Science Highlights
Global Estimate of Turbulent Heat Flux
(Adapted from Wang et al., 2026)
The net heat exchange between atmosphere and ocean is composed of radiative and turbulent components. Radiative components are the net shortwave and longwave fluxes. Turbulent components are the sensible heat flux (SHF) and latent heat flux (LHF), which are an important part of the global atmosphere-ocean heat exchange. The turbulent fluxes can be measured directly, but are often parameterized based on air-sea temperature and humidity differences and the wind stress. These parameterizations are sometimes called semi-empirical bulk formulas, as exemplified by the COARE algorithm (Edson et al., 2013). The bulk formulas for turbulent flux are tuned using available observations, but may not perform well in environmental conditions where validation is lacking. Thus, there is interest in improving global fields of SHF and LHF using other approaches.
A recent study by Wang et al. (2026) used a neural network approach to create high-resolution (0.25 degree) global ocean flux fields. For ground truth, the authors utilized nearly 200 buoys from 13 projects and arrays, including 6 buoys from OOI. The OOI Southern Ocean, Argentine Basin and Irminger Sea Arrays were particularly important for extending the geographic coverage to high latitude where long-term marine meteorological data are scarce (Fig. 3). The analysis period (1993 to 2017) was determined by the availability of the in-situ datasets.
The in-situ meteorological variables were used to compute turbulent heat fluxes using the COARE 3.6 algorithm (Edson et al., 2013). A unique aspect of the processing was to quality-control the fluxes using the expected values for the Bowen ratio, defined as B = SHF/LHF. The quality-controlled, observation-based fluxes were then used to train and validate the neural network model. The model jointly estimated SHF and LHF while constrained by limits to the Bowen ratio based on observations. The model was further trained using multiple “learning data sets”, which included atmospheric reanalysis products, sea surface temperature, salinity, wind and wave products, and satellite-derived sea surface height.
The results were compared to 7 different global flux products. Notable in the comparisons was the consistently low RMS error in Bowen ratio across all ocean basins for the neural network model. Considering temporal trends over the analysis period (Fig. 2), showed that the neural network model had significant positive trends in SHF (different from all but one of the products) and LHF (similar to four of the products). Spatial maps of the trends indicated that the positive trends tend to be at high latitude for SHF and in the tropics and mid-latitudes for LHF.
This study highlights the value of long-term ocean observations, and in particular the importance of meteorological observations at high latitude. The constrained neural network approach showed good results compared to other global flux products. The resulting 0.25 degree, gridded global turbulent flux field is an important complement to existing reanalysis fluxes and has the advantage of more accurate representation of the Bowen ratio. As noted by the authors, improved understanding of turbulent heat fluxes on a global scale is an important step towards achieving global closure of the ocean surface energy budget.
[caption id="attachment_38060" align="alignnone" width="958"]
Figure 1: Locations of 197 buoy sites used in the analysis. Note the relative scarcity of sites in the southern oceans and in the high latitude Atlantic Ocean. From Wang et al., 2026.[/caption]
[caption id="attachment_38061" align="alignnone" width="698"]
Figure 2: Time variability of global-mean sensible (upper) and latent (lower) heat flux for the neural network (BrTHF) and seven other flux products. Trends (right hand panel) that pass a significance test are shown with an asterisk. From Wang et al., 2026.[/caption]
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References:
Wang, Y., R. Tang, M. Liu, L. Huang and Z.-L. Li, 2026. Bowen ratio-constrained global dataset of bulk air-sea turbulent heat fluxes from 1993-2017, Earth Sys. Sci. Data, 18, 3391-3414, https://doi.org/10.5194/essd-18-3391-2026.
Edson, J.B., K. Venkata, R. A. Weller, S.P. Bigorre, A.J. Plueddemann, C. Fairall, S.D. Miller, L. Mahrt, D. Vickers and H. Hersbach. 2013. On the Exchange of Momentum over the Open Ocean, J. Phys. Oceanogr., 43, 1589–1610, https://doi.org/10.1175/jpo-d-12-0173.1.
