The stakes of this question are enormous. Methane is a far more potent greenhouse gas than carbon dioxide over short timescales, trapping nearly 30 times more heat per molecule while persisting in the atmosphere for a much shorter period. That combination of high potency and brief atmospheric lifetime makes methane reduction one of the fastest available levers for slowing near-term warming, and it explains why the gas has become a central target for emissions monitoring programs worldwide. Scot Miller, an associate professor of environmental health and engineering at Johns Hopkins University and senior author of the study, emphasized that the flat trend carries both reassurance and disappointment. The good news, he noted, is that emissions have not markedly increased despite the enormous growth in natural gas production that followed the hydraulic fracturing boom. The bad news is that oil and gas operations still account for a large share of U.S. methane emissions, and the research found no detectable evidence that recent federal legislation had an impact on the total.

The regulatory backdrop against which this study unfolds is remarkable. In 2021, the Environmental Protection Agency restarted the process of developing rules to address methane emissions under the Clean Air Act, reviving an effort that had been stalled. Congress then enacted the Inflation Reduction Act of 2022, which went further than any previous federal measure by establishing fees on methane emissions from oil and gas facilities and allocating more than $1 billion in technical assistance to help the industry detect and repair leaks. Although some of these provisions proved short-lived in practice, the researchers describe the package as an unprecedented push toward reducing one of the major contributors to climate change. The central question motivating the study was whether that push produced measurable results in the atmosphere, where it ultimately matters.

Answering that question required a methodological approach capable of seeing past the self-reported inventories that have historically dominated emissions accounting. The research team turned to space. They combined observations from Europe’s TROPOMI instrument and the GOSAT satellite, both of which measure the concentration of methane in the air at countless locations across the globe, with sophisticated atmospheric modeling. Because methane released at the surface does not simply hover above its source but is carried and dispersed by winds and other meteorological forces, the researchers developed an algorithm that traced the gas observed from orbit back to its origins on the ground. This inverse modeling framework allowed them to estimate where methane emissions from the oil and gas sector occurred across the United States and how large those emissions were, year by year, for the period bookending the legislative activity from 2019 through 2024.

The numbers that emerged paint a picture of remarkable stability. Total methane emissions from oil and gas activities across the contiguous United States remained within a narrow band, between 9.3 and 10.4 teragrams per year, throughout the study period. Emissions declined by 0.58 teragrams between 2019 and 2023, a modest dip that was partially offset by a slight rise from 2023 to 2024. Set against the backdrop of rising production, that stability is itself a finding. Ao Chen, a PhD student at Johns Hopkins and the study’s first author, stated plainly that the team does not see a detectable decrease in emissions after the Inflation Reduction Act. She was careful, however, to acknowledge the limits of such an assessment: there is no way to test the counterfactual, and it remains possible that without the legislation, methane emissions would have climbed much higher.

One metric did show meaningful movement. The intensity of emissions, defined as the amount of methane released relative to the volume of oil and gas produced, decreased by approximately 11 percent over the study period. Yet the researchers interpret this decline cautiously, describing it as the continuation of a decades-long trend rather than a sudden improvement attributable to policy. Emissions intensity has been gradually falling for years as the industry has matured, and the new data suggest the recent period simply extends that trajectory. In other words, the sector is becoming somewhat more efficient at delivering energy without leaking methane, but because production keeps growing, the absolute quantity of methane entering the atmosphere has not budged.

The gradual improvement in emissions intensity may reflect a fundamental economic shift in how the industry treats natural gas. Methane, the primary component of natural gas, was once regarded largely as a nuisance byproduct of oil extraction, something to be disposed of as cheaply as possible. When there is no pipeline to carry gas from a wellhead to market, drilling companies have little financial incentive to prevent leaks and often simply flare the gas to get rid of it. But when pipeline infrastructure became available in regions such as West Texas, that same gas moved to market, where consumers burned it for heating, cooking, powering appliances, and generating electricity. Evidence from other studies suggests that leaks decline when gas becomes a valuable commodity, because every cubic foot that escapes is revenue lost. Companies have also been updating and improving their infrastructure, replacing aging equipment and adopting better operational protocols. As Miller put it, better industry protocols and less flaring have likely helped gradually curb emissions intensity even as gas and oil production have increased.

Beneath the national averages, the study uncovered striking regional variation. Texas, home to the largest oil-producing basin in the country, recorded a 14 percent decline in oil and gas methane emissions over the same period, a drop that stands out given the state’s dominant role in American energy production. By contrast, the researchers found that California and Colorado are likely falling short of their own emissions reduction goals, suggesting that state-level commitments have not yet translated into atmospheric reality in those jurisdictions. This geographic heterogeneity underscores a key advantage of the satellite-based approach: rather than relying on bottom-up inventories that may lag or misrepresent actual conditions, the method captures what is genuinely happening on the ground, basin by basin, and can reveal where progress is real and where it remains aspirational.

The findings arrive at a moment of uncertainty for methane policy in the United States. The fee mechanism established under the Inflation Reduction Act and the EPA’s Clean Air Act rules represented the most aggressive federal attempt yet to price and regulate methane leakage, yet the atmosphere, at least through 2024, shows no clear signature of their effect. Chen warned that without long-term regulatory durability, the industry may lack the incentive to further reduce methane emissions, and she argued that while curbing emissions intensity is a step in the right direction, a reduction in total methane emissions is what is truly needed to have an impact on the climate. The study is part of a broader scientific effort to determine whether federal greenhouse gas legislation and mandates have meaningfully decreased methane emissions, and its verdict so far is sobering: stability in the face of growth is preferable to the increases many scientists feared, but holding the line is not the same as bending the curve downward.

For the growing community of researchers and policymakers focused on methane, the study demonstrates both the power and the promise of atmospheric monitoring from space. By pairing satellite observations with models that trace pollutants back to their sources, scientists can now audit national emissions claims with a degree of independence that was impossible a decade ago. As more satellites come online and inversion techniques grow more refined, the ability to verify whether policies, technologies, and market forces are genuinely reducing methane pollution will only sharpen. For now, the U.S. oil and gas sector presents a paradox worth watching closely: an industry producing more energy than ever, leaking no more methane than before, and yet still releasing roughly ten teragrams of one of the most powerful greenhouse gases into the atmosphere every single year, with the total showing no sign yet of the sustained decline that climate goals demand.

Subject of Research: Satellite-based assessment of U.S. oil and gas methane emissions and the impact of federal climate policy from 2019 to 2024

Article Title: U.S. methane emissions flatline, despite increases in oil and gas production

Article References: U.S. methane emissions flatline, despite increases in oil and gas production. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: methane emissions, oil and gas, greenhouse gases, satellite monitoring, Inflation Reduction Act, EPA regulations, hydraulic fracturing, emissions intensity, TROPOMI, GOSAT, climate policy, Communications Earth & Environment

The study, led by Xuewen Lei and Qingyan Meng of the Aerospace Information Research Institute at the Chinese Academy of Sciences, together with colleagues at the University of Chinese Academy of Sciences, Sun Yat-sen University and the Institute of Geographic Sciences and Natural Resources Research, examined 1,029 cities around the world over the two decades from 2000 to 2019. Rather than treating every urban population as equally exposed and equally fragile, the team built a multidimensional social vulnerability index and folded it into a comparative heat risk assessment. The result is one of the clearest quantitative demonstrations yet that who you are and where you live jointly determine how dangerous a warming city becomes.

To understand why this matters, it helps to unpack how heat risk is actually constructed. In the standard risk framework used across climate science, risk emerges from the interaction of hazard, exposure and vulnerability. The hazard is the heat itself: how hot it gets, how often, and for how long. Exposure describes how many people and assets sit in the path of that hazard. Vulnerability captures how susceptible a population is to harm, encompassing factors such as age structure, health status, income, education, access to infrastructure and the capacity of communities and institutions to prepare for and recover from extreme events. Global assessments have long been able to map hazard and exposure with satellites and population data, but vulnerability is far harder to measure consistently across thousands of cities in dozens of countries, where census categories and survey methodologies differ wildly.

