The study, led by Deepti Tandel with Mani Kant Verma and M.K. Verma, set out to quantify how large-scale ocean-atmosphere interactions shape regional monsoon variability at a scale that matters for farmers and water managers. Climate change is increasingly altering rainfall patterns, and understanding the fingerprints of ENSO and the IOD on district-level rainfall, monsoon onset, and wet-dry conditions provides a scientific basis for drought monitoring and agricultural planning. The team assembled daily rainfall data for the monsoon season across the full 65-year record, then applied a battery of statistical tools designed to detect trends, classify drought severity, and test associations with ocean indices.

Methodologically, the researchers used the Modified Mann-Kendall test, which corrects for autocorrelation in time series, together with Sen’s slope estimator to quantify the magnitude of trends in rainfall. To characterise drought and wetness, they computed the Standardised Precipitation Index (SPI), a widely used metric that expresses rainfall anomalies in units of standard deviation, with values below zero indicating drier-than-normal conditions and values above zero indicating wetter-than-normal ones. Associations with ocean conditions were tested using both Pearson and Spearman correlation analyses, while differences among groups were evaluated with the Kruskal-Wallis test and Dunn’s post-hoc comparisons. This combination of non-parametric and correlation-based techniques allowed the team to assess trends and teleconnections robustly across districts with differing rainfall regimes.

The results paint a picture of substantial spatial variability. District-level SPI values ranged from approximately −2.5 to +3.0, spanning severe drought to pronounced wetness within a single state. The analysis identified 15 major drought years: 1965, 1966, 1968, 1974, 1979, 1982, 1986, 1991, 1997, 2002, 2009, 2013, 2015, 2017, and 2023. In contrast, seven years stood out as major wet years: 1961, 1980, 1981, 1994, 2001, 2003, and 2025. During the major drought years, the mean SPI across districts ranged from −1.733 to −0.505, confirming that these events were widespread rather than localised, yet the spread of values also underscored how unevenly drought stress is distributed across the state.

Monsoon onset, a critical variable for sowing decisions in rainfed agriculture, varied considerably across the state, from 14 June in the earliest districts to 2 July in the latest. This three-week spread means that neighbouring districts can face very different planting windows in the same season, complicating one-size-fits-all agricultural advisories. The timing of onset was found to be significantly influenced by conditions in the preceding months: the March-April-May Oceanic Niño Index (MAM ONI), a measure of Pacific sea surface temperature anomalies, and the state of the IOD both had significant effects on rainfall variability and on when the monsoon actually arrived over individual districts.

The statistical link between the Pacific and Chhattisgarh’s rains was quantified directly. The association between ONI and monsoon rainfall was significant in both correlation frameworks, with Pearson’s r = 0.401 (p = 0.001) and Spearman’s ρ = 0.416 (p = 0.006). These moderate but highly significant coefficients indicate that a substantial fraction of year-to-year monsoon variability in the state is traceable to the phase of ENSO, a finding consistent with the broader literature on how Pacific sea surface temperature anomalies modulate the Indian summer monsoon through large-scale atmospheric circulation changes.

Perhaps the most striking result is the spatial pattern of emerging aridity. The districts of Mungeli, Kabirdham, Bilaspur, Balodabazar, and Surajpur experienced moderate to extremely dry conditions, while Bastar, Bijapur, Narayanpur, and Sukma, in the forested south of the state, showed a transition from extremely wet to moderately wet conditions. This shift indicates an emerging tendency toward dryness even in historically wetter districts, suggesting that the drying signal is not confined to the already arid margins but is creeping into areas whose farming systems and ecosystems were built around more abundant rainfall.

The authors attribute this increasing tendency toward aridity to the combined influence of ENSO, the IOD, and regional hydroclimatic processes. The IOD, a seesaw of sea surface temperatures between the western and eastern Indian Ocean, can reinforce or offset ENSO’s influence on Indian rainfall depending on the relative phases of the two modes. When both act in concert, their combined effect on monsoon circulation can be amplified, and the Chhattisgarh analysis suggests that such interactions leave detectable imprints on district-scale rainfall, onset timing, and drought severity across the 65-year record.

