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Coastal marine heatwaves (MHWs) derived from satellite and blended sea surface temperature (SST) products often disagree, but the magnitude and drivers of this uncertainty remain poorly quantified. Using four daily SST products from 1982 to 2023, we quantify agreement at 9,946 global coastal points using two inter‐product intersection‐over‐union metrics, a daily‐scale co‐identification rate (γ1${\\gamma }_{1}$ ) and an event‐scale rate (γ2${\\gamma }_{2}$ ) based on overlapping event intervals. We find low global agreement, with daily‐ and event‐scale rates averaging 12.34% ± 7.84% and 16.33% ± 8.35%, respectively, and interquartile ranges of 6.34%–17.19% and 10.17%–21.55%. Both γ1${\\gamma }_{1}$and γ2${\\gamma }_{2}$increase systematically with event duration and annual cumulative intensity. MHW trends are generally consistent across products, whereas trend attribution ratios show substantial inter‐product divergence. These results indicate comparatively consistent estimates of long‐term change but highlight the need to explicitly report multi‐product uncertainty in coastal attribution.

Marine heatwaves (MHWs) are extreme events characterized by abnormally high sea surface temperatures, and they have significant impacts on marine ecosystems and human society. The rapid and accurate forecasting of MHWs is crucial for preventing and responding to the impacts they can lead to. However, the research on relevant forecasting methods is limited, and a dedicated forecasting system specifically tailored for the South China Sea (SCS) region has yet to be reported. This study proposes a novel forecasting system utilizing U-Net and ConvLSTM models to predict MHWs in the SCS. Specifically, the U-Net model is used to forecast the intensity of MHWs, while the ConvLSTM model is employed to predict the probability of their occurrence. The indication of an MHW relies on both the intensity forecasted by the U-Net model exceeding threshold T and the occurrence probability predicted by the ConvLSTM model surpassing threshold P. Incorporating sensitivity analysis, optimal thresholds for T are determined as 0.9 °C, 0.8 °C, 1.0 °C, and 1.0 °C for 1-, 3-, 5-, and 7-day forecast lead times, respectively. Similarly, optimal thresholds for P are identified as 0.29, 0.30, 0.20, and 0.28. Employing these thresholds yields the highest forecast accuracy rates of 0.92, 0.89, 0.88, and 0.87 for the corresponding forecast lead times. This innovative approach gives better predictions of MHWs in the SCS, providing invaluable reference information for marine management authorities to make well-informed decisions and issue timely MHW warnings.

Reanalysis data reveals that the South China Sea (SCS) experiences intensified subsurface marine heatwaves (MHWs) and marine cold spells (MCSs) near the thermocline. On the interannual scale, surface and subsurface events demonstrate an opposite correlation with ENSO, primarily due to distinct drivers at different depths. During the developing phase of El Niño, the Luzon Strait transport, indicative of the SCS throughflow (SCSTF), increases and necessitates stronger upwelling for mass balance. This upwelling, acting on large subsurface vertical temperature gradients, induces significant subsurface cooling and the occurrence of MCSs. As El Niño matures, excessive atmospheric heat flux warms the surface layer, triggering surface MHWs. This heat is then transported downward mainly by vertical turbulent mixing, diminishing subsurface cooling, and terminating subsurface MCSs. The scenario reverses during La Niña events. The SCSTF serves as a vital oceanic pathway, transmitting ENSO signals into the SCS and profoundly modulating subsurface MHWs and MCSs. Plain Language Summary Marine heatwaves and cold spells are prolonged ocean temperature extremes that can occur at any ocean depth, severely threatening marine life. In the South China Sea (SCS), these events peak in mean intensity, duration, and cumulative intensity near the thermocline. Notably, surface heatwaves and subsurface cold spells occur during El Niño and vice versa during La Niña. This is due to varying drivers at different depths. The surface events are predominantly driven by atmospheric processes, while the subsurface events are mainly attributed to oceanic processes. The SCS features a throughflow that includes inflow from the Luzon Strait, which subsequently upwells and exits the basin through several shallow passages. During developing phase of El Niño, increased Luzon Strait transport indicates a strengthened throughflow, which entails enhanced upwelling. The subsurface layer, where the vertical temperature gradient peaks, experiences upward transport of cold water, leading to occurrence of cold spells. As El Niño matures, excessive atmospheric heat flux warms the surface layer, and this heat is transported downward, ending subsurface cold spells. During La Niña, the situation reverses. The SCS throughflow is a crucial oceanic pathway for transmitting ENSO influences, significantly modulating the subsurface events in the SCS. Key Points In the South China Sea (SCS), subsurface heatwaves and cold spells are distinctly associated with La Niña and El Niño phases, respectively The SCS throughflow is a key oceanic pathway that strengthens in El Niño and weakens in La Niña, modulating subsurface events Vertical advection associated with variations in the SCS throughflow dominates the occurrence of subsurface events