Faced with that data problem, many global studies have taken a shortcut: they assume vulnerability is spatially homogeneous, meaning that a resident of a wealthy European capital and a resident of a rapidly growing South Asian megacity are treated as equally susceptible to the same temperature. The new research set out to test how much that shortcut bends the conclusions. The answer, quantified across two decades of city-level data, is dramatic. When social vulnerability is properly accounted for, the upward trend in urban heat risk in the Global South is nearly five times steeper than the trend in the Global North. Under the traditional homogeneous assumption, that widening North-South divide is underestimated by roughly 65 percent.

That figure deserves a moment of reflection. Sixty-five percent is not a rounding error or a marginal correction at the edge of a confidence interval. It means that the conventional approach, the one embedded in many global risk maps and adaptation planning documents, has been telling a fundamentally softened story about climate inequality. The physical hazard of urban heat is rising everywhere as cities warm under climate change and as the urban heat island effect intensifies local temperatures. But the risk, the actual probability of harm to human lives and livelihoods, is compounding fastest precisely in the places with the fewest resources to cope, and the standard methodology has been largely blind to that compounding.

The findings also complicate a comfortable assumption within the Global North itself. It might be tempting to read the study as a story about a distant South bearing the brunt while wealthy nations watch from the sidelines. The data say otherwise in an important way. When the researchers measured inequality within regions using the Gini index, the standard statistical measure of how unevenly something is distributed, they found that intraregional inequality in long-term heat risk is actually larger within the Global North than the simpler picture would suggest. And here too the homogeneous-vulnerability shortcut takes its toll, underestimating that internal inequality by nearly 15 percent. Wealthy countries contain their own pockets of acute heat vulnerability: elderly residents in poorly insulated housing, low-income neighborhoods with sparse tree canopy and little air conditioning, migrant and marginalized communities concentrated in the hottest, densest districts.

The technical achievement of the study lies in making vulnerability measurable at global scale without sacrificing its multidimensional character. A single proxy, such as income or gross domestic product per capita, cannot capture the texture of social fragility. The multidimensional index assembled by the team aggregates indicators spanning the social, economic and infrastructural conditions that shape a population’s capacity to endure heat. Feeding that index into a risk framework across 1,029 cities and twenty years of observations allowed the researchers to run what is effectively a controlled comparison: the same hazard and exposure data evaluated once under the homogeneous assumption and once under the vulnerability-informed approach. The differences between the two runs are the systematic bias they report.

Why does this bias point in one direction, toward underestimation of inequality, rather than scattering randomly? The logic is structural. Homogeneous vulnerability effectively averages away the very signal that distinguishes a fragile city from a resilient one. In the Global South, where rapid urbanization has outpaced infrastructure, where informal settlements lack cooling and healthcare, and where adaptive capacity is thinnest, true vulnerability sits well above the global average, so flattening it suppresses measured risk. Within the Global North, the same flattening erases the steep gradients between protected and precarious neighborhoods. In both cases the shortcut compresses the distribution of risk, shrinking the measured gaps between the safest and most endangered populations. The bias is therefore not noise; it is a systematic downward pressure on every inequality statistic the field produces.

The implications reach directly into policy. Heat adaptation resources, from early-warning systems and cooling centers to urban greening and building retrofits, are allocated on the basis of risk assessments. If those assessments understate Southern risk by two-thirds relative to the North, funding formulas and international climate finance priorities inherit that distortion. The authors frame their work as a foundation for advancing climate justice in a rapidly warming world, and the phrase is apt: justice arguments in climate negotiations often hinge on quantified evidence of unequal burden, and this study supplies evidence that the burden has been mismeasured in a way that flatters the wealthy world. Correcting the measurement does not itself redistribute anything, but it removes a technical excuse for inaction.

There are also lessons here for the research community about the hidden costs of data scarcity. The homogeneous-vulnerability assumption was never malicious; it was a pragmatic response to the genuine difficulty of harmonizing social data across borders. But this study demonstrates that pragmatic simplifications in risk science are not neutral. They carry directional consequences that can reshape global narratives about who suffers and who is safe. As satellite-derived socioeconomic data, machine-learning-based downscaling and open census archives continue to improve, the excuse for flattening vulnerability weakens. The 1,029-city assessment shows what becomes visible when the flattening is removed: heat risk rising everywhere, rising nearly five times faster in the Global South, and pooling most dangerously in the neighborhoods, North and South, where vulnerability has always been highest. In a century that will be defined by heat, seeing that landscape clearly is the first step toward changing it.

Subject of Research: Global assessment of urban heat risk inequality incorporating multidimensional social vulnerability across 1,029 cities

Article Title: Social vulnerability amplifies global inequality in urban heat risk

Article References: Lei, X., Meng, Q., Zhao, Q., Luo, M., Zhang, L., & Fang, C. (2026). Social vulnerability amplifies global inequality in urban heat risk. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04137-z

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04137-z

Keywords: urban heat risk, social vulnerability, climate inequality, Global South, heat waves, climate justice, Gini index, risk assessment, urbanization, heat adaptation, Communications Earth & Environment, vulnerability index

The core of the problem lies in the shape of the distribution. When researchers measure emission rates from individual pieces of oil and gas infrastructure, they do not find a tidy bell curve centered on a typical value. Instead, they find what statisticians call a right-skewed, heavy-tailed distribution: most sources emit relatively small amounts, but a small fraction of sources, the so-called super-emitters, release enormous quantities of gas. The tail of this distribution is so heavy that a handful of facilities can dominate the total emissions of an entire basin. Daniels and Hammerling set out to probe exactly what this statistical structure implies for sampling, using six United States oil and gas basins as their test cases.

The technical issue is one that statisticians know well but that field campaigns have often underappreciated. When a distribution is heavy-tailed, the sample mean, the average computed from a finite set of measurements, is an unstable estimator of the true population mean. Each individual observation carries enormous potential influence. If a sampling campaign happens to catch one or two very large emitters, the estimated average emissions for the region will be pulled sharply upward. If, by chance, the campaign misses those facilities, the estimate will fall far too low. In a well-behaved distribution, adding more observations steadily narrows the uncertainty around the average. In a heavy-tailed one, the rare extreme values control everything, and convergence can be painfully slow.

Daniels and Hammerling translated this abstract statistical concern into concrete, actionable numbers. For each of the six basins they examined, they computed a minimum sample size, the number of measurements a campaign would need to collect in order to bound the error that sampling variability alone introduces into the estimated average emission rate. In other words, they asked how many facilities must be measured before the random luck of which facilities happen to be included stops dominating the result. The answer, they found, is that very large sample sizes can be necessary. The largest emissions in each basin drive the behavior of the sample, and by extension they drive the sample size requirements, meaning that campaigns hoping to characterize a basin’s average emissions cannot simply assume that a few dozen or a few hundred site visits will suffice.

The direction of the bias matters as much as its magnitude. The study shows that samples will underestimate average emissions if super-emitters are observed below their true frequency in the population, and overestimate them if super-emitters appear above their true frequency. This is a subtle but consequential point for policy. A campaign that happens to miss the biggest leakers will report that a basin is relatively clean, potentially delaying regulatory attention and allowing large volumes of methane to continue escaping unchecked. A campaign that happens to catch an unusual cluster of super-emitters will paint an alarmingly pessimistic picture that may not represent the basin as a whole. Either way, the number itself, however precise it looks on a report cover, may be wrong, and nobody can tell which direction the error runs without understanding the underlying distribution.

Perhaps the most consequential finding of the study is its rejection of the one-size-fits-all approach. Because the characteristics of super-emitters differ between basins, the authors find that a uniform sampling strategy applied across all regions is suboptimal. A basin whose emissions are dominated by a small number of extremely large sources demands a different statistical treatment than a basin where emissions are spread more evenly across many moderate leakers. The minimum sample size that guarantees acceptable error in one region may be badly inadequate in another. The practical implication is that future methane measurement campaigns should be designed basin by basin, with the sampling plan tailored to the statistical fingerprint of the emissions distribution in that specific region rather than copied from a template developed elsewhere.

