Hasil untuk "Oceanography"

Dmitrii Pantiukhin, Ivan Kuznetsov, Boris Shapkin et al.

The rapid accumulation of Earth science data has created a significant scalability challenge; while repositories like PANGAEA host vast collections of datasets, citation metrics indicate that a substantial portion remains underutilized, limiting data reusability. Here we present PANGAEA-GPT, a hierarchical multi-agent framework designed for autonomous data discovery and analysis. Unlike standard Large Language Model (LLM) wrappers, our architecture implements a centralized Supervisor-Worker topology with strict data-type-aware routing, sandboxed deterministic code execution, and self-correction via execution feedback, enabling agents to diagnose and resolve runtime errors. Through use-case scenarios spanning physical oceanography and ecology, we demonstrate the system's capacity to execute complex, multi-step workflows with minimal human intervention. This framework provides a methodology for querying and analyzing heterogeneous repository data through coordinated agent workflows.

Maria R. Lancia, Alejandro Vélez-Santiago

We investigate the realization of a myriad of general local and nonlocal inhomogeneous elliptic and parabolic boundary value problems over classes of irregular regions. We present a unified approach in which either local or nonlocal Neumann, Robin, and Wentzell boundary value problems are treated simultaneously. We establish solvability and global regularity results for both the stationary and time-dependent heat equations governed by general differential operators with unbounded measurable coefficients and various boundary conditions at once, first on a general framework, and then by presenting concrete important examples of irregular domains, Wentzell-type boundary conditions, and nonlocal maps. As a consequence, we develop a priori estimates for multiple differential equations under various situations, which are tied to a large number of applications performed over real world regions, such heat transfer, electrical conductivity, stable-like processes (probability theory), diffusion of medical sprays in the bronchial trees, and oceanography (among many others).

K. Marvel, B. Cook, E. Weng et al.

<p>An understanding of Earth's past climate can help put current and future changes into historical context. Widely used tree ring-based drought atlases generally target the Palmer Drought Severity Index or other metrics of soil moisture and/or drought risk. These indices reflect contemporaneous meteorological conditions, and it is possible to extract information about temperature and precipitation given the existing reconstructions. Here, we present a fully Bayesian inverse method that infers a joint posterior for monthly mean temperature and precipitation given tree ring-based PDSI reconstructions from the North American Drought Atlas. The method is skillful at reconstructing early twentieth century conditions when compared to instrumental measurements from the CRU TS dataset. Moreover, the reconstructions can capture the complex temporal and multivariate covariance structure between monthly regional temperatures and precipitation. By reconstructing regional temperature and precipitation for the last millennium, we identify the driest and wettest years and decades in each region. Our results highlight the unique nature of the 1930s Dust Bowl drought in central Kansas and the late twentieth century pluvial in the North American southwest.</p>

Christopher Thierauf

A new AUV mission planning and execution software has been tested on AUV Sentry. Dubbed DINOS-R, it draws inspiration from cognitive architectures and AUV control systems to replace the legacy MC architecture. Unlike these existing architectures, however, DINOS-R is built from the ground-up to unify symbolic decision making (for understandable, repeatable, provable behavior) with machine learning techniques and reactive behaviors, for field-readiness across oceanographic platforms. Implemented primarily in Python3, DINOS-R is extensible, modular, and reusable, with an emphasis on non-expert use as well as growth for future research in oceanography and robot algorithms. Mission specification is flexible, and can be specified declaratively. Behavior specification is similarly flexible, supporting simultaneous use of real-time task planning and hard-coded user specified plans. These features were demonstrated in the field on Sentry, in addition to a variety of simulated cases. These results are discussed, and future work is outlined.

Abdessamad El-Kabid, Loubna Benabbou, Redouane Lguensat et al.

Accurate modeling of physical systems governed by partial differential equations is a central challenge in scientific computing. In oceanography, high-resolution current data are critical for coastal management, environmental monitoring, and maritime safety. However, available satellite products, such as Copernicus data for sea water velocity at ~0.08 degrees spatial resolution and global ocean models, often lack the spatial granularity required for detailed local analyses. In this work, we (a) introduce a supervised deep learning framework based on neural operators for solving PDEs and providing arbitrary resolution solutions, and (b) propose downscaling models with an application to Copernicus ocean current data. Additionally, our method can model surrogate PDEs and predict solutions at arbitrary resolution, regardless of the input resolution. We evaluated our model on real-world Copernicus ocean current data and synthetic Navier-Stokes simulation datasets.

