Abstract:

Chlorophyll-a (Chl-a) concentration is a key indicator of coastal ecosystem health. Its spatio-temporal variability not only reflects primary productivity but also represents the ecosystem’s integrated response to climate change and human activities. To quantify long-term Chl-a trends in the Yellow and Bohai Seas and to identify regional differences across concentration levels, this study used a multi-source remote sensing reconstruction dataset generated with deep learning algorithms. By applying quantile regression, we characterized long-term Chl-a changes across different concentration percentiles. We also examined how environmental drivers—including sea surface temperature, mixed layer depth, wind speed, and sea surface height anomalies—shape long-term variability in representative marginal-sea environments such as eutrophic estuaries, aquaculture zones, and deep-water regions. Our results show that from 2005 to 2024, Chl-a concentrations in the Yellow and Bohai Seas decreased consistently across the 75th, 50th, and 25th percentiles, with decline rates of –4.82×10-3, –4.50×10-3, and –4.09×10-3 mg/(m³·a), respectively. The rate of change also displayed strong seasonal differences: the summer decline (–0.0638 mg/(m³·a)) was substantially greater than that in winter (–0.04 mg/(m³·a)). Spatially, reductions were more pronounced in high-concentration nearshore waters than in offshore regions. Analysis of underlying mechanisms indicates that mixed-layer depth and wind speed are the primary physical controls on Chl-a variability, though their impacts differ regionally. In nearshore areas such as Qinhuangdao, strong wind-wave disturbance and deepening of the mixed layer enhanced vertical mixing, leading to light limitation and sediment resuspension, ultimately suppressing phytoplankton growth and driving the observed Chl-a decline. In contrast, offshore waters were more strongly influenced by mesoscale processes such as fronts and eddies, with local physical forcing exerting comparatively weaker direct effects on phytoplankton dynamics. Overall, this study provides new insights for improving the modelling and management of coastal ecosystems under the combined pressures of climate change and anthropogenic activities.

Abstract: Geostrophic current velocity anomalies at the mid-latitudes of the three oceans are highlighted, and their role in the genesis of low-pressure systems in boreal/austral winter. These anomalies are attributed to quasi-stationary Rossby waves resonantly forced by the solar declination in harmonic modes. They develop along the western boundary currents as they leave the continents to re-enter the five subtropical gyres. In the North and South Atlantic, the thermocline behaves as a resonant cavity with rigid boundaries at the edges of the western boundary currents, i.e. the Gulf Stream and the Brazil Current, traversed by first-baroclinic mode, first-meridional mode Rossby waves. In the Indian Ocean, the retroflection of the Agulhas Current south of the African continent causes resonance in two different ways west and east of the Cape of Good Hope: resonance of second-baroclinic mode Rossby waves in the first case, and first-baroclinic mode Rossby waves in the second. The resonant forcing of second-baroclinic mode Rossby waves is also observed in the East Australian Current as it flows along Australia. In the North Pacific, resonant forcing of first-baroclinic mode Rossby waves is observed along the Kuroshio, off the east coast of Japan. Geostrophic current velocity anomalies are proving to be convective zones with a significant climatic impact. Within relevant period ranges, this is highlighted by the close coherence of 1 in the geopotential height anomalies at 500 hPa revealing a causal relationship between the geostrophic current velocity anomalies and the formation of low-pressure systems. The objective of this study is to identify the phenomena that precede the formation of winter low-pressure systems at mid-latitudes. The precursor signals observed in convective zones could be relevant candidates for anticipating these meteorological phenomena 10 to 15 days in advance using deep learning techniques.

Abstract: Obtaining real-time data from the deep ocean remains a major challenge in marine observation. This study presents a deep-sea mooring system that integrates inductive telemetry (EUM6000 modules) with Tiantong satellite communication to achieve real-time, long-term hydrological monitoring in the South China Sea. The system incorporated 25 sensors, including CTDs and ADCPs, and was deployed at a depth of 1247 meters. Over one year of continuous operation, it maintained a data reception rate >90%, with a latency of < 15 minutes from seabed to shore. Compared to acoustic-based systems, the inductive telemetry design significantly improved energy efficiency and reliability. The high-resolution multi-sensor data provide valuable insights into ocean dynamics and support applications in climate research and disaster early warning. This system offers a robust solution for real-time deep-sea observation and serves as a reference for future ocean network development.

