Hasil untuk "Oceanography"

Edoardo Bellincioni, Kevin Zhong, Christopher J. Howland et al.

Melting is omnipresent in nature and technology, with applications ranging from metallurgy, biology, food science, and latent thermal energy storage to oceanography, geophysics, and climate science, and occurring on all scales from sub-millimeter to global scales. The key objective is to understand the rate at which an object melts as a function of its size and of the ambient conditions. To achieve this it is important to be able to extrapolate from small scale experiments and observations to large or even global scales. This is done by scaling laws. However, these are only meaningful if there is no transition from one scaling relation to another one. Here we show, however, that for both fixed and freely-advected melting objects immersed in a turbulent flow a melting transition does exist, namely from slow melting at the small scales to fast melting at the large scales. We do so by controlled melting experiments and corresponding direct numerical simulations, covering four orders of magnitude in scale. The transition corresponds to the transition from a laminar-type boundary layer around the melting object to a turbulent-type boundary layer, i.e., from so-called classical turbulence to ultimate turbulence, with its enhanced transport properties. Our results thus provide a quantitative understanding of the flow physics of the melting process and thereby enable a better extrapolation and prediction of melt rates on large scales such as relevant in geophysics, oceanography, and climate science.

Baohang Wang, Guangrong Li, Chaoying Zhao et al.

Potential tropospheric noise is a critical factor that undermines the effectiveness of deformation monitoring in Synthetic Aperture Radar Interferometry (InSAR) technologies. In most scenarios, many point targets within the InSAR deformation monitoring area either do not undergo deformation or exhibit only minimal deformation trends. The phases of densely distributed stable points can effectively respond to spatial tropospheric delays, particularly turbulent atmospheric phases. This study proposes a data-driven InSAR atmospheric correction method by exploring how to use these densely stable InSAR time series to model atmospheric phase delays. Our focus is on selecting stable InSAR time series point targets and evaluating the impact of different densities of stable points on atmospheric correction performance. Analysis of 645 interferograms derived from 217 Sentinel-1A SAR images, spanning from 13 June 2017 to 15 November 2024, demonstrates that the proposed method reduces the Root Mean Square Error (RMSE) by 70%, 59%, and 69% compared to the terrain-related linear approach, the General Atmospheric Correction Online Service, and common scene stacking methods, respectively. In addition, simulation data and leveling data were used to validate the proposed method. This article does not develop an independent InSAR atmospheric correction method. Instead, the proposed approach starts with the InSAR deformation time series, allowing for easy integration into existing InSAR workflows and widely used atmospheric correction strategies. It can serve as a post-processing tool to improve InSAR time series analysis.

Massimiliano Berti, Ricardo Grande, Alberto Maspero et al.

Rogue waves are extreme ocean events characterized by the sudden formation of anomalously large crests, and remain an important subject of investigation in oceanography and mathematics. A central problem is to quantify the probability of their formation under random Gaussian sea initial data. In this work, we rigorously characterize the tail-probability for the formation of rogue waves of the pure gravity water wave equations in deep water, the most accurate quasilinear PDE modeling waves in open ocean. This large deviation result rigorously proves various conjectures from the oceanography literature in the weakly nonlinear regime. Moreover, the result holds up to the optimal timescales allowed by deterministic well-posedness theory. The proof shows that rogue waves most likely arise through "dispersive focusing", where phase quasi-synchronization produces constructive amplification of the water crest. The main difficulty in justifying this mechanism is propagating statistical information over such long timescales, which we overcome by combining normal forms and probabilistic methods. Unlike prior work, this novel approach does not require approximate solutions to be Gaussian. Our general method tracks the tail probability of solutions to Hamiltonian PDEs with an integrable normal form and random Gaussian initial data over very long times, even in the absence of (quasi-)invariant measures.

Thomas Savary, François Rozet, Gilles Louppe

Data assimilation is widely used in many disciplines such as meteorology, oceanography, and robotics to estimate the state of a dynamical system from noisy observations. In this work, we propose a lightweight and general method to perform data assimilation using diffusion models pre-trained for emulating dynamical systems. Our method builds on particle filters, a class of data assimilation algorithms, and does not require any further training. As a guiding example throughout this work, we illustrate our methodology on GenCast, a diffusion-based model that generates global ensemble weather forecasts.

Zhe Zhao, Yi Zhang, You Xu et al.

