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

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

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

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

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

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

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

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

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

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

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

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

Image Credits: AI Generated

DOI: Not provided

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

The Hadley cell is a vast overturning circulation in which air rises near the equator, flows poleward aloft, descends in the subtropics, and returns to the equator near the surface. Its poleward edge is not fixed. From one winter to the next, the boundary of the Southern Hemisphere branch over the Indian Ocean can shift noticeably toward or away from the pole, and climate scientists have documented a longer-term tendency for tropical circulations to widen as the planet warms. Because the descending branch of the cell helps anchor the subtropical winds and storm tracks of the Southern Indian Ocean, any movement of that edge has the potential to rearrange where storms generate waves and where those waves travel.

To pin down that connection, the team, led by F R Thanvi of the Department of Physical Oceanography at Cochin University of Science and Technology, together with R Sajeev, L. Sheela Nair of the National Centre for Earth Science Studies, and J K Lix, needed a reliable way to measure the cell’s position. They used outgoing longwave radiation, or OLR, the infrared heat emitted by the Earth and atmosphere as observed from satellites. Deep convective clouds near the equator emit low OLR values, while the clear, dry, subsiding air of the subtropics emits high values. By applying an OLR threshold, the researchers could determine the latitude of the poleward edge of the Southern Hemisphere Hadley cell over the Indian Ocean for each winter, and then classify individual years as expansion years, when the edge moved poleward, or contraction years, when it retreated equatorward.

With those years identified, the team turned to wave power, the flux of energy carried by ocean waves, which depends on wave height and period. They drew on the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts, a state-of-the-art reconstruction of past weather and ocean conditions, accessed through the Copernicus Climate Data Store. Crucially, they separated the wave field into two components: wind waves, generated locally by winds blowing over the North Indian Ocean, and swell, the long-period waves that were generated by distant storms and have traveled far from their birthplace. Composite analysis, in which the wave fields of expansion years and contraction years are averaged separately and compared, revealed that the two components respond very differently to Hadley cell shifts.

The swell response proved far more pronounced than the wind-wave response, and it was not uniform across the basin. The eastern North Indian Ocean, including the waters off India’s east coast and the Bay of Bengal, emerged as the clear hotspot of swell variability tied to the cell’s movements. In years when the Southern Hemisphere Hadley cell expanded, swell power in this region was typically enhanced; in contraction years, it was reduced. That asymmetry matters for practical reasons. The eastern North Indian Ocean hosts busy shipping lanes, fishing fleets, ports, and a growing interest in wave energy conversion, so knowing which large-scale atmospheric pattern favors energetic swell winters could improve seasonal planning and coastal hazard assessment.

But identifying a correlation is only the first step. To understand the physical chain of cause and effect, the researchers deployed three complementary techniques: composite analysis, regression analysis, and swell-source back-tracing. Back-tracing is a diagnostic method that follows swell waves backward along their great-circle propagation paths, effectively asking where the energy arriving at a given point came from. The results were unambiguous in their broad strokes: the swell that reaches the eastern North Indian Ocean during boreal winter predominantly originates in the central and eastern Southern Indian Ocean, thousands of kilometers away, where strong winter storms and the westerly wind belt generate long-period waves that race northward with remarkably little loss of energy.

Yet the back-tracing also revealed an important subtlety. Although the central-eastern Southern Indian Ocean is the climatological source region, the exact location of the generating storms varies from year to year. In certain winters, the swell sources are displaced from their usual position, and that displacement modifies the typical anomaly pattern that would otherwise be expected from the Hadley cell shift alone. In other words, the Hadley cell sets the stage, but the precise geography of the Southern Ocean storms determines the final script. This interplay between large-scale circulation shifts and the year-to-year wanderings of storm tracks helps explain why some individual winters depart from the average relationship.

The study also uncovered a role for one of the most famous climate oscillations on the planet. During expansion years, the swell response was further modulated by the El Niño-Southern Oscillation, specifically by La Niña conditions, the cool phase of the tropical Pacific marked by unusually cold sea surface temperatures in the central and eastern equatorial Pacific. The relationship between Hadley cell expansion and enhanced swell power was most clearly expressed when expansion coincided with La Niña. This makes physical sense, because ENSO is known to influence the extent and intensity of the Hadley circulation, and La Niña tends to strengthen the trade winds and reorganize convection across the Indo-Pacific region, with consequences that ripple into the wind fields of the Southern Indian Ocean where the swell is born.

Contraction years told a different story. Rather than a single dominant modulation, the changes in swell power during these winters were associated with contrasting wind conditions over distinct source regions. When the cell’s edge retreats equatorward, the wind patterns over the various swell-generating areas of the Southern Indian Ocean diverge from one another, and the net swell arriving in the north depends on the balance of these regional wind anomalies. This finding underscores that the Southern Hemisphere winter atmosphere is not a monolith: different patches of the storm belt can behave in opposite ways, and the swell climate of the North Indian Ocean integrates all of them.

Taken together, the results suggest a coherent dynamical linkage running from the meridional position of the Southern Hemisphere Hadley cell, through the remote wind forcing over the Southern Indian Ocean, to the displacement of swell source regions, and finally to the swell energy delivered to the eastern North Indian Ocean. The authors frame Hadley cell variability as a contributing large-scale dynamical control on the swell climate of the region, one that operates alongside better-known influences such as the Indian Ocean Dipole and ENSO. For engineers assessing wave-energy potential along the Indian coast, for forecasters anticipating winter swell events, and for coastal planners weighing long-term changes in wave conditions, the message is that the answer may lie as far away as the descending branch of a tropical circulation over the southern Indian Ocean. As the tropical belt continues to broaden under greenhouse warming, understanding how these circulation shifts translate into wave power will only grow in importance, and this study provides a template for tracing that connection from the top of the atmosphere down to the breaking waves on a distant shore.

Subject of Research: Influence of Southern Hemisphere Hadley cell shifts on winter swell wave power variability in the North Indian Ocean

Article Title: Atmospheric circulation driven variability of wave power in the North Indian Ocean: the role of Hadley cell shifts

Article References: Thanvi, F. R., Sajeev, R., Nair, L. S., & Lix, J. K. (2026). Atmospheric circulation driven variability of wave power in the North Indian Ocean: the role of Hadley cell shifts. Ocean Dynamics, 76(11), Article 110. https://doi.org/10.1007/s10236-026-01868-7

Image Credits: AI Generated

DOI: 10.1007/s10236-026-01868-7

Keywords: Hadley circulation, swell waves, wave power, North Indian Ocean, Southern Indian Ocean, boreal winter, La Niña, ENSO, outgoing longwave radiation, ERA5 reanalysis, swell back-tracing, coastal wave climate

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

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

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

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

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

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

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

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

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

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

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

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

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06529-9

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

The study, published in Communications Earth & Environment, draws on multi-decadal observations spanning 1993 to 2025, giving researchers an unusually long window through which to watch a fishery unravel. Rather than attributing the decline to a single cause, the team, led by Seongsik Park of Pukyong National University’s Research Center for Ocean Industrial Development together with colleagues at the National Institute of Fisheries Science and Pukyong National University, traced the collapse through a formal statistical framework known as sequential mediation analysis. This approach allowed them to quantify how rising ocean temperatures transmit their effects through distinct ecological channels before ultimately suppressing squid catches.

