The Ciénaga Grande de Santa Marta, located in the Department of Magdalena, forms the Estuarine Delta System of the Magdalena River and extends to the Caribbean Sea. Its ecosystem assets include the largest mangroves in the Colombian Caribbean, continental wet areas, coastal lagoons, forests, agricultural and transformed land types. The site supports fisheries and agriculture and provides carbon storage, habitat and other services to local communities. It also carries a series of overlapping conservation designations, including a flora and fauna sanctuary, a biosphere reserve, an important bird area, the Salamanca Island Park and Ramsar status. The Ramsar designation dates to 1998.

The wetland’s condition depends on the interaction between freshwater and seawater throughout the year. This exchange shapes water salinity, while changes in river flow alter the salinity of mangrove soils and influence both vegetation and fisheries. Diversion of water from rivers descending from the Sierra Nevada de Santa Marta for agriculture, together with construction of the Barranquilla–Ciénaga and Palermo–Sitio Nuevo roads, has altered exchange inlets and reduced connectivity between the Magdalena River and the lagoon complex. An integral environmental recovery program initiated by INVEMAR in the 1990s included dredging a five-channel network to restore water exchanges among the Magdalena River, lagoon bodies and the Caribbean Sea. Monitoring of the resulting hydrological regime continues, with hydro-sedimentological observation beginning in 2017.

These pressures complicate an ecosystem already affected by climatic variability. Strong and very strong El Niño events in 2015 and 2016 were associated in the study with reduced rainfall in the Colombian Caribbean, increased mangrove-soil salinity and hydrological stress. In 2017, a Ramsar advisory mission found strong changes in the wetland’s ecological characteristics associated with water-balance loss and human intervention, leading to its inclusion in the Montreux Record. The new study combined environmental and socioeconomic data into a spatial account intended to show how changes in ecosystem extent and condition affect the supply of services and the associated economic value.

For the extent account, researchers compared two CORINE Land Cover layers mapped at a scale of 1:100,000, representing 2012 and 2018. They standardized the land-cover classifications, calculated geodesic areas and used spatial intersections to construct a transition matrix showing opening extent, gains, losses and closing extent. Pastures, continental wet areas and mangrove forests recorded the largest losses during 2012–2018, while permanent crops, heterogeneous agricultural areas and areas with herbaceous or shrub vegetation recorded the largest gains. Mangroves, continental wet areas and pastures mainly transitioned into agricultural or transformed-cover classes. The analysis identified where losses occurred but could not attribute each gain or loss to a specific natural event or human action.

Condition accounts were possible only for mangroves and coastal lagoons and covered 2017–2019 because of data availability. The framework classified condition variables under abiotic, biotic and landscape characteristics. Mangrove indicators included basal area, seedling and propagule density, interstitial salinity, bird species richness and change in extent related to water. Coastal-lagoon indicators included dissolved oxygen, total suspended solids, surface salinity and fish species richness. Reference levels drawn from monitoring reports, regulatory criteria, bibliographic sources and observed salinity ranges were used to rescale variables and construct aggregate condition indices.

The two monitored ecosystem types showed different trends. Mangrove condition had a net positive change from 2017 to 2019 because abiotic values rose as interstitial salinity declined, biotic values rose with greater bird richness and more seedlings and propagules, and landscape values improved as mangrove area expanded. Basal area decreased during the period, showing that recovery was not uniform across every measured characteristic. Coastal lagoons recorded a net negative change: dissolved oxygen declined, surface salinity increased and fish species richness fell. The contrasting aggregates demonstrate how condition accounting can distinguish environmental improvement in mangrove forests from deterioration in adjacent lagoon waters.

Mangrove extent increased by 3,503 hectares during 2017–2019, equivalent to a reported recovery of 6.87% relative to the 51,150 hectares recorded in 1956. The researchers associated this increase with freshwater inflows through dredged channels connected to the Magdalena River and with the absence of El Niño-related events during part of the accounting period. Bird richness also increased, with 98 species recorded in 2019. The list included the northern screamer, sapphire-bellied hummingbird and bronzed cowbird, together with numerous migratory species. These observations describe improvement within the selected indicators and period; they do not establish that every component of the lagoon complex recovered.

Fishing-resource data showed how environmental variation appeared in a service used by communities. SIPEIN records showed total artisanal catch ranging from 4,617 to 6,035 tonnes per year between 2015 and 2019, a net difference of 721 tonnes per year between the opening and closing years. Fish contributed the largest catches, followed by crustaceans. Mollusc catches were not collected in 2018–2019 because of logistical problems, so the reported total underestimates those resources in those years. Catch fell sharply in 2016, coinciding with the highest salinity records in two decades, and subsequently recovered as salinity declined and the composition of the fishery shifted among estuarine, marine and freshwater species. The account therefore documents an association between salinity, climate variability and recorded catches rather than isolating the contribution of any one factor.

The climate-regulation account focused on mangrove carbon. Aboveground carbon was estimated from tree diameter and biomass relationships, while belowground estimates were drawn from measurements covering the upper metre of soil. Carbon stocks were valued using Colombia’s carbon tax rate, set at USD 5 per tonne of carbon dioxide in 2017 with annual adjustment. Aboveground carbon content declined across the principal mangrove types over 2015–2019, leaving total mangrove carbon 16.5% lower in 2019 than in 2015. Most of the decline occurred between 2015 and 2017, when mangrove loss, hydrological stress, desiccation and charcoal burning were associated with carbon emissions rather than sequestration. Physical carbon stocks rose during 2018 and 2019, but their monetary value declined as the Colombian peso depreciated against the dollar. Soil-carbon estimates are incomplete because the reference measurements covered only one metre, while mangrove carbon reservoirs extend deeper.

The monetary asset account placed the value of mangrove carbon stocks at USD 68.3 million in 2015 and USD 55.13 million in 2019. Annual wild-fish supplies from mangroves and coastal lagoons were converted to asset values using a net-present-value method with a 100-year asset life and a 3.5% social discount rate. The combined mangrove and coastal-lagoon asset estimate was USD 105.71 million in 2015 and USD 97.27 million in 2019. The resulting difference of USD 21.61 million comprised USD 13.17 million in mangrove losses and USD 8.44 million in losses for the combined coastal-lagoon and mangrove category. These are accounting estimates, not observed losses of cash or conventional market assets. They provide a way to place ecosystem assets and service flows on the same statistical framework as economic activity.

The pilot also exposes important constraints. Catch is recorded at four landing places and distributed across the wetland, rather than assigned to the specific mangroves, lagoons or marine areas that produce it. This prevents precise attribution of fishing benefits within an interconnected coastal landscape. The condition accounts do not include all six classes in the SEEA EA condition typology, and the land-cover transition analysis cannot determine whether individual changes resulted from El Niño, farming, infrastructure or another pressure. Fishers’ income also cannot be inferred from physical catch alone because market prices, price elasticity, consumer preferences and pre-sales arrangements affect the revenue received. Even with those limitations, the account establishes a baseline for monitoring the extent, condition and service flows of a Ramsar wetland and offers Colombia a spatial framework for integrating ecosystem information into environmental statistics, biodiversity reporting and economic planning.

Subject of Research: Pilot ecosystem accounting of Colombia’s Ciénaga Grande de Santa Marta Ramsar Site

Article Title: Accounting of marine and coastal ecosystems at the Ramsar Site, Estuarine Delta System of the Magdalena River, Ciénaga Grande de Santa Marta, Colombia

Article References: Gomez Cardona, C., Moreno, J., Contreras, A., Sanchez-Nuñez, D., Arciniegas Moreno, N., Guerrero, D., Viloria Maestre, E., & Lopez Navarro, J. (2023). Accounting of marine and coastal ecosystems at the Ramsar Site, Estuarine Delta System of the Magdalena River, Ciénaga Grande de Santa Marta, Colombia. One Ecosystem, 8, Article e98852. https://doi.org/10.3897/oneeco.8.e98852

Image Credits: AI Generated

DOI: 10.3897/oneeco.8.e98852

Keywords: Ciénaga Grande de Santa Marta, ecosystem accounting, SEEA EA, mangrove carbon, coastal lagoons, artisanal fisheries, wetland condition, natural capital, El Niño, Ramsar Site, Accounting, marine

The study, led by researchers analyzing nearly four decades of weather station records, satellite imagery and ocean indices, set out to answer a deceptively simple question: when a local climate shifts, how much of that shift belongs to the planet’s natural cycles, and how much belongs to us? To do this, the team contrasted two twenty-year windows, using a single weather station in central Tepic with continuous data from 1980 to 2018 and only 2.6 percent missing readings. They standardized monthly temperature and precipitation anomalies and correlated them with the multivariate El Niño index, a composite measure built from sea-level pressure, winds, sea surface temperature and cloudiness over the tropical Pacific. They then layered on a Bayesian network analysis, a probabilistic technique that estimates the chance of a climatic outcome given an ENSO phase, even when no strict cause-and-effect relationship exists.