F. E. Kemgang Ghomsi, F. E. Kemgang Ghomsi, F. E. Kemgang Ghomsi et al.

This study provides an in-depth evaluation of sea level rise (SLR) and its varied effects across the coastal regions of southern Africa. Utilizing data collected between 1993 and 2022, we analyze SLR patterns alongside land subsidence phenomena, based on observations from 10 strategically located tide gauges and X-TRACK satellite altimetry datasets. To ensure greater accuracy, the Coastal Altimetry Approach was adopted to refine nearshore measurements. Findings indicate that in areas such as Cape Town, sea-level rise rates reach around 6.3 mm/year, which is nearly twice the current global average of 3.3 mm/year. The interaction between rapid sea-level rise and subsidence rates surpassing 2.2 mm/year presents significant threats to coastal communities, critical infrastructure, and natural ecosystems. Moreover, the study highlights how seismic activity contributes to coastal dynamics, illustrating the role of earthquake-induced subsidence in magnifying the impacts of SLR. By incorporating seismic factors into the analysis, a more comprehensive understanding of the interplay between natural and human-induced drivers of sea-level variability is achieved. Additionally, the study examines the broader effects of SLR on Africa&rsquo;s culturally and historically important coastal heritage sites, emphasizing the urgent need for proactive coastal management and climate adaptation efforts.

Jiasen Guo, Ying Qiao, Xuyang Chen et al.

Blepharipoda liberata Shen, 1949, is a distinctive benthic crustacean found in the low tidal zone of the beach in Rizhao, Shandong, China. This study presents the first record of the complete mitochondrial genome of B. liberata. The mitochondrial genome was found to be 15,766 base pairs in length and contained 13 protein-coding genes, two ribosomal RNA genes, and 22 transfer RNA genes. The overall nucleotide composition was characterized by A 38.18%, T 35.94%, C 15.44%, and G 10.43%, with a high A + T content of 74.12%. Phylogenetic analysis indicated that B. liberata is closely related to other species within the Hippoidea family. This research marks the first acquisition of the complete mitochondrial genome of B. liberata, thereby providing valuable insights for future studies focused on the conservation and management of this species.

Jue Ning, Xu Chen, Tao Wang et al.

Abstract The modulation of anticyclonic subsurface‐intensified mode‐water eddies (MWEs) on the oceanic physical and biological responses to tropical cyclones (TCs) is investigated using satellite measurements, in situ observations and numerical model outputs. Extreme cooling of the surface (4.2°C) and mixed‐layer (2.3°C) is observed in a MWE, which can be remarkably stronger than those in adjacent cyclonic eddy and non‐eddy environments. The special thermodynamic structure above the lens of MWEs, which would favor the TC‐induced entrainment more efficiently, facilitates the elevation of substantial subsurface cold water. It also leads to increased mixed‐layer salinity and deepening of the mixed‐layer. Additionally, variations in nitrate and chlorophyll‐a concentrations appear to be depressed and exhibit intricate multi‐layer patterns due to TC‐induced and MWE‐influenced vertical processes. This study provides novel insights into the interactions between TCs and subsurface‐intensified eddies.

Johnathan Daniel Maxey, Neil D. Hartstein, Dane Dickinson et al.

Abstract Aquaculture’s contribution to global N2O emissions is poorly constrained and often reliant on supply chain/industrial emissions/life-cycle analyses which generalise system responses to farm-derived inputs and contain few examples of direct measurements made in situ. Among the studies that do report aquaculture associated N2O emissions the focus has been on pond culture and wetlands systems rather than open marine systems. Our study examined the effects of open system aquaculture culture on water column N2O cycling in two hydrodynamically contrasting southern hemisphere systems: the heavily stratified Macquarie Harbour, Tasmania, Australia and the semi-enclosed but well-mixed Big Glory Bay, New Zealand. Significant, but localised, N2O undersaturation was observed under the active salmon farm in the heavily stratified Macquarie Harbour during the peak feeding season, but not under fallowed salmon farms or the non-farmed areas. This was observed in a low-oxygen but not anoxic water column. Water column N2O was either in equilibrium with the atmosphere or supersaturated in all other instances. In Big Glory Bay N2O undersaturation was observed during winter and spring sampling surveys that generally persisted across the bay and resulted in removal of atmospheric N2O. The specific mechanisms of N2O loss are still uncertain but is likely driven by a combination of particle associated denitrification activity in farm waste plumes, denitrification/DNRA in sediments and on the detritus covered mussel shells and lines. Overall, this study demonstrates that industry impacts to N2O cycling can include loss dynamics which have previously been unreported. Therefore, global estimates of N2O emissions from aquaculture may be significantly overestimated.