Read MoreA Method for Quantifying Correlation in the Shape of Oceanographic Profile Data
Vertical profiles are widely used to identify physical and biogeochemical features of the water column. Recent studies have shown that oceanographic profiles can be represented as functional data objects, where each profile is treated as a single datum and expressed as a function of pressure. This study applies a recently developed technique, which defines a scalar correlation coefficient for functional data, to the analysis of oceanographic profiles. The method represents each profile using basis functions, whose associated weightings are termed basis coefficients, and quantifies dependence through the variability of these coefficients. An important advantage of this method is that the resulting correlation coefficient reflects similarities in overall profile shape, not just correlations between values at specific depths. Two applications of this method are explored: calculating the correlation coefficient between two different oceanographic variables, and estimating the temporal autocorrelation function of a single variable. Each application is demonstrated using two case study datasets: (1) the Coastal Endurance Washington Offshore Profiler Mooring and (2) biogeochemical-Argo floats. The case study using the Washington Offshore Profiler Mooring demonstrates how the method can be used to identify physical drivers of variability in biogeochemical profile structure. For example, Figure 17 shows temporal autocorrelation functions computed from the full profiles of different variables measured by the Washington Offshore profiler mooring. By computing correlation coefficients and autocorrelation functions directly from full profiles, the authors’ approach complements existing methods and naturally incorporates profile shape.
The method has broad potential applications across oceanographic research. It can be applied to the expanding global collection of profiling observations, as well as to ocean model output, to quantify spatio-temporal variability and coupled physical–biogeochemical dynamics. Potential uses include observing system design, evaluation of sampling strategies, assessment of advective versus local variability, validation of machine learning products, and investigation of ecosystem scale decorrelation timescales. A variety of methodological approaches could be integrated with this technique, such as functional regression, clustering, spatial modelling or time series analyses. Together, these extensions would further enhance the ability to quantify and interpret variability in the rapidly growing volume of oceanographic profiling data.
[caption id="attachment_38053" align="alignnone" width="718"] Temporal auto correlation functions for four oceanographic variables measured as profiles at the Coastal Endurance Washington Offshore Profiler Mooring (CE09OSPM).[/caption]
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Reference:
Taylor, M. and S. Henson, 2026. “A method for quantifying correlation in the shape of oceanographic profile data.” Ocean Sci. 22(2). https://doi.org/10.5194/os-22-1377-2026.
Scaling Up Discovery: A Machine Learning–Assisted Framework for Rapid Annotation of Benthic Megafauna in Marine Imagery
Methane hydrate-based ecosystems are amazingly abundant along the ~1000 km-long Cascadia Margin, from Cape Mendocino in Northern California to the northern tip of Vancouver Island. Here, 3,500 methane bubble streams, clustered into more than 1,300 emission sites, have been documented. These sediment-dominated environments, underlain by tonnes of methane hydrate, host robust and diverse microbial communities and are “hot spots” of megafauna. Yet only three sites have been investigated in detail. One is the Regional Cabled Array (RCA) Southern Hydrate Ridge (SHR) site, designated as essential fish habitat. A suite of instruments operates at SHR to understand how these important and dynamic ecosystems respond as shallow hydrate breaks down in response to seismic events, bottom-water warming, and seasonal to decadal change. Among them is a digital still camera focused on the most active emission site, “Einstein’s Grotto.” For over a decade, the camera has streamed 3 images every half hour, 24/7, to shore.
A critical bottleneck in converting the enormous image archive at SHR into reliable ecological data has been the labor-intensive manual identification and annotation of organisms. In “A Machine Learning Assisted Method for Rapidly Annotating Benthic Megafauna in Large Volumes of Marine Imagery,” Bigham and Carter (2026) show how AI, combined with human expertise, can break this bottleneck. Their iterative workflow pairs model predictions with expert validation, correction of misidentified organisms, and retraining to progressively improve performance.
The results highlight how powerful this approach can be. The workflow generated 92,153 annotations across 50,840 images and 10 morphological taxonomic groups in just six weeks. Doing this by hand would have taken approximately 5.9 years. Expert review remained essential for correcting false detections and classification errors, and for recognizing the model’s limits in complex underwater settings.
This study provides a practical, expandable framework for transforming continuous marine imagery into ecological time series that track changes in abundance, community composition, and ecosystem dynamics. With local training and validation, it could serve other habitats, imaging platforms, and long-term observing programs. This work highlights the significant discovery opportunities when RCA’s high-density, continuous data streams are paired with AI and human expertise. It offers a scalable pathway toward more timely, reproducible, and data-rich assessments of deep-sea ecosystems, strengthening our ability to detect ecological change in a rapidly changing ocean.