Abstract: Amplified Arctic warming has led to a pervasive decline in sea ice cover over recent decades, yet the pattern and governing mechanisms of sea-ice concentration (SIC) state transitions remain unclear. This study reveals a stepwise reduction in ice extent during 1979-1991, 1992-2006, and 2007-2024, with pronounced regional SIC contrasts in these transitions. September-mean sea ice in the 70°N-80°N Arctic belt undergoes sustained and significant retreat across three periods, while localized ice gains emerge north of Greenland. In February, the Greenland and Barents Seas exhibit persistent ice loss, whereas the central Arctic Ocean shows significant ice increases. Enhanced ice-albedo feedback, together with concurrent rises in 2-m air temperature and sea surface temperature, dominates ice loss across the 70°N-80°N Arctic belt and the Greenland and Barents Seas. Meanwhile, wind-driven ice convergence promotes localized ice gains north of Greenland in September and within the central Arctic Ocean in February, with both mechanisms amplified during 2007-2024. These findings underscore the spatial heterogeneity of Arctic SIC transitions and highlight the complex interplay of thermodynamic and dynamic processes shaping them.

Abstract: Simulating wave propagation is crucial for forecasting processes offshore and near the coast. Many operational wave models consider only atmospheric and wave forcing as boundary conditions. However, waves and currents are interdependent and simulating their interaction is crucial for accurately representing wave propagation. This study examines the influence of current velocity and water levels on waves in the southern coast of the Iberian Peninsula. These forcing elements were simulated by a 3D hydrodynamic model MOHID and included in the Simulating WAves Nearshore (SWAN) model. The standalone SWAN model was calibrated and validated by comparing results of significant wave height, mean wave direction, and peak period with in-situ observations. Then, the effects of water levels and current velocities on wave propagation were assessed by forcing the SWAN model with water levels as well as current velocities extracted from different depths: the surface layer and depth-averaged velocities from the surface down to 10 m, 20 m, and the full water column. The results revealed that incorporating current velocity and water levels from MOHID in the SWAN model reduced RMSE between 1.6% and 27.6%. The most accurate results were achieved with model runs that included both current velocity from the surface layer and water levels. Opposing currents resulted in increases in wave height whereas following currents resulted in decreases in wave height. This work presents novel results on the effects of hydrodynamics on wave propagation along the southern coast of the Iberian Peninsula, a region of key importance for the blue economy.

Abstract: This study examines the hydrodynamic conditions of the Gulf of California under three climate change scenarios—SSP1-2.6, SSP2-4.5, and SSP5-8.5—projected from 2015 to 2100 using the CNRM-CM6-1-HR global climate model. It evaluates changes in the annual and interannual variability of sea surface temperature (SST), ocean circulation, and key dynamic forcing mechanisms. The results reveal a general warming trend across the Gulf, characterized by an increased frequency of extreme heat events and a prolonged summer season. The Great Islands region emerges as the most resilient to climate change, with tidal forces remaining the dominant hydrodynamic driver. In contrast, the southern Gulf—from the mid-Gulf boundary to the entrance—is identified as the most vulnerable area, experiencing the highest number of extreme events and a more significant reduction in wind speed. This decline is particularly critical, as it affects essential oceanographic processes such as upwelling.

Abstract: Sea surface temperature (SST) gradients modulate surface wind variability at the mesoscale O(100 km), with relevant impacts on surface fluxes, rainfall, cloudiness and storms. The dependence of the SST-wind coupling mechanisms on environmental conditions has been proven using global ERA5 reanalysis data. However, recent literature calls for the need of an observational confirmation to overcome the limitations of numerical models in representing such turbulent processes. Here, we employ O(10 km) MetOp A observations of surface wind and SST to verify the dependence of the downward momentum mixing (DMM) mechanism on large-scale wind U and atmospheric stability. We propose a simple empirical model describing the scaling of the coupling intensity on U, accounting for the role of the characteristic SST length scale L_SST and the boundary layer height h in determining the decoupling of the atmospheric response from the SST forcing due to advection. Fitting such a model to the observations we retrieve a scaling with U that depends on the atmospheric stability, in agreement with the literature. The physical interpretation from ERA5 is confirmed, albeit relevant discrepancies emerge in stable regimes and specific regional contexts. This suggests that global numerical models are not able to properly reproduce the coupling in certain conditions, which might have important implication on air-sea fluxes.