Emma Asbridge, Claire Krause, Richard Lucas et al.

Tropical cyclones can significantly impact mangrove forests, with some recovering rapidly, whilst others may change permanently. Inconsistent approaches to quantifying these impacts limit the capacity to identify patterns of damage and recovery across landscapes and cyclone categories. Understanding these patterns is critical as the changing frequency and intensity of cyclones and compounding effects of climate change, particularly sea-level rise, threaten mangroves and their ecosystem services. Improvements in Earth observation data, particularly satellite-based sensors and datacube environments, have enhanced capacity to classify time-series data and advanced landscape monitoring. Using the Landsat archive within Digital Earth Australia to monitor annual changes in canopy cover and extent, this study aims to quantify and classify immediate and long-term impacts of category 3–5 cyclones for mangroves in Australia. Closed canopy mangrove forests experienced the greatest immediate impact (loss of canopy cover). Most immediate impacts were minor, implying limited immediate mortality. Impacts varied spatially, reflecting proximity to exposed coastlines, cyclone track and forest structure (height, density, condition and species). Recovery was evident across all cyclones, although some areas exhibited permanent damage. Understanding the impacts and characteristics of vulnerable and resilient forests is crucial for managers tasked with protecting mangroves and their services as the climate changes.

I Wayan Sumardana Eka Putra, Agus Saleh Atmadipoera, Henry Munandar Manik et al.

Graphical Abstract Highlight Research • The IASL-1 entry portal in the southern and northern regions shows the emergent SOFAR channels. • The shadow zone and the existence of a SOFAR deep sound channel in the IASL-2 and IASL-3 routes can be triggered by the emergent “saddle” SVP pattern.  • The variability seasonally and interannually due to variations in seawater properties stratification plays an important role in SOFAR channel appearances in IASLs. • The diverse oceanographic characteristics of IASLs necessitate the implementation of sustainable marine geospatial data. Abstract Indonesian Maritime Continent (IMC) is responsible for the three international sea lanes, known as Indonesian Archipelago Sea Lanes (IASLs), which allowed ships to navigate across territorial waters between Pacific and Indian Oceans and vice versa. Gaining knowledge about the distinct oceanographic characteristics of the three IASLs can offer valuable insight into maritime safety and sustainable marine resource management. Therefore, this research aims to review oceanographic characteristics in IASLs regions from available previous research to provide a comprehensive insight into the processes and dynamical oceanography in IASLs region as well as determine the implications for underwater acoustic patterns. The results showed that IASL-1 route is characterized by a shallow shelf passage with homogeneous sound velocity profile (SVP), which has a deep and narrow entry portal in the southern and northern Sound Fixing and Ranging Channel (SOFAR) channels. Seasonal reversal monsoonal wind-driven current dominates the circulation. IASL-2 and IASL-3 routes transported a deep and narrow passage with complexity of seaair interactions that vary on seasonal and interannual time scales. These IASLs were established with the saddle SVP, which trigger the shadow zone and the existence of SOFAR deep sound channel with seasonal and interannual variations in seawater properties stratification. The diverse oceanographic characteristics discussed significantly influence the underwater object detection equipment, the planning time, and the strategies for underwater defense systems. Due to the implications, it is necessary to use marine geospatial database, which may be adopted to facilitate policy-making, providing approximations for marine activities and management along IASLs.

Andrea Meilán-Vila, Rosa M. Crujeiras, Mario Francisco-Fernández

In oceanography, modeling wave fields requires the use of statistical tools capable of handling the circular nature of the {data measurements}. An important issue in ocean wave analysis is the study of height and direction waves, being direction values recorded as angles or, equivalently, as points on a unit circle. Hence, reconstruction of a wave direction field on the sea surface can be approached by the use of a linear-circular regression model, viewing wave directions as a realization of a circular spatial process whose trend should be estimated. In this paper, we consider a spatial regression model with a circular response and several real-valued predictors. Nonparametric estimators of the circular trend surface are proposed, accounting for the (unknown) spatial correlation. Some asymptotic results about these estimators as well as some guidelines for their practical implementation are also given. The performance of the proposed estimators is investigated in a simulation study. An application to wave directions in the Adriatic Sea is provided for illustration.

