costs have bent the curve of future emissions downward, with new scenarios designed to reflect current policies notably lower than most baseline scenarios in the literature.”

“Of course, we still have a long way to go to get emissions down to (net) zero and stabilize global temperatures,” they noted.

The new paper captures the difficult road ahead for climate action: The new scenarios are based on a reduced projection for the increase in emissions, not for the overall amount of emissions—those are still increasing. Unlike before, none of the new emissions scenarios keep the world below 1.5°C (2.7°F) of warming, the limit originally set by the Paris Agreement in 2016. That’s no surprise to scientists, who suggest Earth is already in the 20-year period in which warming will formally surpass this benchmark. 

“The scenarios we create today are different than the scenarios we created 15 years ago, because the world is different today than 15 years ago,” Hausfather told the Washington Post.

—Grace van Deelen (@gvd.bsky.social), Staff Writer

These updates are made possible through information from the scientific community. Do you have a story about science or scientists? Send us a tip at eos@agu.org. Text © 2026. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

According to NOAA, the global average sea level has risen 8–9 inches (21–24 centimeters) since 1880. The rate at which the sea level is rising is increasing, threatening coastal cities and ecosystems around the world.

It may sound counterintuitive, but new research suggests that cleaning up air pollution could contribute to a weakening of the Atlantic Meridional Overturning Circulation (AMOC). This is the ocean current system that acts like a giant conveyor belt, moving warm surface water northward and cool deep water southward.

It was the hardest field trip they had ever been on, but the result was both surprising and exciting. After hiking 9 kilometers with a 400-meter elevation gain and carrying heavy backpacks through very rocky terrain, the researchers spent more than 24 hours in the field and returned with sediment samples from the lake Stuptjørna.

A new study of the largest dam removal project in United States history on the Klamath River in Oregon and California is offering new insight into a long-running water conflict by finding that farmers and conservation groups share priorities that may help guide decision-making on future river restoration projects. The work is published in the journal Society & Natural Resources.

Months after wildfires eliminate vegetation that holds hillside sediment together, debris flows—destructive landslides that carry bulky material down once-stable slopes—can devastate infrastructure, taking out roads and buildings in their wake.

Though the U.S. Geological Survey (USGS) creates hazard predictions used to warn communities of the risk of these postfire debris flows, those predictions haven’t fully considered how recovering vegetation reduces risk over time—until now.

A new study published in Geosphere presents a new way to calculate postfire debris flow risk that takes vegetation recovery into account. The USGS will begin using the new method this wildfire season to create more accurate maps of debris flow hazard in the years after a fire.

“I’m so appreciative that the focus on how the debris flow hazard changes over time after fire is being addressed,” said Nancy Calhoun, a geologist and postwildfire debris flow program manager at the Washington Geological Survey who was not involved in the new study. Calhoun said she relies on the USGS hazard assessments for virtually everything her job requires.

“We’re glad to have a way that we can help our partners moderate those situations where the hazard has decreased,” said Andrew Graber, a geologist at the USGS Landslide Hazards Program and lead author of the new study.

Assessing Hazard, Again

After a wildfire, the USGS creates hazard maps that incorporate information about soil type, steepness, and burn severity (how much vegetation has been lost) to show where the risk of a debris flow may be elevated.

Then, the agency distributes this guidance to the National Weather Service, which uses it to set rainfall thresholds: levels of rainfall at which a debris flow becomes likely. State, county, and city agencies use those rainfall thresholds to issue warnings or take action when rainfall is imminent, for example, by closing highways or triggering evacuations.

“That left us with some uncertainty when we started to get further away in time from the fire.”

The methods used to create the USGS maps, however, historically relied on a snapshot of the burned area taken just after the fire, and the maps weren’t updated to reflect conditions as vegetation grew back and began holding soil in place again.

That led to situations where public safety decisions were made on the basis of outdated maps and rainfall thresholds. For example, concern over debris flows after the 2020 Grizzly Creek Fire in Colorado led to several closures of Interstate 70 in 2022, but the debris flows never happened.

“What [the original assessments] didn’t capture is how the vegetation came back,” Graber said. “That left us with some uncertainty when we started to get further away in time from the fire.”

Intense rainfall in July 2025 triggered a debris flow near Dayton, Wyo., in the 2024 Elk Fire burn area. Credit: USGS, Public Domain

To test an improved method for these hazard assessments, Graber and the research team incorporated satellite imagery of 12 burned areas that showed the degree of vegetation recovery right after the fire, 1 year after the fire, and 2 years after the fire. Then, they tested their new method by comparing its predictions to rainfall and debris flow data from the 12 burned areas.