Abstract: Domoic acid (DA), produced by Pseudo-nitzschia diatoms, is the one of the major toxin threats from harmful algal blooms (HABs) on the west coast of the United States. DA events vary in magnitude, timing, and duration, and understanding drivers for indi-vidual events is a persistent challenge. Monterey Bay experiences near-annual DA events and hosts long-term HAB monitoring at the Santa Cruz Municipal Wharf (SCW). Here we characterize two toxin events, occurring in May 2023 and March 2024. The events were similar in magnitude and duration, but an exploration of physical, biological, and chemical dynamics revealed distinct environmental drivers. These differences resulted in a significant deviation in cellular DA (cDA) within the same species of Pseudo-nitzschia. We also include a novel application of solid phase adsorption toxin tracking (SPATT) for environmental metabolomics. Opportunistic SPATT samples showed 159 metabolites that were strongly correlated with DA in both events and produced a spectral match to a new marine natural product using Global Natural Products Social Molecular Networking (GNPS). This work takes a multivariable approach to understanding toxin drivers and lends proof of concept for the integration of environmental metabolomics in HAB monitoring.

Abstract: Passive acoustic monitoring is a key tool for studying underwater soundscapes and assessing anthropogenic impacts, yet the high cost of hydrophones limits large-scale deployment and citizen science participation. We present the design, construction, and field evaluation of a low-cost hydrophone unit integrated into an acoustic toolkit. The hydrophone, built from off-the-shelf components at a cost of ~20 €, was paired with a commercially available handheld recorder, resulting in a complete system priced at ~50 €. Four field experiments in Greek coastal waters validated hydrophone performance across a marine protected area, commercial port, aquaculture site, and coastal reef. Recordings were compared with those from a calibrated scientific hydrophone (SNAP, Loggerhead Instruments). Results showed that the low-cost hydrophones were mechanically robust and consistently detected most anthropogenic sounds also identified by the reference instrument, though their performance was poor at low frequencies (< 200 Hz) and susceptible to mid-frequency (3 kHz) resonance issues. Despite these constraints, the toolkit demonstrates potential for large-scale, low-budget passive acoustic monitoring and outreach applications, offering a scalable solution for citizen scientists, educational programs, and research groups with limited resources.

Abstract: During the 84th cruise of the R/V Akademik Mstislav Keldysh in August 2021, patterns of phytoplankton composition transformation were revealed along a northward gradient. The study involved three transects in the Fram Strait and adjacent Arctic waters: a southern transect (from the Barents Sea shelf to the Greenland shelf), a central transect across the Fram Strait, and a northern transect along the ice edge. Ten species of diatoms and eleven of dinoflagellates were identified, and their ecological preferences were characterized by determining the minimum, maximum, mean, and median values for abundance, biomass, depth of the biomass maximum, salinity, temperature, and the concentrations and ratios of nitrogen, phosphorus, and silicon. All identified species are of Atlantic origin. In summer, within the relatively warm Atlantic Waters, phytoplankton biomass was dominated by dinoflagellates of the genus Tripos and Protoperidinium depressum. Diatoms contributed insignificantly, with Stephanopyxis turris, Navicula planamembranacea, and Thalassiosira gravida being the most frequently observed. Northward, towards the Fram Strait, the dinoflagellate community shifted to include Protoperidinium breve, Protoperidinium brevipes, and Prorocentrum cordatum, while diatoms were increasingly represented by Thalassiosira rotula, Chaetoceros borealis, and Rhizosolenia styliformis. A further decline in temperature and salinity favored the dominance of the dinoflagellates Protoperidinium pellucidum and Gyrodinium lachryma, and the diatoms Eucampia groenlandica, Rhizosolenia hebetata f. semispina, and Rhizosolenia hebetata f. hebetata. The dinoflagellates Protoperidinium granii and Protoperidinium islandicum, along with the diatom Porosira glacialis, thrived at the lowest temperatures and salinities. Diatoms generally grew at silicon concentrations of 1–3 µM and nitrogen concentrations above 1 µM, except for R. hebetata f. semispina, R. hebetata f. hebetata, and Porosira glacialis. The dinoflagellates P. depressum, P. islandicum, P. brevipes, P. breve, and Gyrodinium lachryma were associated with lower nitrogen concentrations (< 2 µM), while others preferred higher levels. Diatom biomass was regulated by ambient nitrogen concentration, whereas dinoflagellate biomass was correlated with the biomass of small flagellates.

