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 two patterns at the heart of the study are the monsoon’s fingerprints of the El Niño-Southern Oscillation, or ENSO, in the Pacific, and the Indian Ocean Dipole, or IOD, in the Indian Ocean. El Niño events, marked by unusually warm sea surface temperatures in the equatorial eastern Pacific, have long been known to suppress Indian rainfall, while La Niña conditions tend to enhance it. The IOD, a see-saw of sea surface temperatures between the western and eastern Indian Ocean, similarly modulates the monsoon, with positive dipole events generally favouring above-normal rain. What has remained poorly understood is how these two influences combine, particularly during the recent decades of accelerating ocean warming.

To disentangle the two signals without imposing any preconceived filter on the data, the team applied a data-adaptive statistical technique called multi-channel singular spectrum analysis, or MSSA. The method decomposes daily rainfall and satellite-measured outgoing longwave radiation into space-time patterns, extracting oscillations and persisting structures directly from the observations. Because the rainfall data cover only India’s land area, the researchers first identified the seasonally persisting modes in outgoing longwave radiation, which spans both land and ocean, and then projected the century-long rainfall record onto those modes. This procedure yielded two clean components, dubbed M-ENSO and M-IOD, each retaining the same sign of anomaly through most of the June-to-September season but varying from year to year.

The results are striking. The sum of the two modes correlates at 0.83 with the observed seasonal rainfall anomaly across the full 1901 to 2021 period, meaning that the combined influence of the Pacific and Indian oceans explains the bulk of the year-to-year variation in India’s summer rain. Individually, the ENSO-related mode correlates at 0.55 and the IOD-related mode at 0.6 with the total anomaly. Crucially, the two modes sometimes reinforce one another and sometimes cancel out. In 1983, both modes were positive and the season ended with a strong rainfall anomaly of 0.89 millimetres per day; in 1972, both were negative, producing a weak monsoon at minus 1.62 millimetres per day. In 1989 and 1997, the modes opposed each other and the seasonal rainfall came out near normal.

The year 1997 stands out as a dramatic illustration of this destructive interference. That year brought the strongest El Niño of the twentieth century, an event that on its own would likely have produced severe drought across India. Instead, a coincident positive IOD event counteracted the Pacific influence, and the seasonal rainfall anomaly finished at just minus 0.08 millimetres per day, essentially normal. Over the full record, the two modes were jointly positive in 32 years, yielding an average anomaly of 0.48 millimetres per day, and jointly negative in 37 years, averaging minus 0.68 millimetres per day. Years of opposing phases, 52 in total, produced near-normal seasons regardless of which mode dominated.

Beneath this interannual drama, the study uncovers a longer-term reorganisation of the monsoon system. Splitting the record into two epochs, 1901 to 1960 and 1961 to 2021, the researchers found that sea surface temperatures in both basins showed little or no warming trend in the first epoch but steep warming in the second. The Indian Ocean warmed faster than the Pacific, consistent with the assessment of the Intergovernmental Panel on Climate Change that the Indian Ocean and western Pacific have warmed faster than the global average. The variance of the Niño-3.4 index, a standard measure of ENSO, increased from 0.29 to 0.42 square kelvin between the epochs, while the variance of the dipole mode index rose from 0.08 to 0.12 square kelvin, signalling more energetic variability in both oceans.

The rainfall itself followed suit. Nonlinear trend analysis, performed with ensemble empirical mode decomposition and independently confirmed by the MSSA method, reveals that the all-India monsoon rainfall was dominated by strong positive anomalies before 1960 and by predominantly negative anomalies with an almost flat trend after 1960. The two ocean-driven modes shifted in opposite directions: the ENSO-related rainfall mode, which had an increasing trend in the first epoch, settled into a near-flat but positive regime in the second, while the IOD-related mode flipped from positive anomalies in the first epoch to a pronounced negative trend in the second. The relative strength of the two modes, rather than the behaviour of either alone, therefore largely determines the long-term character of the monsoon.