The temperature signal was unambiguous. Average temperature climbed from 21.9 degrees Celsius in the historical period to 22.9 degrees in the recent one. Maximum temperatures rose by about 0.8 degrees, but the most dramatic change came at night: minimum temperatures jumped by roughly 1.3 degrees, and during the autumn and winter months of October through January, the increase exceeded 2 degrees. Rising nighttime minimums are a classic fingerprint of urbanization, because asphalt and concrete absorb heat all day and release it slowly after dark. They are also among the most dangerous manifestations of warming for human health, depriving bodies of the overnight recovery window during heat waves and straining the cardiovascular systems of the elderly and children.

Precipitation told a more turbulent story. The annual total barely moved, hovering near 1,130 to 1,160 millimeters across both periods, but the seasonal rhythm shifted sharply. Summer rainfall declined by between 2 and 6 percent, while autumn and winter rains surged by 13 to 20 percent. That combination, drier summers and wetter autumns, is a recipe for both water stress and flooding, and Tepic is poorly equipped for the latter. The city’s drainage infrastructure is more than fifty years old, its natural watercourses have been obstructed by construction, and buildings have spread into flood-prone zones. The researchers warn that increasingly intense autumn storms will overwhelm sewers and urban rivers, a problem they trace directly to decades of unplanned growth.

The ENSO analysis revealed something unexpected: the Pacific’s grip on Tepic’s climate is not static, and it is moving in opposite directions for temperature and rain. El Niño’s influence on temperature variation doubled, from 10 percent in the historical period to 20 percent in the recent one, with warm Niño events now reliably associated with temperature increases and cool Niña events with decreases. The correlation between the ocean index and minimum temperature flipped entirely, from an inverse relationship of minus 10 percent to a positive one of 19 percent. In winter and spring months, the probability that a Niño event would raise minimum temperatures leapt from 8 percent historically to 34 percent in the current period. Meanwhile, ENSO’s influence on precipitation weakened, falling from 17 percent to 8 percent, yet the anomalies it produces grew more extreme, with the amplitude of wet and dry swings widening in the recent record.

Those shifting probabilities matter for forecasting. During summer El Niño events, the probability of reduced rainfall doubled from 10 percent to 20 percent, and the phenomenon’s seasonal footprint contracted from July through September to June through August, heightening the risk of drought precisely when crops and reservoirs need water most. In winter, Niña events now carry a 33 percent probability of precipitation decrease, up from 24 percent, threatening the severe droughts that historically struck between March and May. On the wet side, autumn El Niño events still bring torrential rains, though with diminished probability, 14 percent versus 31 percent historically. The Bayesian analysis also showed anomaly ranges stretching from severely dry to extremely wet conditions, a sign that when ENSO does act on Tepic’s rain, it acts harder.

To measure the human hand directly, the team turned to satellites. They processed thermal infrared imagery from Landsat 5, 7 and 8 for March of 1986, 2000 and 2018, converting raw radiance into surface temperature through standard brightness-temperature transformations calibrated across the different sensors. The picture that emerged was of a city cooking itself. In 1986, surface temperatures across Tepic ranged from 20.1 to 36.9 degrees Celsius. By 2000 the maximum had climbed to 43.9 degrees, and by 2018 it reached 45.3 degrees, roughly 8 degrees hotter than the historical ceiling. The heat island itself, defined as the zone of very high surface temperatures, covered 9.2 percent of the city in 1986, shrank in relative terms to 6.8 percent in 2000 and 6.1 percent in 2018, but in absolute area it exploded: the 2018 footprint amounted to 345.5 hectares against 217.1 hectares in 2000, a 62.8 percent expansion.

The geography of that expansion tells its own story. In 2000 the heat island was concentrated in the historic center. By 2018, scorching zones had appeared in the southeast, precisely where the city’s fastest growth occurred. The urban footprint doubled between the mid-1980s and 2015, and grew another 43.6 percent between 2000 and 2018 alone, much of it at the expense of the forests surrounding the city, including the Sierra de San Juan, a state-level biosphere reserve that supplies critical ecosystem services. The region lost about 30 percent of its adjacent forest cover over the study period. Vegetation absorbs thermal radiation and releases moisture, creating a microclimate buffer against planetary-scale phenomena; strip it away, the researchers argue, and the city loses its natural shield, leaving local temperatures more exposed to swings driven by the Pacific.

That loss of buffering may explain the study’s most provocative finding: the apparent link between heat island growth and ENSO’s doubled influence on temperature. The relationship remains descriptive rather than statistically proven, and the authors are careful to say so. They relied on a single weather station, made only three satellite observations across four decades, and could not perform a formal statistical correlation of heat island area against climate variability. They call for annual monitoring, in-situ temperature measurements of different urban surfaces, an inventory of green spaces, and the inclusion of future climate scenarios. They also suggest examining other ocean-atmosphere drivers, from the Pacific Decadal Oscillation to the North American monsoon and hurricanes, that could be shaping Tepic’s climate alongside ENSO.

Even with those caveats, the implications reach far beyond one mid-sized Mexican city. Tepic’s population of nearly half a million in its metropolitan area, hosting over 40 percent of the state of Nayarit’s people, makes it a template for hundreds of cities across the developing world where urban sprawl is outpacing planning. The consequences documented here, higher electricity demand and greenhouse emissions, water stress, intensified heat waves, flooding from aging drainage, and risks to public health ranging from viral disease to psychological strain, are the standard costs of unplanned growth. The researchers’ prescription is blunt: expand meteorological monitoring networks, invest in climate action research, and treat urban planning as an essential instrument for building climate-resilient cities. As global temperatures rise and the Pacific keeps oscillating, the cities that protect their forests and green space, the study suggests, will be the ones best armored against both.

Subject of Research: The influence of ENSO and the urban heat island on temperature and precipitation variation in Tepic, western Mexico

Article Title: Influence of ENSO and the urban heat island on climate variation in a growing city of the western Mexico

Article References: Nájera González, O., Nájera González, A., Marceleño Flores, S., & Flores Vilchez, F. (2024). Influence of ENSO and the urban heat island on climate variation in a growing city of the western Mexico. One Ecosystem, 9, Article e125302. https://doi.org/10.3897/oneeco.9.e125302

Image Credits: AI Generated

DOI: 10.3897/oneeco.9.e125302

Keywords: ENSO, El Niño, urban heat island, climate change, Tepic, Mexico, urbanization, deforestation, Landsat, precipitation, Bayesian networks, urban planning

The stakes of this upgrade are considerable. Wildfires are not merely local disasters; they are a planetary carbon pump whose output fluctuates wildly from year to year. In extreme fire years, such as those that scorched Canada, Australia, and Siberia in recent memory, fires can emit carbon on a scale comparable to the annual fossil fuel emissions of major industrial economies. Yet the scientific community has often had to wait for carefully vetted datasets to catch up before quantifying those events. The new system, called the Global Fire Emissions Database near real time extension, or GFED-NRT, changes that calculus fundamentally, offering daily updates that can be compared directly against the historical record.

At its core, the system builds on the same architecture that made the original GFED the gold standard for fire emissions accounting. The approach begins with satellite observations of burned area, derived from instruments that detect the characteristic spectral signatures of freshly burned landscapes. Those observations are then combined with estimates of fuel loads, the amount of vegetation available to burn, and combustion completeness, the fraction of that fuel actually consumed by flames. Multiplying these factors together yields the mass of biomass burned, which is then converted into emissions of carbon dioxide, carbon monoxide, methane, particulate matter, and dozens of other trace gases and aerosols using standard emission factors for each vegetation type.

What makes the near real time version possible is a shift in the satellite data stream. Rather than relying on the moderate resolution burned area products that require extensive post-processing, GFED-NRT draws on the Visible Infrared Imaging Radiometer Suite, or VIIRS, aboard the Suomi NPP and NOAA-20 satellites. VIIRS provides daily global coverage with a spatial resolution fine enough to capture the patchwork of fire activity across savannas, forests, and croplands. The researchers calibrated their algorithm against the historical GFED record, ensuring that the new daily estimates are consistent with the multi-decadal archive that scientists have used for carbon budgeting, atmospheric modeling, and policy analysis.

