Hasil untuk "Oceanography"

Jake Spisak, Christopher P. Riedel, Andrey Sushko et al.

WindBorne Systems has developed a constellation of long-duration atmospheric balloons to collect meteorological data across the globe, filling gaps in current in-situ data collection methods. Each Global Sounding Balloon (GSB) is capable of flying for weeks or months and performing dozens of soundings while measuring pressure, temperature, humidity, and GNSS-derived position, altitude, and wind velocity. This data is transmitted to ground via satellite, processed, and made available within minutes of being collected. The current meteorological sensor package has remained largely unchanged since mid-2024 and has flown on thousands of GSBs totaling over one million hours of flight time. Here we present the design and performance of this sensor package. The custom readout architecture and housing allow for data collection across nearly all in-flight conditions while minimizing sources of bias and noise. Uncertainty is characterized via sounding reproducibility studies and in-house calibration of pressure, humidity, and temperature sensors. The calibration and data processing procedures have been optimized and validated by comparison with external datasets. We present external validation in the form of 1) side-by-side radiosonde launches performed in collaboration with the Center for Western Weather and Water Extremes at the Scripps Institution of Oceanography, which show agreement within expected uncertainty limits, and 2) intercomparison studies with European Centre for Medium-Range Weather Forecasts Reanalysis v5, which show an aggregate root mean square difference of: Geopotential height -- 14 m; Pressure -- 0.36 hPa; Temperature -- 0.91 K; Wind speed u -- 2.45 m/s; Wind speed v -- 2.50 m/s; Relative humidity -- 13%.

Pascal Meurer, Sebastian Buschow, Svenja Szemkus et al.

The increasing occurrence of extreme weather events since the beginning of the 21st century has led to the development of new methods to attribute extreme events to anthropogenic climate change. How the extreme event is defined has a major influence on the attribution result. A frequently disregarded or evaded aspect concerns the temporal dependence and the clustering of extremes. This study presents an approach for attributing complete time series during extreme events to anthropogenic forcing. The approach is based on a non-stationary Markov process using bivariate extreme value theory to model the temporal dependence of the time series. We calculate the likelihood ratio of an observational time series from ERA5 given the distributions as estimated from CMIP6 simulations with historical natural-only and natural and anthropogenic forcing scenarios. The spatial fields are condensed by the extremal pattern index as a compact description of spatial extremes. In addition, the study examines the extent to which attribution statements about the occurrence of extreme heat events change when the effect of the mean warming is eliminated. The resulting attribution statement provides very strong evidence for the scenario with anthropogenic drivers over Europe, especially since the beginning of the 21st century. For central and southern Europe, the influence of anthropogenic greenhouse gas emissions on heatwaves could already have been proven in the 1970s using today's methods. There is no reliable signal apart from a general increase in temperature, neither in terms of the temporal dependence of extreme heat days nor in terms of the shape of the extreme value distribution.

Béatrice Lessard-Hamel, Marcel Babin, Simon Thibault

Sea ice harbours a rich community of well-adapted microorganisms that inhabit liquid micro-spaces where extreme conditions prevail. Currently at risk under climate change, the sea-ice microbiome holds mysteries about evolution of life on Earth and possibly elsewhere, which require methodological innovation to be unravelled. Gaining microscopic insight into the internal structure and biology of sea ice has traditionally been limited to destructive and extrusive ice core sampling methods. Here we present an in situ microscopic imaging system to observe undisturbed living microorganisms directly within sea the ice matrix. The complex and heterogeneous nature of sea ice, including its water crystal lattice, brine channels, air bubbles, and various impurities, presents engineering challenges for the development of this imaging system. Despite the fragile nature of the sea-ice matrix, we could successfully deploy, test and use the new in situ microscope during a recent expedition on the icepack in Arctic. We collected numerous images of live and intact single-celled and colony-forming diatoms, and documented for the first time at such a high resolution some microphysical features of sea ice. The hardware and software design of the endoscope is presented along with acquisition results of the microstructure and diatom images. These findings collectively demonstrate the potential for this new in situ microscopic imaging system to transform the way we study sea ice and to allow a deeper understanding of its complex microstructure and living microorganisms.