The practical implications are considerable. Chhattisgarh’s economy is heavily dependent on rainfed agriculture, and previous work by the same group has documented how dry and wet spells affect crop productivity in the state. By demonstrating that pre-monsoon ocean conditions carry usable information about subsequent rainfall variability and onset timing, the study provides a scientific foundation for district-level drought monitoring, seasonal agricultural planning, and water-resource management. The identification of specific drought-prone and wet-to-dry transition districts offers a spatially targeted basis for climate-resilient strategies, from crop choice and irrigation investment to contingency planning for delayed monsoons.

As climate change continues to reshape global precipitation patterns, studies of this kind highlight how global ocean oscillations and regional processes interact to determine the fate of individual farming districts. For Chhattisgarh, the message from six and a half decades of data is clear: the monsoon is becoming more uneven, drought years are a recurring feature of the record, and even the wettest corners of the state are drifting toward drier conditions. Translating that statistical evidence into early-warning systems and adaptive water management may prove essential for the millions of people whose livelihoods depend on the timing and abundance of the Southwest monsoon rains.

Subject of Research: Influence of ENSO and the Indian Ocean Dipole on Southwest monsoon rainfall variability and drought across Chhattisgarh, India

Article Title: Spatiotemporal variability of Southwest monsoon rainfall and drought in Chhattisgarh: associations with ENSO and IOD

Article References: Tandel, D., Verma, M. K., & Verma, M. (2026). Spatiotemporal variability of Southwest monsoon rainfall and drought in Chhattisgarh: associations with ENSO and IOD. Theoretical and Applied Climatology, 157(11), Article 728. https://doi.org/10.1007/s00704-026-06662-5

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06662-5

Keywords: monsoon, Chhattisgarh, ENSO, Indian Ocean Dipole, drought, Standardised Precipitation Index, rainfall variability, monsoon onset, climate change, trend analysis, India, agriculture

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 core of the approach is a machine learning technique called a self-organizing map, or SOM, an unsupervised neural network first introduced by Teuvo Kohonen in the 1980s. SOMs have long been a workhorse of synoptic climatology, the branch of meteorology that classifies daily weather into recurring circulation patterns. Instead of asking whether a rainfall gauge has crossed some magic number, the method asks a more fundamental question: which large-scale atmospheric pattern is sitting over the region today? By grouping thousands of daily weather maps into a grid of representative patterns, the SOM turns the messy continuum of atmospheric states into an ordered catalogue of circulation regimes.

Islam and Sheridan trained separate 9 by 9 SOMs—one for each of five near-surface atmospheric variables drawn from the NCEP/NCAR Reanalysis, a widely used gridded reconstruction of historical weather. The five variables were sea-level pressure, 2-meter air temperature, 2-meter relative humidity, near-surface winds, and precipitation. Each of the 81 nodes in a given SOM represents a distinct, characteristic pattern of that variable across the South Asian domain. Every day in the reanalysis record is then mapped to the node whose pattern it most closely resembles, effectively assigning each day a circulation fingerprint.

The crucial innovation comes next. Rather than eyeballing the map grid to decide which patterns belong to which season, the researchers objectively assigned nodes to the four meteorological seasons recognized in the region—winter, pre-monsoon, monsoon, and post-monsoon. Once every node carries a seasonal label, the transition dates fall out naturally: the monsoon begins on the day the atmosphere settles into monsoon-labeled patterns and ends when it departs them. Because the assignment is systematic, the same procedure can be repeated for any variable, any region, or any sub-period, producing onset and withdrawal dates that are reproducible rather than dependent on the judgment of individual analysts.

The results reveal a striking and previously underappreciated picture of how differently the seasons announce themselves depending on what you measure. The study found no single, distinct correlation between the onset timings derived from the five variables, meaning that pressure, temperature, humidity, winds, and rainfall each tell their own story about when the seasons turn. Monsoon season, when defined by sea-level pressure, relative humidity, or temperature, tends to run longer than when it is defined by precipitation alone—a sign that the large-scale circulation reorganizes well before the rains become sustained.

That gap is not a curiosity; it is physically meaningful. The analysis shows that precipitation-based monsoon onset arrives roughly one week later than circulation-based onset, and precipitation-based withdrawal comes roughly one week earlier than the circulation suggests. In other words, the atmosphere shifts into its summer monsoon configuration before the rain fully commits, and it begins to relax out of that configuration before the rain fully quits. This is consistent with the well-established requirement for preconditioning: the large-scale flow must build up moisture convergence and low-level winds before sustained rainfall can develop, and it lingers in a summer-like state as the rains taper off.

