Abstract Barrier layer (BL) thickness (BLT) modulates tropical cyclone (TC) intensity, yet its evolution mechanisms remain debated. While statistical studies attribute BL thickening to heavy precipitation in strong or slow‐moving TCs, numerical experiments suggest that enhanced wind‐driven mixing tends to erode it. Here, using reanalysis‐based statistical and composite analyses, we reconcile previously conflicting findings. Weak TCs predominantly thicken the BLT through precipitation‐driven surface freshening. In contrast, strong TCs tend to erode the BL owing to enhanced wind‐driven mixing and Ekman upwelling, which weaken salinity stratification and shoal the isothermal layer base, respectively. TC translation speed modulates these responses via the duration of forcings: fast‐moving TCs induce relatively weak BLT changes, whereas slow‐moving TCs generate stronger thickening and erosion. Across all translation speeds, however, precipitation effects dominate over wind‐driven processes, making thickening the prevailing response. These results clarify the competing mechanisms controlling BLT evolution and provide guidance for improving TC intensity forecasts.

The diurnal temperature range (DTR), defined as the difference between daily maximum and minimum temperatures, is a key indicator of diurnal climate variability and a sensitive measure of model performance. Since 1901, the observed global DTR has declined significantly, a trend previously underestimated by climate models. Here, we show that the latest model ensemble of Coupled Model Intercomparison Project phase 6 (CMIP6) simulates this decline more accurately than CMIP5. This improvement is primarily due to a stronger overall response to external forcings, particularly from greenhouse gases (GHG) and natural forcing (NAT), which leads to a multi-model mean trend much closer to observations. Furthermore, optimal fingerprinting analysis reveals a fundamental shift in attribution structure: while CMIP5 attributes the change almost solely to GHG, CMIP6 supports a more physically coherent, multi-forcing framework in which GHG remains dominant but statistically detectable contributions from NAT and anthropogenic aerosols (AER) emerge, collectively yielding a more realistic forcing synergy. CMIP6 also better captures the distinct regional DTR patterns driven by anthropogenic aerosols. A central reason for this enhanced forcing response is the higher equilibrium climate sensitivity (ECS) in CMIP6 models. Models with ECS values closer to observationally constrained estimates simulate a more substantial and consistent DTR decline. This link is likely due to improved cloud physics, which simultaneously elevates ECS and refines the surface solar radiation variations driving DTR. Therefore, CMIP6's superior performance stems from a more realistic physical basis rather than error compensation. These findings deepen the understanding of DTR changes and provide key insights for future climate model development.

Abstract The influence of the tropical Atlantic on El Niño‐Southern Oscillation (ENSO) predictability remains debated, with contrasting views on whether it reflects a genuine teleconnection or ENSO's autocorrelation. Using a convolutional neural network (CNN), we revisit this issue and demonstrate the important role of summer tropical Atlantic in ENSO predictions. The CNN reveals that tropical Atlantic during boreal summer, autumn, and winter enhances ENSO predictability, whereas its predictive value is limited in spring. We employ pacemaker simulations to elucidate mechanisms underlying CNN findings. Warm summer sea surface temperature (SST) anomalies near Intertropical Convergence Zone (ITCZ) amplify atmospheric deep convection, generating atmospheric Kelvin waves, and modifying zonal atmospheric circulation that alter Pacific Walker circulation and thermocline adjustments, promoting winter La Niña. In contrast, weaker convection arises as spring SST anomalies lie farther from ITCZ, diminishing their influence. This study provides new evidence for a season‐dependent Atlantic‐Pacific linkage and highlights a summer‐initiated pathway for ENSO predictability.

Abstract The Indian Ocean Dipole (IOD), traditionally defined by the sea surface temperature (SST) anomaly gradient between the tropical western and eastern Indian Ocean, is revealed here to comprise two distinct types. Using multiple systematic approaches, including standard deviation analysis and SST mode combinations, we identify a western–eastern type and a central–eastern type, distinguished by their SST anomaly patterns, seasonal evolution, and feedback mechanisms. The western–eastern type reaches its peak later in boreal autumn due to a strong but delayed wind–thermocline–SST feedback, whereas the central–eastern type peaks earlier, governed by a weaker and earlier feedback. Crucially, the positive western–eastern type—more strongly linked to enhanced East African rainfall than the traditional IOD—has intensified in recent decades, heightening the risk of rainfall-related disasters across East Africa. These findings refine the conceptual framework of the IOD and underscore the growing climate hazard posed by its changing characteristics.