The calibration process was far from trivial. Fire emissions depend on subtle interactions between weather, vegetation moisture, and ignition patterns, and a naive translation of satellite fire detections into emissions could introduce systematic biases. The team therefore developed a statistical framework that ingests VIIRS active fire observations and converts them into estimates of burned area and fuel consumption, using machine learning and physical relationships tuned to reproduce the historical GFED estimates as closely as possible. They validated the system against independent datasets, including burned area maps derived from Landsat imagery and atmospheric measurements of carbon monoxide from satellites, confirming that the near real time product tracks the true evolution of fire seasons with remarkable fidelity.

The payoff is already visible in the study’s analysis of recent fire years. The researchers used GFED-NRT to examine the extraordinary fire seasons of 2023 and 2024, periods that saw unprecedented burning in the boreal forests of Canada and in tropical ecosystems across South America, Africa, and Southeast Asia. The system captured the explosive onset of the Canadian fires in the spring of 2023, the relentless summer emissions that followed, and the anomalous fire activity in regions where climate change is lengthening the fire season. By placing these events in the context of the full GFED archive stretching back to 2000, the researchers could quantify just how unusual these years were, and how the frequency of extreme fire seasons appears to be increasing as the planet warms.

One of the most striking findings concerns the interplay between climate variability and fire activity. The team showed that the transition from La Niña to El Niño conditions in 2023 reshaped fire patterns across the tropics, suppressing fires in some regions while intensifying them in others. In Southeast Asia, the onset of drought conditions associated with El Niño drove a surge in peatland and forest fires, releasing not only carbon dioxide but also methane and particulate matter with serious consequences for regional air quality. In the Amazon, the combination of drought and land use pressures pushed fire emissions to levels not seen in decades. GFED-NRT tracked these shifts in real time, offering a preview of how climate oscillations translate into fire behavior on the ground.

Beyond its scientific value, the system has immediate practical applications. Fire emissions estimates feed directly into air quality forecasts, which public health agencies use to warn communities about smoke exposure. They inform carbon accounting under international climate agreements, where countries need to report emissions from land use change and fires. They support atmospheric transport models that trace the movement of smoke across hemispheres, and they underpin studies of how fire-driven aerosols affect clouds, rainfall, and radiative balance. With daily updates, these applications can now operate with a timeliness that was previously impossible, and the researchers have made the data freely available to the scientific community and the public.

The researchers are candid about the system’s limitations. Near real time estimates necessarily rely on assumptions about fuel loads and combustion that cannot be verified until more detailed post-fire assessments are complete, and the conversion of active fire detections into burned area introduces uncertainties that are larger than those in the retrospective GFED product. The team emphasizes that GFED-NRT is designed as a complement to, not a replacement for, the full GFED archive, and they plan to refine the system as new satellite data and improved vegetation maps become available. Future versions may incorporate higher resolution burned area products, better representations of peatland combustion, and more sophisticated treatment of the small fires that dominate emissions in many agricultural landscapes.

Nevertheless, the arrival of a near real time fire emissions monitor marks a turning point in humanity’s ability to understand and respond to a rapidly changing fire regime. As climate change lengthens fire seasons, dries out forests, and expands the geographic reach of burning, the need for timely, accurate, and transparent emissions data has never been greater. GFED-NRT provides exactly that, transforming a decades-long scientific effort into a living system that watches the planet burn and reports what it sees, day by day, in numbers that scientists, policymakers, and the public can trust.

Subject of Research: Near real time satellite monitoring of global wildfire emissions

Article Title: Tracking recent extremes and interannual variability of global fire emissions using a near-real-time extension to the Global Fire Emissions Database

Article References: Chen, Y., van der Werf, G. R., Mu, M., van Wees, D., Hall, J. V., Giglio, L., Vernooij, R., Morton, D. C., Xu, L., Liu, T., Scholten, R. C., Coffield, S. R., Follette-Cook, M. B., Ott, L., & Randerson, J. T. (2026). Tracking recent extremes and interannual variability of global fire emissions using a near-real-time extension to the Global Fire Emissions Database. Earth System Science Data, 18(10), 7535-7555. https://doi.org/10.5194/essd-18-7535-2026

Image Credits: AI Generated

DOI: 10.5194/essd-18-7535-2026

Keywords: wildfire emissions, GFED, satellite monitoring, carbon cycle, climate change, VIIRS, fire seasons, air quality, El Nino, boreal forests, Tracking, recent

“Rapid destabilization is now a diagnosis rather than a warning for the future,” said William Ripple, distinguished professor emeritus in the Oregon State University College of Forestry and one of the report’s co-lead authors. Ripple emphasized that while the accelerating expansion of renewable energy and advances in battery storage are genuinely encouraging, they represent only one component of the transformation required to stabilize the climate system. In his assessment, a more resilient and sustainable future depends heavily on deep cuts in greenhouse gas emissions, effective adaptation measures and the protection of ecosystems that regulate the planet’s energy balance. The purpose of the annual exercise, he explained, is to monitor the Earth’s “vital signs” in the way a physician tracks a patient, and to encourage global leaders and policymakers to abandon the business-as-usual approach that has persisted despite decades of evidence linking human activities to dangerous climate change.

The numbers underpinning that diagnosis are stark. Atmospheric carbon dioxide now stands at 428 parts per million, a concentration higher than at any point in the last two million years and roughly fifty percent above pre-industrial levels of the late eighteenth century. July 2026 was the hottest month ever recorded in the contiguous United States, and global ocean surface temperatures also reached an all-time high that month, a double record that reflects the enormous amount of heat the climate system is now absorbing. The rate of global warming itself appears to be accelerating: the report calculates that the warming trend nearly doubled, from approximately 0.19 degrees Celsius per decade between 1970 and 2010 to about 0.36 degrees per decade in the years since. That acceleration means that projections based on earlier decades may understate the pace of change currently underway.

The cryosphere, the frozen portion of the Earth system, is showing some of the most alarming signals. Glacier thickness and the total ice mass of Greenland are both at all-time lows in the observational record. In recent decades, the Greenland ice sheet has experienced intense melting episodes that have driven a sixfold increase in summer meltwater volume, water that ultimately flows into the North Atlantic and contributes to global sea level rise. Wildfire, too, has become both a symptom and a driver of the crisis. Global tree cover loss due to fires reached 10.8 million hectares in 2025, an area roughly the size of Tennessee and the third-highest level on record. Because burning forests release the carbon stored in their biomass, increasing wildfire activity now feeds back into the very warming that makes fires more likely, a loop the authors flag as particularly concerning.

On the emissions side of the ledger, the report documents that fossil fuel consumption rose by 0.9 percent in 2025, with oil up 1.0 percent, coal up 0.4 percent and gas up 1.3 percent, each reaching a record high. Annual energy-related carbon dioxide emissions surpassed 41 gigatonnes for the first time in history. These figures underscore a central tension in the report: even as clean energy expands at unprecedented speed, the absolute scale of fossil fuel use continues to grow, meaning the transition is additive rather than substitutive so far. The authors warn that a very strong El Niño expected to develop this fall could add substantially to global warming in the coming months, putting 2026 on track to rank among the hottest years ever recorded.

Yet the report is not uniformly grim, and its authors deliberately frame the findings as challenges paired with opportunities. Low-carbon sources now provide about 43 percent of global electricity, a share that has led the researchers to suggest the world may be witnessing the emergence of what they call the “Age of Electricity.” “That is a reason for hope, but fossil fuel use and emissions are still at record levels, so the transition needs to accelerate dramatically,” said Christopher Wolf, a former Oregon State postdoctoral researcher and the report’s other co-lead author, now a scientist with Corvallis-based Terrestrial Ecosystems Research Associates. On the land side, the rate of deforestation in the Brazilian Amazon has declined for four consecutive years, offering evidence that policy interventions can bend curves, while solar and wind energy consumption has increased by roughly 18 percent, a growth rate that outpaces most other components of the global energy system.

The authors stress that cutting emissions, while essential, is no longer sufficient on its own. Because a certain amount of further warming is already locked in, they call for rapidly deployable adaptation measures, including urban cooling strategies, the restoration of wetlands and mangroves that buffer coastlines and store carbon, improved wildfire preparedness, water conservation programs, distributed solar energy installations and more resilient food systems. This dual-track logic, mitigation and adaptation pursued in parallel, reflects a growing recognition in the scientific community that some climate impacts can no longer be avoided and must instead be managed. The report notes that extreme heat, floods, droughts, storms and wildfires are no longer rare events, and that climate change is increasingly interacting with global biodiversity loss, freshwater stress, food insecurity, pathogens and geopolitical instability, amplifying risks across interconnected human and natural systems.