ABSTRACT: In this study, we constructed an integrated framework of a farming–breeding–bioenergy system to estimate the greenhouse gas (GHG) emission inventories of various farming and breeding processes in the northeast region of China from 2000 to 2021 based on life cycle assessment. Then, we compared the emission differences between the farming–breeding–bioenergy integrated system and the traditional farming–breeding system in different production segments. Finally, we assessed the environmental impact of the integrated system on agricultural GHG emissions. Results showed that the main sources of GHG emissions in Northeast China include enteric fermentation, fertilizer application, crop energy reduction, crop cultivation, and manure management. Emission hotspots also showed a trend of shifting from south to north and from east to west. In terms of environmental impact intensity, the largest increase in environmental impact intensity values among the farming and breeding systems was recorded in Heilongjiang Province (0.36) and Inner Mongolia (0.13), respectively. In terms of mitigation effects, the farming and breeding systems showed a considerable amount of residual straw and manure that can be fed into bioenergy systems, at 1 801.47 and 394.12 Mt, respectively. The farming–breeding–bioenergy integrated system demonstrated mitigating effects on agricultural GHG emissions.

Sifan Gu, Zhengyu Liu, Ning Zhao et al.

Abstract The rapid CO2 rise during the early deglaciation is often linked to enhanced ventilation by intensified Antarctic Bottom Water (AABW) overturning. The recorded radiocarbon ventilation seesaw during the early deglaciation, which describes improved Southern Ocean and reduced North Atlantic abyssal radiocarbon ventilation, has been interpreted as intensified AABW and reduced North Atlantic Deep Water convections. However, abyssal radiocarbon records also reflect changes in surface reservoir ages and interior water mass mixing. Using isotope-enabled simulations, we show that this seesaw results from weakened AABW overturning and decreased Southern Ocean surface reservoir age. With AABW occupying the abyssal ocean, weakened AABW overturning increases transit time, with the magnitude increasing northward. This transit time increase outpaced the declining $$\Delta ^{14}C_{{atm}}$$ Δ 14 C a t m induced Southern Ocean surface reservoir age decrease in the abyssal North Atlantic, but not in the abyssal Southern Ocean, thus producing a radiocarbon ventilation seesaw. Our results suggest sluggish deep water overturning from both poles during the early deglaciation.

Jilong Chen, Xing Chen, Wenjin Li et al.

In deep-sea mining hydraulic lifting systems, centrifugal pumps are very important as power units. In the process of transportation, the fluid prewhirl phenomenon in the impeller inlet will lead to changes in the state of motion of the particles and fluid and cause the wear of the inlet pipe, which can lead to centrifugal pump failure in serious cases. In this paper, a numerical simulation of the centrifugal pump is carried out based on the CFD-DEM coupling method to analyze the influence of the prewhirl on the wear of the inlet pipe. The results show that the velocity streamline near the impeller inlet position changes significantly. The flow field velocity increases along the radial direction of the inlet pipe, and it has a maximum value at <i>r/R</i> = 0.98. The prewhirl flow pulls the particles to change their original motion direction, and the area where the particles are subjected to high fluid force is concentrated between 0.5 <i>d/D</i> and 1 <i>d/D</i>, about 0.015 to 0.018 N, resulting in the uneven distribution of particles. The high-wear area appears in the bottom-left area (specifically, L4, L9, and L13), and this is also the location of the largest cumulative force; the high-wear area shows a triangle. The collision energy loss of particles increases due to the influence of the prewhirl, which leads to an increase in wear.

Wenbo Zhao, Xinghua Cheng, Dezhi Wang et al.

Abstract In the field of underwater target detection, the passive sonar is an important means of long‐distance target detection. The sonar detection information typically includes both surface and underwater targets, whereas it is a great challenge on effectively distinguishing between surface and underwater targets solely based on sonar information. Effective fusion of sonar and AIS (Automatic Identification System) data can leverage their complementary nature to compensate for the limitation of sonar information. However, the sonar information and AIS information are acquired based on different detection principles and systems, which are essentially multi‐source heterogeneous information with obvious spatio‐temporal misalignment in nature. Existing fusion methods normally struggle to effectively align sonar and AIS data in both time and space subject to the complexity of the problem. In this study, the Dynamic Time Warping (DTW) algorithm is applied to align sonar and AIS data in the time domain. In addition, a deep learning algorithm with multi‐head attention mechanism is proposed to achieve the spatial alignment of sonar and AIS data, where the matching between the surface targets in AIS data and the same surface targets in sonar data can also be successfully achieved. It provides a priori knowledge to enhance the underwater target detection of the passive sonar by eliminating the interference of the surface targets. Based on the attention mechanism, the abstract features extracted from the intermediate‐layer of the neural networks are found to be effective to represent the typical features of the target motion trajectories, which also demonstrates the effectiveness of the attention mechanism. The experiment results show that the proposed method can successfully achieve a MatchingSucccessRate of over 95% between the AIS targets and sonar detection targets.