La Niña events vary widely in duration, from single-year to multi-year. However, their influence on Bering Sea ice concentration remains unclear. Here, we show that single-year and multi-year La Niña events produce contrasting impacts on spring Bering Sea ice concentration. Multi-year events mitigate the long-term decline—without them, the rate of ice loss would be 11.1% higher. During the first two decay-phase springs, multi-year events generate a negative meridional Rossby wave train that induces northerly wind anomalies, enhancing cold advection and upward sensible heat fluxes, thereby slowing ice loss. In contrast, single-year events coincide with a positive North Pacific Oscillation pattern that drives southerly anomalies, reduces heat fluxes, and suppresses ice formation. These results identify La Niña duration as a key predictor of Bering Sea ice variability. An increasing frequency of multi-year events could therefore help buffer spring Bering Sea ice decline under global warming, highlighting the importance of tropical–subarctic teleconnections in subarctic climate variability. Multi-year La Niña events mitigate the long-term decline in spring ice concentration in the Bering Sea, whereas single-year events suppress ice formation, as revealed by observations and climate model simulations.

Tropical cyclone (TC) activity over the western North Pacific (WNP), the most active TC basin worldwide, is generally viewed as being controlled by remote oceanic forcing, especially the El Niño–Southern Oscillation. However, oceanic forcing alone cannot fully explain variability in TC genesis. Here we show that the record-low WNP typhoon season of 2023 emerged from strong seasonal asymmetry rather than uniform suppression. Despite unfavorable large-scale ocean conditions, summer TC genesis frequency remained near climatology because a weakened Indian summer monsoon (ISM) triggered an atmospheric Kelvin-wave response that induced a WNP cyclonic circulation anomaly. This circulation offset the ocean-forced anticyclone and maintained environmental conditions favorable for TC genesis. In contrast, remote ocean forcing dominated during autumn, producing unprecedented suppression and driving the seasonal minimum. These results highlight a pathway by which ISM variability can counteract basin-scale oceanic forcing and regulate WNP TC variability, with potential implications for improving TC prediction.

The occurrence of marine heatwaves (MHWs) and phytoplankton blooms is accelerating under climate change, yet the frequency and drivers of their compound co-occurrence remain poorly understood. Using coastal-optimized satellite observations from 2003–2020, we mapped global compound MHW–phytoplankton bloom (MHW-PB) events across coastal large marine ecosystems and quantified their spatiotemporal trends and environmental predictors. Compound events are increasing at 4.8% yr−1, driven primarily by a 6.5% yr−1 rise in MHW frequency; a temporal shuffle test confirms this trend falls below random co-occurrence expectation, indicating biological suppression actively constrains compound event growth. The compound independence factor (CIF) reveals latitudinal heterogeneity: low-latitude upwelling systems show MHW–PB mutual exclusivity, while high-latitude and eutrophic coastal regions show positive co-occurrence tendency. Interpretable machine learning further shows that nutrient availability dominates bloom responses at low latitudes whereas light dominates at high latitudes, with MHW intensity exhibiting nutrient-dependent non-linear associations with bloom probability. Paradoxically, compound frequency accelerates nearly twice as fast in low latitudes (6.1% yr−1) as in high latitudes (3.5% yr−1), driven by rapid tropical MHW acceleration. These diverging regimes signal dual ecological risks: trophic mismatches in upwelling systems and escalating hypoxia and harmful algal bloom hazards in eutrophic coastal waters.

In April 2024, South China experienced unprecedented rainfall causing widespread socioeconomic disruption. We show that this extreme rainfall arose from atmospheric anomalies driven by record-breaking sea surface temperature anomalies across the tropical Pacific, Indian Ocean, and North Atlantic. Observations reveal that the western North Pacific subtropical high reached its northernmost position since 1979, intensifying moisture transport into South China, while an enhanced Okhotsk High promoted cold-air intrusions, thereby amplifying South China rainfall. Climate model experiments demonstrate that the sea surface temperature anomalies across all three basins reinforced the anomalous anticyclone over the western North Pacific and enhanced Southeast Asian rainfall. Additionally, warming in the tropical Indian and Atlantic Oceans may enhance rainfall by intensifying the Okhotsk High. These results identify pan-tropical ocean warming as a key driver of the event and highlight the synergistic impacts of inter-basin interactions. Our findings underscore the growing importance of warm ocean basins in shaping regional hydroclimate extremes and provide insights to improve prediction and risk management in a warming climate. The extreme rainfall event in South China in April 2024 is driven by exceptional pan-tropical ocean warming, which strengthens the northward shift of western North Pacific subtropical high and intensifies Okhotsk High, revealed by observations and climate model experiments.

