The AMOC carries warm, salty surface water northward, where it cools, densifies and sinks before returning southward as cold, deep water. The researchers calculated overturning strength at every latitude from 30° S to 65° N and expressed future changes as percentage reductions from a 1850–1899 reference. Ten-year running means were used to suppress short-term variability. To trace the basin-wide signal, they identified the first year in which a specified weakening threshold was exceeded at each latitude. A threshold spanning a particular percentage decline therefore formed a line across the Atlantic, and the slope of that line provided an estimate of how quickly the weakening signal moved southward.

Under the SSP5-8.5 scenario, the 5% weakening threshold took roughly three decades to travel from its northern onset to 30° S. The 25% threshold required about 45 years in depth space and 55 years in density space. Density space, which organizes circulation according to water density and therefore represents high-latitude water-mass transformation more directly, placed the origin of weakening farther north: between 51° and 61° N, compared with 45° and 51° N in depth space. The 25% threshold was reached in 2035 in the density-space analysis and in 2047 in the depth-space analysis. South of 40° N, however, the two representations produced broadly similar propagation speeds.

This difference matters for the potential use of high-latitude measurements as precursors of change farther south. In the density-space analysis, the model-average timing of 25% weakening at the latitude represented by the OSNAP array, around 57° N, preceded its appearance at the RAPID array near 26.5° N by 17 years under SSP5-8.5. The corresponding lead in depth space was only about five years. Even when the comparison began at 45° N, density space retained an 11-year lead over 26° N, compared with eight years in depth space. These are model-based lead times rather than validated forecasts of the real ocean, but they suggest that density-based indicators could provide a more useful framework for early-warning research.

Future forcing altered not only the magnitude of AMOC decline but also the structure of its propagation. By the end of the century, multi-model mean weakening at 51° N reached 63% in SSP5-8.5 and 41% in SSP1-2.6. At 26° N, the corresponding values were 47% and 32%, while at 30° S they were 25% and 22%. Under SSP5-8.5, a 25% decline emerged around 2036 at 51° N, 2055 at 26° N and 2095 at 30° S. The lower-emission scenarios, SSP1-2.6 and SSP2-4.5, showed a continuous reduction in propagation gradient as thresholds increased, whereas the higher-emission SSP3-7.0 and SSP5-8.5 cases tended toward a plateau at stronger levels of weakening.

That contrast may reflect two kinds of adjustment, the authors said. Under weaker forcing, the decline in propagation speed could progressively constrain weakening to the North Atlantic, preventing a strong southern signal from developing. Under stronger forcing, the circulation may reach a state in which a relatively constant minimum propagation speed persists. The analysis does not establish which process causes the slowdown, and the authors cautioned that it is unclear whether reduced propagation is itself responsible for the more geographically limited response or is a consequence of it. Pairwise comparisons also showed that differences among scenarios often became evident only after 2050, while some lower-emission experiments temporarily exhibited more weakening than higher-emission ones, likely reflecting model variability and scenario-specific aerosol forcing rather than a simple emissions-response relationship.

Individual models did not behave uniformly. In 10 of the 15 models, the weakening gradient decreased as the AMOC declined; two of those models, CESM2-WACCM and TaiESM1, eventually formed a plateau. CanESM5 and EC-Earth3 instead showed increasing gradients, while ACCESS-CM2, IPSL-CM6A-LR and MRI-ESM2-0 displayed no clear directional trend. Among models with multiple ensemble members, CNRM-CM6-1, MIROC6 and UKESM1-0-LL reproduced the overall slowing pattern. CanESM5 propagated weakening relatively slowly and almost uniformly, whereas IPSL-CM6-1 produced irregular threshold lines that made a simple linear slope less reliable. Ensemble averaging generally produced smoother, more coherent signals than individual realizations, highlighting the importance of internal variability in determining when a threshold is crossed.

The authors proposed that the slowing of AMOC weakening is consistent with an advective mechanism. A gradient of roughly 2 degrees of latitude per year corresponds to an approximate propagation speed of 0.6 centimetres per second, far too slow to be explained by internal Kelvin-wave propagation, which can travel at around 1 metre per second. A more plausible pathway is the transport of density anomalies by the mean circulation, including the Deep Western Boundary Current and interior routes. As the AMOC weakens, the pressure gradients that drive these currents may also weaken, reducing the speed at which the weakening signal travels. Supporting this interpretation, models with a historically stronger AMOC initially propagated the low-threshold weakening signal faster, although the relationship was statistically significant only at thresholds of 10% or less and should not be treated as a firm law.

Several limitations restrict how directly the findings can be applied to the real ocean. All 15 models used coarse, approximately 1-degree grids that did not resolve ocean eddies. Higher-resolution models may represent boundary currents and wave-mediated adjustment more accurately, potentially producing faster propagation than these results suggest. Ten models supplied only one ensemble member, and those models’ threshold lines could be distorted by multi-decadal variability. The method also depends on the chosen historical reference, which is imperfect because early observations are sparse. Nevertheless, the study demonstrates that AMOC weakening is not simply a simultaneous basin-wide reduction. It emerges first at high northern latitudes, then spreads southward at a rate that can change with forcing and model behavior, adding a new dimension to projections and to the search for possible early indicators of a major circulation change.

Subject of Research: Latitudinal propagation and changing speed of projected AMOC weakening in CMIP6 models

Article Title: AMOC weakening across latitude and time in CMIP6 future scenarios

Article References: Ashton-Key, H., Mecking, J., Marsh, R., Drijfhout, S., Oltmanns, M., & Sanchez-Franks, A. (2026). AMOC weakening across latitude and time in CMIP6 future scenarios. Ocean Science, 22(5), 3245-3286. https://doi.org/10.5194/os-22-3245-2026

Image Credits: AI Generated

DOI: 10.5194/os-22-3245-2026

Keywords: AMOC, Atlantic Ocean, CMIP6, climate models, ocean circulation, North Atlantic, climate scenarios, early warning signals, model projections, weakening, across, latitude

The analysis primarily used the CISE-LOCEAN database, whose stable-isotope samples have been analyzed at the LOCEAN isotope laboratory since about 1998. Associated salinity measurements generally came from calibrated CTD casts or discrete samples measured with a salinometer. The database combines isotope-ratio mass spectrometry with cavity ring-down spectroscopy, or CRDS; about 80% of its surface measurements were produced with CRDS, allowing the researchers to examine δ2H and d-excess in addition to δ18O. Quality-control procedures included reference-material insertions, duplicate analyses and flags for samples that may have evaporated during prolonged storage. The investigators also assessed possible offsets among analytical methods and excluded a group of 1998–1999 equatorial δ18O measurements with an estimated negative offset of about 0.15‰ from the relevant seasonal analysis.

Surface water is nearly conservative with respect to chemical and biological processes apart from fractionation during phase changes and meteoric inputs, making isotope-salinity relationships useful for tracing freshwater sources and water masses. Evaporation generally increases both salinity and the abundance of heavy isotopes, while precipitation and other freshwater inputs often lower salinity and are depleted in heavy isotopes. The research therefore fitted linear relationships between each isotope variable and practical salinity within oceanographic boxes, restricting salinity ranges to avoid the most strongly freshened waters directly affected by rivers, heavy rainfall or major sea-ice melt. Samples were grouped into four three-month seasons. To reduce the influence of uneven seasonal sampling on annual estimates, the authors averaged the seasonal regression coefficients rather than fitting one line to all available observations.

The resulting regional slopes varied substantially. For δ18O and δ2H, the isotope-salinity slopes were generally largest in the northern and western North Atlantic subpolar gyre and in the southern Indian Ocean, and smallest near the equator. In the tropical and subtropical Atlantic, slopes also tended to be lower in the western ocean than in the east. The annual regional relationships commonly explained about 40% to 70% of the observed variability, although d-excess at high latitudes and δ18O and δ2H near the equator were exceptions. In the latter setting, explained variance was often only 20% to 30%, with correlations marginally significant at p=0.02 or p=0.05. The d-excess regression explained about 40% of variance in equatorial Atlantic boxes and had a Pearson correlation of 0.63, significant at p=0.01. These spatial differences are compatible with varying contributions from evaporation, precipitation, river discharge, sea-ice melt, upwelling and the advection of isotopically distinct water masses.