The framework also captured a long-term trend in the winter season that will interest climate monitors. Winter length has increased over the record, driven by onset shifting earlier and withdrawal shifting later. Because the method is threshold-free, such trends emerge directly from the circulation record rather than from any chosen definition of what counts as a winter day, making them easier to compare across studies and across variables. The authors note that the same procedure can be applied regionally as well as across the whole domain, and their results demonstrate transferability across sub-regions within the same climate regime—meaning a forecaster in Bangladesh and one in northwestern India can apply the identical recipe and get internally consistent answers.

The technical elegance of the SOM approach lies in what it removes. Traditional monsoon onset definitions—such as the classic criteria for onset over Kerala used by the India Meteorological Department—typically hinge on thresholds: so many millimeters of rain at so many stations for so many consecutive days, or a specified reversal of the upper-level zonal winds. Those criteria are operationally useful but inherently arbitrary in their cutoffs, and different thresholds yield different dates. Hydrological definitions based on vertically integrated moisture transport, dynamical definitions based on wind reversals, and station-based rainfall definitions have all coexisted for decades, each defensible yet none mutually comparable. By anchoring the seasonal transition in the identity of the circulation pattern itself, the SOM framework sidesteps the threshold problem entirely and produces what the authors describe as a robust platform for multi-variable, circulation-informed seasonal dates.

Why does this matter beyond the academic literature? Monsoon onset timing is among the most consequential pieces of seasonal information in the world. An early or late onset can shift sowing windows for rice, wheat, and cotton, alter reservoir management decisions, and modulate the risk of flooding during the pre-monsoon and post-monsoon transition periods. Forecast systems have made real progress in predicting onset—the study’s reference list includes work on coupled seasonal forecast models and extended-range prediction built on SOMs—but verification of those forecasts still depends on having a consistent, objective definition of what onset actually is. A framework that yields the same answer whether applied to pressure, humidity, temperature, winds, or rainfall, and at both continental and regional scales, gives forecasters and agrometeorologists a common yardstick for the first time.

The study also carries a broader lesson for climate science: synoptic climatology, the tradition of classifying weather maps into regimes, remains a powerful and underused lens for diagnosing seasonal transitions, not just daily weather. By demonstrating that a single unsupervised learning method can harmonize five different atmospheric variables into one coherent seasonal calendar, Islam and Sheridan have offered the monsoon research community something it has long lacked—a uniform, reproducible, and threshold-free declaration of when the seasons begin and end. As the climate continues to warm and the stakes of getting the monsoon calendar right continue to rise, frameworks like this one may become the standard against which both observations and forecasts are judged.

Subject of Research: A threshold-free self-organizing map framework for determining uniform seasonal onset and withdrawal dates in the South Asian monsoon

Article Title: Uniform seasonal onset declaration in the South Asian monsoon: a SOM-based circulation framework

Article References: Islam, M. R., & Sheridan, S. C. (2026). Uniform seasonal onset declaration in the South Asian monsoon: a SOM-based circulation framework. Theoretical and Applied Climatology, 157(10), Article 660. https://doi.org/10.1007/s00704-026-06598-w

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06598-w

Keywords: South Asian monsoon, monsoon onset, self-organizing maps, synoptic climatology, NCEP/NCAR Reanalysis, seasonal transitions, machine learning, precipitation, sea-level pressure, climate variability, monsoon withdrawal, meteorology

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

The two oscillations in question are easily distinguished by their periods and their pathways. The first is a quasi-biweekly mode, an oscillation with a period of roughly 10 to 20 days that approaches the South China Sea while propagating westward across the western Pacific. The second is the longer 30-to-60-day oscillation, closely related to the Madden-Julian Oscillation, the planet’s most prominent intraseasonal disturbance, which reaches the region while propagating northward from the tropical Indian Ocean. Both carry enhanced convective activity and low-level wind anomalies, and when either one arrives over the South China Sea at the right moment in the seasonal cycle, it can tip the atmosphere past the threshold for monsoon onset. Forecasters have long known that both waves matter, but predicting which one will deliver the decisive push in a given year has remained a stubborn challenge.

