Mark Collier of CSIRO Environment in Melbourne, together with Dylan Harries of the South Australian Health and Medical Research Institute and Terence O’Kane of CSIRO Environment in Hobart, applied a technique known as Bayesian structure learning to decades of climate data. Rather than simply measuring correlations between climate patterns, their method infers directed networks of Granger-causal relationships, in which one time series is said to cause another if knowledge of its past improves predictions of the other. The result is a dynamic Bayesian network: a graph in which the major modes of climate variability appear as nodes, and the most probable lagged influences between them appear as arrows pointing forward in time. Because the approach is Bayesian, it does not deliver a single definitive diagram but a probability distribution over possible networks, allowing the researchers to quantify exactly how confident they are in each inferred connection.

The team drew on the ERA5 reanalysis, the European Centre for Medium-Range Weather Forecasts’ state-of-the-art reconstruction of the historical atmosphere, which blends observations with numerical weather prediction to provide a physically consistent record back to 1940. From this dataset they computed a battery of standard climate indices: the multivariate ENSO index capturing El Niño-Southern Oscillation variability in the tropical Pacific, the Indian Ocean Dipole measuring east-west sea surface temperature gradients in the Indian Ocean, the Madden-Julian Oscillation indices RMM1 and RMM2 tracking the eastward-propagating pulse of tropical convection, and a suite of extratropical atmospheric patterns including the North Atlantic Oscillation, the Pacific North American pattern, the Arctic Oscillation, the Southern Annular Mode, the Pacific South American patterns, and Scandinavian blocking. The IPO itself was represented by the Tripole Index, which contrasts sea surface temperature anomalies in the central tropical Pacific against those in the northern and southern subtropics.

The observational record poses a stubborn problem for anyone studying multidecadal variability: it contains only one clear positive IPO phase, from roughly 1977 to 1998, and one clear negative phase, from 1948 to 1976, long enough for reliable statistical fitting. To overcome this limitation, the researchers turned to an ensemble of historical simulations from the ACCESS-CM2 coupled climate model, run under CMIP6 protocols from 1850 to 2014. Because each simulation evolves its own internal variability, the ensemble provides multiple independent realizations of IPO phase transitions, giving the team a much richer sample of background states than the single observed transition. The trade-off was that daily model output needed to compute the MJO indices was unavailable for the model runs, so the researchers ran parallel analyses of the reanalysis data with and without the MJO to make fair comparisons.

The headline result is that the causal architecture of the climate system looks strikingly different depending on which way the IPO is leaning. During the negative IPO phase, which is characterized by cooler tropical Pacific waters, the IPO index shows strong autocorrelation persisting out to six-month lags, and the learned networks reveal an enhanced role for extratropical teleconnections acting on the tropics. Long-lagged influences from the Pacific North American pattern, the Southern Annular Mode, and the IPO itself become prominent. During the positive IPO phase, by contrast, the picture flips: IPO autocorrelation shrinks to about two months, while the Indian Ocean Dipole becomes far more persistent, and the Madden-Julian Oscillation emerges as a powerful conduit linking tropical convection to both the IOD and ENSO. This is consistent with the enhanced Walker circulation that prevails when tropical Pacific waters are warm, and with the observation that El Niño events are more frequent and longer-lived during positive IPO periods.

Perhaps the most striking discovery concerns the humble Madden-Julian Oscillation, an eastward-moving envelope of clouds and rain that circles the tropics every one to two months. When the researchers removed the MJO indices from their analysis, the learned networks underwent a dramatic collapse. Crucial pathways connecting the Northern Hemisphere’s tropospheric modes, including the North Atlantic Oscillation and the Pacific North American pattern, to equatorial sea surface temperatures vanished, while posterior edge weights between ENSO, the IPO, and the IOD swelled to compensate. In other words, the MJO is not merely an intraseasonal curiosity confined to the Maritime Continent; it is the key intermediary that transmits extratropical variability down into the tropical ocean-atmosphere system and helps sustain the very persistence of ENSO and the IPO themselves. Without it, the tropics and extratropics become largely strangers to one another in the inferred graphs.

The directionality of the learned edges also carried physical meaning that aligns with independent lines of evidence. The networks recovered a robust one-month-lagged influence of the negative phase of the North Atlantic Oscillation on the second MJO index, meaning that a strong negative NAO tends to precede and shape subsequent MJO behavior. This dovetails with earlier studies showing that seasonal prediction models initialize MJO forecasts more skillfully when the NAO state is strong and negative, and with proposed mechanisms involving extratropical Rossby wave propagation into the tropical upper atmosphere. Similarly, the analysis found that when the IPO is included as a node, the Southern Annular Mode exerts a statistically significant influence on ENSO at six-month lags, a relationship that paleoclimate reconstructions had hinted at but that the instrumental record had been too short to pin down.