The clearest seasonal departures from annual relationships appeared in the North Atlantic subpolar gyre, where repeated sampling around Iceland and the Irminger Sea provided comparatively dense coverage. In the best-sampled Irminger Sea box, salinity relationships explained a substantial share of the variation in δ18O and δ2H, with mean Pearson correlations of 0.69 and 0.67 across the four seasons; all seasonal correlations were significantly different from zero at p=0.01. The corresponding mean correlation for d-excess was only 0.35. Winter observations showed a slightly steeper isotope-salinity slope and more negative intercepts, especially in the western gyre, while spring d-excess values at a given salinity shifted toward lower values. The researchers linked these patterns to seasonal changes in Arctic-origin freshwater and the formation and melting of sea ice, but the data do not isolate the responsible processes.

That qualification is important because a simple sea-ice explanation does not account for every observed feature. Brine release can raise salinity while leaving the isotopic composition of the remaining liquid seawater nearly unchanged, allowing samples to move along an established isotope-salinity line. The spring shift in d-excess runs in the opposite direction from that simple expectation, and seasonal differences in d-excess slopes generally remained within their error bars, estimated at about 0.15‰ per practical salinity unit in the well-sampled gyre regions. Active winter air-sea exchange, vertical mixing and transport of freshwater could also affect the relationships. The study presents these as possible influences that would require isotope-enabled modeling rather than as mechanisms demonstrated by the observations.

The central equatorial Atlantic produced a contrasting seasonal structure. Neighboring boxes at 5°–12° N and 5° S–5° N contained cycles in salinity, δ18O, δ2H and d-excess with different timing, demonstrating that the seasonal signal north of the equator was not simply a repetition of the cycle immediately to the south. The equatorial box had a smaller apparent amplitude, and its estimated seasonal variance decreased after an adjustment for uneven spatial sampling. That correction reduced the standard deviation of the salinity cycle from 0.27 to 0.15 and the d-excess cycle from 0.19 to 0.14‰; for δ18O it fell from 0.027 to 0.015‰, and for δ2H from 0.19 to 0.16‰. After correction, δ18O remained correlated with salinity at the 90% confidence level, with r=0.71, whereas δ2H at r=0.60 and d-excess at r=−0.46 did not.

The equatorial timing is associated with the seasonal movement of the Intertropical Convergence Zone and the annual cycle of equatorial upwelling. The convergence zone is farthest south during January–March, while upwelling begins around May as the zone shifts northward. The eastward North Equatorial Counter Current develops later, during July–August, and can transport Amazon plume water toward the central Atlantic. Seasonal differences in δ18O, δ2H and d-excess north and south of the equator were therefore associated with changing rainfall, upwelling, current transport and continental freshwater influence. The analysis does not quantify the contribution of each process or establish a causal partition. Sampling bias remains an additional concern: in the 5° S–5° N box, the spatial standard deviation of monthly climatological salinity often exceeded 0.1, and some monthly isotope estimates had standard errors as high as 0.10‰ for δ18O, with typical errors about six times larger for δ2H and four times larger for d-excess.

Samples collected almost monthly from 2015 through 2022 at the Bermuda Atlantic Time-series Study site, located at 31°50′ N, 64°10′ W, provided a rare check on seasonality without the large spatial-representativeness problem affecting irregular ship-based sampling. The resulting series indicated a defined annual cycle in salinity, δ18O and δ2H, with lower isotope values during June–August, while d-excess was less clearly resolved because of the smaller number of observations and greater measurement uncertainty. Removing the estimated monthly cycle substantially reduced the variance in the isotope records. Even after applying a one-year running mean, however, standard errors averaged 0.026 in practical salinity and 0.018, 0.13 and 0.06‰ for δ18O, δ2H and d-excess, respectively. Storage in imperfectly sealed plastic bottles, possible evaporation, instrument reproducibility problems and monthly sample sizes of only about five or six limited the precision of the record.

The Bermuda observations also suggested that interannual isotope variability is not simply a mirror of salinity. Higher-than-normal δ18O and δ2H occurred around 2017–2018, whereas lower values appeared in 2019 and 2021, and some low-salinity periods were not accompanied by correspondingly low isotope values. The pattern partly resembled the North Atlantic Oscillation: winters with a positive index tended toward higher δ18O and δ2H and lower d-excess, while the more negative index in 2021 was associated with the opposite pattern. This was an association in a short, noisy record, not a demonstrated causal relationship. The authors state that a longer time series, smaller analytical errors and dedicated simulations would be needed to distinguish hydrological-cycle changes from effects of ocean circulation, surface stratification and upwelling. Their overall conclusion is that seasonal isotope-salinity variability is generally modest beside spatial variability, but meaningful in dynamically active regions such as the subpolar gyre and equatorial Atlantic. Denser near-surface observations, sustained time series and careful intercomparison among laboratories are therefore needed to improve understanding of how evaporation, precipitation, sea ice, rivers, glaciers and circulation shape upper-ocean isotope composition.

Subject of Research: Seasonal variation in surface-ocean stable isotopes and their relationships with salinity in the Atlantic and southwestern Indian Ocean

Article Title: Seasonal cycle in surface seawater isotopic composition

Article References: Reverdin, G., Waelbroeck, C., Goeme, L., Voelker, A. H. L., & Steen-Larsen, H. C. (2026). Seasonal cycle in surface seawater isotopic composition. Ocean Science, 22(5), 3225-3243. https://doi.org/10.5194/os-22-3225-2026

Image Credits: AI Generated

DOI: 10.5194/os-22-3225-2026

Keywords: surface seawater, oxygen-18, deuterium, deuterium excess, ocean salinity, North Atlantic, equatorial Atlantic, Indian Ocean, sea-ice melt, ocean upwelling, Seasonal, cycle

The research, published in Nature Communications by Catherine H. Gregory, Urs Hofmann Elizondo, Thibault Guinaldo, and Thomas L. Frölicher, uses a technique known as ensemble boosting to explore physically plausible alternative versions of the 2023 event. Rather than asking what did happen, the team asked what could have happened under the same large-scale climate conditions. The answer is sobering. In their boosted simulations, marine heatwaves emerged that lasted up to 579 days, reached maximum intensities of 4.5 degrees Celsius above the long-term climatology, and accumulated a total heat stress of 717 degree-days. By comparison, the observed 2023 event lasted roughly 240 days, peaked at about 2.9 degrees Celsius above normal, and accumulated 224 degree-days of cumulative intensity.

Ensemble boosting is a relatively new approach in the study of extreme events, and it addresses a persistent problem in climate science: state-of-the-art Earth system models are run as large collections of simulations, but only a handful of members will ever reproduce a truly rare extreme. The technique works by taking a coupled Earth system model and selectively perturbing the initial conditions of individual model members during periods that resemble the preconditioning of a real event. These perturbations are tiny, physically consistent nudges that represent the natural chaos of the atmosphere and ocean. If a nudged simulation goes on to produce an extreme event, that event is not an artifact; it is a legitimate alternative evolution of the same climate system, one that the dice of weather variability could plausibly have rolled.

Applied to the North Atlantic in 2023, the method produced a family of storylines that bracket the observed event and extend well beyond it. The most extreme simulated heatwaves were not freak occurrences requiring exotic physics. They arose from the same oceanic and atmospheric ingredients that produced the real event, arranged in somewhat less favorable configurations. This is the central message of the study: the margin between the 2023 heatwave we experienced and a substantially more severe outcome was narrower than most people would assume, and it was governed largely by the luck of day-to-day and season-to-season weather.

The detailed analysis of the longest and most intense boosted events reveals a set of contrasting mechanisms that conspire to build and sustain extreme ocean warmth. A central player is persistent high atmospheric pressure over the Euro-Atlantic region. When a high-pressure system settles over the North Atlantic, it suppresses cloud formation and calms the winds. Calmer winds mean less evaporative cooling, so the ocean loses less heat to the atmosphere through turbulent fluxes. Clearer skies, meanwhile, allow more incoming shortwave radiation to penetrate the sea surface and warm the upper ocean directly. The combination of reduced turbulent heat loss and enhanced solar heating acts like a lid and a magnifying glass at once, allowing heat to accumulate in the surface layers week after week.

The third mechanism identified by the researchers involves the redistribution of heat within the upper ocean. Marine heatwaves are not simply a story of local heating; they also depend on how heat is stirred, mixed, and transported. In the most extreme simulated events, changes in ocean circulation and mixing patterns kept warm water trapped near the surface or advected additional warmth into the affected region, reinforcing the surface anomaly. The interplay between these atmospheric drivers and oceanic redistribution helps explain why some boosted events persisted for well over a year and a half, far outlasting the observed event, while others of comparable peak intensity faded more quickly.

These findings matter because the consequences of a marine heatwave scale with both its intensity and its duration. Peak temperature anomalies determine the immediate physiological stress on organisms such as corals, fish larvae, and plankton, while cumulative intensity, often measured in degree-days, captures the prolonged exposure that can push ecosystems past tipping points. A heatwave lasting 579 days with a cumulative intensity more than three times that of the observed 2023 event would represent a fundamentally different level of stress for North Atlantic ecosystems, fisheries, and the communities that depend on them. The boosted storylines therefore function as a stress test, revealing the upper range of what present-day climate variability can deliver.