The distribution of those risks is deeply unequal. The authors point out that communities least responsible for historical emissions, particularly in the Global South and among small island nations, are already bearing disproportionately severe consequences, a justice dimension that they argue must inform both international negotiations and domestic policy. They also acknowledge the development realities facing emerging economies, where climate mitigation must be pursued alongside pressing objectives such as expanding access to affordable and reliable energy. “Many climate solutions are already technically feasible and increasingly cost competitive, but because climate change is driven by interconnected energy, economic, ecological and social systems, truly meaningful progress will likely depend on integrated responses across multiple sectors and scales,” Ripple said. In other words, no single technology or policy lever can do the job alone; the response must match the systemic character of the problem.

To help decision-makers and the public grapple with that complexity, the report highlights improved climate tools, citing as an example the En-ROADS Climate Solutions Simulator, an interactive model that allows users to see how combinations of policies, technologies and societal changes could influence future warming, energy systems, economic outcomes and climate risks. Such tools, the authors suggest, can make the trade-offs and synergies among different interventions tangible in ways that static projections cannot. The collaboration behind the report included Jacob Bukoski of the Oregon State University College of Forestry, Jillian Gregg of Terrestrial Ecosystems Research Associates, Michael Mann of the University of Pennsylvania, Johan Rockström of the Potsdam Institute for Climate Impact Research, Unai Pascual of the Basque Centre for Climate Change, Chi Xu of Nanjing University, Sarah E. Perkins-Kirkpatrick of the Australian National University, Thomas M. Newsome of the University of Sydney and Anjal Prakash of FLAME University, with partial funding from the CO2 Foundation.

“Achieving the necessary emissions reductions and societal shifts at the speed and scale required depends on deep transformations in energy generation, consumption patterns, food systems, economic priorities and governance structures, in ways that also promote biodiversity protection,” Wolf said. “Without those transformations, we won’t be able to stabilize the climate system and reduce the risk of crossing dangerous Earth system tipping points.” The 2026 report thus lands on a deliberately double-edged message: the vital signs of the planet are the worst ever recorded, yet the tools, technologies and policy momentum needed to change course are more available than at any point in the industrial era. Whether the coming years tip the balance toward stabilization or further destabilization, the authors conclude, will depend on how quickly societies convert encouraging signals into decisive, systemic action.

Subject of Research: The 2026 annual state of the climate report assessing Earth system vital signs, climate destabilization and emerging solutions

Article Title: Report: Earth’s climate system increasingly unstable, but signs of positive change emerge

Article References: Report: Earth’s climate system increasingly unstable, but signs of positive change emerge. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: climate change, state of the climate report, Oregon State University, BioScience, carbon dioxide, renewable energy, Greenland ice sheet, wildfires, tipping points, El Niño, adaptation, fossil fuels

The tropical Pacific is arguably the most influential single region in the global climate system. Its year-to-year swings, governed by the El Niño–Southern Oscillation, or ENSO, alternate between El Niño, La Niña and neutral phases, and these fluctuations ripple outward across the planet. El Niño events in particular can reshape rainfall, drought, flooding, heatwaves and bushfire conditions in Australia and far beyond, affecting agriculture, water security and ecosystems on multiple continents. Understanding how this pivotal oscillation will behave under continued warming, and crucially after emissions stop, is therefore essential for anticipating the climate risks that future generations will face.

To probe that question, the research team first analysed simulations from nine Earth system models, establishing how the tropical Pacific’s average state changes as the planet warms. They then turned to the Australian ACCESS Earth System Model to run a more demanding experiment: examining how the region evolves for a full 1,000 years after emissions are halted at different points within the 21st century. This two-stage approach allowed the researchers to separate the immediate response of the atmosphere and ocean surface from the much slower adjustments occurring deep in the ocean, where the majority of the excess heat trapped by greenhouse gases is stored.

The simulations revealed a consistent pattern across the models. As warming proceeds, the tropical Pacific’s average conditions shift towards a more El Niño-like state. This does not mean the Pacific becomes permanently locked into an El Niño event; rather, the characteristic temperature contrast between the warm western Pacific and the cooler eastern Pacific weakens. During a typical El Niño, warm surface water extends farther east across the basin, the upwelling of cold, nutrient-rich water along the eastern equatorial Pacific weakens, and major rainfall patterns migrate. The modelling suggests that this configuration could increasingly become part of the Pacific’s background climate rather than an occasional episodic departure from it.

What makes the new findings particularly striking is their persistence. The researchers found that stopping emissions would not immediately return the tropical Pacific to its pre-industrial condition. Instead, the altered ocean temperatures, winds and rainfall patterns could endure for centuries after the last tonne of carbon dioxide is released. The reason lies in the sheer thermal inertia of the ocean. Lead author Aditya Sengupta of the University of Melbourne explained that the atmosphere and the ocean surface can adjust relatively quickly, while the deep ocean absorbs and releases heat over hundreds or even thousands of years, giving the ocean a long memory of previous greenhouse-gas emissions.

This ocean memory has profound implications for how irreversible certain aspects of climate change really are. Even once humanity reaches net zero and the surface stops warming, the Southern Ocean and the deep ocean continue to take up and redistribute heat, sustaining altered circulation patterns in the tropical Pacific long after the atmospheric driver has been removed. According to the study, key aspects of tropical Pacific climate change could therefore be effectively irreversible on timescales of centuries. The deep ocean acts simultaneously as a buffer that slows surface warming and as a reservoir that locks in regional changes once they have been established.

The study’s central practical conclusion is that timing matters enormously. The longer emissions continue, the more heat accumulates within the climate system, and the greater the risk of committing the tropical Pacific to a substantially altered state. Reaching net zero earlier limits the magnitude of the changes occurring within the ocean and reduces the burden passed on to future generations. In other words, while some degree of long-lasting change may already be unavoidable, the difference between reaching net zero in the coming decades versus late in the century could determine whether the El Niño-like shift remains modest or becomes a defining feature of the Pacific for centuries to come.

Co-author Associate Professor Andrew King of the University of Melbourne emphasised that the results reinforce the value of rapid emissions reductions. The research team reported finding clear benefits from reducing emissions quickly, noting that earlier net zero limits the changes occurring within the ocean and reduces the risk of leaving future generations with a substantially altered tropical Pacific. Sengupta added that the findings make it imperative for rapid emissions cuts and long-term climate adaptation planning to go hand in hand, even after net zero is achieved, because the changes already set in motion will not vanish the moment emissions stop.

The work was a collaboration between researchers at the University of Melbourne, the Australian National University, the University of New South Wales, Monash University, the University of Reading and Australia’s national science agency, CSIRO, and was based on computational simulation and modelling rather than new observations. For a region whose variability shapes droughts, floods and heatwaves across the globe, the study reframes the stakes of climate policy. Stopping emissions remains essential, but the deep ocean’s centuries-long memory means that every additional year of delay deepens the commitment to a changed Pacific, strengthening the scientific case for cutting emissions as quickly as possible while preparing adaptation strategies for the changes that are already underway.

Subject of Research: Long-term response of the tropical Pacific and El Niño–Southern Oscillation to net zero carbon dioxide emissions

Article Title: Reaching net zero sooner limits long-lasting El Niño-like shift in the Pacific

Article References: Reaching net zero sooner limits long-lasting El Niño-like shift in the Pacific. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: El Niño, ENSO, tropical Pacific, net zero, climate modelling, ocean thermal inertia, deep ocean warming, Communications Earth and Environment, University of Melbourne, emissions reductions, climate adaptation, Earth system models

The central finding is a shift toward stronger storms near the islands, even as considerable uncertainty remains about whether the total number of tropical cyclones in the region will increase. Lead author Nicole Murray, who conducted the work as a postdoctoral researcher in the SOEST Department of Atmospheric Sciences and is now a scientist at Los Alamos National Laboratory, framed the stakes in terms of the current hurricane season, noting that storms do not need to make a conventional landfall to disrupt communities, damage infrastructure and produce dangerous flooding and wind impacts. That distinction between landfall and impact is critical for Hawaiʻi, where a cyclone passing within a couple hundred miles can still drench mountainous terrain, generate life-threatening surf along exposed coasts and topple power lines across entire counties. The study therefore treats hazard not as a single number but as a multidimensional picture of frequency, intensity, track, duration, forward speed and landfall patterns.