Comparisons with the ACCESS-CM2 model ensemble revealed both the promise and the limits of current climate models. The simulated networks showed considerable diversity across the three IPO transition cases examined, including one in which a nineteen-year neutral period separated the negative and positive phases, and the extratropical-to-tropical connections were systematically stronger than in the reanalysis. The model also exhibited known biases, with an ENSO-like sea surface temperature pattern extending too far west and weakened anomalies over the tropical Indian Ocean. Notably, the observed IOD-to-ENSO connection present during the negative IPO phase did not appear in any of the modeled networks. These discrepancies matter, the authors argue, because the current generation of models often shows large systematic errors in autocorrelations and dependencies, and causal network diagnostics offer a sharp new tool for identifying exactly where those errors originate.

The implications reach well beyond academic diagram-making. The IPO has been linked to periods of accelerated global warming and to the early-century warming hiatus, to Australian rainfall and flood risk, and to the modulation of the Walker and Hadley circulations that shape weather across the Indo-Pacific region. If the strength and even the direction of teleconnections depend on the IPO phase, then seasonal-to-decadal prediction systems may need to condition their forecasts on the background state, and the intrinsic predictability of modes like ENSO may itself be regime-dependent. The authors caution that their directed graphs indicate the probability that causal relationships exist, and that verifying the underlying mechanisms requires detailed follow-up investigation. But the message is clear: the climate system’s wiring diagram is not fixed. It is redrawn, decade by decade, by the slow breathing of the Pacific.

Subject of Research: The influence of Interdecadal Pacific Oscillation phase on tropical-extratropical climate teleconnection dependencies

Article Title: Inferring the role of Interdecadal Pacific Oscillation phase on tropical-extratropical teleconnection dependencies

Article References: Collier, M. A., Harries, D., & O'Kane, T. J. (2026). Inferring the role of Interdecadal Pacific Oscillation phase on tropical-extratropical teleconnection dependencies. Nonlinear Processes in Geophysics, 33(1), 103-122. https://doi.org/10.5194/npg-33-103-2026

Image Credits: AI Generated

DOI: 10.5194/npg-33-103-2026

Keywords: Interdecadal Pacific Oscillation, ENSO, Madden-Julian Oscillation, Indian Ocean Dipole, teleconnections, Bayesian structure learning, causal inference, ERA5 reanalysis, climate variability, Walker circulation, North Atlantic Oscillation, CMIP6

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 research, led by Ingo Richter of the Japan Agency for Marine-Earth Science and Technology together with colleagues from institutions in Japan, the United States, Norway, and Brazil, rests on an unusually broad foundation of evidence. The team compared simulations of a pre-industrial climate with projections of a high-emissions future, known as scenario ssp585, drawn from 23 state-of-the-art climate models participating in the Coupled Model Intercomparison Project Phase 6, the same modeling framework that underpins the assessments of the Intergovernmental Panel on Climate Change. By contrasting these two worlds, one without human interference and one heated by sustained emissions, the researchers could isolate how the machinery of Atlantic variability itself changes when the planet warms.

The headline finding confirms a trend that earlier studies had already hinted at: the variability of sea-surface temperatures along the equatorial Atlantic, the signature of the Atlantic Zonal Mode, weakens under global warming. In plain terms, the Atlantic Niño becomes less intense, swinging less dramatically between warm and cold phases. Off the equator, by contrast, the picture is different, with sea-surface temperature variability tending to increase slightly in the flanking regions of the tropical Atlantic. That split result matters, because the equatorial mode is the one most tightly linked to the seasonal rains that farmers and water managers from Senegal to Angola depend upon, and its weakening has been flagged in previous work as a potential source of forecast uncertainty.

What makes the new analysis distinctive is its dissection of why the weakening occurs. The Atlantic Niño, like its Pacific counterpart, is sustained by the Bjerknes feedback, a self-reinforcing loop in which a warm anomaly in the eastern equatorial ocean weakens the prevailing easterly trade winds, which in turn suppresses the upwelling of cold subsurface water, further warming the surface. The study finds that this feedback is losing its grip. Contrary to some earlier projections, the team found that the mean-state equatorial Atlantic thermocline, the sharp vertical boundary between warm surface water and cold deep water, actually shoals slightly under radiative forcing, a change that should, on its own, strengthen the mode by making the surface more sensitive to subsurface dynamics. The decline of the Atlantic Niño therefore cannot be blamed on a deepening thermocline. Instead, the culprits are a weakening of the mean upwelling that supplies cold water to the surface and a reduced sensitivity of surface winds to sea-surface temperature anomalies, both of which blunt the Bjerknes feedback at its most critical links.