[caption id="attachment_38050" align="alignnone" width="936"]
Example digital still image from the cabled camera at the Regional Cabled Array methane seep site Einstein’s Grotto, Southern Hydrate Ridge. a) Schools of black cod forage above the sedimented seafloor in this nutrient rich environment. Clam shell chaff collects in depressions. b) Annotated image using a human-in-the-loop workflow built around YOLO. A detector trained on manually annotated imagery ran inference over the full image set and wrote YOLO text files with predicted classes and bounding boxes.[/caption]
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Reference: Bigham, K.T., and Carter, A (2026) A machine learning assisted method for rapidly annotating benthic megafauna in large volumes of marine imagery. Limnology and Oceanography: Methods. doi: 10.1002/lom3.70057.
Read MoreAMOC Heat Transport from Reanalyses
(Adapted from Winkelbauer et al., 2026)
Oceanic heat transport is important for understanding the Atlantic Meridional Overturning Circulation (AMOC), and ocean reanalysis models provide a means of evaluating transport variability and trends. A recent paper by Winkelbauer et al. (2026) evaluated the extent to which reanalyses reproduce transports estimated from observations. Their results show that the reanalyses capture the overall character of heat transport in the subpolar North Atlantic, but have limitations in particular times and regions.
The authors used observations from the Overturning in the Subpolar North Atlantic Program (OSNAP) data set compiled by Fu et. al. (2023), which includes both OSNAP-West (Labrador Shelf to West Greenland) and OSNAP-East (East Greenland to Scotland). The OSNAP-East array incorporates the OOI Irminger Sea Flanking moorings. The observation-based transport estimates were compared to those from several reanalysis models. A composite (mean) product was produced from four models with ¼ degree resolution that are based on the Copernicus Marine Service Global Reanalysis Ensemble Product (GREP). A higher resolution product, the Global Ocean Reanalysis System (GLORYS12V1) was also used in the comparison. All of the reanalyses are based on Nucleus for European Modeling for the Ocean (NEMO). It is notable that none of the reanalyses assimilate ocean velocity observations. This means that ocean transports differences will depend largely on velocity differences between observations and models.
Comparisons during the OSNAP observation period (2015-2020) include temperature, velocity and transport. Temperatures are relatively well reproduced by the reanalysis models, albeit with some systematic biases – cold biases in the basin interiors and warm biases on the shelves. The broad structure of ocean currents can be seen in the models, but there are discrepancies in both strength and location of the Labrador Current, West Greenland Current and East Greenland Current. However, it is also noted that limited observations in a few key regions compromise comparisons there. For transport, the reanalyses capture overall variability, and most are well correlated with observations over the ~6 year period (Fig. 3). However, none of the reanalyses capture the 2015 transport peak observed by OSNAP.
The authors dig deeper into the 2015 transport discrepancy and find that it is associated with a region of the OSNAP line near the Iceland and Rockall-Hatton Basins where glider transects supplemented the moored array in the upper ocean. They speculate that changes in the observational coverage due to gliders contribute to the 2015 transport peak that is not captured by the models.
Overall, this comparison study is a relatively strong endorsement of the reanalysis models, which “generally reproduce the broad structure of the AMOC and its associate heat transport”, although not without bias (5-10% in the mean and 60-80% for some times and locations). In addition, some key boundary currents are not well represented in the models. Interestingly, the case study for 2015 shows that the OSNAP moored array also has limitations, and can be improved by the use of gliders to resolve upper-ocean structure between mooring stations.
[caption id="attachment_37794" align="alignnone" width="496"] Figure 1. Time series of heat transport from OSNAP observations (black) compared to reanalysis models. Upper panel compares five different reanalysis products (colors) and the mean of the ¼ degree products (gray). Lower panel compares OSNAP to indirect heat flux estimates. From Winkelbauer et al., 2026.[/caption]
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References:
Fu, Y. and 25 co-authors, 2023. Meridional Overturning Circulation Observed by the Overturning in the Subpolar North Atlantic Program (OSNAP) Array from August 2014 to June 2020, Georgia Institute of Technology [data set], https://doi.org/10.35090/gatech/70342.
Winkelbauer, S. I Winterer, M. Mayer, Y. Fu and L. Haimberger, 2024. Subpolar Atlantic meridional heat transports from OSNAP and ocean reanalyses – a comparison, Ocean Sci, 22, 629-651, https://doi.org/10.5194/os-22-629-2026.