Marine heatwaves (MHWs) have become longer and more frequent over the past century under anthropogenic climate change, with devastating impacts on marine ecosystems. Surface MHWs (SMHWs) and their drivers have been extensively studied using satellite sea surface temperature data, yet the mechanism and characteristics of subsurface MHWs, especially bottom MHWs (BMHWs) along continental shelves, remain unclear. Based on a high-resolution ocean reanalysis dataset, we compare SMHWs and BMHWs along the continental shelf of China and find that BMHWs are typically longer (0–16 d) and more intense (0 °C–50 °C days) than SMHWs. The categorizing of both the BMHW and SMHW shows that moderate and strong events commonly occur in most areas with relatively large spatial coverage, whereas severe and extreme events occur with relatively small spatial coverage. There is a clear negative relationship between the BMHW intensity and ocean depth along the continental shelf, while the BMHW annual days and ocean depth are positively correlated in the Bohai and East China Seas. Generally, BMHWs and SMHWs occur more frequently in shallow coastal regions where the mixed layer depth is more likely to extend to the seafloor, resulting in high BMHW and SMHW synchrony. In addition to spatial coherence, there is a good temporal correspondence between BMHWs and SMHWs across the continental shelf of China from 1993 to 2020.

The East Sea/Japan Sea is one of the regions where ocean warming is the fastest. Selecting the best Global Climate Models (GCMs) specific to the East Sea is a crucial step in reducing uncertainty related to GCM simulations when studying the future projections of marine heatwaves (MHWs). This study identifies the best models that simulate the MHW metrics of frequency, maximum intensity, and duration in the East Sea by evaluating their performance at each grid level. The models were assessed using performance indicators of bias (BIAS) and interannual variability skill score (IVS) with reference to the National Oceanic and Atmospheric Administration (NOAA) dataset. A group decision-making approach was used to rank the models based on their grid-wise performances. Most models showed shortcomings in the simulation of MHW duration compared to that of frequency and maximum intensity. The best performing GCMs from the Coupled Model Intercomparison Project sixth phase (CMIP6) for this area were identified as NorESM2-MM and GFDL-ESM4. Based on the top-ranked approach, these two models were selected for the multi-model ensemble (MME) to analyze the future MHWs in the East Sea. The MME underestimated the frequency and maximum intensity but overestimated the duration for the historical period (1985-2014). The shifting baseline approach was employed for the future projection of MHWs during the near future (2041-2070) and far future (2071-2100) under four Shared Socioeconomic Pathways (SSPs). The projected future changes relative to the historical period suggest a potential increment of MHW frequency and maximum intensity more in the near future compared to that of the far future. In the near future, all the scenarios indicate an increment of frequency (SSP1-2.6: 7.9%, SSP2-4.5: 3.0%; SSP3-7.0: 7.9%; SSP5-8.5: 8.3%) and maximum intensity (SSP1-2.6: 7.5%, SSP2-4.5: 6.9%; SSP3-7.0: 6.2%; SSP5-8.5: 8.7%) compared to the historical period. The spatial analysis of the future changes indicates that certain regions are more vulnerable to changes, and these regions are important in the fisheries and ecosystems.

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.

Marine heatwaves affect the abundance and community structure of microbial plankton, with implications for food web and ecosystem processes, but their impact on microbially mediated elemental cycling remains poorly constrained. To determine the biogeochemical effects of increased temperature, we conducted an experiment in September 2023 in which a plankton community from a coastal, productive ecosystem (Ría de Vigo, NW Iberia) was exposed to a warming of + 2 °C and + 4 °C under unamended and nutrient-enriched conditions. The response of microbial plankton was characterized in terms of organic matter production, carbon fixation, nitrogen uptake, and oxygen net production. We found that warming caused increased nutrient consumption and biomass production, as well as faster bloom dynamics, both in unamended and nutrient-enriched treatments, indicating that the community was robust to thermal perturbation. Accelerated nutrient depletion under warming gave way to an earlier decrease in carbon fixation and nitrate uptake rates, together with a shift towards a negative or less positive metabolic balance. Carbon fixation was less sensitive than nitrate uptake to the different temperature and nutrient scenarios, leading to wide changes in the carbon-to-nitrogen uptake ratio, while respiration increased non-linearly with temperature. Overall, the investigated microbial fluxes were more responsive to nutrient availability than to temperature. Our results show that microbially driven ecosystem services in coastal waters have the potential to be enhanced during short-term warming events.