The study also places these present-day possibilities in the context of future warming, and this is where the implications become most striking. The researchers show that events comparable to the observed 2023 heatwave, which today still qualifies as an extreme outlier, become increasingly common as global warming progresses. In a warmer climate, the baseline temperature of the North Atlantic rises, so the same weather patterns that produced the 2023 anomaly would operate on a warmer starting point, pushing temperatures into ranges that would today seem almost implausible. In effect, the boosted ensemble offers a preview of the kinds of events that routine greenhouse warming will make ordinary. What was a near-miss in 2023 could, within decades, fall within the range of typical summer conditions.

The North Atlantic holds particular importance in the Earth system, influencing weather over Europe and North America, absorbing substantial amounts of heat and carbon dioxide, and hosting some of the most productive fisheries in the world. Prolonged extreme warmth in this basin can alter stratification and nutrient supply, shift the distribution of commercially important species, and contribute to atmospheric circulation anomalies that affect terrestrial heatwaves and droughts. The 2023 event already prompted intense scientific debate about its causes, with proposed explanations ranging from reduced aerosol pollution from shipping to El Niño development and unusual atmospheric circulation. This new study does not settle that debate, but it reframes it: whatever the underlying preconditioning was, the weather-dependent upper tail of possible outcomes was much more severe than what materialized.

Methodologically, the work demonstrates the growing value of storyline-based approaches to climate risk. Instead of assigning a single probability to an observed extreme, ensemble boosting generates a spectrum of physically self-consistent alternatives that illuminate which processes control an event’s severity and how close reality came to a worse outcome. For decision-makers in fisheries management, coastal planning, and marine conservation, such storylines are arguably more useful than abstract return periods, because they describe concrete scenarios that could plausibly unfold next time the same preconditioning arises. As computing resources expand and coupled models improve, techniques of this kind are likely to become a standard tool for assessing the risks posed by compound and record-shattering extremes, on land as well as at sea.

The broader takeaway is a reminder that the record books of the last few years should not be read as a ceiling. The 2023 North Atlantic marine heatwave was extraordinary, but the physics of the present-day climate system, probed systematically by the boosted simulations of Gregory and colleagues, permits events that are longer, hotter, and more cumulative in their impact. As global warming continues to raise the baseline, the gap between what is observed and what is possible will narrow from the other direction, with once-hypothetical extremes becoming the new benchmark. Preparing for the worst plausible outcome, rather than merely the worst recorded one, is emerging as an essential principle for understanding and adapting to the changing ocean.

Subject of Research: Alternative climate model scenarios of the 2023 North Atlantic marine heatwave and its potential for greater extremity

Article Title: The 2023 North Atlantic marine heatwave could have evolved into a far more extreme event

Article References: Gregory, C. H., Elizondo, U. H., Guinaldo, T., & Frölicher, T. L. (2026). The 2023 North Atlantic marine heatwave could have evolved into a far more extreme event. Nature Communications. https://doi.org/10.1038/s41467-026-78863-5

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78863-5

Keywords: marine heatwave, North Atlantic, ensemble boosting, Earth system model, ocean warming, climate extremes, sea surface temperature, Euro-Atlantic high pressure, cumulative intensity, climate change, physical oceanography, future warming

The controversy began in 2021, when researchers reported widespread intervals in Arctic sediments that were barren of excess thorium-230, an isotope produced in seawater from the decay of dissolved uranium, alongside strikingly low concentrations of the cosmogenic isotope beryllium-10, which rains down from the atmosphere. The original team interpreted these signals as evidence of a freshwater-filled Arctic Ocean: without salty, uranium-bearing Atlantic water, little thorium-230 would be produced, and a permanent ice cover would starve the sea of atmospheric beryllium-10. Critics countered that sudden pulses of sediment could simply have diluted both isotopes, leaving the ocean connected after all. The debate has raged ever since, because the interpretation carries enormous implications for how the global climate system behaved during ice ages.

The new research, led by Agathe Ollive of the Alfred Wegener Institute in Bremerhaven together with colleagues from Germany and Norway, sidesteps this dispute by turning to a cleverer tracer: the ratio of two beryllium isotopes, beryllium-10 and beryllium-9, measured in the reactive fraction of seafloor sediments. The beauty of this ratio lies in its resilience. While the concentrations of each isotope individually can be skewed by changing sedimentation rates and particle scavenging, normalizing beryllium-10 against beryllium-9 largely cancels out those effects. What remains is a fingerprint of the water masses themselves—essentially a chemical tag that records which waters bathed the seafloor when the sediments were deposited.

The logic of the test is elegantly simple. Today, the Arctic Ocean is fed by two very different beryllium sources. Atlantic water carries a dissolved beryllium-10 to beryllium-9 ratio of roughly 5 to 7 times ten to the minus eight atoms per atom, while Arctic rivers deliver beryllium with ratios below 1.5 times ten to the minus eight. If North Atlantic inflow had continued during the glacial intervals in question, the sedimentary ratio should have stayed near Atlantic values. But if the Arctic Mediterranean was truly cut off and gradually freshened by river discharge, the ratio should have collapsed toward riverine signatures. The team measured 84 samples from sediment cores spanning the central Arctic Ocean, the Lomonosov Ridge, the Yermak Plateau, the Barents Sea slope, the Morris Jessup Rise, the Nordic Seas and the North Atlantic, at water depths from about 1,073 to 2,802 meters.

The result was unambiguous. During the low-thorium glacial intervals, reactive beryllium-10 to beryllium-9 ratios fell to between 0.06 and 0.64 times ten to the minus eight—uniformly low values that are not merely riverine but even below the range of modern Arctic rivers. Remarkably, this signature appeared at every site, across all the major basins of the Arctic Mediterranean, despite huge differences in water depth, sedimentation rate and sediment source. Such basin-wide homogeneity is exactly what an isolated, freshened sea would produce, and it is utterly incompatible with an active Atlantic inflow, which would have delivered beryllium with ratios one to two orders of magnitude higher. During the warm interglacial of Marine Isotope Stage 5e, by contrast, the ratios rebounded to around 4 times ten to the minus eight in the Nordic Seas and about 1.4 times ten to the minus eight in the central Arctic, matching the signatures of Atlantic-influenced waters seen in modern deep Arctic sediments.

The team then extended the story into the open Atlantic by analyzing core MD95-2016, a site today bathed in dense overflow waters spilling across the Greenland-Scotland Ridge. Because this core contains a continuous oxygen isotope record, it could be aligned precisely to global stratigraphy. Both the Atlantic core and the Nordic Seas core recorded nearly identical beryllium ratios of about 5 times ten to the minus eight during the interglacial, confirming an open connection. But during the MIS6 glaciation, both records plunged. The researchers interpret the low value in the North Atlantic core as marking the moment of reconnection, when water with an extremely low beryllium isotope ratio—stored up in the isolated Arctic during millennia of isolation—suddenly overflowed the Greenland-Scotland Ridge and flooded into the Atlantic.

Crucially, the beryllium evidence converges with entirely independent tracers. In a central Arctic core, the glacial drop in beryllium-10 to beryllium-9 coincides with shifts in neodymium, hafnium and strontium isotopes away from North Atlantic endmember values and toward compositions characteristic of Siberian rivers draining the Putorana Basalts into the Kara Sea. The absence of dinocysts and planktic foraminifera in cores from the same intervals further points to a shutdown of Atlantic water and harsh surface conditions. When multiple unrelated proxy systems all swing in the same direction at the same time, the case for a genuine circulation reorganization becomes very difficult to dismiss.

The authors also ran a steady-state mass balance model to test whether anything other than isolation could explain the numbers. Under modern conditions, the North Atlantic inflow supplies roughly 70 percent of the beryllium-10 entering the Arctic Ocean, and the model reproduces the observed water-column ratio of about 5.14 times ten to the minus eight. Reducing atmospheric deposition under permanent sea ice lowers the ratio by only about 20 percent—nowhere near enough. Closing the Bering Strait actually raises the modeled ratio slightly, because the Pacific inflow carries a relatively low signature. Even catastrophic meltwater outbursts from ice-dammed lakes such as Lake Komi and Lake Yamal, with combined volumes exceeding 30,000 cubic kilometers, could push the ratio down only to about 1.56 times ten to the minus eight. Only a complete shutdown of Atlantic inflow reproduces the measured glacial values of around 0.85 times ten to the minus eight. The team likewise ruled out hyperpycnal sediment flows, nepheloid plumes, brine rejection and benthic fluxes from seafloor diagenesis as primary drivers, each on quantitative grounds.