The spatial fingerprints of the two epochs also differ in revealing ways. Correlation maps show that the ENSO-monsoon relationship has remained essentially stable across the century, with the familiar Pacific pattern of sea surface temperature anomalies linked to Indian rainfall in both epochs. The IOD-monsoon relationship, by contrast, was weak and ill-defined before 1960 but became stronger and better organised after 1960, particularly when the IOD and ENSO influences opposed each other. In the second epoch, positive rainfall anomalies became associated with a clear positive dipole pattern in the Indian Ocean, whereas in the first epoch the corresponding dipole signature was weakly negative. The authors attribute this reorganisation to the anomalous warming of the Indian Ocean, which has significantly altered the intensity and phases of the IOD mode and its associated rainfall over the past six decades.

The implications reach well beyond the archive of historical gauges. India has issued seasonal monsoon forecasts for more than a century, first with statistical regression models that ultimately showed little skill and more recently with dynamical global models that still perform poorly. The authors argue that a central reason for this shortfall is the inadequate representation of the oceans in prediction systems. Their findings suggest that reliable seasonal forecasts and long-term projections demand coupled ocean-atmosphere models capable of correctly simulating sea surface temperatures over both the Pacific and the Indian Ocean, including the Arabian Sea, and of capturing the constructive and destructive interference between the two basins’ influences.

The study also leaves open a compelling question for future research: why did the epochal shift occur around 1960, and how will the monsoon respond as the differential warming of the two oceans continues through the twenty-first century? With ocean heat content expected to keep rising, and with the livelihoods of more than a billion people hanging on the answer, the framework developed by Krishnamurthy and Shukla provides a unified way to read the monsoon’s past and a sharper lens for anticipating its future. What emerges is a monsoon not governed by a single oceanic puppeteer, but by a delicate duet between two warming basins, one whose harmony, and discord, may now be changing with the climate itself.

Subject of Research: Long-term variability of Indian summer monsoon rainfall linked to ENSO and the Indian Ocean Dipole under differential ocean warming

Article Title: Long-term variability of Indian monsoon rainfall related to warming of Indian and Pacific oceans

Article References: Krishnamurthy, V., & Shukla, J. (2026). Long-term variability of Indian monsoon rainfall related to warming of Indian and Pacific oceans. Climate Dynamics, 64(11), Article 451. https://doi.org/10.1007/s00382-026-08409-4

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08409-4

Keywords: Indian monsoon, ENSO, Indian Ocean Dipole, sea surface temperature, ocean warming, climate variability, seasonal prediction, Climate Dynamics, monsoon rainfall, Pacific Ocean, Indian Ocean, climate change

Marine heatwaves are defined as periods when ocean temperatures exceed a seasonally varying threshold for at least several consecutive days, and they have earned a reputation as some of the most disruptive climatic events in the sea. Globally, these events have been linked to mass coral bleaching, collapses in fisheries, shifts in species distributions, and economic losses for coastal communities. The Arabian Sea is one of the fastest-warming ocean regions on the planet, and the Lakshadweep Sea, an archipelago of coral atolls off India’s west coast, sits squarely within this warming bullseye. Yet while scientists have extensively catalogued surface marine heatwaves using satellite sea surface temperature records, the subsurface story has remained largely unwritten, particularly for the tropical Indian Ocean.

To fill that gap, Chacko combined high-resolution satellite sea surface temperature data from NOAA’s OISST archive with the Copernicus GLORYS ocean reanalysis, which reconstructs three-dimensional ocean conditions, and atmospheric fields from the ERA5 reanalysis. This combination allowed the study to track heatwave events not just at the surface but layer by layer through the upper ocean, from the wind-stirred mixed layer down through the thermocline, the zone of rapid temperature decrease that separates warm surface waters from the cold depths. The analysis applied standard marine heatwave metrics, including frequency, duration, and cumulative intensity, at each depth level, painting a vertical cross-section of extreme warming that surface-only studies cannot provide.

The headline finding is striking: the Lakshadweep Sea experiences roughly two to three surface marine heatwaves each year, typically lasting twelve to eighteen days, and all the key surface metrics are trending upward. But the real drama happens below. Although heatwave frequency decreases with depth, both the duration and the intensity of events increase, peaking within the thermocline. The maximum cumulative intensity was found between 80 and 100 meters, identifying this narrow band of the water column as the epicenter of subsurface heatwave activity. In other words, the ocean’s most punishing thermal stress in this region is not at the surface where monitoring is easiest, but in the twilight zone where light-loving reef organisms and thermally sensitive plankton live.