To overcome the fundamental limitation of a sparse observational record, the team turned to the Columbia Tropical Cyclone Hazard computer model, developed by study co-authors Chia-Ying Lee and Suzana Camargo of Columbia University. The approach is a form of statistical-dynamical downscaling: the model ingests the atmospheric and oceanic conditions simulated by seven different global climate models and generates thousands of years’ worth of synthetic tropical cyclones consistent with those large-scale environments. Because the synthetic catalog contains vastly more storms than any observational dataset could, it allows researchers to estimate the probabilities of rare events, such as a strong hurricane passing directly over Oʻahu, with far better statistical confidence than the historical record alone would permit. The technique also makes it possible to compare present-day hazard with mid-century and late-century hazard under identical analytical assumptions, isolating the climate signal from the noise of natural variability.

The analysis focused on storms passing within 300 nautical miles of the Hawaiian Islands, a buffer that captures the majority of cyclones capable of producing significant impacts even without a direct landfall. For each synthetic storm, the researchers tracked its frequency, intensity, trajectory, duration, translational speed and landfall behavior under historical, mid-century and late-century climate conditions. The future simulations employ a high-emissions scenario, a deliberate choice designed to reveal how tropical cyclone activity responds to substantial warming rather than to bracket the full range of possible policy outcomes. Crucially, the team also separated storms occurring during El Niño years from those during La Niña years, creating parallel catalogs that allowed them to test whether the well-documented relationship between the El Niño-Southern Oscillation and Hawaiʻi’s hurricane hazard might itself be altered by climate change.

That ENSO relationship has long been one of the most useful tools in the seasonal forecasting toolkit for the central Pacific. Historically, El Niño conditions, characterized by warmer-than-average sea surface temperatures in the eastern and central equatorial Pacific, tend to favor stronger and more frequent tropical cyclones near Hawaiʻi compared with La Niña. The mechanisms are well understood: El Niño shifts the patterns of vertical wind shear, low-level vorticity and deep convection in ways that are generally more hospitable to cyclone development and intensification in the subtropical latitudes where the islands sit. Emergency managers and meteorologists have relied on this teleconnection to anticipate which seasons warrant heightened vigilance, making any erosion of that relationship a matter of practical consequence rather than academic curiosity.

The late-century simulations reveal exactly such an erosion. In the warmer future climate, the differences between El Niño and La Niña become less pronounced, particularly for tropical cyclone wind hazard around the islands, while the spatial pattern of storm tracks also changes. Under El Niño conditions in the late-century simulations, tropical cyclone tracks shift to the southwest of the Hawaiian Islands relative to the tracks seen under La Niña conditions, altering which communities and coastlines lie in the most exposed corridors. Co-author Christina Karamperidou, a professor of atmospheric sciences at SOEST, emphasized the broader implication: climate change may alter not only the overall tropical cyclone hazard facing Hawaiʻi, but also how climate patterns such as El Niño and La Niña relate to when and where that hazard is greatest. In other words, the diagnostic tools that forecasters and planners have used to translate Pacific-wide climate signals into local risk may need recalibration as the background climate warms.

The study’s framing of risk extends well beyond the question of how many hurricanes make landfall, a metric that has always understated the threat to the islands. Storms passing near Hawaiʻi can produce damaging winds, extreme rainfall, flooding, landslides, high surf and cascading secondary hazards that ripple through interconnected systems of power, water, transportation and communication. The 2026 hurricane season offered a vivid demonstration of this impact-without-landfall dynamic. Hurricane Lala passed just south of the islands in August and produced severe flooding and damaging winds across the state, while Hurricane Lowell approached from the south in September before passing west of the islands, generating damaging winds, heavy rainfall and flooding with particularly severe impacts on Kauaʻi. Neither storm followed the classic trajectory of a landfalling hurricane, yet both delivered consequences that communities felt directly and, in some cases, painfully.

Methodologically, the study exemplifies a growing trend in climate hazard research: rather than relying on global climate models to resolve tropical cyclones directly, which remains computationally challenging at the resolutions typically used for century-scale projections, researchers translate the large-scale climate projections into storm-level statistics through specialized hazard models. This allows the team to generate return periods, the average intervals between events of a given severity, for wind and other hazards at the level of individual counties, information that is directly usable in engineering design, insurance pricing and emergency planning. It also allows the researchers to distinguish robust signals, those that appear consistently across the seven underlying climate models, from areas of model disagreement, which is essential for honest communication of uncertainty.

That commitment to communicating both risk and uncertainty runs through the team’s account of the work. As Murray explained, the research is designed to determine which parts of the projections are robust, understand why models disagree, and communicate both the risks and the uncertainties accurately to those who need them. For emergency managers, infrastructure planners and community leaders in Hawaiʻi, the practical takeaway is twofold. First, the hazard profile of the islands appears to be shifting toward stronger storms, which raises the ceiling on worst-case scenarios even if average storm counts remain uncertain. Second, the traditional El Niño rule of thumb for anticipating active seasons may become a less reliable guide, meaning that preparedness planning cannot lean as heavily on seasonal climate outlooks in a warmer future.

The research also connects the abstract dynamics of the tropical Pacific, the shifting sea surface temperatures, wind shear patterns and convective envelopes that define ENSO, to the concrete hazards that reach the doorsteps of communities across the island chain. In a state where a single storm can isolate neighborhoods, contaminate water systems and strain emergency response capacity across multiple islands at once, translating global climate model output into county-level storm statistics is more than an academic exercise. The study, published under the title describing tropical cyclone activity in the vicinity of Hawaiʻi in present and future climates, offers a template for how rare-but-consequential hazards can be assessed in data-sparse regions, and it delivers a clear message: the islands’ hurricane future will not simply be a warmer version of the past, and the climate patterns that once signaled danger may speak in a different accent as the century progresses.

Subject of Research: Projected changes in tropical cyclone activity and its relationship with the El Niño-Southern Oscillation near Hawaiʻi under climate warming

Article Title: Warmer climate could reshape hurricane risk and its relationship with El Niño around Hawaiʻi

Article References: Warmer climate could reshape hurricane risk and its relationship with El Niño around Hawaiʻi. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: tropical cyclones, Hawaiʻi, El Niño, La Niña, climate change, hurricane risk, synthetic storm modeling, wind hazard, storm tracks, ENSO, Pacific climate, hazard projection

The research team, led by Aditya Sengupta of the University of Melbourne, combined two complementary modelling frameworks. The first was the Zero Emissions Commitment Model Intercomparison Project, or ZECMIP, in which nine Earth system models branch off a transient warming simulation at the point where cumulative emissions reach 1000 petagrams of carbon and then run with emissions set to zero. The second was a set of bespoke, millennial-length simulations with the Australian Earth system model ACCESS-ESM1-5, in which emissions cease at seven different points between 2030 and 2060 and the climate is then allowed to evolve freely for 1000 years. Together, these experiments let the researchers ask a question that standard climate scenarios rarely address: what happens to the tropical Pacific after humanity stops emitting?

The answer is sobering. Under transient warming, nearly all models agree that the zonal temperature gradient of the equatorial Pacific—the difference in sea surface temperature between the warm western Pacific and the cooler eastern Pacific—weakens, producing a mean state that resembles a permanent El Niño. In the ZECMIP simulations, this weakened gradient persists for decades to centuries after emissions cease, with no meaningful recovery. The global mean surface temperature stabilises at roughly 2 degrees Celsius above pre-industrial levels, but the Pacific does not bounce back to its pre-industrial configuration.

The consequences for extreme weather are equally persistent. The researchers used a metric linking the meridional temperature gradient across the eastern equatorial Pacific to local rainfall, a well-established proxy for extreme El Niño events of the kind seen in 1997/98 and 2015/16. In the unforced pre-industrial control runs, only about 9.8 percent of El Niño events in the ZECMIP ensemble were extreme. During transient warming, that share more than doubled to about 21.3 percent—and after emissions stopped, it remained at 20.25 percent. In the longer ACCESS-ESM1-5 runs, the baseline was even lower, at 1.73 percent of El Niño events, yet in the late-cessation B2060 simulation, extreme events still accounted for 26.3 percent of all El Niño events centuries after net zero was achieved. Crucially, the changes scale with warming level: the later emissions cease, the larger and longer-lived the shift.

Not every aspect of El Niño–Southern Oscillation behaviour behaves so coherently. Changes in ENSO amplitude—the typical strength of the oscillation—turn out to be non-monotonic and strongly model-dependent. Seven of the nine ZECMIP models showed amplification during transient warming, and the ensemble median stayed elevated after cessation, but the 30-year rolling time series wobbled considerably, dominated by multi-decadal internal variability. Only when the researchers applied a 100-year averaging window in the ACCESS simulations did a sustained elevation of ENSO amplitude emerge clearly from the noise, particularly in the late-cessation pathway. The forced signal, in other words, is real but only reveals itself on multi-centennial timescales.