During summer 2025, subtropical Asia experienced concurrent flooding over western South Asia and hot-dry extremes over the Yangtze River Basin, forming a pronounced zonal dipole across the western and eastern flanks of the Tibetan Plateau (TP) near 30 degrees N. While this pattern closely resembles the record-breaking extremes of 2022, the associated lower-tropospheric circulation anomalies differ remarkably. From a historical perspective, we identify anomalous upper-tropospheric zonal flow over the TP as a key triggering mechanism. Given the climatological warm center over the TP in summer, upper-tropospheric easterly (westerly) anomalies induce anomalous ascent (descent) over the western flank and descent (ascent) over the eastern flank of the TP, thereby generating a zonal dipole in surface climate. Upper-tropospheric easterly anomalies reached record strength in 2022 and were the second strongest in 2025 since 1979, providing a unified dynamical explanation for these Asian zonal-dipole climate extremes. Variability of the zonal flow over the TP is primarily a regional manifestation of subtropical zonal-mean zonal flow, modulated by meridional sea surface temperature (SST) contrasts between the tropical and North Pacific. Exceptionally weak Pacific meridional SST contrasts, as observed in 2022 and 2025, reduce the meridional tropospheric temperature gradient and weaken subtropical upper-tropospheric westerlies through thermal wind balance. These results identify subtropical upper-tropospheric zonal flow as a key bridge linking Pacific SST variability to Asian zonal-dipole climate variability across the TP.

The Amazon Basin has undergone rapid deforestation since the 1970s, causing biodiversity loss, regional climate shifts, and increased greenhouse gas emissions. Yet its impact on tropical ocean-atmosphere coupled variability remains unknown. Using observational datasets and targeted coupled general circulation model experiments, here we find that Amazon deforestation has contributed substantially (~23%) to the observed weakening of Atlantic Niño variability since 1970. Observational analyses and model experiments reveal that local warming and drying associated with deforestation enhance the interhemispheric thermal contrast over the tropical Atlantic. The enhanced thermal contrast strengthens surface cross-equatorial southerly winds, which in turn reduce the sensitivity of zonal wind stress to the zonal sea surface temperature gradient, weakening the Bjerknes feedback and Atlantic Niño variability. The combined observational and modeling results highlight a critical influence of land surface changes on the dynamics of the tropical coupled ocean-atmosphere system.

Coral reefs worldwide are suffering from severe bleaching due to their high sensitivity to the prolonged and intense marine heatwaves (MHWs). However, the geographical differences in MHW characteristics remain insufficiently explored across global coral reef zones during the warm season, limiting our understanding of coral reef ecological response to spatially inhomogeneous MHWs. Here, we present a comprehensive global assessment of mean values, trends, and category changes in MHWs across 10 key regions based on the daily Optimum Interpolation Sea Surface Temperature (SST) dataset from 1982 to 2021. We also examine SST variability between the 20th (1900–1999) and 21st (2000–2099) centuries in coral reef zones and assess projected changes in MHW metrics under a 1.5 °C warming scenario. Results indicate that, in contrast to the declining maximum and mean intensities of MHWs, annual days and cumulative intensity have increased in most key regions during 1982‒2021. MHW in Moderate (1‒2×) and Strong (2‒3×) categories have become increasingly dominant (7.91 ± 1.11 and 1.81 ± 0.94 counts per decade, p < 0.01) over 1982‒2021. The first mode of Empirical orthogonal function (EOF) analysis of seasonal MHW days reveals a clear El Niño–Southern Oscillation signal, and a composite analysis further confirms the contribution of spring and summer MHWs to the widespread coral bleaching. Under both SSP245 and SSP585 scenarios, increased SST variability (0.0–0.4 °C), projected increases in upper ocean heat content (1–6 × 108 J/m2 per decade) and reductions in mixed layer depth (−0.2–−1.6 m per decade) may lead to longer and more intense MHWs. These MHWs further challenge the thermal tolerance of coral reefs that already live at their upper limit, urging a more comprehensive understanding of their ecological response that may help develop alleviation measures.

Abstract The record‐breaking annual mean global sea surface temperature in 2024 fueled extensive marine heatwaves (MHWs) across global coral reef zones, yet their spatiotemporal characteristics have not been comprehensively quantified. Here, we show that during the 2024 warm‐season, MHW total days and cumulative intensity exceeded the historical mean by more than 3 standard deviations. Widespread and persistent MHWs occurred across major coral reef regions, particularly in the Red Sea, Coral Triangle, Fiji, the Caribbean, and Brazil. Most coral biogeographic provinces experienced significant increases in the frequency of Moderate, Strong, and Severe MHW categories relative to the 1985–2024 climatology. These extreme events were associated with substantial accumulation of ocean heat content in the Indo‐Pacific warm pool and tropical Atlantic following the transition from the triple‐dip La Niña (2020–2023) to the 2023–2024 El Niño. Regional oceanographic conditions further modulated the intensity and drivers of warm‐season MHWs in 2024.