Even more concerning is the severity comparison. Surface marine heatwaves in the Lakshadweep Sea are typically classified as moderate or strong on the standard severity scale. Subsurface events, by contrast, are often more severe than their surface counterparts, meaning the temperature anomalies relative to their local baselines are larger and the events more punishing for organisms at depth. This asymmetry has profound implications. Coral reefs in Lakshadweep depend not only on water temperature at the reef surface but on the thermal structure of the entire water column, and deep-dwelling species, larval stages, and subsurface chlorophyll maxima may experience thermal stress that no satellite could ever detect.

The study’s composite analysis of atmospheric and upper-ocean conditions during heatwave onset and decline reveals the machinery behind these events. During the onset phase, coherent changes appear in net heat flux, mixed layer depth, stratification, and wind stress curl. A shallower mixed layer and enhanced stratification can trap heat in a thin near-surface layer, allowing temperatures to spike rapidly, while shifts in wind stress curl influence how heat is redistributed horizontally and vertically. These atmospheric and oceanic ingredients interact in ways that precondition the sea for extreme warming, echoing findings from other regions such as the Yellow Sea and eastern Australia, where stratification has been shown to play a key role in heatwave development.

The ocean heat budget analysis adds quantitative weight to this picture. Chacko found that the warming during the onset of heatwave events is driven by a combination of surface heat fluxes, horizontal advection of warm waters, and other unresolved processes that the reanalysis cannot fully capture. During the decline phase, however, the story changes: heat loss is dominated by horizontal advection, meaning that currents sweeping cooler water into the region are the primary mechanism that ends these events. This distinction matters for forecasting, because it suggests that predicting the end of a Lakshadweep heatwave requires understanding regional circulation, not just local weather patterns.

The findings place the Lakshadweep Sea within a growing global recognition that marine heatwaves are fundamentally three-dimensional phenomena. Recent international studies have documented bottom marine heatwaves along North American continental shelves, subsurface intensification off southeastern Australia, and hidden heatwaves beneath the surface of the global ocean. A global assessment published in Nature Climate Change in 2023 warned that marine biodiversity is exposed to prolonged and intense subsurface heatwaves that surface observations systematically miss. The Lakshadweep study extends this message to the northern Indian Ocean, where the combination of strong seasonal monsoon forcing, eddy activity, and rapid basin-wide warming creates a particularly dynamic environment for extreme events.

For the Lakshadweep archipelago itself, the stakes could hardly be higher. The atolls support hard coral communities whose diversity and spatial structure have been documented in studies of islands such as Agatti, and coral bleaching episodes worldwide have repeatedly followed marine heatwave events. Thermal stress concentrated in the 80 to 100 meter band may affect organisms and ecological processes that reef monitoring programs, which typically focus on shallow depths, never observe until damage is already done. Subsurface heatwaves could also influence the vertical distribution of chlorophyll and plankton in the region, with cascading effects through the food web to fish populations that support local livelihoods. As the study notes, thermal stress within ecologically sensitive subsurface layers can have profound implications for marine ecosystems that surface observations alone cannot adequately capture.

The broader lesson of this research is a call to rethink how we monitor and prepare for ocean extremes. Satellites see only the skin of the sea, and as this study demonstrates, that skin can be a misleading guide to what lies below. Sustained subsurface observing systems, high-resolution ocean reanalyses, and heat budget diagnostics will be essential tools as the Arabian Sea continues to warm at one of the fastest rates on Earth. For the coral atolls of Lakshadweep, and for the millions of people whose coasts border the Indian Ocean, understanding the hidden vertical structure of marine heatwaves may prove just as important as tracking the heat we can see from space.