The research team, led by Xue Han of the National Marine Environmental Forecasting Center in Beijing together with Kuiping Li of the First Institute of Oceanography and colleagues, approached the problem using the ERA5 global reanalysis, a state-of-the-art reconstruction of past atmospheric and oceanic conditions produced by the European Centre for Medium-Range Weather Forecasts. Rather than simply cataloguing which wave arrived in which year, the team asked a more fundamental question: what physical processes allow each oscillation to moisten the atmosphere over the South China Sea in the critical period before onset? Their focus settled on the planetary boundary layer, the lowest kilometer or so of the atmosphere, where moisture accumulates ahead of the oscillation’s main convective center and sets the stage for the deep thunderstorms that define the monsoon.

Using a formal moisture budget diagnosis, a mathematical accounting of every term that adds or removes water vapor from the boundary layer, the researchers found that the key to pre-onset moistening is not the oscillation acting alone. Instead, it is the interaction between the intraseasonal perturbation and the slowly evolving background state of the atmosphere and ocean, the anomalies that persist on interannual timescales of a few years. When the products of these two components are evaluated in the moisture budget, the cross-terms reveal how the background flow can either amplify or suppress the wave’s ability to build moisture in the boundary layer. In other words, the same intraseasonal wave can arrive over a South China Sea that is primed to receive it or one that resists it, depending on the larger climate setting of that particular year.

The team then separated onset years according to which oscillation played the leading role and compared the interannual background anomalies between the two groups. The differences were striking. In years when the 10-to-20-day quasi-biweekly oscillation triggers the onset, the subtropical high strengthens over the northern South China Sea and easterly vertical wind shear becomes pronounced over the western Pacific. The sea itself tends toward dryness, with suppressed convection and a low-level anticyclonic circulation sitting over the region. On its face, this seems like an inhospitable environment for a monsoon trigger, yet the analysis shows precisely the opposite: against this particular background, the interaction between the anomalies and the 10-to-20-day perturbations enhances boundary-layer moistening through two specific channels, the horizontal advection of moisture by the combined flow and a moisture source term associated with the anomalies. The dry, anticyclonic setting thus acts as an amplifier for the faster wave rather than a barrier.

The picture reverses almost completely for years governed by the 30-to-60-day oscillation. In those years, easterly wind shear dominates the Indian Ocean while westerly shear prevails over the western Pacific, a configuration that shapes how the longer wave develops as it migrates northward. The South China Sea in these years is warmer than normal and rich in moisture, with low-level convergence drawing air upward and stronger convection already under way. Here, the critical moistening pathway is meridional moisture advection, the north-south transport of water vapor, which strengthens the boundary-layer moistening through the interaction between the interannual anomalies and the 30-to-60-day perturbations. This process preconditions the basin for the slower, northward-propagating wave, allowing it to complete the monsoon onset when it arrives.

These findings matter because the two oscillations carry very different implications for prediction. The quasi-biweekly mode evolves rapidly, giving forecasters perhaps a week or two of lead time, while the 30-to-60-day mode, being an extension of the Madden-Julian Oscillation, offers the potential for sub-seasonal forecasts issued several weeks in advance. Knowing which interannual background state favors which trigger means that seasonal outlooks can, in principle, identify the more likely onset pathway before the intraseasonal wave even forms. If the background anomalies resemble the dry, anticyclonic, easterly-shear configuration, attention can shift to monitoring the western Pacific for quasi-biweekly disturbances; if the warm, moist, convergent configuration appears, the Indian Ocean’s slow-moving envelope of convection becomes the object to watch. Such conditional forecasting strategies could sharpen the lead times for one of the most consequential seasonal transitions in Asia.

The stakes are considerable. The South China Sea summer monsoon onset marks the beginning of the rainy season for southern China and influences rainfall across much of East and Southeast Asia, affecting agriculture, water resources and flood risk for hundreds of millions of people. The onset date varies substantially from year to year, and errors in anticipating it cascade into errors in seasonal rainfall prediction across the entire East Asian monsoon domain. Previous work has linked onset variability to sea surface temperature anomalies associated with El Niño and La Niña events, to the thermal state of the tropical western Pacific, and even to tropical cyclones that occasionally deliver the final nudge. The new study adds a crucial mechanistic layer to this picture by showing that these large-scale influences do not merely shift the mean conditions; they selectively modulate which intraseasonal vehicle carries the monsoon into being.