This work arrives at a moment when the stakes for methane measurement have never been higher. Governments are building methane intensity standards and import rules around measured emission rates, satellite missions are scanning producing regions from orbit, and companies are competing to demonstrate low-emission supply chains to climate-conscious buyers. All of these mechanisms depend on numbers produced by measurement campaigns, and all of them inherit the statistical vulnerabilities that Daniels and Hammerling document. An emissions factor derived from an underpowered sample is not a neutral data point; it propagates into inventories, certification schemes, and regulatory thresholds, where its hidden bias can distort decisions worth billions of dollars and millions of tonnes of avoided emissions.

The study also carries a lesson about the relationship between measurement and modeling. Heavy-tailed distributions do not just complicate fieldwork; they complicate the interpretation of every dataset built from limited observations, including the aircraft surveys, ground-based mobile measurements, and continuous monitoring records that feed national inventories. The authors’ framework, which provides basin-specific minimum sample sizes tied explicitly to the error budget of the average estimate, offers campaign designers a principled way to decide in advance how much data they need, rather than discovering after the fact that their estimates are too noisy to be useful. That kind of prospective design, grounded in the statistics of the emissions themselves, represents a meaningful shift in how the field can approach the problem.

Funding for the research came in part through the Energy Emissions Modeling and Data Lab and through the Colorado Ongoing Basin Emissions project, supported by the Colorado Department of Public Health and Environment, reflecting the growing interest of state agencies in reliable basin-level emissions data. The work was published open access in Communications Earth & Environment, with Daniels now based at Johns Hopkins University. As satellite constellations multiply and methane regulations tighten worldwide, the study’s central message is likely to echo through campaign planning for years to come: the rare, enormous leaks that dominate a basin’s climate footprint also dominate its statistics, and only sampling strategies designed with that heavy tail in mind, tailored to each basin’s own character, can deliver the trustworthy average emission rates on which climate accountability depends.

Subject of Research: Statistical sampling requirements for measuring methane emissions from oil and gas basins

Article Title: Future methane measurement campaigns require basin-specific sampling strategies

Article References: Daniels, W. S., & Hammerling, D. M. (2026). Future methane measurement campaigns require basin-specific sampling strategies. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04089-4

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04089-4

Keywords: methane, oil and gas, super-emitters, heavy-tailed distributions, sampling strategies, emissions measurement, basin-specific, greenhouse gas monitoring, sample size, Communications Earth & Environment, climate mitigation, emissions statistics

Seasonal forecasting sits in an awkward middle ground between weather prediction and climate projection. Weather forecasts lose most of their useful skill after about two weeks, because the atmosphere is chaotic and small errors grow rapidly. Climate projections, meanwhile, look decades ahead and are shaped mainly by greenhouse gas emissions scenarios. In between lies a window of months in which slow variations in the ocean and land surface — patterns that evolve over seasons rather than days — can nudge the atmosphere in predictable ways. The El Niño-Southern Oscillation, the periodic warming and cooling of the tropical Pacific, is the best-known of these memory sources, and it is precisely the kind of signal that a well-designed seasonal model can exploit.

What makes the new work distinctive is the way it dissects where spring solar predictability actually comes from. Rather than treating forecast skill as a single number, the researchers identify two leading sources of solar predictability. The first and dominant component is linked directly to primary El Niño-Southern Oscillation conditions, meaning the canonical state of the tropical Pacific during the season in question. When the Pacific is in a pronounced El Niño or La Niña phase, it reshapes atmospheric circulation patterns far beyond the tropics, altering cloudiness and hence the amount of sunlight reaching solar panels in the American Southwest.

The second component is subtler and, in many respects, more scientifically interesting. It is associated with the diversity of El Niño events themselves — not all El Niños look alike, and their different flavors have different atmospheric consequences — together with variability in the tropical Atlantic. El Niño diversity has become a major topic in climate science precisely because conventional indices can mask important differences between events centered in the eastern versus central Pacific. By separating this secondary component, the study shows that the spatial structure of forecast skill across the United States, and the physical drivers behind it, can be traced to identifiable and interpretable climate phenomena rather than appearing as an opaque statistical byproduct.

The practical implications of that interpretability are considerable. A grid operator who knows that a forecast of above- or below-normal spring sunshine is tied to a specific, monitored pattern in the tropical Pacific has some basis for judging how much confidence to place in it, and for watching whether that pattern is strengthening or weakening as the season approaches. A forecast that is merely a correlation with no physical story behind it offers no such guidance. In this sense, the study provides what the authors describe as a physically interpretable foundation for integrating seasonal forecasts into wind-solar energy planning.

The team did not stop at regional averages. They evaluated their forecasts at the level of individual states, a scale that matters enormously for real-world energy decisions because electricity markets, transmission planning, and renewable portfolio standards are largely organized along state lines. The results show robust solar prediction skill in high-resource states — those with large installed solar capacity and abundant insolation. For states whose economies and grids increasingly hinge on the sun, the finding suggests that seasonal outlooks could move from an academic curiosity toward a genuine operational tool, complementing the day-ahead and week-ahead forecasts that already guide dispatch decisions.

Perhaps the most consequential part of the research concerns what happens when wind and solar resources fluctuate together. Because solar and wind generation are both weather-driven, they can decline simultaneously, producing what energy analysts call energy droughts, or surge together, producing surpluses that stress storage and transmission. The historical co-fluctuations of wind and solar output are not random; they are shaped by the same large-scale climate patterns that govern seasonal averages. The study’s forecast system captures this compound behavior of wind-solar variability, meaning it can in principle anticipate seasons in which the two resources rise and fall in tandem — the situations that pose the greatest risk to a grid increasingly reliant on variable renewables.

Compound risk management has become a central theme in climate adaptation literature, and the energy sector is one of its most demanding arenas. A single-resource shortfall can often be covered by another generator or by storage, but a compound event — a spring in which weak winds and cloudy skies coincide across a broad region — can exhaust those buffers. By demonstrating that a seasonal model can reproduce the historical co-fluctuations associated with such events, the research opens a path toward seasonal-scale warnings of compound energy risk, giving planners months rather than days to arrange reserve capacity, adjust maintenance schedules, or coordinate fuel purchases.

The study arrives at a moment when the stakes for forecast-informed planning are rising quickly. The United States has added solar and wind capacity at a record pace in recent years, and the technical challenges of balancing a weather-dependent grid scale up with every gigawatt installed. Batteries help smooth out hour-to-hour swings, but they are not yet an economical solution to a season-long resource deficit. Hydro resources, which traditionally provide flexible seasonal storage in the western grid, are themselves climate-sensitive. In that context, even a modest seasonal signal — for example, an enhanced likelihood of a cloudy spring in the Southwest during certain Pacific states — carries real economic and engineering value if it can be trusted.

Yang and his colleagues, all based at NOAA’s Geophysical Fluid Dynamics Laboratory in Princeton apart from co-author Colleen McHugh, worked with a forecast system of the kind that underpins operational seasonal prediction worldwide: coupled ocean-atmosphere models initialized from observed conditions and run forward in ensembles, so that the spread among ensemble members provides a measure of forecast uncertainty. The work was supported through base funding from NOAA to the Geophysical Fluid Dynamics Laboratory, and the authors report no competing interests. The article was received in April 2026, accepted in September, and published in open-access form on October 3, 2026.

The broader significance of the paper lies in its framing of renewable energy forecasting as a climate science problem. Much of the current effort in renewable meteorology focuses on short horizons — nowcasting cloud fields, predicting wind ramps over hours, refining day-ahead dispatch models. The new results argue that the seasonal horizon deserves equal attention, and that the tools to fill it already exist. Two decades of investment in El Niño prediction, tropical Atlantic monitoring, and coupled model development have quietly produced a capability that the energy transition now needs.

There are, inevitably, limits to what any seasonal forecast can deliver. Skill varies by region, by season, and by the state of the climate system in a given year; years without a strong Pacific or Atlantic signal will remain difficult to anticipate. The study itself makes clear that predictability is structured, not uniform: it is the two identified components, tied to El Niño conditions and their diversity plus tropical Atlantic variability, that together explain the spatial pattern of skill. That honesty about the boundaries of predictability is part of what makes the work usable — operators can know when a forecast is likely to be informative and when it is likely to be a coin flip.