The mechanism behind this persistence lies in the uneven way the ocean absorbs and releases heat. After emissions stop, the surface of the Northern Hemisphere stabilises or even cools, but the Southern Ocean and the deep ocean continue to warm for a very long time. This delayed warming shrinks the temperature difference between the hemispheres, which shifts the tropical convergence zones—the ITCZ and the South Pacific Convergence Zone—net equatorward and drives cross-equatorial atmospheric flow. The result is a sustained weakening of the easterly trade winds over the equatorial Pacific, which reinforces the El Niño-like background state.

Beneath the surface, the story continues into the upper ocean’s circulation machinery. During warming, the slope of the equatorial thermocline—the tilted boundary between warm surface water and cold deep water, tracked by the 20 degree Celsius isotherm—flattens, shoaling in the west and deepening in the east. After cessation, sea surface temperatures cool slightly while the subsurface keeps warming, so the flattened thermocline never recovers its tilt. The researchers also found hemispherically asymmetric changes in the Subtropical Cells, the shallow overturning circulations that carry cold water toward the equator. Anomalous low pressure and cyclonic winds over the South Pacific drive Ekman suction that slows the southern cell, reducing the upwelling of cold water, while the water that does upwell in the east is anomalously warm. Both effects inhibit any recovery of the zonal temperature gradient.

Feedback diagnostics add a final piece to the causal chain. Using linear regression, the team showed that the atmospheric wind–SST feedback strengthens during transient warming but returns to within its pre-industrial range once emissions cease—atmospheric coupling adjusts quickly. The oceanic feedbacks, by contrast, intensify and stay intensified: the thermocline–SST feedback remains elevated for centuries, meaning eastern Pacific surface temperatures become more sensitive to subsurface anomalies, and wind anomalies tilt the thermocline more efficiently. This reorganisation of oceanic feedback, combined with the persistently weakened zonal gradient and equatorward-shifted convergence zones, keeps ENSO variability amplified long after radiative forcing has stabilised.

The findings fit into a broader, non-linear picture of how ENSO responds to climate change. Palaeoclimate proxies and previous modelling work indicate that ENSO amplitude does not scale simply with warming: moderate shifts of the convergence zones under moderate warming can enhance variability, while extreme warming under very high carbon dioxide concentrations can suppress it, producing a permanent El Niño-like state with weakened variability. Net zero scenarios, which branch off at moderate warming levels, appear to sit in the amplifying regime—locking in a weakened gradient and elevated variability for centuries without ever reaching the extreme concentrations of idealised abrupt-forcing experiments. The study also differs from earlier work suggesting robust ENSO weakening under fixed high carbon dioxide, underscoring that the response depends critically on both the level and the trajectory of forcing.

The authors are careful about limitations. The millennial-scale feedback analysis rests on a single model, and ACCESS-ESM1-5 shares common biases such as a cold tongue and double ITCZ that could exaggerate eastern Pacific convection changes. Yet checks across the ZECMIP ensemble suggest the direction of the response is robust: in eight of nine models, the zonal gradient continues to weaken after cessation regardless of each model’s background state. The clear message for policy is that early mitigation matters twice over—delaying net zero not only increases the magnitude of the Pacific shift but also its persistence, committing generations to more frequent extreme El Niño events and altered rainfall patterns over regions such as East Asia and Australia. Net zero slows further change, the study concludes, but it does not restore the Pacific we knew.

Subject of Research: Persistence of an El Niño-like tropical Pacific mean state under net zero emissions due to ocean thermal inertia

Article Title: Ocean thermal inertia sustains a tropical Pacific mean state shift under net zero

Article References: Sengupta, A., King, A. D., Brown, J. R., Maher, N., Freund, M. B., Ziehn, T., Ong, E. Q. Y., Taschetto, A. S., McGregor, S., & Dittus, A. (2026). Ocean thermal inertia sustains a tropical Pacific mean state shift under net zero. Communications Earth & Environment, 7(1), Article 810. https://doi.org/10.1038/s43247-026-04082-x

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04082-x

Keywords: El Niño, ENSO, net zero emissions, tropical Pacific, ocean thermal inertia, Southern Ocean, thermocline, climate modelling, ZECMIP, ACCESS-ESM1-5, extreme El Niño, ITCZ

The pre-monsoon season, spanning March, April, and May, has long been treated as a transitional period in Indian meteorology, a time of thunderstorms, heat, and scattered convective showers before the large-scale monsoon circulation locks in. The new analysis shows that this period over Kerala has undergone a meaningful shift. Rainfall during these months has been rising steadily in recent decades, and the increase is not a statistical fluke confined to a few stations. It reflects a large-scale reorganization of the atmosphere and ocean over the North Indian Ocean basin, driven by stronger warming of the sea surface during the pre-monsoon months.

The mechanism the researchers identify begins with the ocean itself. The North Indian Ocean, which encompasses the Arabian Sea and the Bay of Bengal, has been warming more strongly during the pre-monsoon season. That warming strengthens the westerly wind flow toward southern India, which in turn enhances moisture transport into the Arabian Sea, across South India, and into the Bay of Bengal. More moisture in the atmosphere means more fuel for rainfall, and the result is an increase in large-scale precipitation across the region. In effect, the warming ocean acts as an ever-larger reservoir of atmospheric water, and the winds are pumping that water over the subcontinent earlier in the year than before.

Superimposed on this warming background is a familiar player from the tropical Pacific: the El Niño–Southern Oscillation. The study finds that the strong pre-monsoon rainfall years over Kerala are associated with a La Niña pattern in the tropical Pacific, the cool phase of the oscillation that typically favors enhanced convection over the Indian sector. During these strong years, southwesterly flow over the Kerala region from the Arabian Sea intensifies, delivering additional moisture to the coast. Weak pre-monsoon years, by contrast, show El Niño anomalies in March and April, followed by weak La Niña cooling in May. The researchers interpret this as a transition phase, marked by feeble cross-equatorial flow and suppressed regional-scale activity, in which neither the ocean nor the atmosphere provides the conditions needed for abundant rain.

One of the most consequential findings concerns the character of the rainfall itself. In the strong pre-monsoon years, convective rainfall makes a major contribution to the seasonal total, and it does so through a greater number of active days. The number of extreme rainfall events also intensifies during these strong years. This matters because extremes, rather than the seasonal average, are what stress infrastructure, trigger landslides in the Western Ghats, and disrupt agriculture. The authors conclude that regional-scale changes are a major contributor to pre-monsoon rainfall and its increasing trend, meaning that local and basin-scale processes, not just remote climate drivers, are reshaping Kerala’s wet season before the wet season officially begins.

The second half of the study turns to the question that has occupied Indian meteorologists for more than a century: what determines the date on which the summer monsoon sets in over Kerala? The onset of the southwest monsoon is one of the most closely watched events in world weather, and its timing carries enormous economic weight for a nation where agriculture remains deeply rain-dependent. The researchers show that the state of the pre-monsoon season leaves a fingerprint on the onset evolution itself, through a subtle choreography of rainfall pauses, sea surface temperatures, and low-pressure systems.

During strong pre-monsoon years, the analysis reveals a striking pattern: the pre-monsoon rainfall shows a brief pause of five to six days just before the monsoon onset. That lull is not a sign of a failing monsoon but a functional part of the transition. During the pause, sea surface temperatures rise in the southern Bay of Bengal and the Arabian Sea, warming the ocean surface precisely where the incoming monsoon needs it. These strong years are then associated with the formation of low-pressure systems in both the Bay of Bengal and the Arabian Sea. The Bay of Bengal system moves toward southeastern India, while the Arabian Sea system moves toward northwestern India, and together they initiate organized convection and its characteristic northward propagation, the hallmark of the monsoon’s advance across the subcontinent.

Weak pre-monsoon years tell a very different story. In those years, a low-pressure system forms only in the Bay of Bengal, and instead of steering toward the Indian mainland, it recurves eastward toward Bangladesh. Without a second system in the Arabian Sea and without the pre-onset warming of both basins, the organized convection that drives a robust onset fails to assemble in the same way. The contrast between the two scenarios suggests that the pre-monsoon season functions as a kind of staging ground: the rainfall, winds, and ocean heat accumulated between March and May determine whether the monsoon arrives with a full complement of atmospheric ingredients or limps into gear with only part of the machinery in place.