Abstract: Mesoplankton (netplankton >250 µm) were sampled over one year at three stations in the Shannon Estuary system, Ireland. A net with three mesh sizes was used to capture a wider range of plankton sizes than a standard single-mesh net. An innovation was the incorporation factorial analysis of celestial (seasonal) variables, spring equinox (Spr) and summer solstice (Sum), together with physicochemical and biological variables, without presuming cause or effect. Principal Component Analysis extracted dimensions D1, D2, and D3 accounting for 26%, 17%, and 12% of the variance, respectively. In the D1-D3 plane, Spr and Sum were positioned ~90° apart. Theapproximate trophic impact of by major taxa was estimated from abundance and published clearance rates. Overall, the mean herbivorous/detritivorous clearance by mesoplankton was 54 L·m⁻³·d⁻¹. Of this, mysids, Mesopodopsis slabberi (predominantly April–November), contributed 96.3% and the appendicularian Oikopleura dioica (May–October) 2.0% (nano- and pico-plankton) and copepods only 0.98%. The ctenophore Pleurobrachia pileus (present April–October) cleared an 2.0% (carnivorous clearance). Mysids and copepods contributed additional unquantified carnivorous clearance. These data, collected 45 years ago, provide a valuable baseline for assessing subsequent ecological changes.

Abstract: This study investigated the vertical structure of an anticyclonic eddy (AE) in the northern South China Sea (SCS) in August 2017 and its response to Typhoon Hato using underwater glider and satellite altimeter data. Additionally, comparative experiments with and without typhoon forcing were conducted using the Regional Ocean Modeling System (ROMS) for supplementary analysis. The observational results reveal that the maximum temperature and salinity differences between the center and edge of the AE did not occur at the sea surface but near the 100 m depth. The typhoon caused a significant temperature decrease above 200 m, with the maximum cooling (~2°C) occurring near 50 m. Near this depth, salinity initially increased due to upwelling but later decreased due to surface mixing. The most pronounced cooling and salinity changes occurred one day after the typhoon passage, followed by a gradual deepening of the mixed layer over the next four days, with conditions below the mixed layer largely returning to pre-typhoon states. Numerical modeling quantitatively assessed the typhoon's impacts. Upwelling rapidly intensified during the typhoon’s passage, the typhoon’s wind stress decreased kinetic energy at the AE site, while the input of positive vorticity reduced absolute vorticity, disrupting the surface AE structure. The flow field adjusted faster than temperature and salinity, with surface currents and the AE structure largely recovering within two days after the typhoon’s passage. These findings highlight the multifaceted impacts of typhoon on AE and provide critical insights for predicting the evolution of mesoscale oceanic structures under extreme weather events.

Abstract: The way in which phytoplankton communities are structured - often referred to as phytoplankton community composition (PCC) - exerts fundamental control on ocean biogeochemical cycling, climate regulation, and marine ecosystem dynamics. Accurate quantification of these groups from satellite ocean color data remains challenging due to spectral similarities among phytoplankton types and the limitations of existing empirical and semi-analytical models. In this study, we used an extreme gradient boosting (XGBoost) tree-based regression model to retrieve multiple PCCs and total chlorophyll-a concentrations from simulated hyperspectral remote sensing top-of-atmosphere (TOA) ocean color data as well as some ancillary data. The intent is to mimic what could be gathered from the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission and auxiliary data sources to characterize to characterize the environment. In its final form, the model, validated on an out-of-sample set, demonstrated strong predictive performance across most functional groups, with R2 values exceeding 0.95. Dinoflagellate retrievals showed lower accuracy (R2 = 0.53). Further analysis revealed that temperature was a key predictor alongside hyperspectral TOA radiance, suggesting that integrating external temperature data could enhance future retrieval models. Furthermore, despite using only 10% of the available hyperspectral bands, feature importance analysis showed that specific spectral regions disproportionately contributed to model predictions. These findings highlight the potential of machine learning for phytoplankton classification and inform future algorithm development for hyperspectral ocean color missions.