For the rapidly growing community of grid planners, commodity analysts, and climate scientists now working at the intersection of weather and energy, the message of the study is encouraging: the atmosphere’s slow ocean memory, harnessed by modern seasonal prediction systems, can illuminate spring solar resources in one of the nation’s most important solar regions months in advance, and can capture the joint behavior of wind and sun that determines how risky a given season will be for a renewable-powered grid. As the energy transition accelerates, forecasts of this kind — physically grounded, regionally validated, and transparent about their sources of skill — are likely to become as familiar to grid operators as today’s seven-day weather outlook is to the rest of us.

Subject of Research: Seasonal predictability of spring solar energy resources and compound wind-solar variability in the United States

Article Title: Seasonal predictability of spring solar resources and wind-solar variability across the United States

Article References: Yang, X., Delworth, T. L., Jia, L., Johnson, N. C., McHugh, C. E., Cooke, W. F., & Wittenberg, A. T. (2026). Seasonal predictability of spring solar resources and wind-solar variability across the United States. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04114-6

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04114-6

Keywords: seasonal forecasting, solar energy, wind energy, El Niño-Southern Oscillation, renewable energy grid, energy droughts, tropical Atlantic variability, southwestern United States, climate prediction, compound variability, NOAA Geophysical Fluid Dynamics Laboratory, Communications Earth & Environment

The study, led by Ying Yan, Hamed Sharif, and Ali A. Ameli of the University of British Columbia, rests on an extraordinary volume of evidence. The researchers identified and analyzed approximately 1.7 million runoff-producing events across 4,838 catchments spanning six continents. Each event was classified according to two descriptors that together define its hydro-meteorological character: the type of water input, whether rainfall, snowmelt, or rain falling on snow, and the wetness of the soil before the event began, sorted into dry, moderate, or wet antecedent conditions. That ninefold classification scheme allowed the team to ask, in a standardized way, whether a given basin treats a rainstorm on dry soil the same way it treats snowmelt on saturated ground.

The scale of the computation behind this work is itself a story. Identifying individual runoff-producing events in millions of streamflow and precipitation records is a task far beyond what a desktop workstation can handle, so the bulk of the analyses ran on the Compute Canada network of parallel high-performance computing clusters. The effort was supported by grants to Ameli through the Natural Sciences and Engineering Research Council of Canada’s Discovery Grants program. The result is a dataset that turns a question once explored catchment by catchment, in scattered field campaigns and modeling studies, into a globally quantified phenomenon.

The first major finding concerns the diversity of what the authors call dominant hydro-meteorological event types. For each catchment, the team summarized which combination of water-input type and antecedent soil moisture most frequently produced runoff, doing so separately for the dormant season and the growing season. Rather than converging on a handful of universal regimes, the global catchment population displayed a wide diversity of dominant types. Some basins are, in effect, rain-on-dry-soil systems; others are dominated by snowmelt onto wet ground; still others by rain on moderately moist soils. That heterogeneity alone is a caution against one-size-fits-all hydrology, but it is not the paper’s central surprise.

The central surprise is the pervasiveness of time-variance. The researchers quantified, for every catchment, how much the precipitation-to-streamflow transfer function, the mathematical representation of catchment hydrologic function, varied from event to event. The verdict was stark. In the dormant season, 95.6 percent of catchments showed moderate to strong event-to-event variation in their hydrologic function. In the growing season, that figure rose to 99.0 percent. In other words, virtually every river basin on Earth examined in this study behaves differently from one runoff event to the next, at least to a degree that the authors classify as meaningful.

What makes this result more striking is that the variation is not simply a byproduct of events arriving under obviously different weather. Even catchments that experienced highly similar hydro-meteorological conditions across their events, the same input types striking similarly wet or dry soils, remained functionally time-variant. Something beyond the coarse descriptors of input type and antecedent wetness is modulating how these landscapes convert water into runoff. The study points to one candidate mechanism with particular force: within-catchment spatial heterogeneity in hydro-meteorological conditions. A single basin is rarely uniform. One hillslope may be drenched while another stays dry; snow may linger on shaded aspects while sun-facing slopes shed meltwater days earlier. Because different parts of a catchment are activated under different conditions, the integrated streamflow response at the outlet shifts depending on which portions of the landscape are doing the work during any given event.

The implications ripple outward quickly. The precipitation-streamflow transfer function is not an academic abstraction; it is the backbone of how hydrologists translate meteorological forecasts into flood warnings, how engineers size culverts and reservoirs, and how water managers estimate how much of a season’s precipitation will actually arrive in rivers and aquifers. If that transfer function is stable, a model calibrated on past events can be trusted, within limits, to anticipate future ones. If it is time-variant, as this study suggests it almost universally is, then confidence in flood-risk and water-security assessments, the very applications the authors cite as motivation, is directly limited by how well those shifting dynamics are captured. A forecasting system tuned to wet-season events may misjudge a dry-season storm in the same basin, and a model built on rain-dominated events may falter when a rain-on-snow episode arrives.

The study also establishes a link between variability in function and variability in outcome. Greater time-variance in a catchment’s hydrologic function was associated with greater event-to-event variation in the catchment’s runoff response. That connection matters because runoff response is what communities experience: how fast a river rises, how high it crests, how much water is available downstream. Basins whose internal translation rules fluctuate strongly are also basins whose rivers behave less predictably. Identifying such basins, and understanding what drives their internal heterogeneity, could become a priority for flood-risk mapping and infrastructure design in a warming climate, where rain-on-snow events and abrupt shifts between dry and saturated soil conditions are expected to become more frequent in many regions.

Methodologically, the paper demonstrates the power of treating the planet’s river basins as a single statistical population rather than as a collection of idiosyncratic case studies. By imposing a common event classification, rain, snowmelt, or rain-on-snow crossed with dry, moderate, or wet antecedent soil moisture, and by applying it uniformly across 1.7 million events, the researchers could measure time-variance on a comparable scale everywhere. The seasonal split, analyzing dormant and growing seasons separately, adds another layer of nuance, revealing that functional variability is even more widespread when vegetation is active, a hint that evapotranspiration and plant-driven soil dynamics may deepen the nonstationarity of catchment behavior during the growing season.

The broader message is one of humility and opportunity for hydrology. The assumption that a catchment has a single, learnable personality, a fixed transfer function waiting to be calibrated, appears to be wrong for nearly every basin on Earth. That does not mean prediction is hopeless; it means prediction must embrace variability as the norm rather than the exception. Models may need to represent within-catchment heterogeneity explicitly, and forecasting frameworks may need to condition their parameters on event type and antecedent state rather than assuming a single set of values. For a world facing intensifying storms, shrinking snowpacks, and rising demands on freshwater, knowing that the planet’s river basins rarely behave the same way twice is not a discouraging finding. It is, instead, an accurate map of the challenge ahead, drawn from nearly two million events and nearly five thousand landscapes, and it gives hydrologists a far clearer picture of where and why their forecasts are most likely to bend.

Subject of Research: Time-variance in catchment hydrologic function across global river basins

Article Title: Catchment hydrologic function is widely time-variant

Article References: Yan, Y., Sharif, H., & Ameli, A. A. (2026). Catchment hydrologic function is widely time-variant. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04079-6

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04079-6

Keywords: hydrology, catchments, streamflow, runoff events, soil moisture, snowmelt, rain-on-snow, flood risk, water security, transfer function, global analysis, Communications Earth & Environment

The central variable the team examined is flood peak timing, abbreviated FloPT in the study: the day of the year on which a river’s water level reaches its annual maximum. Hydrologists have long regarded FloPT as a sensitive indicator of how watersheds respond to a warming climate, because the timing of a flood peak integrates the effects of snow accumulation and melt, the seasonal migration of rain-bearing weather systems, and the storage and release of water by soils, wetlands, and reservoirs. If spring arrives earlier, snow-fed rivers should crest earlier. If the rainy season shifts, rain-fed rivers should follow. Yet until now, global assessments of flood peak timing have been severely constrained by the distribution of in-situ discharge gauges, which are dense in North America, Europe, and parts of Asia but sparse or entirely absent across much of Africa, South America, Southeast Asia, and the Arctic. The result has been a lopsided understanding of one of the planet’s most consequential hydrological signals.