Yongqiang Sun, Yongping Zhang, Anqi Wei et al.

Foam drainage agents enhance gas production by removing wellbore liquids. However, due to the ultra-high salinity environments of the Hechuan gas field (salinity up to 32.5 × 10⁴ mg/L), no foam drainage agent is suitable for this gas field. To address this challenge, we developed a novel nanocomposite foam drainage system composed of quaternary ammonium and two types of nanoparticles. This work describes the design and synthesis of a quaternary ammonium foam drainage agent and nano-engineered stabilizers. Nonylphenol polyoxyethylene ether sulfosuccinate quaternary ammonium foam drainage agent was synthesized using maleic anhydride, sodium chloroacetate, N,N-dimethylpropylenediamine, etc., as precursors. We employed the Stöber method to create hydrophobic silica nanoparticles. Carbon quantum dots were then prepared and functionalized with dodecylamine. Finally, carbon quantum dots were incorporated into the mesopores of silica nanoparticles to enhance stability. Through optimization, the best performance was achieved with a (quaternary ammonium foam drainage agents)–(carbon quantum dots/silica nanoparticles) ratio of 5:1 and a total dosage of 1.1%. Under harsh conditions (salinity 35 × 10⁴ mg/L, condensate oil 250 cm³/m³, temperature 80 °C), the system exhibited excellent stability with an initial foam height of 160 mm, remaining at 110 mm after 5 min. Additionally, it displayed good liquid-carrying capacity (160 mL), low surface tension (27.91 mN/m), and a long half-life (659 s). These results suggest the effectiveness of nanoparticle-enhanced foam drainage systems in overcoming high-salinity challenges. Previous foam drainage agents typically exhibited a salinity resistance of no more than 25 × 10⁴ mg/L. In contrast, this innovative system demonstrates a superior salinity tolerance of up to 35 × 10⁴ mg/L, addressing a significant gap in available agents for high-salinity gas fields. This paves the way for future development of advanced foam systems for gas well applications with high salinity.

Jiarui Liu, Kun Yang, Dingchi Zhao et al.

Abstract Over‐estimation of summer precipitation over the Tibetan Plateau (TP) is a well‐known and persistent problem in most climate models. This study demonstrates the impact of a Gaussian Probability Density Function cloud fraction scheme on rainfall simulations using the Weather Research and Forecasting model. It is found that this scheme in both 0.1° and 0.05° resolutions significantly reduces the wet bias through both local feedbacks and large‐scale dynamic process. Specifically, increased cloud water/ice content with this scheme reduces surface shortwave radiation, and consequently surface heat fluxes and evapotranspiration. This, in turn, dampens the large‐scale thermal effect of the TP and weakens the exaggerated monsoon circulation and low‐level moisture convergence. It is this large‐scale dynamic process that contributes the most (∼70%) to the wet bias reduction. Although this paper presents a modeling study, it highlights the cloud radiative feedback to the large‐scale dynamics and precipitation over the TP.

Ruochu Yang, Chad Lembke, Fumin Zhang et al.

Underwater gliders have been widely used in oceanography for a range of applications. However, unpredictable events like shark strikes or remora attachments can lead to abnormal glider behavior or even loss of the instrument. This paper employs an anomaly detection algorithm to assess operational conditions of underwater gliders in the real-world ocean environment. Prompt alerts are provided to glider pilots upon detecting any anomaly, so that they can take control of the glider to prevent further harm. The detection algorithm is applied to multiple datasets collected in real glider deployments led by the University of Georgia's Skidaway Institute of Oceanography (SkIO) and the University of South Florida (USF). In order to demonstrate the algorithm generality, the experimental evaluation is applied to four glider deployment datasets, each highlighting various anomalies happening in different scenes. Specifically, we utilize high resolution datasets only available post-recovery to perform detailed analysis of the anomaly and compare it with pilot logs. Additionally, we simulate the online detection based on the real-time subsets of data transmitted from the glider at the surfacing events. While the real-time data may not contain as much rich information as the post-recovery one, the online detection is of great importance as it allows glider pilots to monitor potential abnormal conditions in real time.