Read MoreEffects of Dissolved Oxygen and Hypoxia on Catch Rates of Nearshore Groundfishes in a Recreational Hook and Line Fishery
Rasmuson et al. (2026) investigate the impact of hypoxic events on a nearshore, multispecies recreational groundfish fishery along the Oregon coast. Using dissolved oxygen (DO) data from the National Science Foundation’s Ocean Observatories Initiative (OOI) Oregon Inshore Mooring (2018–2022, excluding 2020) and trip-level recreational fishery catch data from the Oregon Department of Fish and Wildlife, they modeled catch-per-unit-effort (CPUE) and species encounter rates as functions of DO and regulatory bag limits. Of the 709 days analyzed, 36.8% were characterized as hypoxic (DO < 61 μmol/kg). Of the 4 years, 2021 had the most severe hypoxia and 2019 had the least. Across all trips, CPUE and average number of species encountered generally declined during hypoxic periods, indicating reduced fishing success. However, species-specific responses varied: some, such as blue/deacon and China rockfish (see Fig. 2), showed increased CPUE with higher DO levels, while others like cabezon and quillback rockfish were more frequently caught during hypoxic events. These patterns suggest that hypoxia alters species’ availability and/or catchability, possibly due to shifts in fish behavior, vertical distribution, or tolerance to low DO. Notably, species with increased CPUE under hypoxia are already considered vulnerable or limiting for the Oregon recreational fishery, raising concerns about increased pressure on sensitive stocks. As hypoxic events become more frequent with climate change, incorporating DO metrics into stock assessments and fisheries management would improve population models for exploited species. Their findings highlight the need for fine-scale, species-specific approaches to recreational fisheries management in the context of changing ocean conditions and suggest that recreational fishers may face constraints in adapting to deoxygenation, especially in strongly place-based or single-species fisheries.
[caption id="attachment_37790" align="alignnone" width="615"] Figure (1) Log (CPUE) for four different species versus DO. Species depicted are those with best-fit Gaussian models that included DO. Gray areas are 95% confidence intervals. Data to the left of the red vertical bar indicate hypoxic conditions and to the right indicate normoxic conditions.[/caption]
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Reference:
Rasmuson, L. K., A. D. Whitman, B. T. Cervantes, and J. P. Fram. 2026. “ Effects of Dissolved Oxygen and Hypoxia on Catch Rates of Nearshore Groundfishes in a Recreational Hook and Line Fishery.” Fisheries Oceanography 1–13. https://doi.org/10.1111/fog.70046.
Read MoreHelp Us Solve a Mystery of the Deep
We would like the community’s help in deciphering an unusual “blow down” event impacting environmental conditions near the flank of Axial Seamount (summit depth ~1500 m), located 300 miles offshore Oregon (Figure 1a). A blow down and its impacts were recorded by numerous instruments streaming data back to shore in real time from the Axial Base Shallow Profiler Mooring. The mooring is one of three two-legged moorings on the RCA that include a mechanical anchored leg and a second anchored leg consisting of an Electrical-Optical-Mechanical (EOM) cable supplying power and two-way communications (anchors at ~ 2600 m). Both legs attach to an ~ 3.7 m across central float at ~ 200 m water depth providing 900 Kg buoyancy that pulls on the legs (Figure 1b). The float contains a static platform hosting 8 instruments and a winched science pod with 10 instruments, that conducts a daily science mission of 9 profiles spanning 200 m to ~ 5 m beneath the surface, depending on overlying seastate (see McRae, 2016). For seven of the profiles, the pod ascends at 5 cm/sec and descends at 10 cm/sec. In total, Two profiles are stepped and include 5-minute stops on descent.
The event started April 8, 2026, lasting until April 12, 2026. It was marked by a staggered increase in pressure (depth) closely related to tides, with a mean current of ~ 30 cm sec toward the NE, which blew the platform down almost 40 meters on April 24th (Figure 1c). The water mass included lower dissolved oxygen concentrations and a decrease in pH. Could this reflect an internal wave with tidal forcing? (M. Muglia, pers comm). Over the 12 years of nearly constant monitoring at Axial Base, this is the first time we have witnessed such an event. Several blowdowns have been documented at the Oregon Slope Base and Offshore Shallow Profiler Moorings, but never with the “sawtooth” changes in pressure.