The first of those channels is the slow, cumulative erosion of suitable thermal habitat. Japanese flying squid are a short-lived, fast-growing cephalopod species whose population dynamics are acutely sensitive to water temperature, which governs spawning success, egg development, and the growth of paralarvae. As long-term warming has progressively shifted the temperature envelope of the East Sea, the fraction of the region that remains thermally hospitable to the squid has contracted. This kind of habitat degradation does not produce dramatic headlines in any single year, but its steady accumulation steadily narrows the reproductive base of the population, leaving it with less capacity to absorb shocks.

The second pathway is far more abrupt. The researchers identified a striking teleconnection, a long-distance climate link, in which an intensified early-summer La Niña phase of the El Niño-Southern Oscillation amplifies marine heatwaves over the major squid fishing grounds during the following autumn and winter. Marine heatwaves, defined as prolonged periods when sea surface temperatures exceed seasonal thresholds, have become more frequent and intense worldwide as the ocean absorbs the bulk of the excess heat trapped by greenhouse gases. In the East Sea, these events arrive precisely when squid populations are concentrated in the fishing grounds, subjecting them to acute thermal stress that can impair physiology, disrupt migration, and elevate mortality across entire cohorts.

The third pathway is perhaps the most ecologically revealing, because it exposes a trade-off that warming oceans impose on vulnerable species. As waters warmed, Seriola quinqueradiata, the Japanese amberjack, a powerful predatory fish adapted to warmer conditions, rapidly expanded into the squid’s habitat. The study frames this predator influx as an ecological trade-off linked to the same thermal changes that stress the squid: conditions that become more favorable for warm-adapted fish become simultaneously less survivable for the squid, which now faces both direct physiological strain and intensified predation pressure. The combination means the squid is squeezed from two directions at once, its habitat shrinking and its enemies multiplying.

What makes the analysis particularly compelling is the way these three mechanisms interlock. The mediation analysis demonstrated that rising ocean temperatures drive the squid collapse not through a single direct effect but through these interconnected pathways operating in sequence and in parallel. Gradual warming erodes the population’s baseline resilience, heatwaves deliver acute shocks that can decimate a year class, and the predator influx converts thermal stress into additional mortality. A population weakened by one mechanism has little margin left to withstand the others, which is precisely the signature of a cascading collapse rather than a simple decline.

The implications extend well beyond the East Sea. The authors describe the squid fishery’s trajectory as an early warning for climate-driven species replacements in warming oceans, a phenomenon likely to recur wherever commercially important species sit near the warm edge of their thermal tolerance. Short-lived pelagic species such as squids are especially instructive in this regard, because their populations turn over within a single year, meaning that environmental signals are translated into catch statistics almost immediately. Long-lived fish can buffer bad years with surviving adults; squid cannot, so their fisheries function as sensitive barometers of ocean change.

Perhaps the most sobering finding comes from the study’s forward-looking component. Climate model projections indicate that under unabated warming, the risk of the regional squid fishery reaching a zero-catch state increases substantially by the 2040s, and critically, this elevated risk emerges across multiple emissions scenarios. That robustness across scenarios matters: it suggests that even substantial near-term reductions in greenhouse gas emissions may not fully avert the threat to this fishery within the next two decades, although the pace and severity of decline would still depend on the emissions pathway humanity follows. The window for adaptation, however, is closing.

The researchers argue that these findings underscore the urgent need for transboundary, climate-adaptive management of the fishery. Japanese flying squid migrate across national jurisdictions in the Northwest Pacific, meaning that no single country can protect the population alone. Climate-adaptive management would require fishing quotas and seasonal closures that respond dynamically to ocean conditions rather than fixed historical baselines, coordinated monitoring of marine heatwave forecasts, and international agreements that anticipate shifting stock distributions instead of reacting to them after catches have already crashed. The study was supported by the Korea Institute of Marine Science & Technology Promotion, funded by the Ministry of Oceans and Fisheries of Korea, reflecting the growing institutional recognition that fisheries science must now be climate science.

For the fishing communities that depend on the East Sea’s squid grounds, the message of this research is difficult to ignore. The collapse they have witnessed is not the result of overfishing alone or of natural variability alone, but of a climate system reshaping the thermal architecture of the ocean faster than the species within it can adapt. The Japanese flying squid, a species that has sustained one of the region’s defining fisheries, is being displaced by warming waters, battered by heatwaves, and hunted by newcomers from the south. Whether its fishery survives the 2040s will depend not only on the trajectory of global emissions but on whether the nations bordering these waters can act, together and quickly, on the warning that the ocean has already delivered.

Subject of Research: Climate-driven collapse of the Japanese flying squid fishery in the East Sea through thermal habitat loss, marine heatwaves, and predator influx

Article Title: Cascading fishery collapse associated with thermal habitat degradation, marine heatwaves, and predator influx

Article References: Park, S., Yoon, S., Lee, I.-C., & Kim, K. (2026). Cascading fishery collapse associated with thermal habitat degradation, marine heatwaves, and predator influx. Communications Earth & Environment. https://doi.org/10.1038/s43247-026-04110-w

Image Credits: AI Generated

DOI: 10.1038/s43247-026-04110-w

Keywords: Japanese flying squid, fishery collapse, marine heatwaves, La Niña, ocean warming, thermal habitat degradation, Japanese amberjack, East Sea, climate change, mediation analysis, fisheries management, species replacement

The research focuses specifically on offshore rapid intensification, meaning the dramatic strengthening that occurs close to land rather than in the open ocean. This distinction matters enormously for disaster preparedness. A storm that intensifies rapidly a thousand kilometers from any coastline is a problem for shipping; a storm that does the same thing a few hundred kilometers offshore, as it bears down on the Philippines, Vietnam, or southern China, is a potential catastrophe. Recent work by other research groups has documented a global increase in rapid intensification events in offshore regions, and a separate migration of tropical cyclones toward coastlines, which makes understanding the year-to-year variability of near-shore intensification an urgent scientific and practical priority.