The combined weight of the thorium and beryllium systems points to a single coherent picture: during parts of MIS6 and MIS4, the Arctic Mediterranean was largely cut off from the global ocean, its salts progressively replaced by river freshwater within perhaps less than 10,000 years, all sealed beneath a grounded ice shelf that blocked exchange across the shallow straits of the Greenland-Scotland Ridge. Such a state would have fundamentally altered deep-water renewal, strengthened stratification and limited oxygen penetration to the deep basins—conditions consistent with geochemical hints of past anoxia in both the Canadian and Eurasian Basins. It would also have meant that a key nursery of today’s Atlantic Meridional Overturning Circulation simply switched off.

Perhaps the most tantalizing implication lies at the end of each isolation episode. When the Arctic ice shelf collapsed and the straits reopened, the enormous reservoir of low-salinity water accumulated over millennia would have been released through Fram Strait in short order. Whether such pulses were powerful enough to disrupt North Atlantic thermohaline circulation and trigger the abrupt cooling events recorded in ice cores remains an open question, and one the authors flag as a priority for future work. What is already clear is that the Arctic Ocean of the ice ages was not simply a colder version of today’s sea. It was, at times, a fundamentally different world—a giant, dark, freshwater basin sealed beneath ice, waiting for the lid to come off.

Subject of Research: Geochemical evidence for episodic isolation and freshening of the Arctic Mediterranean from the North Atlantic during late Pleistocene glaciations

Article Title: Episodic isolation of the Arctic Mediterranean from the North Atlantic during late Pleistocene glacials

Article References: Ollive, A., Geibert, W., Matthiessen, J., Loftfield, J., Lachner, J., Koll, D., Patton, H., Vogt, C., & Adolphi, F. (2026). Episodic isolation of the Arctic Mediterranean from the North Atlantic during late Pleistocene glacials. Communications Earth & Environment, 7(1), Article 821. https://doi.org/10.1038/s43247-026-04133-3

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04133-3

Keywords: Arctic Ocean, North Atlantic, beryllium isotopes, thorium-230, Pleistocene glaciations, ice shelf, paleoceanography, freshwater, AMOC, Greenland-Scotland Ridge, marine sediments, climate

The central insight of the study is that ocean biology is not a passive passenger in the climate system. Chlorophyll and other pigments inside phytoplankton absorb incoming sunlight within the upper ocean, and the amount of light they intercept depends on how much of the pigment is present in the water. During bloom years, when phytoplankton concentrations are high, more solar radiation is absorbed within the shallow late-summer mixed layer of the North Atlantic. That extra absorption warms the sea surface. In years when blooms are weaker, more sunlight penetrates deeper into the water column or reflects back to space, and the surface stays relatively cooler. In other words, the microscopic life floating in the ocean can act like a dimmer switch on sea surface temperatures, and those temperature anomalies can then ripple through the atmosphere.

The researchers found that this bloom-driven warming is accompanied by a distinctive pattern in atmospheric pressure. Higher pressure develops near the region of the bloom, while lower pressure appears over Europe. This pressure contrast strengthens the westerly winds that flow from the Atlantic toward the European continent. Because those winds carry moisture inland, a stronger westerly flow means more moisture is delivered to central Europe. The result, according to the study, is a wetter central Europe during bloom years. More rainfall during the growing season means more water available for plants, and the study reports that gross primary productivity, the total amount of carbon that land ecosystems fix through photosynthesis, rises by roughly 15 to 20 percent during the growing season in response.

The magnitude of that response is striking. A 15 to 20 percent swing in the productivity of one of the world’s most agriculturally important regions, driven in part by the abundance of microscopic algae in a distant ocean, would represent a substantial source of year-to-year variability. Central Europe hosts extensive croplands and forests, and fluctuations in water availability during the growing season have direct consequences for harvests, carbon accounting, and ecosystem health. If bloom conditions in the North Atlantic can be monitored or predicted, the findings suggest they could provide an early indicator of growing-season conditions on land, complementing existing seasonal forecasting tools that rely on sea surface temperatures and atmospheric circulation patterns.

A key strength of the work lies in how the team tested whether the link between blooms and European productivity is causal rather than coincidental. The researchers used a chlorophyll-interactive Earth system model, a type of climate model in which the optical properties of the ocean respond dynamically to simulated phytoplankton concentrations. In this configuration, the model can represent the feedback loop in which blooms absorb more sunlight, alter sea surface temperatures, and influence the atmosphere. When the model was run with this interactive chlorophyll, the chain of events connecting blooms to wetter European summers and higher land productivity emerged. When chlorophyll was instead held fixed at its climatological average, removing the year-to-year influence of blooms on ocean optics, the picture changed in an instructive way.

In those control experiments with prescribed chlorophyll, sea surface temperature anomalies still developed, indicating that other processes can produce similar ocean warming patterns. However, the European productivity response was largely absent. This asymmetry is the crux of the paper’s argument. If the atmospheric circulation and rainfall anomalies over Europe depend on the interactive influence of chlorophyll on the ocean’s absorption of sunlight, then marine ecosystems are playing an active role in shaping terrestrial climate variability, not merely responding to it. The authors conclude that variability in marine ecosystems is therefore a potentially important pathway shaping productivity on land, a conclusion that challenges the conventional treatment of ocean biology and land vegetation as separate, non-communicating components of the global carbon cycle.

The findings add to a growing body of work on what climate scientists call biologically mediated feedbacks. Phytoplankton have been shown in previous studies to influence phenomena ranging from the evolution of multi-year La Niña events to the development of marine heatwaves, and the new study extends this line of research to the North Atlantic to European sector. The physical logic is elegant: pigments change where solar energy is deposited in the ocean, the resulting temperature anomalies reshape pressure patterns, pressure patterns steer winds, and winds transport moisture that plants convert into growth. Each link in that chain is well established in isolation, but demonstrating that the full sequence operates strongly enough to move continental-scale productivity by double-digit percentages is a significant step.

There are important caveats and open questions. The evidence presented relies heavily on model experiments with a chlorophyll-interactive Earth system model, and the fidelity of such models in representing the vertical distribution of chlorophyll, the depth of the mixed layer, and the coupling between ocean optics and atmospheric circulation remains an active area of research. Observational confirmation of the full causal chain, from bloom intensity to sea surface temperature to European rainfall to gross primary productivity, will require coordinated analysis of satellite ocean-color records, in situ measurements, atmospheric reanalysis data, and land carbon flux observations. The study’s authors also note that the mechanism operates most clearly in the shallow late-summer mixed layer, when phytoplankton are concentrated near the surface and their optical influence is strongest, which means the effect may vary seasonally and regionally.

Nevertheless, the implications are broad. Climate models used for projections of future carbon uptake and food security often simplify or omit the optical effects of marine ecosystems, and this work suggests that doing so may miss a real source of variability in land productivity. If phytoplankton blooms in the North Atlantic can modulate European hydroclimate, then changes in ocean biology driven by warming, stratification, or nutrient shifts could feed back onto continental water supplies and vegetation in ways not currently anticipated. The study also highlights the deep interconnection of Earth’s systems: the green of the ocean and the green of the land, usually studied by different communities with different models, are linked by sunlight, wind, and water. As the authors put it in their conclusion, marine ecosystem variability is a potentially important pathway shaping productivity on land, and recognizing that pathway may improve both our understanding of natural climate variability and our ability to anticipate the growing seasons of the future.

Subject of Research: The influence of North Atlantic phytoplankton blooms on European hydroclimate and terrestrial productivity

Article Title: North Atlantic chlorophyll blooms modulate European hydroclimate and terrestrial productivity

Article References: Yang, Y.-M., Park, J.-H., Park, J.-Y., An, S.-I., Kug, J.-S., Yeh, S.-W., Kwon, E.-Y., Lee, J.-Y., Wang, B., & Li, T. (2026). North Atlantic chlorophyll blooms modulate European hydroclimate and terrestrial productivity. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04018-5

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04018-5

Keywords: phytoplankton, chlorophyll, North Atlantic, hydroclimate, gross primary productivity, Earth system model, sea surface temperature, Europe, climate variability, ocean biology, westerly winds, carbon cycle

The study, published in the journal Weather and Climate Dynamics by Aleksa Stanković, Rodrigo Caballero and Gabriele Messori, tackles a long-standing puzzle in atmospheric science. By most bulk measures, such as zonally averaged eddy kinetic energy or median annual surface winds, the Southern Ocean is the stormier hemisphere. Its vast, unbroken expanse of water, largely free of continental barriers, allows storms to circle the planet with little interference. Yet when it comes to the extremes, the picture flips: the strongest surface winds consistently occur over the Northern Hemisphere oceans, and above all over the North Atlantic. Understanding why the hemisphere with the calmer average winds produces the fiercest storms is essential for improving projections of how wind extremes will change as the climate warms.