The technical breakthrough in the new work lies in the use of so-called virtual stations. Satellite radar altimeters, flying on missions originally conceived for oceanography, emit microwave pulses toward the Earth’s surface and measure the time it takes for the echo to return. Over oceans this yields sea surface height with centimeter precision, but over land the same echoes can be used to estimate the height of a river’s water surface where the satellite ground track crosses a river channel. Each crossing point functions as a virtual gauge, logging water level every time the satellite passes overhead. By stitching together repeated passes over the same river crossings, the researchers constructed time series of water level at thousands of locations worldwide, identified the annual maximum in each year, and derived the day of that maximum to build a global map of flood peak timing. The spatial coverage achieved represents what the authors describe as a dramatic improvement over gauge-based assessments, with particularly large gains in Global South countries where hydrological monitoring infrastructure is thinnest.

The global map that emerges is strikingly heterogeneous. In snowmelt-dominated basins, flood peaks cluster in late spring and early summer, when accumulated winter snowpack melts rapidly under warming temperatures and long daylight. In precipitation-driven regions, by contrast, the timing of the annual peak tracks the local wet season, which can fall at almost any point in the calendar depending on the behavior of monsoons, the Intertropical Convergence Zone, and mid-latitude storm tracks. This contrast between snow-controlled and rain-controlled regimes is not merely descriptive; it matters because the two regimes respond to climate change in fundamentally different ways. Snowmelt systems are governed by the energy balance at the snow surface and are expected to shift earlier as springs warm, while rain-fed systems shift only when the atmospheric circulation delivering their rainfall changes, which can push peak timing in either direction.

When the researchers examined trends over the period from 2008 to 2025, the heterogeneity deepened. Across the virtual stations analyzed, 52.2 percent exhibited earlier flood peak timing, and at the outlets of the fifty largest river basins on Earth, twenty-seven showed earlier peaks. Earlier flood peaks were most pronounced at high latitudes and high elevations, a pattern the study finds consistent with accelerated snowmelt: as the climate warms, snow melts sooner and faster, pushing the annual maximum downstream earlier in the year. This is one of the clearest fingerprints of climate change in the hydrological cycle, and the satellite record now captures it in places where no human has maintained a gauge. The finding matters for water managers in mountain-fed regions, because earlier snowmelt can decouple water availability from agricultural demand and increase the risk of late-summer shortages even when total annual runoff is unchanged.

Not every river is peaking earlier, however. The study identifies delayed flood peaks in several major systems, including the upper Mississippi in North America, the southern Amazon in South America, and the central Congo basin in Africa. In these regions, the observed delays are consistent with shifts in the timing of precipitation maxima, suggesting that changes in atmospheric circulation and rainfall seasonality, rather than snow processes, are controlling the flood rhythm. The upper Mississippi has experienced changing storm tracks and altered precipitation seasonality; the southern Amazon sits in a zone where the timing of the wet season onset is sensitive to both large-scale circulation and land surface feedbacks; and the central Congo basin experiences some of the most complex and poorly monitored rainfall regimes in the tropics. That satellite altimetry can now detect these delays in basins where ground data are scarce underscores the technology’s value as a global observing system for river behavior.

The study also highlights a factor that is often overlooked in purely climatic analyses: human water management. Dams, reservoirs, diversions, and irrigation schemes do not merely change how much water flows down a river; they change when it flows. By storing floodwater during wet periods and releasing it during dry ones, reservoir regulation can flatten seasonal peaks, delay them, or in some cases eliminate the natural annual maximum altogether. The researchers found that abrupt changes in flood peak timing within individual basins are shaped by water management, and that stronger regulation constrains the shifts that would otherwise occur. In other words, in heavily engineered basins, the flood peak that satellites observe is a hybrid signal, part climate and part infrastructure. Disentangling these influences is essential if FloPT is to be used as a climate indicator, and the new global dataset provides the raw material for doing so at unprecedented scale.

The implications extend well beyond hydrology. Flood peak timing governs the synchronization between river flooding and vulnerable human activities: a flood that arrives three weeks earlier may strike before levees are inspected, before crops are harvested, or before emergency systems are staffed. It also governs ecology, since fish migration, floodplain spawning, and the germination of flood-adapted vegetation are all cued to the seasonal pulse of rivers. A world in which flood peaks shift earlier in the Arctic but later in the Congo is a world in which adaptation strategies must be tailored region by region, not applied as a single global template. The pronounced data gaps that have historically hampered such tailoring, particularly across Africa, South America, and Central Asia, are precisely the gaps the satellite approach closes.

There are, of course, limitations inherent in the method. Altimetric virtual stations sample a river only when the satellite passes overhead, which means the true annual maximum can be missed if it occurs between passes, and the record length examined here, 2008 to 2025, is short compared with the multi-decadal archives of many gauge networks. Water level peaks, moreover, are not identical to discharge peaks in rivers where channel geometry changes with stage. Yet the study’s central achievement stands: a globally consistent, observationally grounded map of flood peak timing, with dense coverage in exactly the regions where conventional monitoring has failed. As newer missions with improved orbit repeat cycles come online, the resolution and accuracy of these virtual stations should continue to improve, and the record will lengthen year by year.

What the study ultimately delivers is a new baseline. For the first time, scientists, engineers, and policymakers can see, on a single map, when the world’s rivers crest, where that timing is advancing, where it is lagging, and where human intervention has frozen it in place. The heterogeneity the satellites reveal is itself the message: the hydrological consequences of a changing climate and a managed landscape do not arrive uniformly, and the rivers of the Global South, long invisible to global flood assessments, are now part of the picture. As warming continues to reshuffle the seasonal water cycle, this satellite view of flood peak timing offers an early-warning lens on one of the most consequential and least observed dimensions of planetary change.

Subject of Research: Global flood peak timing and its recent shifts observed by satellite altimetry

Article Title: Satellite altimetry reveals heterogeneity in global flood peak timing and its shifts

Article References: Zhou, X., Chen, P., Fang, G., Jiang, L., Zhao, G., Lin, P., Yin, J., Tang, G., & Zhu, D. Z. (2026). Satellite altimetry reveals heterogeneity in global flood peak timing and its shifts. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04115-5

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04115-5

Keywords: satellite altimetry, flood peak timing, hydrology, climate change, snowmelt, virtual stations, river discharge, Global South, water management, precipitation seasonality, Communications Earth & Environment, Satellite

Marine heatwaves, defined as periods when sea temperatures exceed a seasonally variable threshold for at least five consecutive days, have been growing in both frequency and intensity around the world as the climate warms. The most severe events, categorized on a scale that runs from I to IV, represent temperature extremes so far outside the historical norm that they have virtually no precedent in the local record. The June 2023 event studied by the team reached Category IV status, the most extreme classification, making it a natural laboratory for understanding what happens to the base of the marine food web when the ocean overheats.

The setting was a seasonally stratified shelf sea, an environment common across the temperate latitudes where warming surface waters sit atop colder, denser deep water, separated by a sharp transition known as the thermocline. This layered structure fundamentally changes how nutrients, light, and plankton interact. In spring, strong mixing delivers nutrients to the sunlit surface, fueling the famous spring bloom. By early summer, stratification locks those nutrients away from the surface, and phytoplankton become concentrated in a subsurface chlorophyll maximum, a hidden layer of elevated algal biomass that thrives near the thermocline where light still penetrates and nutrients remain accessible. Satellite ocean color sensors, which measure the light scattered by chlorophyll at the very surface, are effectively blind to this layer.

The research team, led by Charlotte A. J. Williams of the National Oceanography Centre in Liverpool, deployed an autonomous ocean glider to profile the water column repeatedly through the heatwave. Gliders are torpedo-shaped robots that alter their buoyancy to dive and rise in sawtooth patterns, collecting high-resolution measurements of temperature, salinity, and chlorophyll fluorescence as they go. This vertical dimension of observation proved essential. Surface chlorophyll, the quantity that satellites would detect, rose rapidly from less than 1 milligram per cubic meter to more than 5 milligrams per cubic meter, briefly pushing concentrations beyond the climatological range defined by two standard deviations above and below the long-term mean by as much as 40 percent. Yet this dramatic surface excursion was short-lived, a fleeting pulse rather than a lasting shift.