Using the International Best Track Archive for Climate Stewardship, the standard global database of tropical cyclone positions and intensities, together with atmospheric reanalysis products from the ERA5 dataset and ocean reanalysis data from SODA version 3, the team compiled a record of offshore rapid intensification events across the western North Pacific. They then examined how the annual counts of these events fluctuate from one year to the next and searched for the climate fingerprints behind those fluctuations. A crucial early finding emerged from this analysis: offshore rapid intensification does not simply track the overall level of tropical cyclone activity in the basin. A year can be busy with storms yet quiet with respect to near-shore explosive intensification, or the reverse, which means the two phenomena are governed by partly independent sets of climate drivers.

Through a systematic screening of candidate climate indices, the researchers identified two dominant players. The first is the El Niño–Southern Oscillation, the famous Pacific climate pendulum, represented here by the La Niña index. The second is a less familiar but increasingly influential pattern: the boreal spring Hadley circulation over the Indo-Pacific warm pool, abbreviated IPWP_HC. This circulation describes the large-scale vertical and meridional overturning of air over the warmest ocean waters on the planet during the Northern Hemisphere spring, months before the peak typhoon season arrives. When the team fed both indices into a multiple linear regression model, the combined picture explained a substantial fraction of the year-to-year variability in offshore rapid intensification, and, remarkably, each driver stamped its influence on a different part of the basin.

The La Niña signal concentrates its effects near the Philippines. During La Niña-like conditions, the tropical Pacific reorganizes in ways that raise the heat content of the upper ocean in the Philippine Sea region. Upper-ocean heat content, often quantified as the integrated thermal energy stored in the layer above the thermocline, is a critical fuel gauge for intensifying hurricanes. A deep, warm layer resists the cooling that a storm’s own winds would otherwise stir up through mixing, allowing the cyclone to keep drawing energy from the sea surface without throttling itself. The study shows that when the La Niña index points to these conditions, offshore waters near the Philippines carry more of this thermal reserve, tilting the odds toward rapid intensification for storms passing through the region.

The spring Indo-Pacific warm pool Hadley circulation, by contrast, exerts its strongest influence over the South China Sea, and it does so mainly through dynamical rather than thermodynamic channels. A stronger or differently configured spring Hadley circulation leaves behind an enhanced low-level cyclonic circulation over the South China Sea during the following typhoon season. This background rotation does two things at once. It helps storms spin up by providing ambient vorticity that the developing vortex can exploit, and it reshapes the vertical structure of the atmosphere in ways that favor intensification. The researchers found that both the La Niña index and the spring Hadley circulation index are associated with increased mid-level relative humidity and reduced vertical wind shear in their respective regions, two of the most consistently identified preconditions for rapid intensification in the global literature.

Vertical wind shear, the change in wind speed and direction with height, is the great destroyer of developing tropical cyclones. Strong shear tilts the storm’s core, vents its heat and moisture away from the center, and disrupts the organized eyewall convection needed for explosive growth. Mid-level humidity matters because dry air entrained into a storm’s circulation evaporates, cools, and suppresses the deep convective bursts that drive pressure falls at the center. By independently promoting a moist, low-shear environment, each climate driver creates a window in which a passing storm can cross the threshold into rapid intensification. The regional separation of these windows, one anchored near the Philippines by ocean heat content and the other over the South China Sea by circulation dynamics, is the study’s central and most actionable insight.

The implications for seasonal forecasting are significant. Because the spring Indo-Pacific warm pool Hadley circulation is established months before the typhoon season peaks, it functions as a potential precursor signal, giving forecasters a head start of one to two seasons in anticipating whether the South China Sea will be unusually prone to offshore intensification events. Similarly, the state of the ENSO system, which is monitored continuously by climate centers worldwide, provides guidance on the Philippine Sea sector. A two-parameter statistical model of the kind the authors constructed cannot predict individual storms, but it can sketch the seasonal landscape: which sub-basins are likely to be loaded with the ingredients that turn ordinary typhoons into monsters just before landfall.

The study also fits into a broader and rapidly evolving research landscape. Other recent work has linked ENSO to rapid intensification globally, documented shifts in where and when western North Pacific storms intensify under different ENSO flavors, and connected decadal patterns such as the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation to intensification behavior in the basin. By demonstrating that offshore events obey their own interannual rules, distinct from basin-wide storm counts, the new analysis adds an important layer of nuance. It suggests that operational agencies and risk modelers who estimate coastal typhoon threat from storm frequency alone may be systematically missing a key dimension of the hazard.

For the tens of millions of people living along the rim of the South China Sea and the Philippine Sea, the difference between a gradually strengthening storm and one that detonates offshore can be measured in lives. Rapid intensification compresses the time available for evacuation, and history is full of storms whose final-day transformation turned manageable events into disasters. This research does not eliminate that uncertainty, but it narrows it. By identifying two independently verifiable climate signals, one oceanic and thermal, one atmospheric and dynamical, and mapping exactly where each one loads the dice, the study converts a chaotic-seeming year-to-year pattern into a structure that seasonal forecasts can begin to exploit. As offshore intensification events continue to rise worldwide, that kind of foresight will only grow more valuable.

Subject of Research: Interannual variability of offshore tropical cyclone rapid intensification in the western North Pacific

Article Title: Interannual variability of tropical cyclone rapid intensification in offshore regions of the western North Pacific

Article References: Chen, Z.-X., Guo, Y.-P., & Chen, X. (2026). Interannual variability of tropical cyclone rapid intensification in offshore regions of the western North Pacific. Climate Dynamics, 64(11), Article 444. https://doi.org/10.1007/s00382-026-08405-8

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08405-8

Keywords: tropical cyclones, rapid intensification, western North Pacific, ENSO, La Niña, Hadley circulation, South China Sea, Philippine Sea, vertical wind shear, upper-ocean heat content, seasonal prediction, Climate Dynamics

Chaetognaths occupy a pivotal position in marine food webs. Roughly 133 valid species are recognized worldwide, and after copepods they are typically the most numerically dominant group in marine zooplankton communities, accounting for between 5 and 30 percent of total zooplankton abundance. They feed aggressively on smaller plankton, structuring and regulating pelagic ecosystems and contributing to the biological pump, the process by which carbon is transported from the surface ocean to the deep sea. Because different species are associated with specific water masses and hydrographic conditions, chaetognaths also serve as sensitive biological indicators of environmental change, which makes them ideal subjects for tracking how tropical coastal ecosystems respond to climate variability.

The research team, led by M. C. Franco-Gordo of the University of Guadalajara, sampled a coastal oceanographic station in Bahía de Navidad, Jalisco, where the seafloor lies about 150 meters down. Every month from November 2010 to December 2016, before dawn and typically around 4:30 in the morning, the researchers towed a one-meter conical net with 250-micrometer mesh from roughly 40 meters depth to the surface. A calibrated flowmeter measured the volume of water filtered on each tow, while conductivity-temperature-depth profilers recorded vertical profiles of temperature, salinity, and, during the first half of the study, dissolved oxygen. Surface chlorophyll-a concentrations were measured in the laboratory as a proxy for phytoplankton biomass, and coastal upwelling was quantified using the Bakun upwelling index, including a fifteen-day lagged version designed to capture the delay between physical forcing and biological response.