Alexey V. Slunyaev, Anna V. Kokorina

By means of the direct numerical simulation of directional waves on the surface of deep water it is shown that extreme waves can exhibit such asymmetry that the occurrence of deeper troughs is several times more likely on the wave rear slopes. This effect becomes most pronounced in the case of steep short-crested waves. It is not related to the Benjamin - Feir instability, but is a result of complex contribution from nonlinear combination harmonics, mainly cubic in nonlinearity. The discovered asymmetry can lead to remarkably different estimates of the rogue wave probability based on either down- or up-zero-crossing methods for individual wave selection, commonly used in the oceanography.

Ubaldo Jorge Augusto de Filipe André, Ana Paula Sarmento do Santos, Onelis Portuondo Savón et al.

Context: Today, quite a few environmental problems require swift responses toward adjustment, mitigation, and sustainability. Accordingly, how could university students acquire effective environmental education so they can play their social roles in balance with environmental protection? Aim: To recommend methodological actions to contribute to student education at the Faculty of Natural Sciences, the University of Namibe, Angola. Methods: Consequently, this study took from qualitative methods of social research. Methods and techniques, such as analysis-synthesis, inductive-deductive, and documentary review for processing information about environmental education and climate change in university education. Results: Five methodological guidelines for environmental education were established. They were inserted in subject Physics II, in the first year of the Marine Biology Bachelor Degree, with six general actions that link theory and practice, through the teaching process in the degrees of Oceanography, Marine Biology, and Marine Resources. The study demonstrated the fulfillment of learning objectives related to Sustainable Development Goals No. 13 and 14, based on UNESCO (2017) guidelines. Conclusions: There is a potential for students to acquire environmental information through methodological actions by the staff, in terms of subject preparation at the Faculty of Natural Sciences, the University of Namibe.

Maxime Beauchamp, Quentin Febvre, Hugo Georgentum et al.

The reconstruction of sea surface currents from satellite altimeter data is a key challenge in spatial oceanography, especially with the upcoming wide-swath SWOT (Surface Ocean and Water Topography) altimeter mission. Operational systems however generally fail to retrieve mesoscale dynamics for horizontal scales below 100km and time-scale below 10 days. Here, we address this challenge through the 4DVarnet framework, an end-to-end neural scheme backed on a variational data assimilation formulation. We introduce a parametrization of the 4DVarNet scheme dedicated to the space-time interpolation of satellite altimeter data. Within an observing system simulation experiment (NATL60), we demonstrate the relevance of the proposed approach both for nadir and nadir+swot altimeter configurations for two contrasted case-study regions in terms of upper ocean dynamics. We report relative improvement with respect to the operational optimal interpolation between 30% and 60% in terms of reconstruction error. Interestingly, for the nadir+swot altimeter configuration, we reach resolved space-time scales below 70km and 7days. The code is open-source to enable reproductibility and future collaborative developments. Beyond its applicability to large-scale domains, we also address uncertainty quantification issues and generalization properties of the proposed learning setting. We discuss further future research avenues and extensions to other ocean data assimilation and space oceanography challenges.

Ruochu Yang, Mengxue Hou, Chad Lembke et al.

This paper utilizes an anomaly detection algorithm to check if underwater gliders are operating normally in the unknown ocean environment. Glider pilots can be warned of the detected glider anomaly in real time, thus taking over the glider appropriately and avoiding further damage to the glider. The adopted algorithm is validated by two valuable sets of data in real glider deployments, the University of South Florida (USF) glider Stella and the Skidaway Institute of Oceanography (SkIO) glider Angus.

Luka Schlegel, Volker Schulz

Adjoint-based shape optimization most often relies on Eulerian flow field formulations. However, since Lagrangian particle methods are the natural choice for solving sedimentation problems in oceanography, extensions to the Lagrangian framework are desirable. For the mitigation of coastal erosion, we perform shape optimization for fluid flows, that are described by Lagrangian shallow water equations and discretized via smoothed particle hydrodynamics. The obstacle's shape is hereby optimized over an appropriate cost function to minimize the height of water waves along the shoreline based on shape calculus. Theoretical results will be numerically verified by exploring different scenarios.