Abstract: The stability of a circular vortex is studied in the thermal quasi-geostrophic (TQG) model. Several radial distributions of vorticity and of buoyancy (temperature) are considered for the mean flow. First, the linear stability of these vortices is addressed. The linear problem is solved exactly for a simple flow and two stability criteria are then derived for general mean flows. Then, the growth rate and most unstable wavenumbers of normal-mode perturbations are computed numerically for Gaussian and cubic exponential vortices, both for elliptical and higher mode perturbations. In TQG, contrary to usual QG, short waves can be linearly unstable on shallow vorticity profiles. Linearly, both stratification and bottom topography (under specific conditions) have a stabilizing role. Second, we use a numerical model of the nonlinear TQG equations. With a Gaussian vortex, we show the growth of small-scale perturbations during the vortex instability, as predicted by the linear analysis. In particular, for an unstable vortex with an elliptical perturbation, the final tripolar vortices can have a turbulent peripheral structure, when the ratio of mean buoyancy to mean velocity is large enough. The frontogenetic tendency indicates how small-scale features detach from the vortex core towards its periphery, and thus feed the turbulent peripheral vorticity. We confirm that stratification and topography are stabilizing as shown by the linear theory. Then, by varying the vortex and perturbation characteristics, we classify the various possible nonlinear regimes. The numerical simulations show that the influence of the growing small-scale perturbations is to weaken the peripheral vortices formed by the instability, and by this, to stabilize the whole vortex. Axisymmetrization replaces tripole formation, and tripole formation replaces dipolar breaking, as the mean buoyancy amplitude is increased. A finite radius of deformation and/or bottom topography also stabilize the vortex as predicted by linear theory. An extension of this work to stratified flows is finally recommended.

Abstract: Coastal communities and marine ecosystems face increasing risks due to changing ocean conditions, yet effective wave monitoring remains limited in many low-resource regions. This study investigates the use of seismic data to predict significant wave height (SWH), offering a low-cost and scalable solution to support coastal conservation and safety. We developed a baseline machine learning (ML) model and improved it using a longest-stretch algorithm for seismic data selection and station-specific hyperparameter tuning. Models were trained and tested on consumer-grade hardware to ensure accessibility and availability. Applied to the Sicily-Malta region, the enhanced models achieved up to a 0.133 increase in R2 and a 0.026m reduction in mean absolute error compared to existing baselines. These results demonstrate that seismic signals, typically collected for geophysical purposes, can be repurposed to support ocean monitoring using accessible artificial intelligence (AI) tools. The approach may be integrated into conservation planning efforts such as early warning systems and ecosystem monitoring frameworks. Future work may focus on improving robustness in data-sparse areas through augmentation techniques and exploring broader applications of this method in marine and coastal sustainability contexts.

Abstract: Temporal and spatial variations in water temperature were analysed from 23 time series across two contrasting Basque coast estuaries over a 26-year period (1998-2023). We examined long-term trends, seasonality, and intra- and inter-estuary variability, as well as links to local hydrometeorological factors and North Atlantic climate-ocean teleconnections. Time-series decomposition, clustering, and regression and correlation analyses were used. Water temperature interannual and seasonal patterns differed mainly between outer neritic waters and shallow transitional waters. Most water masses exhibited an overall warming trend, with temperature increases until 2003-2006, followed by declines until 2013-2015, and a sharp rise in 2020-2023, largely driven by spring temperatures. Warming was strongest (0.24-0.25 °C decade-1) in middle-estuary waters, while no trend or even cooling occurred in inner above-halocline waters of the stratified system. Spring, particularly May, experienced the highest warming rates, reaching 0.49 °C and 0.80 °C decade-1, respectively, in transitional waters of the mixed estuary. Seasonal temperature minima and maxima occurred earlier in surface transitional waters than in neritic waters and deep transitional waters of the stratified system. Over time, annual maxima advanced, minima were delayed, and spring temperatures rose, this extending the warm period. Air temperature, especially over-sea, was the primary driver of water temperature trends. River flow modulated the trends to annual and seasonal scales, inducing cooling, mainly in spring. AMO index was the teleconnection best related to water temperature, while links with the NAO index and the EA pattern were more restricted to specific seasons.

Abstract: The Gulf of Guinea is experiencing accelerated sea-level rise (SLR), with localized rates exceeding 10 mm yr⁻¹, more than twice the global average. Integrated analysis of GRACE/FO ocean mass data, reanalysis products, and machine learning reveals a fundamental regime shift in the regional sea-level budget after 2015. Ocean mass increase, primarily driven by intensified terrestrial hydrological discharge, accounts for over 60% of observed SLR near major riverine outlets, indicating a transition from steric to barystatic-manometric dominance. This transition aligns with increased monsoonal precipitation, wind-driven changes in equatorial wave dynamics, and coupled Atlantic-Pacific climate variability. Piecewise regression identifies a significant 2015 breakpoint, with mean coastal SLR rates rising from 2.93 ± 0.1 to 5.4 ± 0.25 mm yr⁻¹. GRACE data show extreme mass accumulation (>10 mm yr⁻¹) along the eastern Gulf coast, strongly linked to elevated river discharge and estuarine retention. Physical analysis indicates that intensified wind stress curl has altered Rossby wave dispersion, enhancing zonal water mass convergence. Random Forest modeling attributes 16% of extreme SLR variance to terrestrial runoff, close to wind stress’s 19%, highlighting underestimated land-ocean coupling. Current global climate models underrepresent these manometric contributions by 20–45%, causing critical biases in projections for high-runoff regions. The societal impact is severe, with over 400 km² of urban land in Lagos and Abidjan at risk of inundation by 2050. These findings expose a hybrid steric-manometric regime in the Gulf of Guinea, challenging existing paradigms and indicating similar dynamics may affect tropical margins globally. This calls for urgent model recalibration and tailored regional adaptation strategies.