The six-year window was fortuitously timed to capture the full drama of ENSO variability. A prolonged La Niña event dominated the beginning of the series, from November 2010 to March 2012, followed by a long neutral period from April 2012 to October 2014, and then an extended El Niño from November 2014 to May 2016 that included the exceptionally strong 2015–2016 event. A shorter La Niña returned at the end of the series in late 2016. Overlaid on this interannual seesaw was the region’s pronounced seasonal cycle: a mixed season from January to May, when coastal upwelling brings cool, nutrient-rich water to the surface, and a stratified season from July to November, when the water column warms, freshens under monsoon rains, and becomes vertically layered.

In total, the team identified 145,077 chaetognath specimens, representing fifteen species in three families and ten genera. Just three species dominated numerically: Zonosagitta bedoti, Parasagitta euneritica, and Flaccisagitta enflata together accounted for 73.2 percent of total abundance, and with Aidanosagitta septata the top four species made up nearly 90 percent. Remarkably, these dominants persisted across every season and every ENSO phase, a signal of ecologically resilient local populations with broad environmental tolerance. The community was overwhelmingly tropical in character, with about 56 percent of recorded species having tropical biogeographic distributions, and the sampling captured roughly 87.5 percent of all chaetognath species known from the Central Mexican Pacific.

The abundance story unfolded in three acts. During the early La Niña, chaetognath numbers were at their lowest. They climbed steadily through the neutral years, peaking spectacularly in 2013, when the highest abundances of the entire series were recorded between January and July. During the strong El Niño of 2015–2016, abundance declined moderately, but species richness told a different story: it peaked during the warm event, reaching up to 12 species per sampling date. This inversion—more species but fewer individuals during El Niño, and fewer species but booming populations during neutral conditions—contrasts sharply with other zooplankton groups in the region, such as copepods, euphausiids, and fish larvae, which typically decline during El Niño.

To disentangle the environmental drivers, the researchers deployed a battery of statistical tools. Permutational multivariate analysis of variance confirmed significant differences in community structure between mixed and stratified seasons and among the three ENSO phases, although the interaction between the two was not significant, and dispersion tests urged some caution in interpretation. Redundancy analysis, constrained by eight environmental gradients, explained 25.6 percent of the total variance in community structure. Its first axis, correlated strongly with temperature at 10 meters depth, chlorophyll-a, and the lagged upwelling index, reflected the seasonal upwelling cycle, while the second axis captured ENSO-driven interannual variability. Species-level generalized linear models reinforced the picture: chlorophyll-a was the most frequently selected predictor, followed by the fifteen-day upwelling index, underscoring how tightly these predators are coupled to the productivity fueled by coastal upwelling.

The species-specific responses were ecologically telling. Zonosagitta bedoti and Parasagitta euneritica were associated with strong upwelling and low temperatures, thriving in the cool, productive mixed season. In contrast, Serratosagitta bierii, Aidanosagitta septata, Aidanosagitta regularis, and Serratosagitta pacifica were linked to moderate-to-high temperatures. Flaccisagitta enflata and its relative F. hexaptera reached peak abundance during stratified periods and El Niño conditions, coinciding with anomalously warm water, deeper mixed layers, and a subsurface hypoxic layer lying near 45 meters depth. F. enflata is known to tolerate a wide thermal range, from 15 to 30 degrees Celsius, and to adjust its metabolism to ambient temperature, which likely explains its success under warm, low-oxygen conditions. Indicator species analysis added finer texture: S. pacifica typified the La Niña stratified season, A. septata the El Niño stratified season, and F. hexaptera and S. bierii the neutral stratified season.

Among the more striking discoveries was the second recorded occurrence of Sagitta bipunctata in the Central Mexican Pacific, the first having been reported 53 years earlier. This circumglobal species is typically regarded as oceanic, so its appearance in nearshore waters is remarkable, and its sporadic records, along with those of S. pacifica and Pterosagitta draco, suggest that rarer species are more sensitive to hydrographic variability and dispersal constraints than the resilient dominants. The study also documented exceptional chlorophyll-a peaks during the mixed seasons of the neutral years, in April 2013 and April 2014, with zooplankton biovolume tracking the same rhythm, low during stratified periods and comparable across ENSO phases.

The overarching conclusion is that seasonal hydrographic variability, not ENSO, is the primary architect of chaetognath community structure in this tropical coastal system, with ENSO anomalies exerting secondary but clearly detectable effects. El Niño-related stratification appears to open the door to additional species while limiting overall biomass, whereas La Niña enhances productivity but favors a reduced set of dominant taxa. As the authors note, continued long-term monitoring, complemented with genetic tools, ecological niche modeling, and physiological assays, will be essential to clarify the mechanisms behind chaetognath persistence and to predict how these voracious, ecologically indispensable predators will fare as the tropical Pacific continues to warm.

Subject of Research: Long-term chaetognath community structure and its response to seasonal and ENSO-driven environmental variability in the coastal Central Mexican Pacific.

Article Title: Chaetognath community structure in the coastal Central Mexican Pacific: persistent seasonal signals amid ENSO variability (2010–2016)

Article References: Franco-Gordo, M. C., Plascencia-Palomera, V., Godínez-Domínguez, E., Lozano-Cobo, H., Gómez-Gutiérrez, J., Ambriz-Arreola, I., Kozak, E. R., & Suárez-Morales, E. (2026). Chaetognath community structure in the coastal Central Mexican Pacific: persistent seasonal signals amid ENSO variability (2010–2016). Discover Oceans, 3(1), Article 8. https://doi.org/10.1007/s44289-026-00121-9

Image Credits: AI Generated

DOI: 10.1007/s44289-026-00121-9

Keywords: chaetognaths, arrow worms, zooplankton, ENSO, El Niño, La Niña, coastal upwelling, Mexican Pacific, Bahía de Navidad, marine ecology, time series, biodiversity

A new study published in Climate Dynamics by Haonan Guo, Jiehong Xie, Ziqian Wang, Haolin Luo, Xiaomin Cai, and Song Yang, researchers at Sun Yat-sen University and Chengdu University of Information Technology, dissects exactly how this happened. Their analysis, built on the high-resolution ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts and the ERSSTv5 sea surface temperature record from NOAA, reveals that the delayed onset was not a failure of the ocean’s seasonal memory but a consequence of fast-moving atmospheric waves arriving from both the tropics and the extratropics in a nearly perfectly timed sequence. The finding reinforces a growing suspicion in the monsoon community: the predictive utility of the El Niño–Southern Oscillation, or ENSO, for pinning down the South China Sea monsoon onset date has weakened in recent years, and the day-to-day choreography of intraseasonal oscillations now matters more than the slow drift of equatorial sea temperatures.