Subject of Research: Subsurface marine heatwaves, their vertical structure and drivers in the Lakshadweep Sea of the Arabian Sea

Article Title: Subsurface marine heatwaves in the Lakshadweep Sea: characteristics, vertical structure, and drivers

Article References: Chacko, N. (2026). Subsurface marine heatwaves in the Lakshadweep Sea: characteristics, vertical structure, and drivers. Climate Dynamics, 64(10), Article 417. https://doi.org/10.1007/s00382-026-08370-2

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08370-2

Keywords: marine heatwaves, Lakshadweep Sea, Arabian Sea, subsurface ocean warming, thermocline, coral reefs, ocean heat budget, Climate Dynamics, ocean stratification, Indian Ocean warming, sea surface temperature, marine ecosystems

Zooplankton occupy a pivotal position in marine ecosystems. As the principal consumers of phytoplankton, they convert microscopic plant production into animal biomass that can be passed to higher trophic levels, including commercially important fish stocks. They also play an outsized role in biogeochemical cycling, influencing the exchange of carbon dioxide between the atmosphere and the surface ocean and packaging organic carbon into fecal pellets that sink toward the deep sea. Any sustained change in their abundance therefore ripples outward, affecting nutrient cycling, water quality, fisheries yields, and the ocean’s capacity to sequester carbon. Yet despite their importance, zooplankton dynamics in the Indian Ocean have received far less attention than in other ocean basins, partly because quality-controlled, gridded biogeochemical data for the region have long been scarce.

To overcome this data gap, the team drew on the Coastal and Oceanic Plankton Ecology, Production, and Observation Database, known as COPEPOD, a global archive containing more than 400,000 records of copepods and other plankton taxa, with observations stretching back to around 1913. The biomass fields from the upper epipelagic layer, typically between the surface and 200 meters, were converted into carbon mass and merged into a single gridded product at one-degree horizontal resolution. The researchers then evaluated how well seven Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project, or CMIP6, could reproduce the observed patterns, integrating model zooplankton values down to 200 meters for the historical period 1975 to 2014 and for future scenarios running from 2061 to 2100.

The observed picture is strikingly asymmetric. Zooplankton concentration in the Arabian Sea averages about 15.6 milligrams of carbon per cubic meter, roughly 20 percent higher than in the Bay of Bengal, where the mean is about 13.0 milligrams per cubic meter. The difference stems from the fundamentally different hydrography of the two basins. The Arabian Sea experiences monsoon-driven upwelling, winter convective mixing, and high evaporation that produces dense, salty surface water which sinks and stirs the water column, all of which replenish nutrients in the sunlit layer. The Bay of Bengal, by contrast, is drenched by freshwater runoff from major rivers, which suppresses salinity, strengthens stratification, and blocks the upward transport of nutrient-rich subsurface water. Only near river mouths, where terrigenous nutrients locally offset the stratification, does the Bay of Bengal show elevated zooplankton concentrations.

The seasonal rhythm of zooplankton in the Arabian Sea is equally distinctive. Biomass peaks twice each year. The dominant peak arrives during the summer monsoon from July to September, when the strong southwesterly winds drive coastal and open-ocean upwelling, particularly along the western Arabian Sea, where the northward-flowing Somali Current lifts nutrient-laden deep water to the surface. A secondary peak occurs in winter from December to February, when the dry northeast monsoon cools the surface waters of the northern Arabian Sea, weakens thermal stratification, and allows convective mixing to fertilize the euphotic zone. Concentrations bottom out in April and May, when intense solar heating strengthens stratification and cuts off the vertical nutrient supply. The Bay of Bengal, in contrast, shows remarkably little seasonal variability, with a modest maximum in August and September.

Before projecting the future, the authors rigorously tested the models against observations. Statistical measures including correlation coefficients, root mean square errors, and skewness revealed that GFDL-ESM4, MPI-ESM1-2-HR, and IPSL-CM6A-LR performed best at capturing both the spatial pattern and the temporal variability of zooplankton over the Indian Ocean, with correlations between roughly 0.58 and 0.68, significant at the 99.9 percent level. Other models fared poorly: CanESM5 showed the worst performance, while CESM2 produced an abruptly high error of 9.06 milligrams of carbon per cubic meter. The team constructed a multi-model mean from the three best performers, a strategy that prioritizes spatial pattern fidelity over ensemble size. The authors also caution that converting modeled zooplankton biomass from nitrogen to carbon units introduces uncertainty, since plausible copepod carbon-to-nitrogen ratios alone can shift estimated biomass by 10 to 40 percent, though model bias generally explains the larger discrepancies.