The research also speaks to a broader theoretical development in tropical meteorology, the growing recognition that intraseasonal oscillations behave as moisture modes, disturbances whose propagation and amplification depend fundamentally on how they reshuffle water vapor within the circulation. By demonstrating that the boundary-layer moistening ahead of the convective center, the same mechanism emphasized in modern theories of the Madden-Julian Oscillation, is central to monsoon onset over the South China Sea, the study ties a regionally specific forecasting problem to a unifying physical framework. The finding that interannual anomalies enter through specific budget terms, horizontal advection and the moisture source in one regime and meridional advection in the other, provides a quantitative handle that model developers can use to evaluate whether their simulations capture the right physics.

There remain open questions. The analysis rests on reanalysis data, which blend observations with model physics, and the regional distinctions the team identified will need to be tested in prediction systems and climate models to confirm their practical value. Still, the central message is clear and potentially transformative for monsoon forecasting: the annual contest between two atmospheric rhythms over the South China Sea is not a coin flip but a choreographed outcome, decided years’ worth of climate memory in advance. By reading the background state of the basin each spring, scientists may now be able to anticipate not just when the monsoon will begin, but which of two very different atmospheric clocks will ring in its arrival.

Subject of Research: Interannual modulation of intraseasonal oscillations triggering the South China Sea summer monsoon onset

Article Title: Interannual modulation of two dominant intraseasonal oscillations triggering the South China sea monsoon onset

Article References: Han, X., Li, K., Shi, Z., Han, Y., Wang, L., Yuan, J., Feng, L., & Chen, X. (2026). Interannual modulation of two dominant intraseasonal oscillations triggering the South China sea monsoon onset. Climate Dynamics, 64(10), Article 433. https://doi.org/10.1007/s00382-026-08388-6

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08388-6

Keywords: South China Sea summer monsoon, monsoon onset, intraseasonal oscillations, quasi-biweekly oscillation, Madden-Julian Oscillation, planetary boundary layer moistening, moisture budget, interannual variability, wind shear, subtropical high, ERA5 reanalysis, Climate Dynamics

The research, led by John K. Lix and R. Sajeev of the Department of Physical Oceanography at Cochin University of Science and Technology, together with Ramasamy Venkatesan of the Indian Institute of Technology Mandi, draws on high-resolution observations from a moored OMNI buoy stationed at 15°N, 68.9°E in the east-central Arabian Sea, close to Nanauk’s track. The buoy recorded air temperature, pressure, humidity, wind speed and direction at 3-meter height, along with temperature and salinity at discrete depths from 1 to 500 meters, every hour. This rare in-situ time series allowed the team to reconstruct exactly how the upper ocean responded as the depression that would become Nanauk passed overhead.

Nanauk’s story began on 10 June 2014, when a depression formed over the east-central Arabian Sea under favorable conditions: sea surface temperatures above 31°C, tropical cyclone heat potential of roughly 60 to 80 kJ cm⁻², strong low-level vorticity and convergence, and upper-level divergence. The system strengthened into a deep depression and then a cyclonic storm by the early hours of 11 June, peaking with maximum sustained winds near 23.1 m s⁻¹, a minimum central pressure of 986 mb, and a radius of maximum wind of about 37 km. Vertical wind shear during the monsoon onset phase ultimately curbed its growth, and the storm weakened by 13 June.

The upper-ocean response to a tropical cyclone is traditionally divided into a forced stage, when strong winds within the radius of maximum wind directly drive mixed-layer currents, and a relaxation stage, dominated by near-inertial currents generated as winds subside. During the forced stage, two mechanisms cool the mixed layer: Ekman-pumping-driven upwelling and entrainment mixing, in which shear instability at the base of the mixed layer stirs colder thermocline water upward into the warm surface layer. Because cooling at the surface reduces the enthalpy flux — the sum of latent and sensible heat that fuels a cyclone — sea surface cooling acts as a negative feedback that can weaken storms.

During Nanauk’s depression stage, the mooring recorded a striking and rapid sea surface temperature drop of about 1.9°C within 12 hours. The mixed layer, typically oscillating between 20 and 30 meters in depth under calm pre-monsoon conditions and diurnal solar cycling, deepened dramatically as wind stress intensified — from 35 to 70 meters between 11 and 12 June, while the depth of the 26°C isotherm plunged from 70 to 90 meters. Satellite sea-level anomaly data revealed an anticyclonic warm-core eddy on the right side of the track, where cooling was notably weaker, while stronger cold wakes formed on the left side — an asymmetry that is rare, since cyclone-induced cooling is usually strongest to the right of the track where wind-driven current shear is greatest.