The subsurface story was entirely different. Within the subsurface chlorophyll maximum, concentrations that would normally sit at typical post-bloom values of 1 to 2 milligrams per cubic meter climbed to more than 3 milligrams per cubic meter, and during episodic peaks they exceeded 9 milligrams per cubic meter, a several-fold intensification of the hidden algal layer. Unlike the surface spike, this subsurface enhancement persisted, sustaining elevated biomass over the course of the event. When integrated over the entire water column, the total chlorophyll inventory reached 140 milligrams per square meter, a depth-integrated measure that captures the full standing stock of phytoplankton and revealed that the heatwave had substantially increased the total amount of algal life the sea could support, not merely shuffled it around vertically.

Understanding why the heatwave produced these extremes requires grappling with the interplay of physical and biological processes. The authors found that the bottom mixed layer, the cold water hugging the seafloor, warmed at an accelerated rate during the event, and that horizontal temperature gradients across the region strengthened. These signals are consistent with a possible influence of horizontal transport processes, meaning that the heatwave may have been associated with lateral movement of water masses, potentially advecting warm water and possibly associated nutrient or biomass signatures into the region. Elevated surface irradiance, the greater light availability that can accompany the calm, clear conditions often linked to heatwave weather patterns, may also have contributed to the enhanced phytoplankton growth. The observations cannot definitively separate these mechanisms, but both point to a plausible explanation in which physical forcing during extreme warming amplifies biological productivity in ways that standard theory might not predict.

The implications ripple outward through the marine ecosystem. Phytoplankton are the foundation of nearly all marine food webs, converting sunlight and dissolved nutrients into the organic matter that sustains everything from copepods to fish to seabirds. A sustained, several-fold increase in subsurface chlorophyll during a heatwave means that the vertical distribution of food available to grazing zooplankton, fish larvae, and other organisms could shift substantially. In stratified seas, many animals forage at or near the thermocline precisely because that is where the food is. Altering the intensity and extent of the subsurface chlorophyll maximum could therefore restructure foraging behavior, growth rates, and ultimately the productivity of commercially important species. The research was conducted as part of the PELAgIO project within the Ecological Consequences of Offshore Wind programme, reflecting growing interest in how climate extremes and human infrastructure interact in shelf sea ecosystems.

There is also a sobering message here for how we monitor the ocean. Much of what we know about global phytoplankton trends comes from satellite ocean color imagery, which samples only the uppermost meters of the sea. If heatwave-driven changes concentrate in the subsurface, as this study shows they can, then satellite-based assessments would record a brief surface anomaly and miss the sustained ecological response below. The depth-integrated chlorophyll increase to 140 milligrams per square meter would be largely invisible to a satellite pass. Only platforms capable of repeated vertical profiling, such as gliders, Argo floats equipped with biological sensors, or dedicated shipboard sampling, can capture these subsurface dynamics. As marine heatwaves become more common, the case for investing in vertically resolved observing systems grows correspondingly stronger.

The findings also complicate our understanding of what marine heatwaves do to marine productivity. A common assumption holds that warm stratified waters should depress phytoplankton growth by tightening stratification and cutting off nutrient supply to the sunlit zone. The observations from this Category IV event run counter to that expectation in important ways, showing rapid surface enhancement and, more significantly, sustained subsurface intensification. The researchers suggest that horizontal transport processes, capable of moving water properties laterally across the shelf, may be part of the explanation, and they caution that the combined influence of enhanced irradiance and advective effects cannot be cleanly disentangled from the available data. This honesty about mechanism is itself valuable: it flags precisely which processes future studies, and future models, must resolve if we are to forecast how shelf sea ecosystems will fare under continued warming.

Shelf seas punch far above their weight in the global carbon cycle and in the fisheries that hundreds of millions of people depend upon, so understanding their response to climate extremes is far from an academic exercise. The 2023 heatwave observations demonstrate that the most dramatic ecological responses to ocean warming in these seas may occur out of sight, below the surface, sustained over timescales long enough to matter for the food web. As temperatures continue to climb and events of this severity grow more frequent, the hidden layers of the ocean are emerging as a critical frontier for climate science, and the gliders that probe them may prove to be among the most important instruments in the modern oceanographer’s toolkit. The study, published open access in Communications Earth & Environment, stands as a reminder that in a warming ocean, what we see at the surface is only the beginning of the story.

Subject of Research: Subsurface chlorophyll response of a seasonally stratified shelf sea to a Category IV marine heatwave observed by an autonomous ocean glider

Article Title: Chlorophyll extremes during a surface marine heatwave in a seasonally stratified shelf sea

Article References: Williams, C. A. J., Scott, B. E., Rippeth, T. P., Jacobs, Z. L., Wihsgott, J. U., Palmer, M. R., O’Hara Murray, R., & Hopkins, J. E. (2026). Chlorophyll extremes during a surface marine heatwave in a seasonally stratified shelf sea. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04118-2

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04118-2

Keywords: marine heatwave, chlorophyll, phytoplankton, shelf sea, ocean glider, seasonal stratification, subsurface chlorophyll maximum, thermocline, ocean warming, satellite ocean color, marine ecosystem, Communications Earth & Environment

Ground-level ozone is not emitted directly by fires. Instead, it is a secondary pollutant, formed when reactive gases produced by combustion react chemically in the presence of sunlight. In the lower atmosphere, ozone is harmful to human health and, crucially, interferes with the physiology of plants. When ozone enters leaf tissue through the same microscopic pores that trees use to absorb carbon dioxide, it damages cells and impairs photosynthesis. For a forest already stressed by drought and fire, this additional burden means that the trees that survive a blaze are less able to resume their role as carbon absorbers in the months and years that follow. The result is a double blow to the climate: fires release carbon dioxide directly when biomass burns, and the ozone they generate suppresses the ability of the remaining forest to capture and store that gas.

The research team quantified this effect using nearly three decades of observations and a global vegetation model, tracking how ozone damage evolved between 1997 and 2024 alongside patterns of fire activity and drought. Their analysis shows that the impact of fire-driven ozone is strongest during major droughts, when hot, dry conditions simultaneously fuel more fires and leave vegetation more vulnerable to pollution damage. Alarmingly, three of the most extreme Amazon droughts of the past three decades — in 1997/98, 2015/16 and 2023/24 — all occurred during El Niño events, the warm phase of a natural, recurring global climate cycle. While El Niño is not caused by human activity, climate change means it now sits atop rising baseline temperatures, making it more likely to push global temperatures to record highs and intensify extreme weather.

Lead author Dr Flossie Brown, of ETH Zurich, emphasized that the problem extends well beyond the flames themselves. Forest fires do not just release carbon dioxide when they burn, she explained; they also contribute to the rise in ground-level ozone, a pollutant that damages the leaves of surviving trees and reduces their ability to keep absorbing carbon afterwards. According to the study, this hidden effect is equivalent to around a quarter of the carbon released by the fires themselves — a significant loss to the Amazon’s carbon budget that had not previously been considered. In other words, every hectare of burned forest inflicts a further, largely unmeasured penalty on the intact forest around it, eroding the region’s capacity to recover the carbon that has been lost.

The drought years examined in the study each left a distinct signature in the data, but the most recent event stands out starkly. Ozone damage during the 2023/24 drought nearly doubled compared with the average of the previous decade, a jump that coincided with record fire activity across the basin. Dr Brown warned that, given a comparably strong El Niño appears to be developing again this year, the researchers are concerned that history could repeat itself. Forecasters have indicated that the emerging El Niño has the potential to become one of the most intense on record, raising the prospect of another major spike in this hidden carbon loss. If drought conditions and fire activity mirror those of 2024, the ozone-driven suppression of photosynthesis could once again strip a substantial fraction of the Amazon’s remaining carbon uptake capacity at precisely the moment it is most needed.

The mechanics of this damage are rooted in the chemistry of the tropical atmosphere. Wildfires release a cocktail of precursor gases, including nitrogen oxides and volatile organic compounds, which react under the intense sunlight of the tropics to produce ozone near the ground. Unlike the stratospheric ozone layer that shields the Earth from ultraviolet radiation, ground-level ozone is a pollutant. In plants, it enters through stomata — the tiny pores on leaf surfaces that regulate gas exchange — and triggers oxidative stress that damages cellular machinery. Stressed trees may close their stomata to limit ozone uptake, but doing so also restricts the influx of carbon dioxide, directly reducing photosynthesis. Over large areas and extended periods, this physiological impairment translates into measurably lower carbon uptake across the forest, compounding the losses from drought stress and fire mortality.

