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Ice–ocean interactions at the bases of Antarctic ice shelves are rarely observed, yet have a profound influence on ice sheet evolution and stability. Ice sheet models are highly sensitive to assumed ice shelf basal melt rates; however, there are few direct observations of basal melting or the oceanographic processes that drive it, and consequently our understanding of these interactions remains limited. Here we use in situ observations from the Ross Ice Shelf to examine the oceanographic processes that drive basal ablation of the world’s largest ice shelf. We show that basal melt rates beneath a thin and structurally important part of the shelf are an order of magnitude higher than the shelf-wide average. This melting is strongly influenced by a seasonal inflow of solar-heated surface water from the adjacent Ross Sea Polynya that downwells into the ice shelf cavity, nearly tripling basal melt rates during summer. Melting driven by this frequently overlooked process is expected to increase with predicted surface warming. We infer that solar heat absorbed in ice-front polynyas can make an important contribution to the present-day mass balance of ice shelves, and potentially impact their future stability.High melt rates in a key location beneath the Ross Ice Shelf result from a seasonal inflow of water heated in the Ross Sea Polynya, according to in situ observations.

Tropical cyclones have always been a concern of meteorologists, and there are many studies regarding the axisymmetric structures, dynamic mechanisms, and forecasting techniques from the past 100 years. This research demonstrates the ongoing progress as well as the many remaining problems. Machine learning, as a means of artificial intelligence, has been certified by many researchers as being able to provide a new way to solve the bottlenecks of tropical cyclone forecasts, whether using a pure data-driven model or improving numerical models by incorporating machine learning. Through summarizing and analyzing the challenges of tropical cyclone forecasts in recent years and successful cases of machine learning methods in these aspects, this review introduces progress based on machine learning in genesis forecasts, track forecasts, intensity forecasts, extreme weather forecasts associated with tropical cyclones (such as strong winds and rainstorms, and their disastrous impacts), and storm surge forecasts, as well as in improving numerical forecast models. All of these can be regarded as both an opportunity and a challenge. The opportunity is that at present, the potential of machine learning has not been completely exploited, and a large amount of multi-source data have also not been fully utilized to improve the accuracy of tropical cyclone forecasting. The challenge is that the predictable period and stability of tropical cyclone prediction can be difficult to guarantee, because tropical cyclones are different from normal weather phenomena and oceanographic processes and they have complex dynamic mechanisms and are easily influenced by many factors.

Reef passes are deep, navigable channels dissecting coral reefs around volcanic islands. Many reef passes are located offshore of large island river basins, suggesting a potential causal relationship. To clarify the mechanisms that form and maintain reef passes, we quantify the relationships between reef pass location and drainage basin size in the Society Islands. River basins draining toward reef passes are larger than those draining toward unbroken reef flats, suggesting that rivers help create and sustain reef passes. The correlation between reef passes and large rivers weakens for older islands, suggesting that oceanographic processes increasingly maintain passes as islands age and subside. We propose two river‐driven reef pass formation mechanisms: reef incision, in which rivers erode into reefs during sea‐level lowstands, and reef encroachment, in which corals growing in lower‐elevation submerged river valleys preferentially drown during periods of rapid sea‐level rise, leaving gaps in the accreting reef.

The islands of the Maritime Continent are highly vulnerable to sea‐level rise driven by barystatic, sterodynamic, and vertical land motion (VLM) processes. While tectonics is known to affect relative sea‐level through VLM, its influence on long‐term geocentric sea level (GSL) through crustal deformation and gravity field perturbations remains poorly constrained. A process decomposition of satellite‐observed GSL change (1993–2021) reveals a significant residual trend along the Sumatra–Andaman subduction zone that cannot be explained by known oceanographic processes. This signal coincides with GRACE‐derived long‐term geoid change and the 2004 Indian Ocean earthquake rupture zone, indicating that tectonic deformation may imprint a measurable signal on long‐term GSL change. Confirming this tectonic origin, given the possible deep ocean sterodynamic contributions, requires sustained ocean in situ observations and geophysical modeling.