To answer the question, the team turned to ERA5, the most advanced atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts, which blends observations with a numerical weather model to create a physically consistent record of the atmosphere. The researchers focused on the winter months, December through February in the Northern Hemisphere and June through August in the Southern Hemisphere, when cyclones in both hemispheres reach their peak intensity. They restricted their analysis to the satellite era beginning in 1979, because satellite observations are crucial for reliably capturing the sparsely monitored Southern Ocean, and extended the record through 2020.

Identifying the top 100 extremes in each basin required a careful, two-step procedure. First, the team defined storm tracks as regions where the annual 98th percentile of daily maximum surface wind speed exceeds 18 metres per second, a criterion that isolates three comparable basins: the North Atlantic, the North Pacific and the Southern Ocean. Areas within 300 kilometres of the coasts of Greenland and Antarctica were excluded, since the ferocious winds there arise mainly from small-scale katabatic and barrier processes rather than the large-scale cyclone dynamics of interest. Then, for every winter day, the researchers computed a wind severity index over contiguous footprints of extreme winds. The index, widely used in insurance loss modelling, scales with the cube of the wind speed relative to the local climatological threshold, a choice with physical grounding because the cube of wind speed represents the flux of kinetic energy. The 100 days with the highest severity in each basin defined the top 100 extremes, and each event was linked to the nearest objectively tracked cyclone centre.

The heart of the analysis is a time-lagged composite technique. Rather than examining storms one by one, the researchers averaged the atmospheric fields of all 100 extreme events in each basin, aligning them by the location of the cyclone centre and the time of maximum surface winds. Because lines of latitude converge toward the poles, the fields were regridded onto radial grids centred on each storm. Statistical significance was assessed by generating 100 random composites for each basin, in which the real cyclone locations were paired with randomly chosen winter dates, yielding 10,000 random samples, with anomalies accepted as significant only after correction for false discovery.

The composites revealed a strikingly consistent large-scale recipe. A few days before the peak winds, a pre-existing cyclone is already present downstream, situated poleward and eastward of the developing extreme storm. The young cyclone begins as a weak, spatially limited pressure anomaly that grows in size and intensity as it approaches its older neighbour. By the time of maximum winds, the two systems merge into a broad area of low sea-level pressure. In fact, roughly half of the top 100 extremes in each basin, 49 in the North Atlantic, 53 in the North Pacific and 56 in the Southern Ocean, were formally classified as multi-centre cyclones by the tracking algorithm around the time of peak winds. The pre-existing storm is not a passive bystander: it advects high potential vorticity air equatorward, sharpening the upper-level potential vorticity gradients and strengthening the jet streak, the narrow band of ferocious winds near the tropopause, within which the new storm develops and crosses the jet.

Where the hemispheres diverge is in the numbers, not the narrative. Northern Hemisphere extremes develop under stronger upper-level potential vorticity gradients, more powerful jet streaks and broader regions of high mid-tropospheric Eady growth rate, a classical measure of how rapidly baroclinic instabilities amplify in a sheared, stratified atmosphere. Higher Eady growth rates signal a greater potential for rapid intensification, and the observations bear this out dramatically. The rate at which eddy kinetic energy rises in the two days before peak winds is far greater in the Northern Hemisphere, and explosively deepening storms, those whose central pressure falls by more than 24 hectopascals in 24 hours, account for 69 percent of North Atlantic and 75 percent of North Pacific extremes but only 38 percent of Southern Ocean ones. Since vertical wind shear below the jet is the main driver of the hemispheric difference in growth rates, the stronger jets of the Northern Hemisphere, reinforced by the pre-existing downstream cyclones, emerge as the key to the hemisphere’s more violent wind extremes.

To test whether these dynamical differences trace back to the underlying geography of each basin, the team ran sensitivity experiments with ISCA, an open-source intermediate-complexity climate model developed at the University of Oxford and collaborators. Encouragingly, even at the coarse T42 resolution used, ISCA reproduced both the hemispheric asymmetry in extreme winds and the correct ranking of basins, with the North Atlantic strongest, followed by the North Pacific and the Southern Ocean. This suggests the asymmetry is driven primarily by large- and planetary-scale processes rather than by fine-scale features the model cannot resolve. The researchers then systematically altered the model’s boundary conditions across 11 experiments, comparing a realistic control configuration with setups in which sea-surface temperatures were smeared into zonal bands, made hemispherically symmetric, and combined with a planet stripped of mountains.

The results were remarkably clean. When sea-surface temperatures were zonalized across the tropics and extratropics, the difference in extreme winds between the North Atlantic and North Pacific nearly vanished, shrinking by 82 percent, as warming spread over the Pacific storm track and cooling weakened the Atlantic jet. Removing the interhemispheric contrast in sea-surface temperatures and flattening the orography reduced the Atlantic–Southern Ocean asymmetry by 83 percent, through a combination of weaker Atlantic extremes and stronger Southern Ocean ones. Across all experiments and basins, the winter 98th percentile of mid-tropospheric Eady growth rate correlated with the 98th percentile of surface wind speed with a Pearson coefficient of 0.97, significant at the 1 percent level. In other words, one number, the potential for storms to grow quickly, largely determines how extreme the winds can become, regardless of which ocean they form over.

The study comes with honest caveats. The focus on large scales leaves out mesoscale and boundary-layer processes that can contribute to surface wind extremes, and the analysis deliberately set aside the detailed mechanics of cyclone merging and storm–storm interaction. ISCA, lacking a realistic representation of clouds, could not reproduce the pre-existing downstream cyclone in the evolution of its own most extreme individual storms, even though it captured the climatological relationship between growth rates and winds. Still, the broader message stands: the recipe for the planet’s most extreme oceanic windstorms is written once and applied everywhere, with a helper storm downstream, a strong jet overhead and a fast-deepening cyclone at the centre. The only thing that varies between hemispheres is how generously the ocean basins supply the ingredients, a conclusion that should help sharpen both weather forecasting and the climate models on which future windstorm projections depend.

Subject of Research: Large-scale dynamics of extreme surface winds in extratropical cyclones across the Northern and Southern Hemisphere storm tracks

Article Title: Interhemispheric perspective on the most extreme surface winds in the storm tracks

Article References: Stanković, A., Caballero, R., & Messori, G. (2026). Interhemispheric perspective on the most extreme surface winds in the storm tracks. Weather and Climate Dynamics, 7(3), 1507-1523. https://doi.org/10.5194/wcd-7-1507-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1507-2026

Keywords: extratropical cyclones, storm tracks, extreme winds, Eady growth rate, ERA5 reanalysis, jet stream, potential vorticity, Southern Ocean, North Atlantic, North Pacific, ISCA climate model, explosive cyclogenesis

The team’s focus was the Atlantic Multidecadal Variability, or AMV, a slow oscillation in North Atlantic sea surface temperatures that swings between warm and cool phases over decades. When the AMV is in its positive phase, a characteristic ‘horseshoe’ pattern emerges at the ocean surface: the subpolar gyre south of Greenland warms strongly, and a band of warm water spreads across the tropical North Atlantic, lagging slightly behind. Decades of research have linked this pattern to European summer climate, yet the observational record of such multidecadal variability is barely 45 to 70 years long — far too short to cleanly separate the tropical and extratropical contributions to the phenomenon using observations alone.

To overcome that fundamental limitation, the researchers turned to one of the largest decadal prediction experiments ever assembled: an 80-member hindcast ensemble built with the low-resolution Max Planck Institute Earth System Model, MPI-ESM-LR. The members were initialised every November from 1960 to 2019, with the ocean nudged toward the EN4 ocean reanalysis through an ensemble Kalman filter and the atmosphere constrained toward observed conditions. Each member was run for at least ten years beyond its start date, and a subset of sixteen members was extended to twenty. By comparing this initialised ensemble with fifty uninitialised historical runs from the MPI Grand Ensemble, the team could isolate exactly what initialisation — the act of telling the model what the ocean is doing right now — buys in terms of predictive skill.