The second major discovery concerns the changing character of the mode’s forcing. In the pre-industrial simulations, the Atlantic Zonal Mode is driven primarily by dynamic forcing, meaning anomalies in surface wind stress that stir the ocean and rearrange its heat content. In the high-emissions future, the composites of Atlantic Niño events show that this dynamic pathway diminishes, while thermodynamic forcing takes on a more prominent role. Thermodynamic forcing operates through the exchange of heat at the ocean surface, particularly through latent heat flux, the energy carried away by evaporation, and through shortwave radiation, the sunlight that warms the upper ocean. In a warmer world, the Atlantic Niño becomes less a story of winds pushing water around and more a story of clouds, evaporation, and radiant heat reshaping the sea surface.

That shift in mechanism is tied to a striking change in the Atlantic’s relationship with the Pacific. The analysis reveals that the influence of the El Niño-Southern Oscillation on the Atlantic Zonal Mode strengthens under global warming, to the point that a positive correlation emerges between the two phenomena, with Pacific events preceding their Atlantic counterparts by roughly half a year. In today’s climate, the connection between El Niño and the Atlantic Niño has long been described as inconsistent and fragile, appearing in some decades and vanishing in others, a puzzle that has occupied tropical climate scientists for years. The new projections suggest that the greenhouse-warmed atmosphere will knit the two basins together more tightly, transmitting Pacific signals across Central America and the tropical atmosphere with greater reliability.

Two processes appear to explain this tightening bond. First, El Niño itself grows stronger in the high-emissions simulations, and a more powerful Pacific oscillator naturally broadcasts a louder signal into neighboring basins. Second, and perhaps more intriguingly, the weakening of the coupled air-sea feedbacks within the equatorial Atlantic leaves that ocean more susceptible to external forcing. A system whose internal feedbacks have gone quiet is one that listens more attentively to remote voices. When the Atlantic’s own Bjerknes feedback can no longer dominate its variability, the Pacific’s influence, arriving through atmospheric bridges such as shifts in the Walker circulation and changes in tropical tropospheric temperature, finds less resistance and leaves a clearer imprint on Atlantic sea-surface temperatures.

Paradoxically, this foreign domination may carry a silver lining for forecasters. A simple linear analysis performed by the team indicates that, in some of the models, the association of the Atlantic Zonal Mode with El Niño makes the Atlantic mode more predictable, even as its amplitude fades. The logic is straightforward: if a large fraction of Atlantic variability can be traced back to a Pacific precursor that emerges about six months in advance, then forecast systems that skillfully predict El Niño gain, for free, a measure of skill in predicting the Atlantic Niño. Seasonal prediction centers in Africa, Europe, and the Americas could eventually exploit this teleconnection to extend the useful lead time of rainfall outlooks for the Sahel, the Guinea Coast, and northeastern Brazil, regions where the Atlantic mode’s influence on the West African monsoon and coastal precipitation is well documented.

The study also underscores how much remains uncertain. The 23 models do not speak with one voice; the emergence of the ENSO-Atlantic correlation is clear in the ensemble but varies in strength from model to model, and tropical Atlantic simulations remain haunted by persistent mean-state biases that have plagued coupled models for decades. The researchers cross-checked their projections against observational and reanalysis products, including the ERA5 atmospheric reanalysis, the ORAS5 ocean reanalysis, and the HadISST sea-surface temperature dataset, all of which are publicly available, but the fundamental limits of simulating a basin as small and as seasonally locked as the equatorial Atlantic still apply. Whether the real ocean will follow the models’ script is a question that only the coming decades of observation can answer.

Still, the implications are hard to ignore. A tropical Atlantic that dances increasingly to the Pacific’s tune would alter the risk landscape for coastal fisheries, which are disrupted when the cold tongue fails to deliver its usual nutrient-rich upwelling, and for agricultural planners who rely on the statistical rhythms of Atlantic variability. It would also complicate attribution studies, since an Atlantic event that once looked like a local fluke may in the future be the distant echo of an El Niño half a world away. The research, published in Climate Dynamics as volume 64, article 450, offers both a warning and a tool: the Atlantic Niño of the future may be weaker and less self-reliant, but by borrowing predictability from the Pacific, it may also become a signal that humanity can see coming with more confidence than ever before.