What makes the new findings particularly consequential is that the ozone effect operates on surviving forest rather than burned land. Conventional carbon accounting for wildfires focuses on the immediate emissions from combustion and the slower losses from tree death and decomposition. The ozone penalty, by contrast, is invisible in satellite images of smoke and scorched earth, yet it accumulates across vast swathes of intact forest downwind of burning areas. By combining long-term observational records with a global vegetation model, the researchers were able to isolate this signal and express it in carbon budget terms, showing that the atmosphere suffers significantly more damage from each Amazon fire season than direct emissions alone would suggest.

There is, however, a clear and actionable message embedded in the research. Almost all fires in the Amazon are started by people, whether through deliberate land clearance or through agricultural burning that escapes into standing forest. The worst ozone damage is concentrated in the so-called Arc of Deforestation, the frontier zone where agricultural land is expanding into the rainforest. Professor Stephen Sitch, of the University of Exeter, stressed that this means the extra ozone damage described in the study is largely preventable. Reducing deforestation and forest degradation would cut direct fire emissions, but the study shows it would also protect the Amazon from this secondary, invisible source of carbon loss. The same policy lever, in other words, addresses both problems at once.

Co-author Dr Alexander Cheesman, of James Cook University, argued that the findings demonstrate why air pollution, land-clearing and climate change cannot be treated as separate problems when determining the future of the Amazon. These impacts interact and need to be considered together, he said, but that interaction also means solutions may deliver multiple benefits. Policies that tackle deforestation and degradation address both the carbon dioxide released directly by fires and the ozone pollution quietly eroding what is left of the forest’s ability to soak that carbon back up. In a region where the margin between sink and source grows thinner with each drought, such co-benefits could prove decisive.

As the developing El Niño raises the specter of another record fire season, the study serves as a timely reminder that the true climate cost of Amazon fires is greater than the smoke plumes suggest. The research was funded by the Natural Environment Research Council, partly via the GW4+ Doctoral Training Partnership, and the underlying paper is entitled Fire-derived ozone and intensifying droughts undermine the Amazon carbon sink. Its central conclusion is stark: every fire season in the Amazon now carries a hidden surcharge, paid not in flames but in the diminished photosynthesis of the trees that survive. Protecting the world’s largest rainforest, the authors make clear, requires confronting not only the fires themselves but the polluted air they leave behind.

Subject of Research: Fire-derived ground-level ozone pollution and drought reducing carbon uptake in the Amazon rainforest

Article Title: Wildfire ozone pollution weakening Amazon's ability to absorb carbon

Article References: Wildfire ozone pollution weakening Amazon's ability to absorb carbon. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Amazon rainforest, ozone pollution, wildfires, carbon sink, El Niño, drought, deforestation, climate change, photosynthesis, Communications Earth & Environment, Arc of Deforestation, ground-level ozone

The numbers behind that conclusion are sobering. The researchers found that 10 percent of the Amazon basin, an area larger than 700,000 square kilometres and bigger than Afghanistan, has seen extreme temperatures during the dry season rise by at least 0.75 degrees Celsius per decade, accumulating to more than 3.22 degrees Celsius since 1981. That is a pace of change far exceeding the basin-wide average warming of 0.21 degrees Celsius per decade, which sits roughly in line with the global average. In other words, the climate extremes that matter most for ecosystems and people are intensifying much faster than conventional assessments of average temperature suggest, and they are concentrating in places that standard analyses have overlooked.

The methodological innovation at the heart of the study explains why. The team divided the Amazon into grid cells of 11 kilometres and combined satellite observations with data from local weather stations, allowing them to identify the dry season for every individual part of the biome. This matters because the Amazon spans the equator: areas north of it have a dry season at a different time of year from the south, meaning earlier assessments focused on the southern dry season systematically missed what was happening elsewhere. On top of this, the researchers used a new measure of water deficit that accounts for the effect of temperature on water loss, capturing how hotter air drives faster evaporation and deeper physiological stress in forests.

Crucially, the team assessed climate change in two distinct ways. The first, the ‘central tendency’, is the measure most commonly used to date and emphasises average rates of change in temperature and water deficit across all years. The second, the ‘extreme tendency’, emphasises the most exceptional years, providing a more accurate indication of how the hottest and driest periods are evolving. Professor Jos Barlow of Lancaster University, lead author of the report, explained the rationale. “We are most interested in things when they are at their hottest and driest as that is when the most harm can be caused by high temperatures,” he said. “While this has been assessed in the Southern Amazon, which shares a largely similar dry season, it has never been assessed across the whole of the Amazon, which includes regions north of the equator which have a different dry season period.”

The contrast between the two measures produced the study’s most consequential insight. When average temperature changes are considered, the Southern Amazon, which has suffered extensive deforestation and land-use change, is confirmed as the fastest warming region. But when extremes are examined, the central north Amazon emerges as the area of most rapid change. “The rates of change in climate extremes are much higher than the rates of change of average climate in the Amazon, and the most affected regions are also different for extremes and average climate,” said Dr Nathália Carvalho, post-doctoral research associate at the Lancaster Environment Centre. “This is important because we show that Amazonia’s climate is not changing uniformly. This information will be crucial when planning and implementing climate change adaptation strategies.”

Perhaps the most politically significant implication is what the geography of change rules out. The area experiencing the fastest growth in extreme temperatures lies far from the arc of deforestation, the band of forest loss along the basin’s southern and eastern edges. That means local drivers such as deforestation and land-use change cannot explain the pattern. “Given the area that is experiencing the fastest growing in extreme temperature is far from the arc of deforestation, these rapid rises cannot be explained by local changes such as deforestation and land-use changes,” Professor Barlow said. “It’s showing how the Amazon is being affected by global climate change. It’s the world’s emissions that are responsible.” For a biome often discussed in terms of national land-use policy, the finding reframes the Amazon’s fate as a genuinely global responsibility.

The biological consequences of intensifying extremes are already visible across the region. Recent exceptionally hot or dry periods have driven extensive forest fires, large-scale animal and tree deaths, and threats to human health from heat and air pollution. Recent studies cited by the research team document the first observed mass death of mammals in the Amazon, with sloths and other animals found dead on the forest floor or hanging from understorey trees, alongside reductions in the size of bird populations and measurable changes to bird lifespans, appearance and behaviour. Megafires linked to extreme heat and drought have generated air pollution that reached the Amazonian city of Manaus, while rivers that shrank during droughts disrupted the transport networks and water supplies on which forest communities depend.

The human dimension is equally stark. Dr Joice Ferreira of the Brazilian Agricultural Research Corporation, Embrapa, highlighted how extremes are eroding rural livelihoods. “Extreme climate events are impacting local livelihoods in many ways, affecting key products like açaí,” she said. “This removes the safety net that forests provide, threatening food security and weakening their role in a growing socio-bioeconomy. Most concerning, it could derail public policies currently being designed and implemented by Brazilian and state governments to drive positive transformation in the region, such as forest restoration plans. This scenario demands global action to halt climate change in the name of climate justice.” For communities whose economies and diets are woven into the forest, the loss of predictable seasonal rhythms is not an abstraction but a direct threat to food security and to emerging sustainable bioeconomies.

The timing of the findings adds urgency. With the El Niño of 2026 expected to be the largest in living memory according to the UK Met Office, the Amazon may face extremely high temperatures and drought just two years after the last major drought of 2024, leaving little time for forests, wildlife and people to recover. Scientists involved in the study warn that if the rapid increases in extreme climate events continue, the region could be pushed past critical thresholds, with cascading consequences for biodiversity, carbon storage and regional rainfall. Professor Barlow argued that adaptation measures are urgently required, including preventing factors that amplify climate risks such as deforestation, strengthening capacity to fight forest fires, and supporting local people when the rivers they rely on for navigation dry up, especially in a year with the arrival of what he described as a super El Niño.