The first result concerns the ocean itself. In the uninitialised historical simulations, the model reproduced the horseshoe pattern of AMV sea surface temperatures only weakly, with the subpolar gyre signal considerably underdone and displaced toward the south and east. In the initialised hindcasts, by contrast, the subpolar gyre anomalies were dramatically stronger and closely matched the observations from the HadISST dataset and the ERA5 reanalysis. When the researchers defined AMV phases using ERA5 rather than the model’s own index, the strong subpolar signal survived intact across forecast lead years one to seven — meaning those temperatures are highly predictable — while the tropical signal essentially vanished, revealing that AMV-driven tropical SST anomalies are poorly predicted at these lead times.

That contrast matters enormously because the two halves of the AMV drive European summer weather through completely different atmospheric pathways. The extratropical pathway is grounded in classic theory: warm subpolar sea surface temperatures act as a diabatic heat source, and the atmosphere responds with a shallow cyclonic circulation a quarter-wavelength downstream, producing a low pressure anomaly west of Great Britain and Ireland. This feature, closely related to the East Atlantic Pattern of variability, advects warm air polewards and has been linked to hotter summers in central Europe. The tropical pathway is more exotic: warm tropical Atlantic waters generate upper-level divergence, launching Rossby waves — vast undulations in the jet stream — that arc from the Caribbean toward the extratropical North Atlantic and Europe.

When the team examined sea level pressure composites, a striking divergence appeared. Observations from HadSLP and ERA5 showed the expected negative pressure anomaly west of Britain and Ireland during positive AMV summers, but the uninitialised historical ensemble produced almost nothing in the extratropics, even though its tropical response was comparable to reality. The initialised hindcasts, however, did produce the cyclonic anomaly — in the right place, but with an amplitude notably weaker than observed. Crucially, when the hindcasts were evaluated against ERA5-defined AMV phases, this extratropical signal persisted, indicating genuine predictability. Correlation skill maps confirmed it: the highest skill for multi-year mean sea level pressure sat precisely off the west coast of Europe, where the AMV response is strongest and statistically significant.

Yet the weakness of the modelled response opened a door to one of climate science’s most perplexing puzzles: the signal-to-noise paradox. In a well-behaved forecast system, the correlation between the ensemble mean and observations should be no higher than the average correlation between the ensemble mean and its individual members. In the North Atlantic-Europe sector, this is routinely violated — the real atmosphere appears more predictable than the models themselves suggest. By sampling 100,000 single-member timeseries of East Atlantic pressure against the ERA5 AMV index, the researchers found that the observed regression slope was stronger than 99 percent of the hindcast samples, and the ratio of predictable components exceeded two with high significance. Most remarkably, the joint distribution revealed a correlation of minus 0.50 between the weak AMV response and the paradox’s diagnostic errors, directly linking the underestimated ocean-driven signal to the reliability failure.

The story grew richer still when the researchers climbed into the upper troposphere at 200 hectopascals. In reanalyses, the surface cyclonic response extends upward as a deep, near-equivalent-barotropic column over the eastern Atlantic. In the model simulations, however, the dominant upper-level response instead resembles a Rossby wave train emanating from the Caribbean — the tropical pathway. By varying the length of the rolling averaging window from one to fifteen years, the team showed why: tropical Atlantic SSTs carry relatively more interannual variability, while extratropical SSTs dominate on longer timescales, and the correlation between the two basins strengthens with window length. On interannual timescales, both models and reanalyses agree on the Caribbean wave train; on decadal timescales, reanalyses shift toward the extratropical response while the model, whose surface response is too weak, remains dominated by the tropical mechanism.

The implications are profound. The study demonstrates that dynamically driven, multi-year predictability for European summers genuinely exists — rooted in ocean temperatures that models can observe and initialise — and that large ensembles are essential to realise it. But it also shows that the extratropical diabatic heating response, though simulated, is severely underestimated, and that this deficiency cannot simply be fixed by adding more ensemble members or post-processing the output, because the two competing mechanisms interfere destructively in the upper troposphere. The authors point toward higher atmospheric and oceanic resolution, better representation of ocean-atmosphere coupling and eddy feedback, and targeted bias reduction as the most promising routes forward. Until the signal-to-noise paradox is solved, they conclude, large-ensemble forecasts with appropriate correction will be necessary to deliver the summer predictions that a continent increasingly vulnerable to extreme heat urgently needs.

Subject of Research: Decadal predictability of European summer climate through Atlantic Multidecadal Variability mechanisms in large-ensemble climate model hindcasts

Article Title: Predictability of European summer climate: the influence of competing mechanisms related to Atlantic Multidecadal Variability

Article References: Williams, N. C., Müller, W. A., & Pinto, J. G. (2026). Predictability of European summer climate: the influence of competing mechanisms related to Atlantic Multidecadal Variability. Earth System Dynamics, 17(4), 1007-1023. https://doi.org/10.5194/esd-17-1007-2026

Image Credits: AI Generated

DOI: 10.5194/esd-17-1007-2026

Keywords: Atlantic Multidecadal Variability, decadal prediction, European summer climate, sea surface temperature, subpolar gyre, Rossby waves, signal-to-noise paradox, MPI-ESM-LR, climate models, North Atlantic, predictability, diabatic heating

The two dominant players in North Atlantic climate are the Atlantic Multidecadal Variability, or AMV, a basin-wide fluctuation in sea surface temperatures, and the North Atlantic Oscillation, or NAO, the pressure seesaw between the Azores high and the Icelandic low. Both are major sources of predictability on seasonal to decadal timescales, influencing Atlantic hurricane frequency, shifts in the Intertropical Convergence Zone, drought in the Sahel, and summer climate across Europe and North America. Yet the physical processes and feedback mechanisms linking the oceanic AMV to the atmospheric NAO have remained fiercely debated, with proposed drivers ranging from internal ocean circulation to anthropogenic aerosols, greenhouse gases and stochastic atmospheric forcing. What has been missing, the researchers argue, is a compact mathematical description that captures how these variables actually interact over decades.

To find one, the team employed the Sparse Identification of Nonlinear Dynamics algorithm, known as SINDy, a sparse regression method that learns governing equations directly from time-series data. The researchers trained the algorithm on monthly indices of the AMV, the NAO and North Atlantic precipitation anomalies derived from the ERA5 reanalysis dataset spanning January 1950 to December 2022. A twelve-month running average was applied to filter out high-frequency noise, and the candidate library of functions included constant, linear and quadratic polynomial terms, yielding thirty possible terms across three equations. A LASSO optimiser with sparsity thresholding forced the regression to retain only the most important terms, while a bootstrapping ensemble of one thousand resampled datasets ensured the identified coefficients were robust. Validation and testing used independent segments of the ERA20C reanalysis from 1900 to 1949, data the models had never seen during training.

The procedure generated 344 unique candidate models of varying complexity, and the team faced a subtle selection problem. Simpler models with thirteen or fewer terms either collapsed onto stable fixed points, converged on rigid limit cycles, or blew up entirely, none of which resembles the restless variability of the real North Atlantic. Models with fourteen to twenty terms were stable but produced unnaturally sparse power spectra with delta-like peaks, unlike the broad-band spectra seen in observations. Only models with twenty-one or more terms exhibited chaotic attractors and physically realistic variability. The researchers ultimately selected a twenty-six-term model sitting on the Pareto front, the optimal trade-off between accuracy and complexity, whose fifty-thousand-year simulated trajectories reproduce the irregular, Lorenz-like character of the observed climate system.

Remarkably, the decadal timescales embedded in these equations were never explicitly taught to the model. Because SINDy fits instantaneous tendencies, the emergence of a pronounced quasi-periodic twenty-year oscillation across all three variables is an entirely emergent property. The model’s power spectra show strong peaks near twenty years and thirty-five years, matching significant signals in the observed NAO and precipitation records, along with weaker peaks near 13.5 and 15.5 years. The team interprets the twenty-year mode as a damped oscillatory ocean mode, set by internal ocean dynamics but excited by decadal NAO forcing, consistent with earlier inverse modelling studies that identified oscillatory eigenmodes of North Atlantic sea surface temperature at periods of roughly twenty and thirty-seven years.

The most striking discovery lies in the structure of the equations themselves. Cross-terms multiplying precipitation with either the AMV or the NAO, written as AP and NP products, appear among the largest and most robust coefficients across the entire ensemble of 344 candidate models, persisting even in the sparsest formulations. Because precipitation serves as a proxy for both latent heat release in the atmosphere and freshwater fluxes into the ocean, these terms point to diabatic processes acting as a dynamical bridge between ocean and atmosphere. In the AMV equation, the negative NP term suggests that heavy rainfall over the Labrador Sea region, combined with a positive NAO, freshens the surface ocean, increases stratification, weakens deep convection and thereby dampens the overturning circulation and the AMV itself.