The study draws on a comprehensive set of observational datasets, which lends weight to its conclusions. Rainfall comes from the India Meteorological Department’s daily gridded dataset and the Global Precipitation Climatology Project, sea surface temperatures from the Met Office Hadley Centre’s HadISST 1.1 analysis extending back to 1870, atmospheric fields from the ERA5 reanalysis produced by the Copernicus Climate Change Service, and daily outgoing longwave radiation from NOAA’s Climate Data Record as a proxy for deep convection. Tropical cyclone and low-pressure system tracks come from the India Meteorological Department’s Regional Specialized Meteorological Center for the North Indian Ocean. By combining these independent records, the authors were able to link rainfall trends, ocean warming, circulation changes, and system formation into a single coherent narrative.

The implications extend well beyond Kerala. For forecasters, the identification of a pre-onset rainfall pause and the dual low-pressure system signature in strong pre-monsoon years offers a potential diagnostic for anticipating how the monsoon onset will unfold. For planners in Kerala and neighboring states, the finding that extremes intensify in strong pre-monsoon years underscores the need to prepare for flooding and landslide risks earlier in the calendar than traditional monsoon preparedness assumes. And for climate scientists, the study adds a piece to the larger puzzle of how rapid Indian Ocean warming is rewriting the rhythms of the Asian monsoon system. As the North Indian Ocean continues to heat, the line between the pre-monsoon and the monsoon may grow increasingly blurred, with Kerala’s springtime storms serving as both a warning signal and a preview of the season to come.

Subject of Research: Mechanisms behind the recent increase in pre-monsoon rainfall over Kerala and its influence on Indian summer monsoon onset

Article Title: The recent increase in Kerala’s pre-monsoon rainfall: underlying mechanism and its impact on summer monsoon onset

Article References: Eapen, S. S., Pillai, P. A., & Das, R. S. (2026). The recent increase in Kerala’s pre-monsoon rainfall: underlying mechanism and its impact on summer monsoon onset. Theoretical and Applied Climatology, 157(9), Article 599. https://doi.org/10.1007/s00704-026-06529-9

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06529-9

Keywords: Kerala, pre-monsoon rainfall, North Indian Ocean warming, monsoon onset, La Niña, El Niño, Arabian Sea, Bay of Bengal, sea surface temperature, extreme rainfall, Indian monsoon, climate change

The research, conducted by Jose Obregon-Yataco of the Instituto Geofísico del Perú, tackles a long-standing blind spot in operational meteorology. Forecasters have traditionally gauged the potential for thunderstorms using thermodynamic indices such as Convective Available Potential Energy, or CAPE, which measures how much buoyant energy is stored in the atmosphere, and the Gálvez-Davison Index, which adds tropical moisture considerations to the mix. But in the coastal strip of northwestern South America, these indices routinely produce false alarms. The reason, the study argues, is that they measure only the fuel for convection, never the ignition. In a region where large-scale sinking air, or subsidence, persistently suppresses rising motion, atmospheric instability is a necessary but fundamentally insufficient condition for rainfall.

The study’s solution is an elegantly simple mathematical construct called the Buoyancy Work Rate, or BWR. The index is computed by multiplying parcel buoyancy, denoted ΔT and representing the temperature excess of a rising air parcel relative to its surroundings, by the vertical velocity ω, and then integrating this product through the entire atmospheric column from the surface to 100 hectopascals. Crucially, only layers where the air is both positively buoyant and moving upward are counted. The result is a single number that quantifies the rate at which potential energy is actually being converted into kinetic energy by active convection. If the atmosphere is loaded with instability but mechanically clamped down by subsidence, the index zeroes out, filtering exactly the false positives that plague purely thermodynamic metrics.

The physical logic draws on a classic result from 1977, when Cornejo-Garrido and Stone showed that within the Walker circulation, the latent heat released by tropical convection is balanced on climatic timescales by the adiabatic cooling produced by large-scale vertical ascent. In other words, vertical motion and deep convection are two sides of the same coin. The coastal region under study sits beneath the descending branch of this circulation, where trade-wind-driven upwelling of cold water and dry leeward flow off the Andes conspire to keep the air stable. Rain falls only during a brief window in the austral summer, peaking in March, when weakening trade winds and warming sea surface temperatures come into phase. When sea surface temperatures in the adjacent Niño 1+2 region cross a critical threshold of roughly 26 degrees Celsius, this stability regime collapses and the system flips into a tightly coupled state where rising motion and latent heating reinforce each other.

To validate the new index, the study deployed a battery of independent tests. First, a causal discovery algorithm called PCMCI+ was applied to more than four decades of monthly data from 1981 to 2025, using the ERA5 reanalysis and two high-resolution precipitation products tailored to Peruvian topography, PISCO and RAIN4PE. The analysis confirmed that the BWR preserves the dominant causal pathway to precipitation, maintaining a robust direct link with a causal strength of 0.60 that exceeds even the local evaporation signal. Second, an upper tail dependence analysis based on empirical copulas, a statistical technique for examining the behavior of joint extremes, revealed that the index’s agreement with precipitation strengthens precisely where it matters most: at the highest quantiles, the tail dependence coefficient climbs to nearly 0.8, indicating that the BWR becomes a highly reliable diagnostic specifically during the most extreme and potentially disastrous events.

The vertical cross-sections of past extreme events tell the story with striking clarity. During the great El Niño of 1998 and the localized coastal event of 2017, anomalous onshore westerly winds, driven by enhanced sea breezes colliding against the western Andean slope, generated deep ascent columns extending from the surface up to 300 hectopascals, ventilated aloft by diverging easterlies. In these years, atmospheric instability and dynamic ascent synchronized perfectly, and the product of the two peaked between 500 and 400 hectopascals, exactly where the BWR registers its strongest signal. The 2016 event, by contrast, revealed the opposite configuration: a severe layer of mid-level subsidence centered near 600 hectopascals physically severed the atmospheric column, neutralizing surface convergence and capping the instability despite abundant oceanic warmth. The BWR captured this structural decoupling, correctly yielding neutral to negative anomalies where conventional indices screamed flood.

Beyond diagnosis, the index exhibits a subtle but operationally valuable property: memory. Mid-level vertical velocity alone, while dictating instantaneous convection, decorrelates rapidly and is too volatile for continuous monitoring. Because the BWR integrates the buoyancy term, which is anchored to slowly evolving sea surface temperatures through the Clausius-Clapeyron relationship, it inherits the thermal inertia of the ocean. Autocorrelation analysis shows the index retains signal persistence far longer than vertical velocity by itself, making it a more stable proxy for sub-seasonal monitoring. It is, in effect, a physical trade-off: a marginal sacrifice of precision at the extreme tail in exchange for substantial gains in temporal stability.

The most consequential finding, however, concerns seasonal forecasting. Climate models such as the European Centre for Medium-Range Weather Forecasts’ SEAS5 system struggle to predict precipitation in this region because rainfall generation depends on sub-grid convective parameterizations, the simplified schemes that stand in for processes far smaller than the model’s grid cells. When Obregon-Yataco substituted the model’s direct precipitation output with BWR anomalies computed from the model’s predicted wind and temperature fields, predictive skill improved consistently. During the peak rainy season of February through April, forecasts initialized in November and December gained roughly 0.1 to 0.2 in correlation skill. More remarkably, at extended lead times of five to six months, targeting the austral spring, the improvement exceeded 0.3, meaning the index retains skill across the boreal spring predictability barrier that typically degrades long-range forecasts.

The explanation for this advantage is rooted in the hierarchy of physical equations. Vertical motion and temperature structure are explicitly resolved by the primitive equations governing the model dynamics, whereas parameterized rainfall inherits all the microphysical uncertainties of those schemes. By treating the BWR as a physical translator, forecasters can effectively sidestep the weakest link in the modeling chain and read the convective state directly from variables the model simulates with greater fidelity. The index also depends on surface dew point temperature, which is tightly constrained by local ocean conditions, rather than on free-tropospheric humidity, a quantity notorious for inter-model spread and systematic bias.