The Atlantic Niño, a climate pattern involving periodic warming of the tropical Atlantic Ocean, can be categorized into two main types based on where the warming is strongest: in the central (CA) or eastern (EA) basin. Our research investigates whether these two types have different effects on Pacific typhoons. We find that they indeed drive very distinct impacts. Composite and correlation analyses indicate that CA events induce a meridional dipole in TC formation, while EA impacts are weaker and less organized. The results reveal a clear meridional dipole pattern in TC genesis associated with the two types of Atlantic variability. Specifically, CA events exert a pronounced influence, enhancing TC genesis north of 20°N during CA Niño and south of 20°N during CA Niña. After removing the linear influence of ENSO, the relationship between Atlantic variability and TC activity weakens substantially for ATL3 and EA indices, whereas it remains robust for the CA index, suggesting a more direct and independent teleconnection pathway for CA events. CA Niño efficiently excites a well-structured extratropical Rossby wave train that reaches the WNP, whereas EA signals are weaker and more diffuse. Both CA and EA events are associated with a Walker-type circulation linking the tropical Atlantic and Indo–Pacific. CAM4 sensitivity experiments further support these findings, demonstrating that CA-type SST forcing can reproduce the key tropical–extratropical response extending into the WNP, whereas the EA-type forcing yields a substantially weaker adjustment. Overall, these results demonstrate that CA and EA events exert fundamentally different influences on Pacific atmospheric circulation, with CA variability playing a more dominant role in modulating WNP TC genesis.

The southward shift of anomalous westerlies from the equator to the south off‐equatorial areas plays a curtail role in demising El Niño, and was attributed to seasonal changes in the large‐scale environments in previous studies. Given that the southward shift exhibits a distinct spectral peak at the sub‐seasonal timescale, we propose that it could also be caused by the seasonal meridional movement of high‐frequency variabilities in the western tropical Pacific, such as the tropical cyclones (TCs) and Madden Julian Oscillation (MJO). It is found that the TCs and MJOs contribute to approximately 39% and 20% of the southward shift from October in El Niño years to the following March, respectively, both of which are significant at the 95% confidence level. Our findings supplement dynamics regarding to El Niño decay, and imply the necessity of improving seasonal forecast of high‐frequency variabilities for a better prediction of El Niño.

Atlantic Niño can influence ENSO by modulating the Pacific Walker circulation. This interbasin connection is dominated by central Atlantic Niño (CAN) events, which began to emerge around 2000. Our analysis of observational data and climate model simulations reveals that the influence of CAN on ENSO will strengthen in a warming climate due to an enhanced Pacific response. On one hand, increased variability of the eastern Pacific intertropical convergence zone leads to stronger subsidence anomalies induced by CAN; on the other hand, strengthened atmospheric variability over the North Indian Ocean enhances the region’s response to CAN-induced Kelvin waves, promoting easterly anomalies over the western tropical Pacific. These changes are further linked to the pronounced interhemispheric warming contrast projected by climate models. Our findings underscore the growing influence of Atlantic Niño on ENSO, with important implications for seasonal climate prediction and future climate change projections.

The El Ni & ntilde;o-Southern Oscillation is a major driver of global climate and weather variability through atmospheric teleconnections. However, the 2023/24 El Ni & ntilde;o event, despite ranking as the fourth strongest since 1979, exhibited an unusually weak Pacific-North American pattern. Here we show that this unexpected behavior is due to anomalously weak tropical Pacific rainfall changes, a key driver of teleconnections associated with El Ni & ntilde;o. Through analysis of observational data during 1979-2023 and performing atmospheric model experiments, we further reveal that the suppressed tropical Pacific rainfall changes were caused by unprecedented warming in the tropical Indian and Atlantic Oceans in 2023. This warming, partly driven by long-term trends exceeding those in the tropical Pacific, has amplified the influence of these extra-Pacific basins on El Ni & ntilde;o dynamics. Notably, current climate models fail to reproduce this interbasin warming contrast, highlighting critical challenges in their ability to predict future climate impacts associated with El Ni & ntilde;o events.