To understand why the 2025 onset was so late, it helps to start with the physical yardstick that monsoon scientists use to define the event itself. The South China Sea summer monsoon is considered to have begun when the low-level winds over the basin flip from winter’s northeasterlies to summer’s southwesterlies, sustained by a reversal in the meridional temperature gradient—the difference in temperature between the land and ocean to the north and the tropical ocean to the south. When the southern side of the basin becomes warmer than the northern side in the mid-to-upper troposphere, the resulting pressure gradients and thermal winds support the establishment of deep convection and the monsoon circulation. As long as the meridional temperature gradient remains unfavorable, the monsoon cannot switch on, no matter what the equatorial Pacific is doing. The 2025 case, the authors show, was essentially a story about how a series of transient atmospheric disturbances kept resetting that gradient in the wrong direction during the critical weeks of May.

The first blow came from high latitudes. In mid-May, a wave train with a characteristic period of 30 to 50 days propagated southeastward from the extratropical atmosphere toward the South China Sea. This high-latitude intraseasonal oscillation carried cold anomalies into the region, cooling the mid-to-upper troposphere directly over the northern part of the basin. Because the monsoon onset depends on the northern side of the domain warming relative to the south, this injected pool of cold air sharply reduced the meridional temperature gradient over the South China Sea. In effect, the atmosphere over southern China was briefly transported back into a pre-monsoon thermal state, and the switch that should have flipped stayed off. The wave train acted like an invisible hand pressing down on the thermostat precisely when the seasonal background was trying to push it up.

Then the tropics weighed in. Between May 16 and May 24, the boreal summer intraseasonal oscillation—known to specialists as BSISO1, the leading mode of 30-to-50-day convective variability during the Asian summer monsoon—underwent a marked intensification of deep convection over the Indian Ocean. Deep convection of this kind does not stay local. The latent heat released by towering cumulonimbus clouds forces a response in the surrounding circulation, and in this case the intensified Indian Ocean convection excited a northeastward-propagating wave train in the upper troposphere, in the manner classically described by Gill-type solutions for heat-induced tropical circulation. This tropical wave train traveled toward East Asia and, crucially, arrived in phase with the extratropical wave train already cooling the northern South China Sea. The two disturbances reinforced one another, further suppressing the meridional temperature gradient and extending the pre-monsoon deadlock.

The tropical convection also launched a second, faster messenger. The BSISO1-related heating over the Indian Ocean triggered an atmospheric Kelvin wave—an eastward-propagating pulse of pressure and wind anomalies that travels along the equator at speeds of roughly 15 to 20 meters per second. As the Kelvin wave swept across the Maritime Continent and into the western Pacific, it produced easterly wind anomalies over the South China Sea at low levels. Easterlies are the signature of the winter regime; the monsoon onset requires their replacement by southwesterlies. By maintaining easterly anomalies over the basin during the second half of May, the Kelvin wave postponed the onset from a purely dynamical standpoint, independent of the thermal argument. In other words, the tropical oscillation sabotaged the monsoon’s arrival through two channels at once: it cooled and confused the thermal gradient via its upper-level wave train, and it held the low-level winds in the wrong direction via its equatorial Kelvin wave.

Just when it seemed the sequence could not become more intricate, a third actor entered from the North Atlantic. From May 25 to May 28, two distinct wave trains with periods of 8 to 20 days—the quasi-biweekly range that dominates midlatitude weather regimes—originated over the North Atlantic and propagated eastward toward Asia. One traveled along the subtropical westerly jet, the ribbon of strong upper-level winds that guides disturbances across Eurasia; the other followed the polar front jet farther north. Over East Asia, the two wave trains merged, combining their energy into a single, more potent disturbance. This merged system triggered one final, sharp reduction in the meridional temperature gradient over the South China Sea, delivering the decisive blow that pushed the onset date to May 29. The monsoon, in the end, was not merely delayed once but repeatedly, by a cascade of disturbances on three different timescales arriving in a conspiratorial sequence.

The scientific significance of this case study extends well beyond a single unusual spring. For decades, the statistical relationship between ENSO and the South China Sea monsoon onset has been a cornerstone of seasonal prediction for the Asian summer monsoon: La Niña years favor early onsets, El Niño years favor late ones, and forecasters have leaned on this link to anticipate the start of the rainy season that sustains agriculture for hundreds of millions of people. But recent research, including work by some of the same authors, has documented a weakening of this relationship in recent decades, and the 2025 event is perhaps the most vivid demonstration yet. A favorable La Niña background was completely overridden by intraseasonal variability, suggesting that seasonal-mean predictors alone are increasingly insufficient and that subseasonal-to-seasonal forecasting systems must capture the phase and amplitude of the BSISO, extratropical wave trains, and equatorial Kelvin waves to get the onset date right.

The case also highlights the growing recognition that the monsoon is not a purely tropical phenomenon. The North Atlantic has emerged as an increasingly influential upstream driver of South China Sea monsoon onset since the early 2000s, with sea surface temperature anomalies there modulating the waveguides along which disturbances travel toward East Asia. The 2025 episode shows that midlatitude jets can serve as conveyor belts delivering precisely timed perturbations into the tropical monsoon domain, and that the interaction between tropical and extratropical intraseasonal oscillations—rather than either alone—can determine the outcome of the onset process. This kind of cross-latitudinal synergy has been implicated in other extreme events, from persistent Yangtze floods to record-breaking North China rainfall, and the 2025 monsoon delay now joins that roster as a textbook example.

For the people of southern China and Southeast Asia, the practical stakes are considerable. The onset date of the South China Sea summer monsoon marks the transition from the dry pre-flood season to the season of torrential rains, tropical cyclone activity, and the water resources that fill reservoirs and irrigate rice paddies. A delayed onset can prolong drought conditions, stress water management systems, and shift the timing of the most hazardous flood-producing rainfall. A delayed onset can also concentrate the subsequent transition, producing abrupt and intense rainfall once the monsoon finally breaks through. By tracing the 2025 delay to identifiable, physically coherent wave dynamics—each stage documented in the reanalysis record with wave-activity diagnostics and filtering techniques—the study offers forecasters a concrete set of monitoring targets. If the phases of the BSISO, high-latitude wave trains, and quasi-biweekly disturbances from the Atlantic can be tracked in real time, the pieces now exist to anticipate precisely the kind of onset delay that caught the seasonal outlooks off guard in the spring of 2025.