Mike Barrett, chief scientific adviser at WWF-UK, framed the study as a call for action at both global and regional scales. “The rapidly increasing climate extremes revealed in this study highlight the urgent need for global action on climate change,” he said. “However, the new regions of risk also demonstrate the need to support other measures, including an end to deforestation and support for measures such as the Tropical Forest Forever Facility if we are to avoid critical tipping points and environmental collapse.” The study, titled ‘Rapid increase of climate extremes reveals new areas of concern in Amazonia’, also released interactive maps showing rates of change in temperature, vapour pressure deficit and precipitation across the basin, giving policymakers and researchers a tool to target adaptation where extremes are intensifying fastest. What the research makes unmistakably clear is that the Amazon’s climate is not changing uniformly, that its most exceptional years are deteriorating far faster than its averages, and that the heart of the world’s largest rainforest, once assumed to be resilient, is now squarely in the crosshairs of global warming.

Subject of Research: Rapid growth of temperature and water-stress extremes across the Amazon basin

Article Title: As El Niño looms, study finds rapid growth in climate extremes are hitting an unexpected region of the Amazon hardest

Article References: As El Niño looms, study finds rapid growth in climate extremes are hitting an unexpected region of the Amazon hardest. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Amazon, climate extremes, El Niño, drought, deforestation, forest fires, water deficit, indigenous territories, biodiversity, Communications Earth & Environment, Lancaster University, climate adaptation

The study, published in Communications Earth & Environment under the title ‘Subdued surface expression of deep cave collapse’, combined detailed mapping, geophysical surveys, existing cave records and sediment analysis to build a case that is as much about method as it is about discovery. Lead author Dr Matej Lipar, who conducted the work as an Adjunct Research Fellow in Curtin’s School of Earth and Planetary Sciences and is now at the Anton Melik Geographical Institute at the Research Centre of the Slovenian Academy of Sciences and Arts (ZRC SAZU), explained that the features are deceptively ordinary in appearance. From the surface, he noted, they can look remarkably like shallow valleys or drainage channels, yet the evidence shows they have a fundamentally different origin. Instead of being cut from above by running water, they are the end product of sagging ground above caverns dissolved deep within the limestone.

The scale of the features is striking. The trenches range from several kilometres to more than 20 kilometres in length and are generally between 100 and 500 metres wide. Yet their depth is modest: less than nine metres. On a plain as immense and flat as the Nullarbor, that vertical expression is nearly invisible to anyone standing on it, and even conventional imagery struggles to reveal the pattern. The researchers found that exaggerated digital models of the terrain, in which vertical relief is artificially amplified, made the trenches dramatically easier to see and identify. This technique of terrain exaggeration, long used by geomorphologists to tease out faint topographic signals, proved decisive in revealing the full extent of a phenomenon that had been hiding in plain sight across one of the world’s largest karst regions.

What convinced the team that water was not the sculptor was the absence of the usual signatures of fluvial erosion. Typical valleys on Earth, even dry ones, carry the imprint of the streams that formed them: connected drainage networks, channels that converge downstream, sediment deposits sorted by flowing water, and terraces left behind as flows waxed and waned. The Nullarbor trenches show none of this. As Dr Lipar observed, the trenches lack connected streams or any other indication that water once moved through them. In their place, geophysical surveys detected deep underground cavities beneath the surface depressions, and several of the trenches aligned directly with known caves and documented areas of ground collapse. The correlation between surface expression and subsurface voids provided the physical link the team needed to reinterpret the trenches as collapse features rather than channels.

The mechanism the researchers describe is one of slow, progressive failure. In karst landscapes, slightly acidic groundwater dissolves limestone along fractures and bedding planes, opening caverns that can grow to enormous dimensions over millions of years. The Nullarbor Plain, a former seabed of Miocene-age limestone lifted clear of the ocean and exposed to the air, is one of the classic karst terrains of the world, honeycombed with caves that in places extend far below the surface. When a cave roof is thick and strong, the cavern can persist indefinitely. But over geological time, roofs weaken. Support pillars thin, fractures propagate, and chambers begin to fail from the top down. Each small collapse deposits rubble on the cave floor and transfers stress upward through the rock column. Eventually, the cumulative sagging of the overlying material propagates all the way to the land surface, producing a shallow, broad depression rather than a dramatic sinkhole.

That progressive character is written into the geography of the trenches themselves. The team identified a clear spatial progression: in the west of the study area, the features are obvious cave-connected collapse structures, where the rock cover above the caverns is thinner and failure has broken through more completely. Moving eastward, the trenches become wider and more subtle, reflecting caverns buried beneath thicker sequences of rock where collapse has deformed the surface gently rather than rupturing it. This west-to-east gradient, the researchers argue, demonstrates how cave collapse can reach the surface at different stages depending on the thickness and strength of the intervening rock. It effectively turns the Nullarbor into a natural laboratory in which the full life cycle of cave collapse, from intact cavern to subdued surface trench, can be read across the landscape.

Co-author Associate Professor Milo Barham, from the Curtin Frontier Institute for Geoscience Solutions and the School of Earth and Planetary Sciences, emphasised that the Nullarbor’s peculiar qualities make it an ideal place to learn this lesson. Cave systems, he noted, are not always obvious from the surface, but the dry and stable landscape of the Nullarbor strips away much of the noise that obscures subtle landscape characteristics elsewhere. In humid, vegetated, actively eroding terrain, collapse depressions are quickly modified by soil creep, vegetation, slope processes and fluvial overprinting, making their origin difficult to disentangle. On the Nullarbor, where erosion rates are extraordinarily low and the surface has been preserved with remarkable fidelity, the faint signatures of deep collapse survive intact, offering a clean set of indicators that can be applied to far messier landscapes.

The implications extend well beyond southern Australia. Barham pointed out that the findings provide a useful set of indicators for identifying hidden cave systems elsewhere, including on other planets such as Mars. Planetary scientists have long known that Mars hosts candidate caves: collapse pits, skylights and elongated depressions traceable to lava tubes and possible groundwater-carved caverns, imaged from orbit by spacecraft instrumentation. Because orbital data are often the only evidence available, and because the resolution of that data can make subtle relief hard to interpret, recognising subdued surface expressions of deep collapse could substantially expand the inventory of identifiable subsurface voids on the Red Planet. The Nullarbor, with its aridity, stability and faint but legible collapse features, serves as a terrestrial analogue for exactly the kind of terrain where such signatures might be sought on Mars and other planetary surfaces.

The stakes of that search are considerable. Caves on Earth are far more than geological curiosities. They preserve evidence of past environments, from fossil-bearing sediments to mineral deposits and climate archives locked in speleothems, making them invaluable records of how landscapes and climates have changed over millions of years. They also matter in practical terms: Barham noted that caves influence engineering decisions and access to clean drinking water, since karst aquifers supply water to large populations and their unpredictable voids pose hazards for construction and infrastructure. On other planets, potential caves could provide protected subsurface environments relevant to the search for evidence of extraterrestrial life, shielding any biosignatures from radiation and harsh surface conditions, or act as natural shelters and bases for future astronauts. Knowing where to look for them, and how to read their faint surface traces, is therefore a prerequisite for much of that future work.

The study was supported by the Slovenian Research and Innovation Agency and involved researchers from The University of Western Australia, La Trobe University, the University of Ljubljana and The University of Queensland, alongside the Curtin team. Its broader message is a reminder of how much can remain hidden beneath even the most familiar-looking ground. The Nullarbor appears, as Dr Lipar described it, to be a flat, endless plain, yet exaggerated digital terrain models and geophysical probing reveal kilometres-long scars of a hidden underworld slowly caving in. For geomorphologists, the work adds a new diagnostic framework: elongated, shallow, drainage-free trenches in dry karst terrain should no longer be assumed to be valleys, but read instead as the quiet surface record of deep caves in the long process of collapse. For planetary science, it offers a template for finding sheltered subsurface spaces on worlds where no explorer has yet set foot.

Subject of Research: Surface expression of deep cave collapse in the karst landscape of the Nullarbor Plain

Article Title: Hidden caves beneath the Nullarbor revealed by subtle surface

Article References: Hidden caves beneath the Nullarbor revealed by subtle surface. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Nullarbor Plain, karst, cave collapse, geomorphology, digital terrain modelling, geophysical surveys, limestone caves, Curtin University, Mars analogue, sinkholes, Communications Earth & Environment, planetary science