Toshit Jain, Varun Singh, Vijay Kumar Boda et al.

Visual analysis is well adopted within the field of oceanography for the analysis of model simulations, detection of different phenomena and events, and tracking of dynamic processes. With increasing data sizes and the availability of multivariate dynamic data, there is a growing need for scalable and extensible tools for visualization and interactive exploration. We describe pyParaOcean, a visualization system that supports several tasks routinely used in the visual analysis of ocean data. The system is available as a plugin to Paraview and is hence able to leverage its distributed computing capabilities and its rich set of generic analysis and visualization functionalities. pyParaOcean provides modules to support different visual analysis tasks specific to ocean data, such as eddy identification and salinity movement tracking. These modules are available as Paraview filters and this seamless integration results in a system that is easy to install and use. A case study on the Bay of Bengal illustrates the utility of the system for the study of ocean phenomena and processes.

Fernando L. Metz, Cristian Bonatto, Sandra D. Prado

The statistical properties of speckle patterns have important applications in optics, oceanography, and transport phenomena in disordered systems. Here we obtain closed-form analytic results for the amplitude distribution of speckle patterns formed by a random number of partial waves characterized by an arbitrary phase distribution, generalizing classical results of the random walk theory of speckle patterns. We show that the functional form of the amplitude distribution is solely determined by the distribution of the number of scatterers, while the phase distribution only influences the scale parameters. In the case of a non-random number of scatterers, we find an analytic expression for the amplitude distribution that extends the Rayleigh law to non-uniform random phases. For a negative binomial distribution of the number of scatterers, our results reveal that large fluctuations of the wave amplitudes become more pronounced in the case of biased random phases. We present numerical results that fully support our analytic findings.

Bin Wang, Bin Wang, Bin Wang et al.

The summer hypoxia off the Changjiang Estuary is one of the largest coastal hypoxic systems in the world and has displayed spatial heterogeneity in recent years. Based on observation data in the summer of 2014, hypoxia was identified both in the bottom and mid-layers. Except for the typical bottom hypoxia in the submarine canyon, the subsurface oxygen minima (SOM) were captured in the mid-layer of 10~15 m, with lower dissolved oxygen in the mid-layer than at the bottom (30–50 m). This SOM phenomenon was located in the lower boundary of the pycnocline and above the Taiwan warm current (TWC) and Kuroshio subsurface water (KSSW). Due to the southern expansion of Changjiang diluted water (CDW), a high phytoplankton biomass (the maximum chlorophyll a of 25 μg L−1, pH of 8.6, and DO of 11 mg L−1) band occupied the surface area along 123°E. By analyzing the 24-h continuous observation and high-resolution profile data, we revealed that the subsurface oxygen minima were predominantly controlled by remineralization and bottom-flushing effects. Fast local consumption occurred near the pycnocline layer, while the lateral transport of oxygen-rich ambient water replenished the bottom oxygen deficit from south to north. We summarize and contextualize three hot spots of hypoxia into a conceptual diagram and emphasize the influences of advection, mixing, and respiration on their location and severity. Overall, compared with the discussion about the low DO background of TWC/KSSW, this research highlights the flushing effects of TWC/KSSW that will reshape the hypoxia structure and alleviate the hypoxia severity in the south hypoxia area off the Changjiang Estuary.

Samuel K. K. Amponsah, Francis K. E. Nunoo, Angela E. Lamptey et al.

Ports offer economic progress to many coastal developing countries. In view of the economic importance, the rising demand for maritime benefits requires the expansion of existing ports. However, marine ecosystems may become vulnerable to negative impact from the construction of these maritime structures. Therefore, the aim of the study was to establish the impact of Tema port expansion on the diversity and population structure of fish species. Data were collected quarterly from June 2018 to November 2021 through trawling fishing activities off the coast of Greater Accra, Ghana, and subsequently analysed using Primer 6 software. Sampling locations along the coast of Greater Accra included Vernon Bank (VNB), Disposal area (DSA) and Offshore Sakumono (OSK). The increased and reduced number of species at VNB and DSA, respectively, could be alluded to dredging and disposal of dredged spoils. Diversity indices at OSK site was higher than those observed in disturbed areas due to the absence of impact in this control area. Thus, it is recommended to conduct further studies on the assemblage of invasive species that migrated to the VNB during dredging activities, since these species can have severe economic impact on fishing activities of artisanal fishermen, especially at the local level.