Subject of Research: Mechanisms of the extremely delayed 2025 South China Sea summer monsoon onset involving tropical and extratropical intraseasonal oscillations

Article Title: Tropical and extratropical intraseasonal oscillations jointly delayed the 2025 South China Sea summer monsoon onset

Article References: Guo, H., Xie, J., Wang, Z., Luo, H., Cai, X., & Yang, S. (2026). Tropical and extratropical intraseasonal oscillations jointly delayed the 2025 South China Sea summer monsoon onset. Climate Dynamics, 64(10), Article 416. https://doi.org/10.1007/s00382-026-08371-1

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08371-1

Keywords: South China Sea summer monsoon, monsoon onset, intraseasonal oscillation, BSISO, Kelvin wave, ENSO, La Niña, meridional temperature gradient, wave train, North Atlantic, Climate Dynamics, subseasonal prediction

A new study published in the journal Climate Dynamics by Hui Teng, Xinyu Lin, and Yun Qiu of the Third Institute of Oceanography in Xiamen, China, offers the most detailed answer yet. Drawing on more than three decades of ocean reanalysis and observational data spanning 1980 to 2015, the team shows that the interannual variability of sea surface salinity in the Bay of Bengal is tightly coupled to ENSO events, and that this coupling unfolds in two distinct, seasonally locked stages with strikingly different spatial fingerprints.

The first stage arrives with the northeast monsoon, the dry winter season, and peaks between December of the developing El Niño year and the following February. During this window, the researchers found that sea surface salinity drops significantly across the southern Bay of Bengal, the Andaman Sea, and the eastern equatorial Indian Ocean, while at the same time salinity rises markedly in the northern bay. It is a seesaw pattern: as one end of the basin freshens, the other grows saltier, and the two changes are physically connected rather than coincidental.

The mechanism behind the southern freshening, according to the study, lies in the winds. El Niño’s influence on the tropical atmosphere generates an anomalous anticyclonic circulation over the region, a giant swirl of air that spins the surface ocean along with it. This circulation drives a southward advection of low-salinity water, pushing the bay’s famously fresh surface waters down toward the southern bay, the Andaman Sea, and the equatorial Indian Ocean. In effect, El Niño spreads the freshwater signature of the northern bay across a much wider swath of the tropical Indian Ocean than it would normally occupy.

The northern bay, meanwhile, moves in the opposite direction for a different reason. The western boundary current of the bay, the current that flows along India’s eastern coast, intensifies during this stage of an El Niño event. That intensification enhances the northward transport of salty water drawn from the south, delivering a saltier payload to the northern reaches of the basin. The result is a simultaneous freshening in the south and salinification in the north, a dipole of sorts that had not previously been resolved with this level of seasonal precision.

Then, as the seasons turn, the pattern itself turns. During the southwest monsoon stage of El Niño events, particularly in August and October of the year following the event’s onset, the salinity map flips into a new configuration. Salinity decreases sharply in the central and southern bay and in the eastern equatorial Indian Ocean, but now it increases in both the northern bay and the Andaman Sea. The two stages are not mirror images of each other; they are governed by different combinations of forces.

In the summer stage, the study identifies two processes working together to freshen the southern bay. El Niño enhances precipitation over the region, dumping additional freshwater directly onto the sea surface, while an anomalous cyclonic circulation, opposite in sense to the winter anticyclone, advects even more low-salinity water southward. The salinity increase in the northern bay during this stage arises from a strengthened northward advection of high-salinity water combined with a reduction in freshwater input, as the weakened summer monsoon delivers less river runoff and less direct rainfall to the basin’s head.

Crucially, the researchers found that La Niña events, the cool phase of the oscillation, run the same machinery in reverse. Correlation and regression analyses applied to the 36-year record show that the cold phase produces salinity anomalies of opposite sign through the same set of oceanic and atmospheric pathways. This symmetry is a hallmark of a linear response, suggesting that the bay’s salinity system can be modeled and predicted with relatively straightforward tools once the ENSO state is known, at least to first order.

The technical foundation of the work is a careful synthesis of independent datasets. The team used version 3.3.1 of the Simple Ocean Data Assimilation reanalysis, the World Ocean Atlas 2018 climatology, satellite-derived sea surface salinity from the Soil Moisture and Ocean Salinity mission, precipitation from the Global Precipitation Climatology Project, evaporation and heat fluxes from the Objectively Analyzed air–sea Fluxes product, and atmospheric fields from the ERA5 reanalysis. ENSO state was tracked with the standard Niño-3.4 index, and the Indian Ocean Dipole, the basin’s other dominant climate mode, was monitored with the Dipole Mode Index to disentangle the two influences.

Why does this matter beyond the tidy world of salinity budgets? The Bay of Bengal’s freshwater stratification is a linchpin of the regional climate system. A barrier layer of low-salinity water sitting atop denser, saltier water prevents wind-driven mixing from bringing cool water to the surface, allowing sea surface temperatures to stay high and sustaining atmospheric convection that feeds the monsoon. By showing that ENSO systematically redistributes the bay’s salinity in two predictable seasonal stages, the study provides a physical basis for anticipating how the barrier layer, and by extension monsoon convection, may respond when an El Niño or La Niña is brewing in the Pacific.

The findings also sharpen the picture of the tropical Indian Ocean as an active participant in global climate variability rather than a passive responder. Prior work had established links between the Indian Ocean Dipole and salinity anomalies in the equatorial Indian Ocean, and earlier modeling studies had identified processes controlling bay salinity variability in general. What the new analysis adds is a coherent, seasonally resolved framework that ties the bay’s salinity seesaw directly to the evolution of ENSO events, complete with the specific current systems and wind-driven circulations responsible at each stage.

For forecasters and climate scientists, the practical implications are considerable. Because the winter-stage salinity dipole emerges during the peak of an El Niño event, and the summer-stage pattern follows with a predictable lag, sea surface salinity in the bay could serve as an observable fingerprint of ENSO’s downstream reach, one that satellites now monitor routinely. As climate change continues to alter both the strength of ENSO events and the freshwater delivery from Himalayan-fed rivers, understanding the baseline mechanics of this coupling becomes essential for projecting the future of the South Asian monsoon, one of the most consequential climate systems on the planet.

Subject of Research: Interannual variability of sea surface salinity in the Bay of Bengal and its relationship with ENSO

Article Title: Interannual variabilities of sea surface salinity in the Bay of Bengal and its relationship with ENSO

Article References: Teng, H., Lin, X., & Qiu, Y. (2026). Interannual variabilities of sea surface salinity in the Bay of Bengal and its relationship with ENSO. Climate Dynamics, 64(10), Article 425. https://doi.org/10.1007/s00382-026-08383-x

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08383-x

Keywords: Bay of Bengal, sea surface salinity, ENSO, El Niño, La Niña, Indian Ocean, monsoon, ocean circulation, Climate Dynamics, barrier layer, Indian Ocean Dipole, climate variability

The Burrowing Parrot, Cyanoliseus patagonus, is no ordinary bird. It breeds in colonies dug into soft sandstone and limestone cliffs known as barrancas, and the colony near El Cóndor, beside the Río Negro estuary, is the largest known colony of any parrot species on Earth. Stretching 18.1 kilometers along the coast, it holds roughly 71 percent of the global breeding population, with long-term monitoring between 1998 and 2019 recording between 22,000 and 41,000 active nests. Understanding what these birds eat is therefore not a niche question of natural history; it is central to the survival of the majority of the species.