Oceanic dissolved oxygen concentrations are thought to be declining under ongoing global warming, yet their variability remains less well understood than that of physical parameters such as temperature and salinity, primarily due to the limited spatial and temporal coverage of oxygen observation. Here, we examine linear trends in potential temperature, salinity, and dissolved oxygen in the North Pacific over the past two decades (2004–2023), using the GOBAI-O2-v2.2 dataset (Version 4.4). We compare the diagnosed oxygen trends with those of physical parameters to reveal the spatial structure of recent changes. The oxygen trends inferred from GOBAI-O2 are broadly consistent with trends observed along ship-based hydrographic repeat lines. While basin-scale deoxygenation is evident, we also identify localized oxygen increases on specific density surfaces. By relating these patterns to the surrounding physical environment, we find that the spatial heterogeneity in oxygen trends is consistent with known oceanographic processes, including the southward retreat of the oxygen minimum layer and the northward migration of a front separating the subtropical and subarctic gyres. These results underscore the value of GOBAI-O2 data in linking physical variability to previously unrecognized biological and biogeochemical patterns in the ocean.

Sea‐level rise due to both climate change and non‐climatic factors threatens coastal settlements, infrastructure, and ecosystems. Projections of mean global sea‐level (GSL) rise provide insufficient information to plan adaptive responses; local decisions require local projections that accommodate different risk tolerances and time frames and that can be linked to storm surge projections. Here we present a global set of local sea‐level (LSL) projections to inform decisions on timescales ranging from the coming decades through the 22nd century. We provide complete probability distributions, informed by a combination of expert community assessment, expert elicitation, and process modeling. Between the years 2000 and 2100, we project a very likely (90% probability) GSL rise of 0.5–1.2 m under representative concentration pathway (RCP) 8.5, 0.4–0.9 m under RCP 4.5, and 0.3–0.8 m under RCP 2.6. Site‐to‐site differences in LSL projections are due to varying non‐climatic background uplift or subsidence, oceanographic effects, and spatially variable responses of the geoid and the lithosphere to shrinking land ice. The Antarctic ice sheet (AIS) constitutes a growing share of variance in GSL and LSL projections. In the global average and at many locations, it is the dominant source of variance in late 21st century projections, though at some sites oceanographic processes contribute the largest share throughout the century. LSL rise dramatically reshapes flood risk, greatly increasing the expected number of “1‐in‐10” and “1‐in‐100” year events. Key Points Rates of local sea‐level rise differs from rate of global sea‐level rise Differences arise from land motion, ocean dynamics, and Antarctic mass balance Local sea‐level rise can dramatically increase flood probabilities

The dissolved oxygen (DO) levels of coastal ocean waters have decreased over the last few decades in part because of the increase in surface and subsurface water temperature caused by climate change, the reduction in ocean ventilation, and the increase in stratification and eutrophication. In addition, biological and human activity in coastal zones, bays, and estuaries has contributed to the acceleration of current oxygen loss. The Patagonian fjord and channel system is one world region where low-DO water (LDOW, 30 %–60 % oxygen saturation) and hypoxia conditions (<30 % oxygen saturation, 2 mL L−1 or 89.2 µmol L−1) are observed. An in situ dataset of hydrographic and biogeochemical variables (1507 stations), collected from sporadic oceanographic cruises between 1970 and 2021, was used to evaluate the mechanisms involved in the presence of LDOW and hypoxic conditions in northern Patagonian fjords. Results denoted areas with LDOW and hypoxia coinciding with the accumulation of inorganic nutrients and the presence of salty and oxygen-poor Equatorial Subsurface Water mass. The role of biological activity in oxygen reduction was evident in the dominance of community respiration over gross primary production. This study elucidates the physical and biogeochemical processes contributing to hypoxia and LDOW in the northern Patagonian fjords, highlighting the significance of performing multidisciplinary research and combining observational and modeling work. This approach underscores the importance of a holistic understanding of the subject, encompassing both real-world observations and insights provided by modeling techniques.