A. R. C. Buarque, W. S. Dias, F. A. B. F. de Moura et al.

Rogue waves are rapid and unpredictable events of exceptional amplitude reported in various fields, such as oceanography and optics, with much of the interest being targeted towards their physical origins and likelihood of occurrence. Here, we use the all-round framework of discrete-time quantum walks to study the onset of those events due to a random phase modulation, unveiling its long-tailed statistics, distribution profile, and dependence upon the degree of randomness. We find that those rogue waves belong the Gumbel family of extreme value distributions.

Francisco Yanez-Lemus, Rubén Moraga, Carlos T. Smith et al.

Lactic acid bacteria (LAB), obtained from rainbow trout (<i>Oncorhynchus mykiss</i>) intestine, were cultured in MRS medium and probiotic candidates. Concurrently, producers of elemental selenium nanoparticles (Se⁰Nps) were selected. Probiotic candidates were subjected to morphological characterization and the following tests: antibacterial activity, antibiotic susceptibility, hemolytic activity, catalase, hydrophobicity, viability at low pH, and tolerance to bile salts. Two LAB strains (S4 and S14) satisfied the characteristics of potential probiotics, but only strain S14 reduced selenite to biosynthesize Se⁰Nps. S14 strain was identified, by 16S rDNA analysis, as <i>Lactiplantibacillus plantarum</i>. Electron microscopy showed Se⁰Nps on the surface of S14 cells. Rainbow trout diet was supplemented (10⁸ CFU g⁻¹ feed) with Se⁰Nps-enriched <i>L. plantarum</i> S14 (LABS14-Se⁰Nps) or <i>L. plantarum</i> S14 alone (LABS14) for 30 days. At days 0, 15, and 30, samples (blood, liver, and dorsal muscle) were obtained from both groups, plus controls lacking diet supplementation. Fish receiving LABS14-Se⁰Nps for 30 days improved respiratory burst and plasmatic lysozyme, (innate immune response) and glutathione peroxidase (GPX) (oxidative status) activities and productive parameters when compared to controls. The same parameters also improved when compared to fish receiving LABS14, but significant only for plasmatic and muscle GPX. Therefore, Se⁰Nps-enriched <i>L. plantarum</i> S14 may be a promising alternative for rainbow trout nutritional supplementation.

Novikov V. Yu., Rysakova K. S., Baryshnikov A. V.

It is well known that fish belonging to the Salmonidae family differ in their nutritional value. Anatomical and morphological features of different salmon species have a certain similarity; therefore, representatives of this family are most often falsified. Assortment falsification of products from fish of this family is usually carried out by replacing more valuable species with cheaper ones with a reduced nutritional value. Most often, counterfeiting of Atlantic salmon (salmon) by Far Eastern ones (chum salmon, pink salmon, chinook salmon, coho salmon) is found. Near infrared spectroscopy (NIR) is now increasingly used for identification and authentication of closely related organisms, in some cases being a rapid method replacing genetic analysis. We have obtained diffusion reflectance spectra of NIR radiation for three species of fish from the Northern Basin belonging to the salmon family. The best classification by fish species has been obtained by analyzing the NIR spectra of pre-dried fat-free muscle tissue samples. In case of wet samples, the observed differences are less significant, up to insignificant differences in individual values from neighboring clusters. The possibility of using the method of linear discriminant analysis of the NIR reflection spectra of muscle proteins for the species identification of fish has been shown.

Zigeng Song, Yan Bai, Difeng Wang et al.

With the implementation of the 2018–2020 Clean Air Action Plan (CAAP) the and impact from COVID-19 lockdowns in 2020, air pollution emissions in central and eastern China have decreased markedly. Here, by combining satellite remote sensing, re-analysis, and ground-based observational data, we established a machine learning (ML) model to analyze annual and seasonal changes in primary air pollutants in 2020 compared to 2018 and 2019 over central and eastern China. The root mean squared errors (RMSE) for the PM_2.5, PM₁₀, O₃, and CO validation dataset were 9.027 μg/m³, 20.312 μg/m³, 10.436 μg/m³, and 0.097 mg/m³, respectively. The geographical random forest (RF) model demonstrated good performance for four main air pollutants. Notably, PM_2.5, PM₁₀, and CO decreased by 44.1%, 43.2%, and 35.9% in February 2020, which was likely influenced by the COVID-19 lockdown and primarily lasted until May 2020. Furthermore, PM_2.5, PM₁₀, O₃, and CO decreased by 16.4%, 24.2%, 2.7%, and 19.8% in 2020 relative to the average values in 2018 and 2019. Moreover, the reduction in O₃ emissions was not universal, with a significant increase (~20–40%) observed in uncontaminated areas.