Historically, Burrowing Parrots were thought to feed mainly on the native vegetation of the Monte and Espinal ecoregions: seeds and fruits of chañar, caldén, algarrobo trees, berries of native shrubs such as Lycium, Discaria and Schinus, and grasses of the arid scrubland. Early naturalists, including W. H. Hudson in 1923 and Alexander Wetmore in 1926, described a diet rooted firmly in Patagonia’s native flora. The new study, published in The Science of Nature, tells a very different story. Of 202 valid plant molecular operational taxonomic units, or MOTUs, identified in the parrots’ droppings over the annual cycle, only 13 percent corresponded to native plants. Fully 40 percent were introduced species, with a further 4.5 percent presumed introduced, 12 percent ornamental garden plants, and 6.9 percent cultivated crops and pastures.

The methodology behind these numbers is a textbook example of modern molecular scatology. Between January and December 2021, the researchers collected 220 fresh fecal samples from the roosting flocks — 20 per month, except February, when the parrots mysteriously abandon the village roost. DNA was extracted from 178 samples using a stool kit optimized with bead-beating homogenization and extended incubation. Two primer sets were then amplified: one targeting the second internal transcribed spacer (ITS2) of plant nuclear ribosomal DNA, and a second targeting Bilateralia, the group that includes all animals with bilateral symmetry, to detect parasites and other animal DNA. The libraries were sequenced on an Illumina MiSeq with 250-base-pair paired-end reads.

The bioinformatic pipeline was equally rigorous. Reads were quality-trimmed with TRIMMOMATIC, merged with FLASH, de-replicated and screened for chimeras with USEARCH, and clustered into MOTUs. Each MOTU was then matched against the NCBI GenBank nucleotide database using BLASTn, with stringent thresholds: sequences had to be at least 190 base pairs long, with matches above 98 percent identity and an e-value below 0.00001. Species-level assignments required matches above 99.5 percent with consistent quality metrics across all retained hits. Negative extraction controls and PCR-grade water controls showed no contamination, and a dedicated gap analysis confirmed that the reference libraries were adequate: 69 percent of native plant species in the region have reference sequences in GenBank, rising to 97 percent at the genus level — sufficient given that 85 percent of the recovered MOTUs could be assigned to genus or better.

The seasonal patterns that emerged were striking. The parrots consumed 77 plant taxa during the breeding season, 172 during the post-breeding period, 72 in winter and 70 during pre-breeding — a statistically significant difference, with dietary diversity peaking just after the chicks fledge. This post-breeding explosion in dietary breadth coincides with the period when most plants in the region produce fruits and release seeds, and it is a critical window for juvenile survival, as young parrots must build up reserves before the harsh Patagonian winter. Non-metric multidimensional scaling and permutational multivariate analysis of variance revealed considerable overlap in diet across breeding, post-breeding and pre-breeding stages, but far less overlap with winter, when the birds turn to plants such as white spruce, velvet grass, perennial ryegrass and other introduced and ornamental species that are absent from the diet at other times of year.

Could the dominance of introduced plants be an artifact of sampling location? The researchers considered this carefully. Because samples were collected in the evening at the village roost, the diet might theoretically be biased toward items eaten near El Cóndor, where the landscape is most heavily modified. But several lines of evidence argue against it. Observations over five breeding seasons show the parrots flying over fields near the village without stopping to feed, and previous tracking studies show they forage between 58 kilometers northwest and 66 kilometers northeast of the colony. Moreover, digestive transit studies in parrots — corn-fed budgerigars empty their entire digestive tract within 26 hours — indicate that the DNA detected in evening droppings most likely reflects a full day of foraging, not just the last hours.

The most plausible explanation, the authors argue, is environmental degradation. Since the 1970s, a combination of increased rainfall and aggressive land clearing has transformed the region. In the Patagones department, natural vegetation that covered 65 percent of the land in 1975 has been reduced to an estimated 20 to 29 percent; in just three years, from 2015 to 2018, more than 216,000 hectares were cleared. In Adolfo Alsina department, home to El Cóndor, nearly 49,000 hectares were cleared between 1986 and 2006. Such landscape-scale disturbance disrupts native plant communities and opens the door to alien species. The parrots, it appears, are switching from a diet historically based on Monte and Espinal plants to one now dominated by introduced species — either a remarkable display of behavioral flexibility, or a warning sign of a suboptimal strategy that could undermine the persistence of the world’s largest parrot colony. A persistent La Niña event before and during the study may also have reduced the availability of native plants, though the authors caution that a single year of sampling cannot establish causation, and multi-year research is essential, especially as La Niña events are expected to become more frequent under climate change.

The study also delivered an unexpected bonus: a parasitological survey conducted entirely from droppings. Using the Bilateralia primer, the team identified 31 animal MOTUs, including four parasite families never before recorded in the digestive tracts of Burrowing Parrots: Gongylonematidae, which infects the oral cavity of birds and can cause starvation and death; Hymenolepididae and Onchobothriidae, both tapeworm groups previously unknown in parrots — Onchobothriidae had never been reported in any bird; and Capillariidae, thin nematodes known from captive parrots. The Gongylonematidae finding is particularly intriguing. During the 2020–2021 breeding season, at least 1,050 adult parrots died at El Cóndor — compared with the 20 to 30 typically found dead each year — and veterinary experts suspected infection rather than starvation as the primary cause. The authors stress that they can only speculate about a connection, but the possibility of a widespread Gongylonematidae infection driving that mortality event now demands investigation.

For decades, Burrowing Parrots were persecuted as agricultural pests, blamed for damage to maize, sunflowers, wheat and fruit orchards. The evidence tells a more nuanced story: systematic evaluations found that the birds affected only 0.1 to 0.4 percent of the sunflower harvest, leaving wheat and maize undamaged, and the species has been removed from Argentina’s pest-control lists. The new data reinforce this picture — cultivated plants made up just 6.9 percent of the diet, and official agricultural statistics suggest these mostly correspond to forage pastures of oats and barley rather than standing crops. As the clearance of the Monte continues and the El Cóndor colony concentrates the vast majority of the world’s Burrowing Parrots, the authors call for close monitoring of both population size and diet. The droppings collected under those Patagonian power lines have done more than reveal a menu; they have documented a dietary revolution in real time, flagged nine plant species newly introduced to the region, and possibly left a molecular clue to a mass mortality that still awaits explanation.