Nicolas Raillard, Coline Poppeschi, Tessa Chevallier et al.

The rapid expansion of the French offshore wind sector requires a critical reassessment of structural durability in the face of evolving marine conditions driven by climate change. Traditional design methodologies, which rely on the assumption of stationary environmental conditions, are no longer adequate. This study introduces a novel statistical framework to assess future changes in significant wave height by employing non-stationary Generalized Extreme Value (GEV) models applied to monthly maxima. This approach aims to reduce uncertainty and provide robust design tools adapted to the non-stationary conditions of the future. Based on CMIP6 climate models and reanalysis data, results reveal a projected trend towards a more pronounced seasonal contrast along the French Atlantic and English Channel coasts under future scenarios (SSP1-2.6 and SSP5-8.5), whereas the French Mediterranean Sea exhibits results that are more difficult to interpret, due to a weaker increase of extremes and large uncertainties (inter-model spread). Projections indicate more intense winters and calmer summers, along with a shift in the seasonal cycle. Overall, the multi-model ensemble suggests an increase in the design levels for extreme sea states. The research concludes by defining a new methodology for calculating an equivalent design level over the structure's operational lifespan. This tool is deemed essential for ensuring the resilience and economic viability of future offshore wind farms in a changing climate.

Uxue Uribe-Martinez, Leire Mijangos, Juan F. Ayala-Cabrera et al.

The occurrence and spatial distribution of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), fragrances, UV filters and photoinitiators were investigated in surface sediments of Nerbioi-Ibaizabal estuary between 2005 and 2013, in 2020. Samples were extracted by focused ultrasound solid–liquid extraction technique and analyzed by gas chromatography coupled with mass spectrometry. Total PAHs, PCBs, OCPs, musks, UV filters and photoinitiators concentrations ranged between not detected (n.d.) and 43000 ng g⁻¹, n.d. and 2500 ng g⁻¹, n.d. and 820 ng g⁻¹, n.d. and 880 ng g⁻¹, n.d. and 91 ng g⁻¹ and from nd to 120 ng g⁻¹, respectively. Hexachlorocyclohexanes (HCHs) were ubiquitous in the estuary, suggesting that these compounds, although banned, leach from landfills. The PCB concentrations showed a decreasing trend. Ecological risk assessments based on sediment quality guidelines (SQGs) and risk quotient (RQ) suggested semi-volatile organic compounds could represent a potential ecological risk in the Nerbioi-Ibaizabal estuary.

Ziqi Ji, Gang Du, Penghao Duan

Vortex flows are ubiquitous in both natural processes and engineering applications, including phenomena such as typhoons, water currents, and aerospace fluid dynamics. The vortex particle method, a computational approach grounded in vortex dynamics, has been extensively applied in aerodynamics, oceanography, turbulence, and aeroacoustics. With the recent introduction of machine learning into computational fluid dynamics, a hybrid framework known as the differentiable vortex particle method (DVPM) has been proposed, which integrates the vortex particle method with deep learning to enable efficient learning and prediction. However, the original formulation of DVPM is limited to ideal vortex flow conditions, such as inviscid flows without non-conservative body forces, which significantly restricts its practical applicability. In this study, we extend the differentiable vortex particle method beyond idealized flow scenarios to encompass more realistic, non-ideal conditions, including viscous flow and flow subjected to non-conservative body forces. We establish the Lamb-Oseen vortex as a benchmark case, representing a fundamental viscous vortex flow in fluid mechanics. This selection offers significant analytical advantages, as the Lamb-Oseen vortex possesses an exact analytical solution derived from the Navier-Stokes (NS) equations, thereby providing definitive ground truth data for training and validation purposes. Through rigorous evaluation across a spectrum of Reynolds numbers, we demonstrate that DVPM achieves superior accuracy in modeling the Lamb-Oseen vortex compared to conventional convolutional neural networks (CNNs) and physics-informed neural networks (PINNs). Our results substantiate DVPM's robust capabilities in modeling non-ideal vortex flows, establishing its distinct advantages over contemporary deep learning methodologies in fluid dynamics applications.