Multi-year marine heatwaves (MHWs) in the Gulf of Alaska (GOA) are major climate events with lasting ecological and economic effects. Though often seen as local Pacific phenomena, our study shows their persistence depends on trans-basin interactions between the North Pacific and North Atlantic. Using observational data and climate model experiments, we find that prolonged MHWs occur as sequential warming episodes triggered by atmospheric wave trains crossing ocean basins. These wave trains alter surface heat flux, initiating MHWs in the GOA and changing North Atlantic sea surface temperatures (SSTs). In turn, Atlantic SST anomalies reinforce wave activity, fueling subsequent MHW episodes in a feedback loop. This mechanism appears in historical events (1949–52, 1962–65, 2013–16, and 2018–22), highlighting MHWs as a trans-basin phenomenon. Our findings link GOA MHWs to trans-basin atmospheric wave dynamics and identify North Atlantic SSTs as a potential predictor of their duration.

The sea ice variabilities in West Antarctica, crucial for both local and global climate systems, are profoundly affected by the sea surface temperature anomalies over the tropical Atlantic. Analyses based on observational data and numerical model experiments demonstrate that the two recently identified Atlantic Niño types, central and eastern Atlantic Niño (CAN and EAN), have distinct impacts on the sea ice concentration in West Antarctica. The CAN stimulates two atmospheric Rossby wave trains in the Southern Hemisphere through both direct and indirect pathways, collectively strengthening the Amundsen Sea Low. In contrast, the EAN only excites one atmospheric wave train over the South Pacific through an indirect pathway, due to its associated weaker local Hadley circulation, which fails to establish a significant Rossby wave source in the subtropical South Atlantic. Consequently, compared to the EAN, the atmospheric circulation and the associated sea ice concentration anomalies in West Antarctica during the CAN are stronger and more extensive. Therefore, distinguishing between the two Atlantic Niño types could potentially enhance the seasonal prediction capabilities for sea ice concentration in West Antarctica.

Internal tides profoundly influence diapycnal mixing and marine ecosystems in oceans worldwide. Previous estimates on internal tides focused regionally spanning a decade, leaving a knowledge gap regarding their long-term global behavior, especially over centuries. Because of limited long-term observations, a critical question arises: How will global warming affect internal tides? Using the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the High-Resolution Empirical Tidal (HRET) model, we identify a robust accelerating trend in globally averaged internal tide speeds. This trend, increasing from historical rates (0.4 centimeters per second per decade) to future projections (2.0 centimeters per second per decade), is primarily driven by intensified upper-ocean stratification, with background currents playing a secondary role. Our findings suggest that internal tides propagate faster in a warming climate, potentially influencing energy cascade and marine biological productivity.

An analysis of buoy data from the National Data Buoy Center (NDBC) reveals that El Ni & ntilde;o significantly modulates subdaily variations in air-sea latent heat fluxes across the Hawaiian Islands. During El Ni & ntilde;o winter months, the mean amplitude (standard deviation) of these variations reached up to 35 W m22}approximately 11 W m22 greater than during La Ni & ntilde;a winters}representing a 33% increase. To clarify the underlying processes, we examined the drivers of subdaily latent heat flux variability under differing boundary layer stability regimes. Results show that El Ni & ntilde;o-Southern Oscillation (ENSO) phases alter the background air-sea humidity difference and wind speed, thereby influencing the amplitude of subdaily flux variations. By analyzing both daily mean and subdaily anomalies of wind speed and humidity difference during El Ni & ntilde;o and La Ni & ntilde;a events, we quantified their respective contributions. El Ni & ntilde;o enhances subdaily flux variability primarily by increasing background humidity differences and wind speeds under near-neutral boundary layer conditions. Under unstable conditions, the elevated humidity difference continues to dominate the variability. During El Ni & ntilde;o events, the contributions of background humidity difference and wind speed were 61% and 68%, respectively, under near-neutral stability, and 87% and 36%, respectively, under unstable conditions. These findings highlight the dynamic interplay between large-scale climate variability and high-frequency air-sea interaction processes in the central Pacific. SIGNIFICANCE STATEMENT: Latent heat flux plays a critical role in ocean-atmosphere interactions and ocean circulation. Elucidating its subdaily variation mechanisms is essential for advancing our understanding of ocean dynamics, climate impacts, and the global heat budget balance, with direct implications for enhancing predictive models and simulations. This study provides the first observational evidence that El Ni & ntilde;o amplifies subdaily latent heat flux variations near the Hawaiian Islands by up to 33%, driven by large background air-sea humidity differences and wind speeds under different boundary layer stability regimes. By linking small-scale flux variations to long-term climate signals, the findings advance the mechanistic understanding of ocean-atmosphere interactions, offering critical insights for improving the representation of subdaily processes in climate models.