Feedbacks onto the atmosphere appear equally important. In the NAO equation, the positive NP term indicates that enhanced convective precipitation near the southern node of the NAO reinforces a negative NAO state through diabatic heating that lowers surface pressure, echoing recent causal studies of oceanic feedbacks onto the winter NAO. Conversely, the model suggests that the positive feedback of North Atlantic sea surface temperature onto the NAO, in which the familiar SST tripole strengthens the meridional temperature gradient and the zonal winds, is strongest precisely when the precipitation pattern favours a positive NAO state. In other words, the response of the atmosphere to the ocean appears to be conditioned on the sign of rainfall anomalies, a state-dependent coupling that conventional linear analyses would miss entirely.

The predictive credentials of the twenty-six-term model are substantial. Initialised every six months from observed data and integrated forward with a fourth-order Runge-Kutta scheme, the model achieves anomaly correlation coefficients of 0.86 for the AMV and 0.54 for the NAO at one-year lead times on training data, and 0.93 and 0.52 respectively on the unseen early-twentieth-century test data. Most impressively, the model shows significant skill in predicting North Atlantic precipitation anomalies out to a decade ahead, with correlations reaching 0.7 at one-year leads on test data. The authors attribute this precipitation skill to the fact that the decadal precipitation index varies in phase with the damped twenty-year ocean oscillation, so that slow, predictable ocean responses to NAO forcing propagate directly into rainfall patterns over the ocean and adjacent continents.

The researchers are careful to note the limits of their framework. The equations encode dynamical couplings but do not by themselves distinguish cause from effect, and the mechanistic pathways they propose are supported by consistency with existing theory rather than uniquely proven. The characteristic fifty-to-seventy-year signal of the AMV is not well captured, likely because the training record is too short, and external influences such as volcanic eruptions and lunar cycles were not considered. The authors also acknowledge that stochastic processes present in the real system are only implicitly represented through the nonlinear terms, and they propose comparing their models against Linear Inverse Models and coupled climate simulations as future work.

Even so, the study represents a compelling demonstration that machine learning can do more than forecast: it can illuminate physics. As the journal’s editorial statement observes, the paper exemplifies how equation discovery transforms AI from a black box into a hypothesis-generating scientific instrument. If the identified feedbacks hold up under scrutiny, the implications extend beyond academic understanding. Correctly initialised versions of these low-order models could sharpen decadal forecasts of rainfall over the North Atlantic and neighbouring regions such as Europe and North America, offering societies a rare glimpse of climate conditions years in advance. In an era when decadal prediction remains one of climate science’s hardest challenges, three short equations learned by an algorithm may prove to be an unexpectedly powerful key.

Subject of Research: Data-driven discovery of coupled ocean-atmosphere equations governing decadal North Atlantic climate variability

Article Title: New insights into decadal climate variability in the North Atlantic revealed by data-driven dynamical models

Article References: Nicoll, A. J., Christensen, H. M., Huntingford, C., & Smith, D. (2026). New insights into decadal climate variability in the North Atlantic revealed by data-driven dynamical models. Earth System Dynamics, 17(4), 1061-1079. https://doi.org/10.5194/esd-17-1061-2026

Image Credits: AI Generated

DOI: 10.5194/esd-17-1061-2026

Keywords: North Atlantic, Atlantic Multidecadal Variability, North Atlantic Oscillation, equation discovery, SINDy, machine learning, decadal prediction, precipitation feedbacks, climate variability, ocean-atmosphere coupling, ERA5 reanalysis, latent heat

The scale of the analysis is formidable. The researchers examined 13,266 distinct datasets, spanning 54 climate models run under five shared socio-economic pathways, from the ambitious SSP119 scenario to the high-emissions SSP585. Twelve ocean, sea-ice, and atmospheric variables were scrutinised, including sea-surface temperature and salinity, sea-ice concentration, mixed-layer depth, sea-surface height, and the overturning streamfunctions that track the Atlantic Meridional Overturning Circulation, or AMOC. Crucially, the team replaced the expert visual inspection used in an earlier CMIP5 catalogue with a fully automated, reproducible detection algorithm, harnessing modern computing power and machine-learning tools such as the unsupervised clustering method HDBSCAN to isolate candidate regions of at least one million square kilometres.

The detection pipeline works in phases. Monthly model output is first averaged to yearly values and regridded onto a common Gaussian grid, and the historical runs are stitched to the scenario runs while checking that no artificial jump appears at the 2014 seam between them. Four different region-finding approaches then flag promising areas, using thresholds iteratively relaxed from the 99.99th percentile down to the 85th, and comparing variability against preindustrial control runs. Finally, six formal sets of criteria, labelled Ab1, Ab2, and St1 through St4, decide whether a region hosts an abrupt change on decadal timescales or a slower state transition too large to be attributed to the forcing alone. The criteria demand, for example, that a jump exceed 4.5 standard deviations of preindustrial variability, or that sea ice decline by at least 95 percent across an area of five million square kilometres.

The results are grouped into 11 categories, and their composition is telling. Roughly 45 percent of the surprises involve sea-ice cover, 29 percent mixed-layer depth, 19 percent ocean currents, and 7 percent atmospheric systems such as the Intertropical Convergence Zone. The single largest category concerns the transition to large, year-round ice-free areas in the Arctic, detected in 22 models. In the previous CMIP5 catalogue, only five models showed a winter sea-ice collapse, and only under the most extreme scenario, with thresholds between 4.5 and 8.2 degrees Celsius of global warming. In CMIP6, the corresponding warming levels fall to a 68 percent confidence interval of 2.5 to 4.1 degrees, meaning winter Arctic sea-ice disappearance could plausibly begin by the end of this century even under moderate emissions.

The physics behind these sea-ice surprises involves a well-understood web of positive feedbacks. As open water replaces ice, the lower atmosphere moistens and warms, increasing downward longwave radiation and inhibiting freezing. Thinner winter ice then lowers the surface albedo, boosting springtime shortwave absorption, while enhanced ocean heat uptake further erodes the ice pack. The catalogue also documents how sea-ice loss cascades into other variables: in several models, the disappearance of the ice lid unleashes abrupt shifts in sea-surface salinity, near-surface air temperature, and even sea-surface height, as the ocean and atmosphere suddenly exchange heat and freshwater far more vigorously than before.

Perhaps the most consequential finding concerns the North Atlantic. Ten models show a collapse of winter deep convection and mixed-layer depth in the subpolar gyre and Nordic Seas, often beginning around 2020 and in some cases even at warming levels near one degree. In nine models, this convective collapse is followed by a transition of the AMOC to an extremely weak state in which the cell associated with North Atlantic Deep Water formation has essentially vanished, leaving only a shallow, wind-driven residual overturning of about three Sverdrups. The onset of AMOC decline begins between 1980 and 2020 in these models, and the five-Sverdrup boundary is crossed between 2100 and 2140 in most of them. Strikingly, in the MRI-ESM2 model the collapse proceeds even under the low-emissions SSP126 scenario, a novel result suggesting the overturning may become largely independent of the forcing once a tipping point is passed.

The sequencing matters as much as the outcome. By comparing cumulative distributions of the warming level at which each change is maximal, the authors show that the mixed-layer collapse precedes the AMOC shutdown by roughly 0.3 to 0.5 degrees Celsius of global warming, equivalent to about twenty to thirty years. This is a clear example of a tipping point cascade: freshening and reduced heat loss stratify the subpolar North Atlantic, deep mixing fails, and the resulting buoyancy changes then starve the overturning of the dense water it needs. Notably, the freshening is driven by a weakening AMOC transporting less salty water northward, because meltwater from the Greenland Ice Sheet is not included in CMIP6 simulations, meaning the real-world freshwater forcing could be even stronger.

Not every surprise in the catalogue carries equal weight, and the authors are candid about model limitations. An abrupt shift in the North Atlantic Current pathway in the GISS-E2-1-H model appears tied to a known cold bias east of Newfoundland. A reorganisation of the Intertropical Convergence Zone in four models stems from the notorious double-ITCZ bias, though the underlying cloud-convection feedbacks exist in nature. A projected 50 percent intensification of the Antarctic Circumpolar Current is likely spurious, since coarse-resolution models cannot capture eddy saturation, which buffers the current against strengthening winds. By contrast, abrupt sea-ice loss in the Southern Ocean linked to the onset of deep convection, and the eastward expansion of the Ross Gyre, are corroborated by high-resolution regional modelling and observations of the Weddell Polynya mechanism.