Subject of Research: Projected changes in tropical Atlantic sea-surface temperature variability and its coupling to ENSO under global warming

Article Title: Strengthened tropical Pacific influence on tropical Atlantic variability in global warming projections

Article References: Richter, I., Chang, P., Kataoka, T., Kido, S., Keenlyside, N., Kosaka, Y., Okumura, Y., Tokinaga, H., Tozuka, T., & Vilela, I. (2026). Strengthened tropical Pacific influence on tropical Atlantic variability in global warming projections. Climate Dynamics, 64(11), Article 450. https://doi.org/10.1007/s00382-026-08390-y

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08390-y

Keywords: Atlantic Niño, Atlantic Zonal Mode, ENSO, CMIP6, Bjerknes feedback, tropical Atlantic, sea-surface temperature, climate change, thermocline, seasonal prediction, Walker circulation, Climate Dynamics

The research team, led by G. Botetano and including J. C. Espinoza, K. Takahashi, and colleagues from institutions in Peru, France, and Brazil, analyzed the period from 1982 to 2024, using satellite-derived precipitation from CHIRPS, temperature from the ERA5-Land reanalysis, sea surface temperatures from HadISST, and more than forty years of daily water level measurements from the Negro River gauge at the port of Manaus. The Manaus gauge is no ordinary data point. Because the Negro River responds to rainfall across roughly three million square kilometers of upstream Amazonia, its levels integrate the hydrological memory of the entire northwestern basin, lagging behind precipitation by about three months as floodplains and saturated soils buffer and release water.

The technical core of the study rests on empirical orthogonal function analysis, a statistical technique that decomposes complex climate fields into their dominant spatial patterns and corresponding time series. When the researchers applied this method to seasonal precipitation, temperature, and terrestrial water storage anomalies measured by the GRACE and GRACE-FO satellite gravimetry missions, they found something remarkable: the leading modes of all these variables were tightly coupled. Precipitation variability correlated with water storage at around 0.78 to 0.79, river levels tracked precipitation at roughly 0.76 to 0.81, and temperature—the sign-inverted, since heat accompanies drought—correlated with storage at 0.76 to 0.88. In other words, the Amazon does not experience a rainfall anomaly here and a temperature anomaly there; it moves as a coherent compound system.

AB-CHEX distills this coupling into a single number for each season. Negative phases below the 15th percentile mark dry–hot compound events, combining rainfall deficits, anomalous warmth, and falling rivers. Positive phases above the 85th percentile mark wet–cold events, the signature of the great floods. The index validated beautifully against history: it reproduces the documented droughts of 1998, 2005, 2010, 2015–16, and 2023–24, and the floods of 2009, 2012, and 2021–22. It also captures basin-scale water storage variability, correlating with the GRACE-derived storage component at 0.93 in the wet season and 0.88 in the dry season—evidence that the index reflects genuine basin-wide hydroclimatic dynamics rather than the quirks of any single dataset.

Then comes the headline finding. When the researchers constructed a trend-preserving version of the index, AB-CHEXLT, the wet and dry seasons revealed opposite long-term trajectories. During the extended wet season from November to April, the index shows a significant drift toward wetter and colder compound conditions, consistent with an intensifying hydrological cycle and the record flooding that has plagued northern Amazonia—the cumulative duration of flood emergencies at Manaus in the first two decades of this century already exceeds that of the entire twentieth century by about 20 percent. During the dry season from June to September, the index shows a sustained shift toward increasingly dry–hot conditions, and here the decomposition is damning: the linear trend explains nearly a quarter of total dry-season variance, and within that trend, warming alone accounts for 86.9 percent of the long-term signal.

And then there is 2024. Even after removing long-term trends, the AB-CHEX value for 2024 reached its lowest magnitude across both seasons in the entire 43-year record, marking an event the authors describe as unprecedented. The 2023–24 drought combined delayed rainfall onset, record-breaking heat, collapsing river levels, widespread canopy browning, and sharp declines in gross primary productivity, with pronounced soil moisture deficits and elevated vapor pressure deficit covering more than half the Amazon region during the austral springs of 2023 and 2024. Previous severe dry–hot events clustered in recognizable patterns—the wet-season extremes of 1998 and 2016 during strong El Niño years, the dry-season extremes of 2005, 2010, and 2023—but 2024 broke the mold in both seasons simultaneously.