The future projections are sobering. Under the moderate SSP2-4.5 scenario and the very high SSP5-8.5 scenario, zooplankton concentration declines across the entire basin, with regional reductions ranging from 5 to 40 percent. The steepest losses, exceeding 5 milligrams of carbon per cubic meter or roughly 40 percent, are projected for the western and central Arabian Sea under the high-warming pathway, while the southern Bay of Bengal is more affected than the north. When the researchers linearly detrended the datasets to remove long-term warming signals, the projected differences became statistically insignificant, confirming that greenhouse-gas-driven climate change, rather than natural variability, is the dominant cause of the decline. Notably, the projected zooplankton losses exceed the 5 to 20 percent declines in chlorophyll and net primary productivity reported in earlier CMIP5 and CMIP6 studies, hinting at a trophic amplification of climate impacts as warming effects cascade from primary producers to secondary consumers.

The mechanism behind the decline is a familiar one in ocean-climate science but is here documented with unusual regional detail. As the ocean warms, sea surface temperatures rise and sea surface salinity falls, and the upper layers of the Arabian Sea heat faster than the deeper waters. This sharpens the density contrast between surface and subsurface layers, strengthening vertical stratification and shoaling the mixed layer. A thinner, more isolated surface layer receives less nutrient-rich deep water through upwelling and entrainment, so phytoplankton growth slows and zooplankton, which depend on that grazing resource, decline in turn. Because zooplankton also mediate the biological carbon pump, reduced biomass could weaken the export of organic carbon to the deep ocean and increase remineralization in surface waters, with consequences for the ocean’s role in the global carbon budget.

Perhaps the most intriguing finding concerns the changing relationship between zooplankton and the great modes of natural climate variability, the El Niño-Southern Oscillation and the Indian Ocean Dipole. In the historical period, the El Niño-Southern Oscillation is significantly negatively correlated with zooplankton concentration over most of the Arabian Sea and the southern and central Bay of Bengal. Under future warming, however, that negative correlation over the Arabian Sea weakens almost to vanishing, suggesting that long-term stratification and warming trends will override interannual climate signals there. Process-based analysis supports this: ENSO-driven thermocline deepening and weakened wind stress curl anomalies suppress Ekman pumping and upwelling, cutting off the nutrient supply. In the Bay of Bengal and the equatorial Indian Ocean, the opposite occurs, with ENSO and the Indian Ocean Dipole projected to enhance zooplankton concentrations through thermocline shoaling and increased upwelling, potentially making those ecosystems more volatile from year to year.

The regional divergence carries real-world consequences. A more stable but steadily declining zooplankton base in the Arabian Sea, and more erratic swings in the Bay of Bengal, could translate into greater uncertainty in fish catches for the densely populated coastlines that border both basins, threatening food security across Indian Ocean rim countries. The authors acknowledge important limitations: CMIP6 models represent zooplankton as a single aggregated functional group, so shifts in community composition, body size, and trophic efficiency remain invisible to the analysis, even though warming is known to favor smaller, warm-adapted taxa that produce more slowly sinking fecal pellets and export less carbon. Coarse model resolution may also miss vertical redistribution of biomass through diel migration. Even so, the simulated decline in biomass is robust across models, and the study underscores an urgent need for sustained ocean monitoring, taxonomically resolved ecosystem models, and adaptation strategies to manage the changing marine ecosystems of the Indian Ocean.

Subject of Research: Upper-ocean zooplankton variability and projected climate-driven decline in the Indian Ocean using COPEPOD observations and CMIP6 model simulations

Article Title: Understanding upper ocean zooplankton variability in the Indian Ocean using observations and CMIP6 models

Article References: Understanding upper ocean zooplankton variability in the Indian Ocean using observations and CMIP6 models. (n.d.). https://doi.org/10.1007/s44289-026-00177-7

Image Credits: AI Generated

DOI: 10.1007/s44289-026-00177-7

Keywords: zooplankton, Indian Ocean, Arabian Sea, Bay of Bengal, CMIP6, climate change, ocean stratification, upwelling, ENSO, Indian Ocean Dipole, marine food web, monsoon