Abstract: This paper introduces a novel theoretical framework for energy conversion in natural flow systems, primarily focusing on ocean currents while extending its applicability to rivers and artificial channels. The proposed model is based on the concept of volumetric coupling between a conversion device and the surrounding incompressible flow. In contrast to classical approaches, which rely on axial deceleration and wake expansion, this method considers the interaction with an extended upstream volume of fluid whose inertia and continuity support energy extraction through controlled momentum deflection. This dynamic interaction is embedded within the Energy Restoration by Geophysical Fields (ERGF) model, which interprets these flows as open systems sustained by persistent physical mechanisms such as gravity, planetary rotation and thermohaline gradients in oceans, or topographic level differences in rivers and canals. Within this theoretical framework, the study analyses a resonant ideal turbine configuration designed to operate in continuous coupling with the flow, extracting mechanical power with minimal disturbance to large-scale hydrodynamics. Although experimental validation is ongoing, the paper outlines standardised testing methodologies (IEC, ITTC) that will underpin future performance assessments. The theoretical contributions presented herein aim to support the development of highly efficient and low-impact renewable energy systems based on volumetric interaction and continuous energy replenishment principles.

Abstract: The study focuses on the detection of breaking wave crests in the highly dynamic waters of an Antarctic coastal polynya using high-resolution panchromatic satellite imagery. Accurate as-sessment of whitecap coverage is crucial for improving our understanding of the interactions be-tween wave generation, air–sea heat exchange, and sea ice formation in these complex environ-ments. As open-ocean whitecap detection methods are inadequate in coastal polynyas partially covered with frazil ice, we discuss an approach that exploits specific lighting conditions: the alignment of sunlight with the dominant wind direction and low solar elevation. Under such conditions, steep breaking waves cast pronounced shadows, which are used as the primary indi-cator of wave crests, particularly in frazil streak zones. The algorithm is optimized to exploit these conditions and minimize false positives along frazil streaks boundaries. We applied the algorithm to a WorldView-2 image covering different parts of the Terra Nova Bay Polynya (Ross Sea), a dynamic polar coastal zone. This case study demonstrates that the spatial distribu-tion of detected breaking waves is consistent with ice conditions, and wind forcing patterns, while also revealing deviations that point to complex wind-wave-ice interactions. Although quantitative validation of satellite-derived whitecaps coverage wasn’t possible due to the lack of in situ data, the method performs reliably across a range of conditions. Limitations of the pro-posed approach are pointed out and discussed. Finally, the study highlights the risk of misinter-pretation of lower-resolution reflectance data in areas where whitecaps and sea ice coexist at subpixel scales.

Abstract: Turbidite channels are final conduits for the transfer of terrigenous detritus to the deep-sea depositional systems. Studying their morphology and geometric parameters can provide information on density flow characteristics and sedimentary processes, making it an objective and quantitative way to differentiate deep-sea deposits they feed, of special interest to the oil industry. In this work, the morphology is studied, the main geometric parameters are calculated, and the potential sedimentary fill of a turbiditic channel, the Columbretes Grande channel, located on the Ebro continental margin (NW Mediterra-nean Sea), is visualized in 3D. This complete morphometric analysis, performed by applying a specific methodology, shows a concave and smooth channel indicating a profile in equilibrium with local evidence of erosion. Considering the height of the flanks (< 150 m), the existence of well-developed levees, the high sinuosity of some of its reaches, and the relatively low slopes, the channel can be classified as depositional. The sinuosity index closes to 2 in some courses and the gentle slopes suggest that the fine-grained turbidity currents that episodically circulate in its interior reach the channel’s end.