To disentangle the physical processes behind the cooling, the team computed a mixed-layer temperature budget, separating the temperature tendency into net surface heat flux, vertical processes, and residual terms. Surface heat fluxes were estimated with the COARE 3.6b bulk algorithm using in-situ buoy data, while radiation terms came from the ERA5 reanalysis. Because entrainment velocity cannot be measured directly from a mooring, the researchers employed the one-dimensional Price-Weller-Pinkel (PWP) mixed-layer model, which simulates turbulent mixing using static stability, bulk Richardson number, and gradient Richardson number criteria, initialized with pre-storm buoy profiles and forced with observed meteorology.

The model and observations agreed remarkably well during the initial phase of direct wind forcing: from 00 to 07 UTC on 10 June, the mean difference between simulated and observed sea surface temperature was just 0.07°C, and temperature tendencies differed by only 0 to 0.05°C per hour. During this first phase, entrainment mixing dominated the cooling, contributing on average around 81% of the mixed-layer temperature change, with net surface heat flux contributing roughly 13% and the residual term about 6%. At one point, the entrainment term alone accounted for 77% of the observed cooling tendency. Average enthalpy fluxes during the forcing period reached −562 W m⁻², peaking at −648 W m⁻², with latent heat providing 80 to 95% of that loss.

Perhaps the most intriguing finding concerns why such strong entrainment occurred despite relatively weak depression-stage winds. The answer lies in the seasonal structure of the Arabian Sea. During the monsoon onset phase, the east-central basin features a shallow mixed layer — less than 30 meters — sitting atop an elevated temperature gradient at its base, roughly 1.5 to 1.7°C. This sharp stratification meant that even moderate wind-driven shear was sufficient to trigger shear instability, drive entrainment velocities peaking at 3 meters per hour, and pump cold water into the surface layer. Sensitivity experiments confirmed the robustness of this conclusion: switching the mixed-layer depth criterion changed entrainment estimates by only about 5% on average, though lowering the critical bulk Richardson number from 0.65 to 0.5 reduced the entrainment contribution by 17%.

The picture changed during the final phase of forcing, when the one-dimensional model captured only about half the observed cooling, pointing to significant contributions from three-dimensional processes such as wind-stress-curl-driven upwelling — visible as the upward tilting of the 26°C isotherm — horizontal advection, and inertial oscillations. These processes became dominant during the relaxation stage, when alternating upwelling and downwelling with a roughly 46-hour inertial period sustained the cold wake for days to weeks. The authors note that a full three-dimensional model would be needed to close the temperature budget during these later phases.

Crucially, the cooling — about 1.3°C during the direct forcing period — did not weaken the young storm. Post-forcing sea surface temperature at the mooring remained 29.6°C, far above the 26°C threshold needed to sustain a cyclone, so the ocean continued to supply ample heat and Nanauk went on to intensify. But the study carries a broader warning for forecasters: high sea surface temperature and high heat potential alone do not guarantee that a storm will escape oceanic negative feedback. A slow-moving cyclone crossing a shallow, sharply stratified mixed layer can still cool the sea substantially, chipping away at the enthalpy flux that sustains it — as Nanauk’s slow drift over its own cold wake during recurvature may have contributed to its dissipation. Accurately capturing this entrainment physics, the authors argue, requires dense in-situ measurements of temperature, salinity, and currents along storm tracks, and their explicit representation in coupled cyclone forecast models, particularly in the Arabian Sea where such process studies have been scarce.

Subject of Research: Entrainment mixing and mixed-layer cooling in the Arabian Sea during the depression stage of Cyclonic Storm Nanauk

Article Title: The role of entrainment mixing on the mixed layer cooling in the Arabian Sea during the depression stage of the Cyclonic Storm Nanauk

Article References: Lix, J. K., Sajeev, R., & Venkatesan, R. (2026). The role of entrainment mixing on the mixed layer cooling in the Arabian Sea during the depression stage of the Cyclonic Storm Nanauk. Discover Oceans, 3(1), Article 48. https://doi.org/10.1007/s44289-026-00162-0

Image Credits: AI Generated

DOI: 10.1007/s44289-026-00162-0

Keywords: Arabian Sea, Cyclone Nanauk, entrainment mixing, mixed layer cooling, sea surface temperature, PWP model, air-sea interaction, tropical cyclone, moored buoy, ocean heat content, Richardson number, monsoon onset