[caption id="attachment_37786" align="alignnone" width="1049"]
Figure 1. a) Location of the Regional Cabled Array Shallow Profiler Mooring near the base of Axial Seamount (water depth 2600 m), located ~ 300 miles off Oregon. (b) Cabled 2-legged Shallow Profiler Mooring hosting a 12 foot-across platform at 200 m water depth with 1) an array of cabled static instruments (e.g. ADCP, CTD-O2, pH, fluorometer, camera etc); and 2) a winched instrumented profiling “science pod” hosting similar instruments (including CO2, nitrate, PAR etc), which profiles up and down through the water column 9 times a day. c) Platform pressure (depth) and ADCP(m/s) measurements, and winched profiler values for dissolved oxygen concentration and pH.[/caption]
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Reference:
McRae, E., “Continuous real time scanning of the upper ocean water column. Oceans ,” OCEANS 2016 MTS/IEEE Monterey, Monterey, CA Monterey, USA, 2016, pp. 1-6, doi: 10.1109/OCEANS.2016.7761359.
Read MoreShelfbreak Jet Influence on Coastal Sea Level
Flooding and shoreline erosion are increasing threats to coastal communities. Coastal sea levels are influenced by multiple factors, including mean sea level rise, tides, storm surges, river outflow, and waves. A recent paper by Camargo et al. (2025) focused on the extent to which offshore circulation, in particular the shelfbreak jet on the New England shelf, contributed to sea level variability over the period 2014 – 2022. They found that roughly 30% of sea level variance during storm surges can be attributed to the shelfbreak jet.
The authors used a variety of data sets, including tide gauge stations along the New England coastline from Boston, MA to Atlantic City, NJ, wind stress from the ECMWF ERA-5 reanalysis, and shelfbreak jet transport from the OOI Pioneer Array. The jet transport was estimated using upward-looking ADCP data from the Central Inshore, Central, and Central Offshore moorings. The methodology and results are described in Carmargo et al., 2024 and the jet transport data set is available in Zenodo (Carmago, 2024). The data were de-tided and then band-pass filtered (1-15 days) to isolate the storm-surge component of sea level variability. Coherence between coastal sea level and jet transport for 1-15 day periods was established by Carmago et al. (2024).
[caption id="attachment_37571" align="alignnone" width="975"]
Percent of storm surge variance explained by the regression model (red) and for individual parameters: shelfbreak jet (purple), zonal wind stress (orange), and meridional wind stress (green). Tide gauge stations are ordered from north to south along the coastline. From Camargo et al., 2025.[/caption]
The influence of jet transport and two components of wind stress (zonal and meridional) on storm surge was evaluated by means of a linear regression model that determined the regression coefficients for each parameter. The regression was run for each tide station using the previously computed jet transport and the ERA-5 wind stress closest to each station. Overall, the regression model explained about 60% of the storm surge variance, with jet transport and zonal wind stress explaining 28% and 38%, respectively. There was modest along-coast variability in the variance explained by each parameter (Figure 3): Variance explained by zonal wind stress tended to increase from NE to SW along the coast (Fall River to Bridgeport), while variance explained by the jet tended to decrease. The wind stress impact was identified as due to either onshore or downwelling-favorable winds. The jet impact was due to changes in the cross-shelf pressure gradient associated with the geostrophically-balanced currentCase studies for specific synoptic events highlight the complexity of coastal storm surge events and the broad suite of observational tools necessary to determine the influence of different mechanisms. The authors note that simple storm surge models will not capture the influence of offshore currents like the shelfbreak jet, and that such influence is likely to be found elsewhere on the US east and west coast.
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References:
Camargo, C.M.L., C.G. Piecuch and B. Raubenheimer, 2025. Do ocean dynamics contribute to coastal floods? A case study of the shelfbreak jet and coastal sea level along southern New England, Earth’s Future, 13, https://doi.org/10.1029/2025EF006708.
Camargo, C. M. L. (2024). Shelfbreak jet transport from OOI pioneer [Dataset]. https://doi.org/10.5281/zenodo.10814048.
Camargo, C. M. L., Piecuch, C. G., & Raubenheimer, B. (2024). From shelfbreak to shoreline: Coastal sea level and local ocean dynamics in the Northwest Atlantic. Geophysical Research Letters, 51(14), e2024GL109583. https://doi.org/10.1029/2024GL109583 .