Subject of Research: Seasonal diet composition of Burrowing Parrots revealed by DNA metabarcoding of fecal samples

Article Title: Using next-generation sequencing to unravel the diet composition of Burrowing Parrots over the annual cycle

Article References: Masello, J. F., Failla, M., Leder, C. V., & Quillfeldt, P. (2026). Using next-generation sequencing to unravel the diet composition of Burrowing Parrots over the annual cycle. The Science of Nature, 113(5), Article 119. https://doi.org/10.1007/s00114-026-02159-3

Image Credits: AI Generated

DOI: 10.1007/s00114-026-02159-3

Keywords: Burrowing Parrot, DNA metabarcoding, next-generation sequencing, diet composition, Patagonia, El Cóndor colony, molecular scatology, introduced plants, environmental degradation, parasites, Psittaciformes, La Niña

A new study published in Climate Dynamics by Caihong Wen, Wanqiu Wang, Arun Kumar, and Michelle L’Heureux of NOAA’s Climate Prediction Center examines what happened next, and the results are a striking cautionary tale about how a change in input data can propagate through an entire forecast enterprise. The researchers found that the switch from OISSTv2 to NSST coincided with a sharp discontinuity in the sea surface temperatures recorded in CFSR. Before 2020, the reanalysis SST tracked the OISSTv2.1 reference dataset almost perfectly, with negligible differences. After the switch, a large cold bias appeared across much of the global ocean, as if the ocean’s skin had suddenly been cooled by an invisible hand.

The geography of the bias is telling. The largest discrepancies, exceeding minus one degree Celsius, emerged along the energetic western boundary currents such as the Gulf Stream and Kuroshio extensions, and along the Antarctic Circumpolar Current, regions where the ocean is dynamically active and where different SST products can diverge substantially. In the tropical upwelling zones, where winds drive cold water to the surface, the differences were more moderate but still significant, ranging from about minus 0.2 to minus 0.5 degrees Celsius. These are precisely the regions that matter most for the El Niño-Southern Oscillation, the planet’s dominant source of seasonal climate variability, which swings between warm El Niño and cold La Niña states and reshuffles weather patterns from California to Kenya.

What makes the finding particularly consequential is how these biases behaved once forecasts were launched from the reanalysis. The researchers examined two seasonal forecast systems that rely on CFSR for their ocean initial conditions: NCEP’s Climate Forecast System version 2, known as CFSv2, and the Community Climate System Model version 4, or CCSM4, which contributes to the North American Multi-Model Ensemble. Both models ingested the cold anomalies at initialization almost undamped. At zero-month lead time, meaning at the very start of the forecast, both systems exhibited cold anomalies in the eastern tropical Pacific. Rather than fading away as the coupled atmosphere-ocean system evolved, these anomalies intensified and spread westward toward the dateline within four months, contaminating the forecast trajectory itself.

The consequences for ENSO prediction were systematic and measurable. By constructing composites of forecast behavior around historical El Niño and La Niña events, the team showed that forecasts initialized after 2020 carried a persistent cold bias during boreal fall and winter, the seasons when ENSO events typically reach peak strength and when forecast skill is usually highest. In practical terms, the models were systematically underestimating ocean temperatures in the tropical Pacific during the most important window of the ENSO cycle, affecting the predicted amplitude of both El Niño warm events and La Niña cold events. A forecast that starts with a cold ocean and then cools it further will inevitably lean too far toward La Niña-like outcomes.

The 2024 La Niña episode provided a vivid real-world demonstration. Even during seasons when ENSO forecasts historically perform well, the post-2020 forecast systems produced overly cold La Niña predictions, exaggerating the intensity of the event. For forecasters, agricultural planners, disaster managers, and governments that depend on seasonal outlooks for drought, flood, and temperature guidance, such a bias is not an academic curiosity. It shifts probability distributions that inform billions of dollars in decisions, from crop planting to water reservoir management to famine early warning systems across the tropics.

There is also a deeper historical irony embedded in the findings. The CFSR has long been known to carry a warm bias in tropical Pacific SST forecasts, a discontinuity that emerged around 1999 and was documented in earlier studies of the system’s nonstationary errors. The 2020 switch in nudging datasets effectively reversed that sign, replacing a warm bias with a cold one. The result is a forecast system whose errors are nonstationary in time, meaning that bias corrections calibrated on one era of the reanalysis become invalid in another. Statistical post-processing, machine learning corrections, and forecaster intuition all implicitly assume that a model’s errors are reasonably stable; a sudden sign flip violates that assumption and degrades every downstream correction built on it.

The technical root of the problem lies in the subtle difference between what the two SST products actually measure. The OISST analysis targets a foundation SST, broadly representative of the temperature near the ocean surface free of diurnal variability, while the NSST scheme represents the temperature at the very top of the ocean model, including near-surface gradients that can differ from bulk or foundation temperatures. When a reanalysis nudges its top ocean layer toward a product defined differently from what the model layer represents, systematic offsets can be introduced. Because the nudging is strong, the ocean model has little freedom to correct those offsets through its own physics, and because the coupled forecast models are initialized from the reanalysis, the offsets ride along into every prediction. The study’s authors emphasize that although different SST analyses are routinely adopted in operational ocean reanalysis systems around the world, the impacts of switching between them have rarely been examined with this level of rigor.

The broader lesson extends well beyond NCEP. Ocean reanalysis systems operated by centers in Europe, Japan, and the United States all face similar choices about which SST product to assimilate, and operational systems inevitably evolve as datasets are updated or replaced. The Wen and colleagues analysis demonstrates that such transitions deserve the same scrutiny as changes to model physics or observation networks, because a change in the anchoring dataset is, in effect, a change to the climate the reanalysis describes. The researchers suggest that monitoring reanalysis products against independent references, quantifying discontinuities at transition points, and assessing how initialization biases propagate through coupled forecasts should become standard practice whenever operational data streams change. Otherwise, the quiet swap of one temperature dataset for another can silently recalibrate the world’s seasonal forecasts, turning a well-understood prediction system into one that is systematically, and invisibly, off balance.

Subject of Research: Impact of switching the sea surface temperature nudging dataset in the CFSR ocean reanalysis on seasonal ENSO forecast biases.

Article Title: Impact of SST nudging on CFSR analysis and seasonal ENSO forecasts

Article References: Wen, C., Wang, W., Kumar, A., & L’Heureux, M. (2026). Impact of SST nudging on CFSR analysis and seasonal ENSO forecasts. Climate Dynamics, 64(10), Article 418. https://doi.org/10.1007/s00382-026-08375-x

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08375-x

Keywords: ENSO prediction, ocean reanalysis, CFSR, sea surface temperature, SST nudging, seasonal forecasting, CFSv2, CCSM4, NMME, La Niña, forecast bias, Climate Dynamics