The updated method better reflected what had actually happened after the fires, reducing the number of unnecessary warnings without missing real-world debris flows.

Risk Recalibration

The USGS plans to begin using their new workflow to create hazard maps for some higher-profile fires during the coming wildfire season.

“It’s a really important question: Are we still worried about this burn scar?”

That’s exciting for Calhoun. As part of her job, she’s in constant contact with emergency managers who periodically ask how worried they should be about debris flows in areas that burned years ago. “It’s a really important question: Are we still worried about this burn scar?” she said.

Right now, Calhoun has no data to point to in the years after a fire to give an updated answer to that question. Using the new method from Graber and the research team, she will.

“Because they’re using satellite [imagery] and repeatable quantitative methods to look at these burn scars over time, we’ll actually be able to say something useful and informed about vegetation recovery,” she said.

Having a deeper understanding of how debris flow risk evolves over time is especially important because debris flows themselves are becoming a greater risk to the public as a result of increasingly intense wildfires and rainstorms. In addition, more accurate assessments can reduce warning fatigue, which occurs when too many false alarms lead to people ignoring or opting out of alerts.

Graber hopes he and the USGS will continue to improve their methods for assessing debris flow hazards by collecting more debris flow data across the country and improving the underlying equation for hazard assessments so that it better reflects the unique conditions of different ecosystems in the United States. USGS researchers also published a new study in March presenting a method to generate maps of where debris flows might travel if they do occur.

“It’s a big year for USGS’s useful postfire products,” Calhoun said.

—Grace van Deelen (@gvd.bsky.social), Staff Writer

This news article is included in our ENGAGE resource for educators seeking science news for their classroom lessons. Browse all ENGAGE articles, and share with your fellow educators how you integrated the article into an activity in the comments section below.

Citation: van Deelen, G. (2026), A new approach can better predict debris flow hazards years after fires, Eos, 107, https://doi.org/10.1029/2026EO260160. Published on 19 May 2026. Text © 2026. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Source: Geophysical Research Letters  

Real-time hydrologic forecasting predicts river level and flooding inundation by combining continuously updated rainfall measurements, river gauge readings, and weather forecasts. Most of these flood forecasting systems depend on human interpretation and adjustments, or a “forecasters-in-the-loop” approach, which pairs computer models with a human expert on flood dynamics and local conditions. In contrast, in a “forecasters-over-the-loop” system, humans supervise automated forecasts and intervene only if necessary.

Recently, artificial intelligence (AI) and machine learning (ML) have become more integrated into flood prediction, and many of these systems are faster at processing large datasets and learning complex patterns from historical records than traditional models alone. But these new technologies also come with limitations—AI and ML require extensive data and may struggle to capture extreme, rare events.

Even though ML and AI are often touted as the future of flood forecasting, most studies have tested this technology against models that provide historical simulations, not the real-time operational systems that would be used during a flood. These simplified models may lack local details or are tested at daily rather than hourly resolution. Their effectiveness may be overestimated. 

Tran et al. produced the first study comparing the performance of ML models to an actual flood forecasting system used at the California Nevada River Forecast Center (CNRFC) that uses professional forecasters and traditional hydrologic models. The study suggests that a forecasters-in-the-loop approach outperforms the ML models in several key ways, including streamflow predictions and flood event detection, because forecasters can recognize model errors and account for poor input data—actions models cannot take on their own.

The researchers used data gathered from CNRFC river stage forecasts across 50 California and Nevada locations between 2012 and 2022 and river condition lead times from 1 to 96 hours. Compared to the ML models, the Community Hydrologic Prediction System used at CNRFC generally performed better at predicting stream flow and flood peaks, especially with longer lead times. Though the ML models could perform better at very short lead times, their accuracy declined quickly. Though automated forecasting options may seem promising, they are not yet a suitable replacement for human expertise when it comes to protecting lives and livelihoods from damaging floods, the researchers say. (Geophysical Research Letters, https://doi.org/10.1029/2025GL118317, 2026)

—Rebecca Owen (@beccapox.bsky.social), Science Writer

Citation: Owen. R. (2026), Keeping humans in the loop improves flood forecasting, Eos, 107, https://doi.org/10.1029/2026EO260161. Published on 19 May 2026. Text © 2026. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Tidal wetlands are critical, yet vulnerable ecosystems. Tidal marshes, mangrove forests, and tidal flats support biodiversity, protect against flooding and storm surges, sequester carbon, and improve water quality. Due to human development and climate change, tidal wetland areas have been shrinking globally. A new study using 40 years of satellite data shows that this loss has been accelerating in the U.S. and that this acceleration is being increasingly driven by extreme weather events.