Marine heatwaves (MHWs)—discrete and prolonged warm ocean temperature extremes—can cause substantial ecological and socioeconomic impacts, and have been widely investigated based on satellite sea surface temperature observations. However, most studies emphasize lifespan‐averaged metrics or separately as onset and decay phases, without taking account of their complete temporal evolution. Here, we present a comprehensive analysis of MHW diversity based on temporal evolutions, classifying global events into six types with distinct patterns in evolution, spatial distribution, and temporal variability. Notably, bimodal MHWs, which are strongly linked to El Niño events, show the largest area growth rate when compared to other types, such as the canonical type, which features a single peak and balanced growth and decay phases. Furthermore, subsurface analysis reveals a strong correlation between subsurface structure and surface evolution. Finally, using a classification approach, we quantify MHW type predictability. We find that two types demonstrate high early classification skill at the initial time‐step, indicating strong early stage predictability.

This study aims to understand the mechanisms of the activation and evolution of the marine heatwave (MHW) that occurred in the Gulf of Mexico (GoM) during summer 2023. We quantified contributions of the thermodynamic processes that transformed surface waters in the GoM into an unprecedented large volume of extremely warm water (>31.8°C)$( > 31.8{}^{\\circ}\\mathrm{C})$ . Through water mass transformation analysis of reanalyses data, we find that the genesis of this MHW was due to the compounding effect of anomalously warm winter surface water priming the region for a MHW, coupled with greater exposure to strong solar radiation. Transformation due to total surface fluxes (sensible and latent heat, solar and longwave radiation) contributed to the MHW volume at a peak rate of 17.0 Sv (106${10}^{6}$m3${\\mathrm{m}}^{3}$s−1${\\mathrm{s}}^{-1}$  = Sv), while the residual term (including mixing) countered the effect by 22.3 Sv at its peak. Total transformation during this 2023 MHW peaked at 4.9 Sv. Plain Language Summary The goal of this study is to understand what triggered the marine heatwave (MHW) that occurred in the Gulf of Mexico during summer 2023. We investigate this MHW by analyzing what physical processes transform normal water into water with extremely high temperatures and vice versa. This is done by tracking the volume, and its changes, of the very warm water. We find that the 2023 MHW was activated by the ocean surface waters being much warmer than normal in the winter of 2022. This was intensified by increased exposure to summer solar radiation. Other processes, such as mixing, acted to counter the warming effects; however, the counter processes were ultimately no match for the strong heating at the surface, yielding to the activation and persistence of an extreme heat event. Key Points In July 2023, an unprecedentedly large volume of extremely warm water formed during a marine heatwave in the Gulf of Mexico Water Mass Transformation provides a novel quantification of the physical processes that contributed to the creation of this marine heatwave The 2023 marine heatwave was caused by the anomalously high absorption of solar radiation within anomalously warm surface waters

Graphical Abstract Highlight Research The basin has warmed consistently since the 1980s, with rising frequency, duration, and extent of events, most severe south of Java. Seasonal weakening of wind mixing during the Southeast Monsoon and transition months prolongs events, though daily intensity remains relatively stable. El Niño and positive Indian Ocean Dipole phases trigger basin-wide thermal anomalies, underscoring large-scale climatic control over event occurrence and strength. Reduced latent heat loss, enhanced surface thermal radiation, and weaker winds limit ocean cooling, reinforcing persistent surface warming and prolonged heatwaves.   Abstract Marine heatwaves in the Eastern Tropical Indian Ocean occur when sea surface temperature remains above its historical average for several consecutive days or weeks, disrupting marine ecosystems, affecting primary productivity, and reducing fishery yields through habitat degradation and altered species distribution. Despite their growing frequency and impact, the spatial and temporal variability of these events in the region remains poorly understood. This study examined their distribution, intensity, and long-term evolution, along with their relationship to regional climate variability, using high-resolution sea surface temperature data. Detection was performed at each grid point following the method of Hobday and key metrics were calculated to describe event duration and intensity. Empirical Orthogonal Function analysis was applied to identify dominant spatial patterns and temporal modes of variability. Results showed that these marine heatwaves occur about three times annually, with more frequent and prolonged events south of Java than west of Sumatra. Most were moderate in duration and intensity, peaking at around 3.25 days per month during the monsoonal transition, while the strongest intensities appeared in the Southeast Monsoon. Over the past decade, cumulative annual intensity increased significantly, showing a positive trend of 18.88 ± 8.33 °C days per decade. The dominant spatial mode revealed intensified events south of Java, while a secondary mode indicated an increase after the early 2000s. These findings demonstrate a growing intensification of marine heatwaves in the Eastern Tropical Indian Ocean, driven by reduced ocean heat loss and enhanced surface net thermal radiation, highlighting their potential to exacerbate thermal stress on regional fisheries and marine ecosystems under ongoing climate change.