To characterise timing, the team built probability density functions for the global warming level at which each surprise’s change is maximal, applying flexible 20-to-50-year windows to account for methodological uncertainty. These distributions show the frequency of surprises rising steeply below two degrees of warming and remaining high between two and four degrees. Importantly, the authors stress that these are conditional distributions describing when changes peak, not probabilities that a given event will occur, a deliberate choice to avoid politicised threshold debates. They also note that if a tipping point underlies a surprise, it is crossed before the temperature at which the transition is fastest.

The overall message is a sharpened warning. Compared with the 2015 CMIP5 catalogue, which identified 37 abrupt shifts, the new analysis finds nearly twice as many, occurring earlier and at lower warming levels, particularly for Arctic sea ice, North Atlantic convection, and the AMOC. Part of the increase reflects more extended simulations running to 2300 and improved detection methods, but the authors argue that genuinely higher sensitivity in CMIP6 also plays a role, and that observational constraints and the absence of Greenland meltwater both point toward underestimation rather than exaggeration of the risk. Because the criteria remain somewhat subjective and individual surprises can be stochastic, appearing in some ensemble members but not others, any single case demands caution. Yet the pattern across 54 models is difficult to dismiss: the newest generation of climate models suggests that strong nonlinear surprises, from an ice-free Arctic year-round to a shutdown of the Atlantic overturning, may arrive sooner, and at lower levels of warming, than the scientific community had previously assessed.

Subject of Research: Abrupt climate changes and state transitions in ocean, sea-ice, and atmospheric variables in CMIP6 future scenarios

Article Title: Catalogue of strong nonlinear surprises in ocean, sea-ice, and atmospheric variables in CMIP6

Article References: Angevaare, J. R., & Drijfhout, S. S. (2026). Catalogue of strong nonlinear surprises in ocean, sea-ice, and atmospheric variables in CMIP6. Earth System Dynamics, 17(4), 1081-1115. https://doi.org/10.5194/esd-17-1081-2026

Image Credits: AI Generated

DOI: 10.5194/esd-17-1081-2026

Keywords: CMIP6, climate tipping points, Arctic sea ice, AMOC, mixed-layer collapse, abrupt climate change, North Atlantic, deep convection, climate models, nonlinear feedbacks, sea-ice albedo, Earth System Dynamics

The work, carried out by Christian M. Grams of the Federal Office of Meteorology and Climatology MeteoSwiss, updates and thoroughly documents a regime definition first introduced in 2017. Where traditional European regime classifications were built separately for individual seasons, most famously the four canonical winter regimes identified in the 1990s, the year-round framework handles the entire calendar in one consistent system. The key trick is a normalization of anomalies in 500-hectopascal geopotential height, a standard measure of the large-scale flow at mid-altitudes of the atmosphere. Because winter anomalies are naturally much larger in amplitude than summer ones, an unnormalized analysis across all seasons would be dominated by winter. By dividing the low-pass filtered height anomalies by a seasonally varying measure of their climatological variability, the method removes the seasonal difference in amplitude while preserving the spatial shape of the flow, allowing summer and winter patterns to be compared on equal footing.

From this normalized data, an empirical orthogonal function analysis combined with fuzzy clustering identified seven distinct regimes, and the number seven was not chosen arbitrarily. The author tested configurations ranging from two to eleven clusters and used an objective similarity index, the maximum anomaly correlation coefficient between cluster patterns, to judge when clusters stopped being genuinely distinct. With four clusters the familiar canonical regimes reappear, but pushing to seven reveals finer structure while keeping the patterns well separated. Beyond seven, an eighth weak pattern emerges that closely resembles existing regimes, and the similarity between clusters jumps sharply. The seven regimes split into two families: three cyclonic regimes, Atlantic Trough, Zonal, and Scandinavian Trough, dominated by negative height anomalies and enhanced storm activity, and four blocked regimes, Atlantic Ridge, European Blocking, Scandinavian Blocking, and Greenland Blocking, dominated by positive anomalies and high pressure.

One of the study’s central contributions is an objective life cycle definition. Rather than simply labeling each day with a regime category, the method computes a continuous index for each regime, a standardized projection of the current atmospheric state onto the regime pattern. When this index exceeds a threshold of 1.0 for at least five days, a life cycle is identified, complete with onset, maximum, and decay stages. Crucially, life cycles can overlap, so one regime can be building while another is still dissolving, which matches how the atmosphere actually behaves. Roughly thirty percent of all time steps belong to no regime at all, corresponding to flow situations close to climatology. This continuous, dynamical view transforms regimes from a static classification into something closer to living entities with births, mature phases, and deaths.

The practical payoff of this framework is considerable. Weather regimes modulate surface conditions across entire continents for days to weeks, exactly the window where conventional weather forecasts lose skill but before seasonal averages take over. They shape wind speeds critical to Europe’s renewable power supply, including the dreaded Dunkelflaute episodes when low winds and weak sunshine coincide, and they modulate heat waves, cold spells, storm series, and atmospheric river landfalls. Previous work has linked prolonged heat-induced mortality to European blocking and winter stress on the UK health system to Greenland blocking. The new study shows that the most extreme regime life cycles, those lasting more than a month, coincide with Europe’s most extreme seasons. A Zonal regime life cycle in early 1990 lasted an extraordinary 73 days amid severe winter storms, while the longest Scandinavian Blocking life cycle began in July 2003 and lasted 32 days during Europe’s record-breaking heat. A 54-day Greenland Blocking episode starting in November 2010 brought a brutal cold wave.

The regimes also reveal a striking seasonal rhythm. Cyclonic regimes together account for up to forty percent of winter days but only about twenty-two percent in July, while blocked regimes dominate summer, exceeding fifty percent of days in June through August. European Blocking and Scandinavian Blocking alternate in preference: the former peaks in relative frequency in winter and spring, the latter in summer and autumn. Inter-annual variability is enormous. The early 1990s saw a run of strongly zonal years, 2010 brought a dominant negative North Atlantic Oscillation winter, and the hot years 2021 and 2022 featured frequent blocking. No single year matches the climatological average, underscoring how much year-to-year chaos overlays the seasonal cycle.

The most provocative question the study tackles is whether climate change is shifting regime frequencies. Extending the identification back to 1950 using the backward extension of the ERA5 reanalysis, the author finds that inter-annual variability dominates and significant trends are scarce, with one exception: Scandinavian Blocking shows a significant positive trend, concentrated in summer and autumn. But here the story takes a subtle turn. The 500-hectopascal geopotential height across the regime domain has been rising at about 5.4 geopotential meters per decade since 1979, consistent with the thermal expansion of the troposphere as the planet warms. When the regime identification is repeated with this area-averaged trend removed, the significant Scandinavian Blocking trend vanishes entirely. The apparent increase in summer blocking over Scandinavia, the analysis suggests, is likely primarily a thermodynamic signature of global warming rather than a genuine change in atmospheric circulation.

This finding raises what the author describes as an almost philosophical question: in a warmer climate, should a blocked regime be defined as a circulation anomaly deviating from the climatological background, or as a region of very high pressure with strong impacts on the surface? From an impact perspective, the thermodynamic effect of warming alone can already partly explain the recent increase in high-pressure episodes reported in some studies, and higher background temperatures likely amplify the local consequences of blocking, particularly for summer heat waves. The study also cautions that simple linear trend analyses are highly sensitive to the period chosen, and proposes that non-stationary methods, such as the LOESS filters increasingly used by European meteorological services, will be needed to cleanly separate natural variability from climate change signals in future regime research.

The paper is as much an infrastructure project as a scientific analysis. It provides a comprehensive technical appendix documenting every step of the method, from the Lanczos low-pass filtering to the iterative life cycle identification criteria, and the complete regime dataset from 1950 to the present has been openly released on Zenodo along with auxiliary scripts. The author shows that switching from the older ERA-Interim reanalysis to ERA5 changes the attribution of only a tiny fraction of time steps, confirming the robustness of the framework. With ECMWF and MeteoSwiss now working toward operational use of the year-round regimes in sub-seasonal forecasting and climate monitoring, these seven atmospheric archetypes are poised to move from the research literature into the daily toolkit of forecasters, energy traders, and health planners across Europe.

Subject of Research: Year-round weather regimes and their life cycles, variability, and trends in the North Atlantic European region

Article Title: A life cycle definition of year-round weather regimes in the North Atlantic European region

Article References: Grams, C. M. (2026). A life cycle definition of year-round weather regimes in the North Atlantic European region. Weather and Climate Dynamics, 7(3), 1641-1680. https://doi.org/10.5194/wcd-7-1641-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1641-2026

Keywords: weather regimes, atmospheric blocking, North Atlantic, Europe, ERA5 reanalysis, sub-seasonal forecasting, weather regime life cycles, Scandinavian Blocking, climate trends, geopotential height, heat waves, renewable energy