Read MoreLife on Plastics: Deep-Sea Foraminiferal Colonization Patterns and Reproductive Morphology
Burkett (2025) reports plastic debris has become a persistent feature of deep-sea ecosystems, yet its role as a habitat for calcifying organisms remains poorly understood. Foraminifera colonization has been observed in significant numbers on plastic surfaces, suggesting that these materials serve as novel and significant deep-sea colonization sites for these abundant calcifying organisms. Her study uses deep-sea experimental plastic substrates to examine the colonization and reproductive morphology of the benthic foraminifera Lobatula wuellerstorfi across three locations. Two sampling locations used OOI platforms on the Oregon continental margin: the Endurance Oregon Offshore site (575 m), and the Regional Cabled Array Southern Hydrate Ridge site (774 m). The third location, Station M (4000 m) was on the abyssal plain off central California. 482 individuals were analyzed for morphometric traits to investigate reproductive morphotypes. One feature examined was the proloculus diameter. The proloculus is the first chamber formed by the foraminifera. In L. wuellerstorfi, the proloculus is the spherical feature visible at the foraminifera center (see Fig. 2, specimen 4f).
The more traditional test morphology of L. wuellerstorfi —characterized by a flattened, biconvex test and consistently elevated and pore-free sutures — is well represented in the Oregon specimens. These samples also displayed a clear bimodal proloculus size distribution, consistent with alternating reproductive strategies, while Station M populations exhibited a broader, less defined bimodal distribution skewed toward megalospheric forms. This variation likely reflects environmentally driven morphologic responses rather than taxonomic divergence. Burkett’s findings demonstrate that plastics can serve as persistent colonization sites for deep-sea foraminifera, offering a unique experimental platform to investigate benthic population dynamics, ecological plasticity, and potential geochemical implications, as well as the broader impacts of foraminifera on deep-sea biodiversity and biogeochemical cycling.
[caption id="attachment_37568" align="alignnone" width="526"]
Lobatula wuellerstorfi specimens recovered from plastic substrates at the OOI Endurance Oregon Offshore (575 m water depth) after 264 days of deployment. Each specimen (1–5) is shown in six standardized views for comparative analysis. Specimens 1 and 2 represent microspheric forms; specimens 3–5 are megalospheric individuals that recently completed their first whorl and are smaller in overall test diameter. All scale bars = 100 μm. The proloculus diameter, PD, is indicated on specimen 4f.[/caption]
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Reference:
Burkett, A.M. Life on Plastics: Deep-Sea Foraminiferal Colonization Patterns and Reproductive Morphology. J. Mar. Sci. Eng. 2025, 13, 1597. https://doi.org/10.3390/jmse13081597
Read MoreActive Protothrusts and Fluid Highways: Seismic Noise Reveals Hidden Subduction Dynamics in Cascadia
This first of a kind study by Kidiwela et al., (2026) “Active protothrusts and fluid highways: Seismic noise reveals hidden subduction dynamics in Cascadia” (1) applies ambient seismic noise interferometry to a decade of RCA broadband seismometer data at Slope Base and Southern Hydrate Ridge, and on Ocean Networks Canada >400 km to the north at Clayoquot Canyon, to resolve spatio-temporal variations in seismic velocity across the Cascadia Subduction Zone. Along-strike heterogeneity in megathrust behavior, with a strongly coupled (locked) segment in northern Cascadia is in sharp contrast to a weakly coupled central segment characterized by distributed deformation along active protothrusts with slow-slip events. Temporal velocity reductions are suggested to correlate with fluid migration along permeable structures at the plate interface and the subsidiary strike slip Alvin Canyon Fault, indicating that elevated pore-fluid pressures modulate fault mechanical properties. These “fluid highways” facilitate transient weakening and influence stress partitioning, potentially inhibiting the lateral propagation of seismic rupture.
[caption id="attachment_37564" align="alignnone" width="936"]
Figure 1 (after Kidiwela Figs 1-3) a) Cascadia Subduction Zone showing a model for the distribution of locking, depth to the down-going slab, strike-slip faults (blue lines) and location of Regional Cabled Array and Ocean Network Canada broadband seismometers used in this study. The Siletzia terrain, a large buried accreted basaltic body is outlined in red. b) Cross sections showing temporal changes in seismic velocities (dv/v) for the Northern and Central Caldera sites. Histograms for shallow (red) and deep (grey) tremor events shown for Central Caldera. c) The cross section shows fluid migration (blue arrows), splay faults and protothrusts (red lines) and the Alvin Canyon Fault (ACF). Down dip tremor, purple dots, match small locked proportions of the slab, Fluid transport along the décollement and the Alvin Canyon Fault are thought to modulate earthquake behavior.[/caption]
The study demonstrates that seismic noise–derived velocity changes provide a sensitive proxy for real-time monitoring of fault zone hydromechanical processes. It provides new constraints on subduction zone segmentation, coupling, and earthquake rupture dynamics and demonstrates a powerful new way to monitor offshore fault zones, ultimately improving our understanding of when and how large earthquakes might occur in Cascadia.