To find the culprits, the team turned to composite analysis of atmospheric circulation and sea surface temperatures during extreme index phases. During the wet season, the story is fundamentally Pacific. Dry–hot years show pronounced mid-level subsidence between 300 and 600 hectopascals across equatorial Amazonia—a weakening of the ascending branch of the regional Hadley circulation that suppresses deep convection—paired with an eastward shift of the Walker-like zonal circulation that enhances ascent over the eastern Pacific. Sea surface composites reveal the classic El Niño fingerprint: significant warming over the Niño-3.4 region. Quantitatively, ENSO-related Pacific sea surface temperature anomalies explain 61 percent of wet-season AB-CHEX variability, while the regional Hadley circulation index alone correlates at 0.85, accounting for 72 percent. El Niño weakens the overturning cells and starves the basin of moisture; La Niña strengthens them, driving the great wet–cold floods.

The dry season tells a different and, in a warming world, more troubling story. Here the primary control is not the Pacific but the Caribbean–Tropical North Atlantic region. Dry–hot years show intensified subsidence between 500 and 800 hectopascals, a northward-shifted and strengthened descending branch of the regional Hadley cell, and marked warming over the Caribbean–TNA. Warm sea surface anomalies there weaken the meridional pressure gradient, slacken the trade winds, and choke off the Atlantic moisture inflow that sustains dry-season convection. The Caribbean–TNA sea surface temperature index correlates with dry-season AB-CHEX at 0.79, explaining 62 percent of its variability—and crucially, this relationship holds regardless of the Pacific state, remaining significant under warm, neutral, and cold Niño-1+2 conditions. When the researchers removed the shared variance between the two ocean basins using partial correlations, the Pacific influence on dry-season compound extremes vanished entirely, while the Caribbean–TNA influence on wet-season extremes persisted only as a secondary modulation of ENSO-driven variability.

The spatial consequences of these two forcing regimes differ profoundly. During wet-season dry–hot events, precipitation deficits exceeding 25 percent and temperature anomalies above 1.2 degrees Celsius concentrate over northeastern Amazonia, where ENSO’s Walker and Hadley circulation teleconnections bite hardest. Dry-season dry–hot events, driven by the more spatially uniform Caribbean–TNA forcing, produce rainfall reductions exceeding 45 percent and anomalies near plus one degree Celsius across the Peruvian, central, and southern Amazon—wider, deeper, and more severe. Land–atmosphere feedbacks amplify the damage: antecedent soil moisture deficits persist through hydrological memory, suppressing evapotranspiration and shifting the surface energy balance toward sensible heating, which reinforces both the warmth and the rainfall deficit. In total, roughly 68 percent of the basin exhibits significant compound coupling with the index during the wet season, rising to 76 percent during the dry season.

The implications reach beyond atmospheric science. The sustained warming of the Caribbean–TNA since the mid-2000s, the authors note, appears to be intensifying dry–hot compound conditions, strengthening land–atmosphere feedbacks, and amplifying hydroclimatic instability—layered on top of deforestation-driven delays in wet-season onset across southern Amazonia and rising tree mortality across the basin. Because all of AB-CHEX’s inputs are publicly available, routinely updated datasets, the index can be computed operationally by hydrometeorological services and early-warning centers across Amazonian countries, with the caveat that the two-to-three-month hydrological lag limits real-time applications. What the index makes unmistakably clear is that the Amazon’s future hinges on two oceans and a warming atmosphere acting in concert—and that the dry season, where warming already explains most of the long-term drift toward compound drought and heat, is where the rainforest’s margin of safety is eroding fastest.

Subject of Research: Large-scale ocean–atmosphere drivers of compound drought–heat and flood–cold extremes in the Amazon Basin from 1982 to 2024

Article Title: Large-scale climate drivers of extreme compound events in the Amazon from interannual to long-term timescales (1982–2024)

Article References: Botetano, G., Espinoza, J. C., Takahashi, K., Gutierrez Villarreal, R. A., Marengo, J., & Wongchuig, S. (2026). Large-scale climate drivers of extreme compound events in the Amazon from interannual to long-term timescales (1982–2024). Climate Dynamics, 64(10), Article 427. https://doi.org/10.1007/s00382-026-08382-y

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08382-y

Keywords: Amazon Basin, compound extremes, drought, ENSO, El Niño, Tropical North Atlantic, Caribbean sea surface temperature, Hadley circulation, Walker circulation, river levels, GRACE, hydroclimatic variability