The study is candid about limitations. The BWR lacks an explicit humidity term, so it can produce false positives during dry ascent, when strong lifting occurs in moisture-starved air. It is integrated through the full troposphere and therefore misses shallow, warm-rain convection. Its skill degrades over the Amazon basin and the eastern Andes, where precipitation is governed by convective inhibition, orographic lifting, and mesoscale systems too fine for global reanalyses to resolve. And beyond the tropics, where baroclinic instability and frontal lifting dominate, the formulation becomes physically inconsistent. Yet within its intended domain, the dynamically limited coastal zone of northwestern South America, the index condenses a complex three-dimensional convective state into a rapidly interpretable two-dimensional field, distinguishing active convective engines from thermodynamically primed but dynamically suppressed atmospheres. For a region repeatedly battered by floods in 1983, 1998, 2017, and 2023, that distinction could mean the difference between a timely evacuation and a catastrophe caught off guard.

Subject of Research: A coupled dynamic-thermodynamic index for diagnosing and predicting monthly precipitation anomalies in northwestern South America

Article Title: Explaining monthly precipitation anomalies in northwestern South America by integrating vertical dynamics and energetics

Article References: Obregon-Yataco, J. (2026). Explaining monthly precipitation anomalies in northwestern South America by integrating vertical dynamics and energetics. Weather and Climate Dynamics, 7(3), 1547-1570. https://doi.org/10.5194/wcd-7-1547-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1547-2026

Keywords: El Niño, precipitation anomalies, convection, Buoyancy Work Rate, Peru, Ecuador, seasonal forecasting, Walker circulation, vertical velocity, CAPE, ERA5, early warning systems

The events in question are westerly wind bursts, or WWBs. These are episodes lasting a week or two, spanning roughly a thousand kilometres of the equatorial Pacific, in which the normally reliable easterly trade winds reverse or weaken dramatically. They are not rare curiosities. According to the observational record, westerly wind bursts have preceded and amplified every major El Niño event ever documented. The mechanism is physically direct: a burst of westerly wind pushes warm surface water eastward and excites oceanic Kelvin waves, waves that travel along the equatorial thermocline and accelerate warming in the eastern Pacific near the coast of South America. The monster El Niños of 1997 and 2015, two of the strongest in the instrumental record, were both accompanied by multiple powerful wind bursts.

Crucially, these bursts are not purely random weather. Observational analyses have shown that westerly wind bursts tend to occur when equatorial sea surface temperatures begin to warm, and they occur more frequently during the active phase of the Madden–Julian Oscillation, a large-scale pulse of tropical atmospheric variability. This state-dependency creates a feedback loop: warming water makes bursts more likely, and the bursts amplify the warming. In simplified models of ENSO, this behaviour has traditionally been encoded as multiplicative Gaussian noise, a stochastic forcing whose amplitude grows with the sea surface temperature anomaly itself. This formulation fits the observed spectrum and probability distribution of ENSO remarkably well, which is precisely why it became the consensus choice.

But fitting the bulk statistics is not the same as capturing the dynamics. In the new work, Georg Gottwald of the University of Sydney, Eli Tziperman of Harvard University, and Alexey Fedorov of Yale University examined what the wind-burst forcing actually looks like when measured in a global climate model. They computed a time-integrated measure of wind stress from bursts in the Community Earth System Model, combining burst duration and wind speed into a single quantity that reflects the ocean’s exposure to each event. The resulting time series is striking: a quiet background punctuated by sporadic, high-amplitude peaks. That shape, the authors realised, looks nothing like smoothed Gaussian noise. It looks instead like a class of stochastic processes known as correlated additive and multiplicative noise, or CAM noise, which has previously been used to describe non-Gaussian sea surface temperature anomalies and atmospheric variability.

The mathematical distinction matters. When a Gaussian process such as the Ornstein–Uhlenbeck process, the workhorse of stochastic climate modelling, is integrated over time, the central limit theorem guarantees that the result is Brownian motion: continuous, well-behaved, and Gaussian. CAM noise behaves differently. Under certain parameter regimes, its time integral converges to an alpha-stable Lévy process, a random walk punctuated by abrupt jumps of potentially enormous size. The stability parameter alpha controls how large these jumps can be, while a skewness parameter beta controls whether they favour one direction. With parameters chosen so that only positive jumps occur, the integrated CAM noise produces exactly the kind of sporadic, one-sided jolts that a westerly wind burst delivers to the ocean. In the recharge oscillator framework, a positive wind stress anomaly shoals the western Pacific thermocline and amplifies eastern Pacific sea surface temperatures, so one-sided positive jumps translate directly into sudden warming kicks.

The recharge oscillator model itself, introduced by Fei-Fei Jin in 1997, reduces ENSO to two coupled variables: the eastern Pacific sea surface temperature anomaly and the western Pacific thermocline depth. Warm water in the east drives the winds, the winds adjust the thermocline, and the thermocline feeds back on the temperature through the Bjerknes feedback, producing a self-sustained or damped oscillation depending on the parameters. The model is crude, but it has proved remarkably durable as a conceptual laboratory for ENSO theory, and recent reviews have reaffirmed its central role. The question the new study poses is deceptively simple: what kind of random forcing should be injected into this oscillator to represent the winds realistically?

The authors compared three answers. The first was the conventional choice, multiplicative Gaussian Ornstein–Uhlenbeck noise whose amplitude scales with the temperature anomaly. The second was pure additive CAM noise, with its intermittent unbounded peaks. The third, and the study’s central contribution, was a conditional model the authors call CON: when the sea surface temperature anomaly is negative, the forcing is ordinary Gaussian noise, but once the anomaly turns positive and persists over a three-month average, the forcing switches to CAM noise. The rationale is physical. Over a cool equatorial ocean, wind variability may indeed be well described by Gaussian statistics, but as the water warms and El Niño begins to develop, the wind field reorganises, and the burst-like, non-Gaussian character of the forcing takes over.

Each model was calibrated against 153 years of observed NiNO3 index data, from 1870 to 2026, matching the empirical histogram, the power spectrum, and the variance and skewness of the temperature record. On these bulk statistics, all three models performed comparably well. Kolmogorov–Smirnov tests and Wasserstein distances between modelled and observed distributions showed the conventional Gaussian model and the conditional model in a statistical dead heat, with pure CAM noise, as expected, producing too many extreme events and a heavier tail. But the decisive test came from a finer-grained dynamical signature: the number of strong wind bursts occurring in the twelve months before an El Niño peak. In the real climate system, the largest El Niño events are preceded by a cluster of bursts, a signature of the feedback between warming water and burst occurrence. When the researchers counted large noise events preceding the strongest fifth of El Niño events in million-month-long simulations, the CAM and conditional models reproduced this clustering dramatically, while the multiplicative Gaussian model captured it only weakly.

The conditional model also achieved something that normally requires deliberate engineering: it generated the well-known asymmetry between El Niño and La Niña, in which warm events tend to be stronger than cold events, without any deterministic nonlinear terms in the temperature equation. The skewness of the simulated temperature distribution emerged entirely from the skewed, jump-rich structure of the noise itself, echoing earlier work by Martinez-Villalobos and colleagues who showed that a linear model driven by CAM noise can capture the observed asymmetry. The authors did find that including an asymmetric response of sea surface temperature to thermocline depth, with a stronger effect for positive than negative thermocline anomalies, was still needed to match the full observed histogram, but the burst clustering survived even with a symmetric response, confirming that it is the conditional noise, not the nonlinearity, doing the dynamical work.

The implications extend beyond a toy model. If extreme El Niño events are genuinely the product of a sustained sequence of wind bursts rather than a smooth random walk of forcing, then forecasts and projections that rely on Gaussian stochastic parameterisations may systematically underestimate the likelihood and potential intensity of the largest events. The authors suggest that their conditional scheme, which reproduces both the quiet background statistics of ENSO and the burst-driven dynamics of its extremes, offers a better template, and they point toward testing it in more realistic coupled climate models as the natural next step. In a warming world, where the stakes of predicting the next 1997-style event keep rising, the difference between smooth Gaussian noise and a process built from sudden jumps may turn out to be one of the most consequential details in climate mathematics.

Subject of Research: Stochastic modelling of westerly wind bursts in the recharge oscillator model of the El Niño–Southern Oscillation

Article Title: An improved noise model for representing westerly wind bursts in the recharge oscillator model of ENSO

Article References: Gottwald, G. A., Tziperman, E., & Fedorov, A. (2026). An improved noise model for representing westerly wind bursts in the recharge oscillator model of ENSO. Nonlinear Processes in Geophysics, 33(3), 373-383. https://doi.org/10.5194/npg-33-373-2026

Image Credits: AI Generated

DOI: 10.5194/npg-33-373-2026

Keywords: El Niño, ENSO, westerly wind bursts, recharge oscillator, CAM noise, Lévy processes, stochastic forcing, non-Gaussian noise, tropical Pacific, climate modelling, sea surface temperature, Madden–Julian Oscillation