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Reference:
1Kidiwela, M., Denolle, M.A., Wilcock, W.S.D., and Feng, K-F (2026) Active protothrusts and fluid highways: Seismic noise reveals hidden subduction dynamics in Cascadia. Science Advances, 12; https://www.science.org/doi/10.1126/sciadv.aea3684.
Read MoreA Carbon Budget for the Upper Mesopelagic Zone
(Adapted from Stephens et al., 2025)
Upper ocean carbon budgets are difficult to constrain, and those for the mesopelagic zone come with particular challenges. A recent paper by Stephens et al. (2025) took on the challenge of a comprehensive carbon system budget for the upper mesopelagic zone (100-500 m) based on data from the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) program (Siegel et al., 2016). The 2018 EXPORTS field campaign was conducted at Ocean Station Papa in the Northeast Pacific to take advantage of the relatively modest surface forcing, shallow summer mixed layer, tightly coupled food web, and low mesoscale kinetic energy. Nevertheless, the study found that a steady-state assumption for the carbon system was likely not appropriate.
Measuring organic carbon supply and demand is challenging due to a variety of factors. Supply includes sinking particles, migrating zooplankton and fish, disaggregation, mixing and subduction. Demand comes primarily from bacteria and zooplankton. Measurement methods for each supply and demand term have errors, conversions to rates have uncertainties, and each process being measured may have a unique timescale over which a rate integration makes sense. EXPORTS was notable for increasing the number and variety of measurements available for monitoring the mesopelagic carbon budget. Stephens et al. take advantage of this by combining multiple measurement methods, quantifying errors and applying statistical methods for error analysis.
The authors used observations from multiple sources. Near-surface data came from the PMEL Station Papa surface mooring. Shipboard profile data come from two ships operating during the EXPORTS field campaign as well as the OOI Station Papa cruise in 2018. Additional water column data came from two OOI Slocum gliders, one EXPORTS-operated Seaglider, and BGC Argo floats. The authors examined each carbon supply and demand estimate, calculating an uncertainty and discussing potential limitations (Stephens et al., Table 1). A Monte Carlo approach was used to assess overall uncertainty in supply and demand terms, resulting in the conclusion that supply was insufficient to meet demand (e.g. Fig. 1 below). The error analysis allowed the authors to conclude that the mismatch was not the result of problems in estimating supply or demand, but rather a problem with the assumption that supply and demand would balance within the analysis period. In other words, the system was not in steady state.
This project highlights the complexity of the carbon system in the upper ocean and the broad suite of observational tools necessary to address the carbon budget. The authors make three specific recommendations for improved quantification of the biological carbon pump: including the relevant midwater processes, capturing the range of relevant timescales, and providing redundancy in methodology.
[caption id="attachment_37368" align="alignnone" width="928"]
Assessment of the organic carbon budget in the upper mesopelagic zone during EXPORTS. Estimated individual contributions to supply (left) and demand (right) are provided along with error estimates. Terms with multiple measurement methods (far left, far right) were averaged. The center panel shows the cumulative supply and demand relative to a vertical scale in units of mmol C per (m^2 day). From Stephens et al., 2025.[/caption]
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References:
Stephens, B.M., and 20 co-authors, 2025. An upper-mesopelagic-zone carbon budget for the subarctic North Pacific, Biogeosciences, 22, 3301-3328, https://doi.org/10.5194/bg-22-3301-2025.
Siegel, D.A., K.O. Buesseler, M.J. Behrenfeld, C.R. Benitez-Nelson, E. Boss, M.A. Brzezinski, A. Burd, C.A. Carlson, E.A. D’Asaro, S.C. Doney, M.J. Perry, R.H.R. Stanley and D.K. Steinberg, 2016. Prediction of the Export and Fate of Global Ocean Net Primary Production: The EXPORTS Science Plan, Front. Mar. Sci., 3:22, https://doi.org/10.3389/fmars.2016.00022.
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