A detailed understanding of the dynamics of small-scale (10s km) habitat use by the reef manta ray ( Mobula alfredi ) in the Maldives Archipelago is required to develop an effective national conservation management plan for this wide-ranging species. Here, a combination of photo-ID sightings data and acoustic telemetry were used to investigate both long-term M . alfredi visitation trends and small-scale movement patterns to key habitats on the eastern side of Baa Atoll (Hanifaru Bay feeding area, Dhigu Thila multifunctional site, and Nelivaru Thila cleaning station). All tagged and most of the sighted M . alfredi exhibited high affinity to the eastern side of Baa Atoll, where 99% of detections occurred, and 69% of individuals were re-sighted in multiple years. Sightings data suggests that visitation patterns may be associated with differences in habitat use by sex and maturity status. Boosted regression trees indicated that tag detection probability at Hanifaru Bay increased with increased westerly wind speed (>5ms -1 ) during the day, close to a new and full moon just after high tide, and when the tidal range was low. Interaction effects between predictors suggest that wind-driven oceanographic processes, such as Langmuir Circulation, maybe working to increase zooplankton concentration at this location. Tag detection probability increased at Dhigu Thila under similar conditions. At Nelivaru Thila, it increased at lower wind speeds (<5ms -1 ), close to a full moon, three hours after high tide. These results suggest that M . alfredi may utilise cleaning stations during the day when environmental conditions are not suitable for feeding. There was a high level of connectivity between these three locations, which suggests they form part of a network of key habitats that provide essential services to M . alfredi locally. Future conservation efforts should focus on identifying all areas of key habitat use for this species within the Maldives; applying strict protective measures to these sites and any connecting migration corridors which link them.

The turbulent dissipation rate ε is a key parameter to many oceanographic processes. Recently, gliders have been increasingly used as a carrier for microstructure sensors. Compared to conventional ship-based methods, glider-based microstructure observations allow for long-duration measurements under adverse weather conditions and at lower costs. The incident water velocity U is an input parameter for the calculation of the dissipation rate. Since U cannot be measured using the standard glider sensor setup, the parameter is normally computed from a steady-state glider flight model. As ε scales with U2 or U4, depending on whether it is computed from temperature or shear microstructure, respectively, flight model errors can introduce a significant bias. This study is the first to use measurements of in situ glider flight, obtained with a profiling Doppler velocity log and an electromagnetic current meter, to test and calibrate a flight model, extended to include inertial terms. Compared to a previously suggested flight model, the calibrated model removes a bias of approximately 1 cm s−1 in the incident water velocity, which translates to roughly a factor of 1.2 in estimates of the dissipation rate. The results further indicate that 90% of the estimates of the dissipation rate from the calibrated model are within a factor of 1.1 and 1.2 for measurements derived from microstructure temperature sensors and shear probes, respectively. We further outline the range of applicability of the flight model.

Continental shelves encompass gently sloped seascapes that are highly productive and intensively exploited for natural resources. Islands, reefs and other emergent or quasi-emergent features punctuate these shallow (<100 m) seascapes and are well known drivers of increased biomass and biodiversity, as well as predictors of fishing and other human uses. On the other hand, relict mesoscale geomorphological features that do not represent navigation hazards, such as incised valleys (IVs), remain poorly charted. Consequently, their role in biophysical processes remains poorly assessed and sampled. Incised valleys are common within rhodolith beds (RBs), the most extensive benthic habitat along the tropical and subtropical portions of the mid and outer Brazilian shelf. Here, we report on a multi-proxy assessment carried out in a tropical-subtropical transition region (~20°S) off Eastern Brazil, contrasting physicochemical and biological variables in IVs and adjacent RBs. Valleys interfere in near bottom circulation and function as conduits for water and propagules from the slope up to the mid shelf. In addition, they provide a stable and structurally complex habitat for black corals and gorgonians that usually occur in deeper water, contrasting sharply with the algae-dominated RB. Fish richness, abundance and biomass were also higher in the IVs, with small planktivores and large-bodied, commercially important species (e.g. groupers, snappers and grunts) presenting smaller abundances or being absent from RBs. Overall, IVs are unique and vulnerable habitats that sustain diverse assemblages and important ecosystem processes. As new IVs are detected by remote sensing or bathymetric surveys, they can be incorporated into regional marine management plans as conservation targets and priority sites for detailed in situ surveys.