Jing Liu, Richard G. J. Bellerby, Qing Zhu et al.

Abstract Sea surface salinity (SSS) is a master variable in oceanography and important to understand marine biogeochemical and physical processes. In the East China Sea (ECS), a random forest based regression ensemble model (RF) was developed to estimate the SSS with a spatial resolution of ∼1 km based on a large synchronous data set of in situ SSS observations, MODIS‐derived remote sensing reflectance (Rrs) and sea surface temperature (SST). The model showed the best performance when the Rrs(412), Rrs(488), Rrs(555), Rrs(667), SST and Julian day (JD) were used as inputs, with a root mean square error (RMSE) of 0.84, mean absolute error (MAE) of 0.31 and coefficient of determination (R2) of 0.81 for model training (N = 4,504), and a RMSE of 0.77, MAE of 0.30 and R2 of 0.86 for the model test (N = 1,153). The accuracy of the SSS model was examined using an independent data set during the period of 2020–2022 with a RMSE of 0.66 and MAE of 0.39 (N = 2,151). The interannual and seasonal signal of modeled SSS of the ECS, showed that important drivers of variability are the Changjiang discharge and the East‐Asian monsoon. Applications of the model to other Chinese marginal seas (Yellow and Bohai seas) showed good agreement in distribution patterns when compared with the estimated SSS from NASA Soil Moisture Active Passive. Once more empirical oceanographic data is made available, this robust model can be applied to other regions retraining the model with informed local data sets.

Taikang Yuan, Junxing Zhu, Wuxin Wang et al.

Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerical methods or data-driven methods. Physics-based numerical methods rely on marine physics equations and have stable and explicable outputs, while data-driven methods are flexible in adapting to data and are capable of detecting unexpected patterns. We believe that these two types of method are complementary to each other, and their combination can potentially achieve better performances. In this paper, a space-time partial differential equation (PDE) is employed to form a novel physics-based deep learning framework, named the space-time PDE-guided neural network (STPDE-Net), to predict daily SST. Comprehensive experiments for SST prediction were conducted, and the results proved that our method could outperform the traditional finite-difference forecast method and several state-of-the-art deep learning and physics-guided deep learning methods.

Javier Montenegro, Allen G. Collins, Russell R. Hopcroft et al.

IntroductionBotrynema, a genus of medusozoans in the trachyline family Halicreatidae, currently contains two species: B. brucei and B. ellinorae, distinguished by the presence or absence, respectively, of an apical knob as a diagnostic character. However, no study has corroborated if these taxonomic diagnoses have a biological and evolutionary basis. Therefore, in this study we attempted to address the question “do the two nominal species in the genus Botrynema represent independent phylogenetic lineages, or two phenotypic variants of a single species?MethodsIn this study we took advantage of legacy collections from different research expeditions across the globe from 2000 to 2021 to study the phylogenetics and taxonomy of the genus Botrynema.ResultsB. brucei and B. ellinorae present partially overlapping vertical distributions in the Arctic and as a whole in the Arctic the genus seems to be limited to the Atlantic water masses. The phylogenetic reconstruction based on the concatenated alignment corroborates the validity of the family Halicreatidae and of genus Botrynema as monophyletic groups. However no clear differentiation was found between the two presently accepted species, B. ellinorae and B. brucei.DiscussionBased on the evidence we gathered, we conclude that while the genus Botrynema does contain at least two species lineages, these lineages are not concordant with current species definitions. The species B. ellinorae is reassigned as a subspecies of B. brucei and diagnostic characters are provided.

Guangming Shao, Tianliang He, Yinnan Mu et al.

Summary: How organisms cope with coldness and high pressure in the hadal zone remains poorly understood. Here, we sequenced and assembled the genome of hadal sea cucumber Paelopatides sp. Yap with high quality and explored its potential mechanisms for deep-sea adaptation. First, the expansion of ACOX1 for rate-limiting enzyme in the DHA synthesis pathway, increased DHA content in the phospholipid bilayer, and positive selection of EPT1 may maintain cell membrane fluidity. Second, three genes for translation initiation factors and two for ribosomal proteins underwent expansion, and three ribosomal protein genes were positively selected, which may ameliorate the protein synthesis inhibition or ribosome dissociation in the hadal zone. Third, expansion and positive selection of genes associated with stalled replication fork recovery and DNA repair suggest improvements in DNA protection. This is the first genome sequence of a hadal invertebrate. Our results provide insights into the genetic adaptations used by invertebrate in deep oceans.