Mingi Jeong, Cristian Molinaro, Tonmoay Deb et al.

This paper addresses the problem of both actively searching and tracking multiple unknown dynamic objects in a known environment with multiple cooperative autonomous agents with partial observability. The tracking of a target ends when the uncertainty is below a threshold. Current methods typically assume homogeneous agents without access to external information and utilize short-horizon target predictive models. Such assumptions limit real-world applications. We propose a fully integrated pipeline where the main contributions are: (1) a time-varying weighted belief representation capable of handling knowledge that changes over time, which includes external reports of varying levels of trustworthiness in addition to the agents; (2) the integration of a Long Short Term Memory-based trajectory prediction within the optimization framework for long-horizon decision-making, which reasons in time-configuration space, thus increasing responsiveness; and (3) a comprehensive system that accounts for multiple agents and enables information-driven optimization. When communication is available, our strategy consolidates exploration results collected asynchronously by agents and external sources into a headquarters, who can allocate each agent to maximize the overall team's utility, using all available information. We tested our approach extensively in simulations against baselines, and in robustness and ablation studies. In addition, we performed experiments in a 3D physics based engine robot simulator to test the applicability in the real world, as well as with real-world trajectories obtained from an oceanography computational fluid dynamics simulator. Results show the effectiveness of our method, which achieves mission completion times 1.3 to 3.2 times faster in finding all targets, even under the most challenging scenarios where the number of targets is 5 times greater than that of the agents.

Philipp Ertz, Petra Friederichs

The aim of this study is to provide a probabilistic gust analysis for the region of Germany that is calibrated with station observations and with an interpolation to unobserved locations. To this end, we develop a spatial Bayesian hierarchical model (BHM) for the post-processing of surface maximum wind gusts from the COSMO-REA6 reanalysis. Our approach uses a non-stationary extreme value distribution for the gust observations, with parameters that vary according to a linear model using COSMO-REA6 predictor variables. To capture spatial patterns in surface wind gust behavior, the regression coefficients are modeled as 2-dimensional Gaussian random fields with a constant mean and an isotropic covariance function that depends on the distance between locations. In addition, we include an elevation offset in the distance metric for the covariance function to account for the topography. This allows us to include data from mountaintop stations in the training process. The training of the BHM is carried out with an independent data set from which the data at the station to be predicted are excluded. We evaluate the spatial prediction performance at the withheld station using Brier score and quantile score, including their decomposition, and compare the performance of our BHM to climatological forecasts and a non-hierarchical, spatially constant baseline model. This is done for 109 weather stations in Germany. Compared to the spatially constant baseline model, the spatial BHM significantly improves the estimation of local gust parameters. It shows up to 5 % higher skill for prediction quantiles and provides a particularly improved skill for extreme wind gusts. In addition, the BHM improves the prediction of threshold levels at most of the stations. Although a spatially constant approach already provides high skill, our BHM further improves predictions and improves spatial consistency.

John R. Dolan

Per Theodor Cleve is known as a 19th century chemist, credited with discovery of two rare-earth elements. However, throughout his distinguished career as a chemist, he was also a protistologist. From 1863 to 1905, Cleve published prodigiously on protists, authoring over 70 works totaling about 2,500 pages, and he described numerous taxa, especially from the marine plankton. Notably, many of Cleve's works are still cited today. His work concerning the utility of certain protist species in characterizing water masses has been recognized in histories of Oceanography. However, Cleve is not a familiar name to many of us, as he has been consistently overlooked in histories of protistology. Here, first Cleve's life is summarized, and then his contributions to protistology, and oceanography, are reviewed to show his significant, and neglected, contributions to the fields.  

Mahir Tajwar, Mahfuzur Rahman, Mahmudul Hasan et al.

Groundwater quality is under increasing threat in rapidly urbanizing Southeast Asian megacities, where unregulated expansion and industrial activity are altering subsurface geochemical conditions. In Dhaka, Bangladesh, groundwater serves as a crucial source of potable water for millions, necessitating rigorous assessment of its suitability for human and agricultural use. This research seeks to comprehensively assess the hydrogeochemical characteristics of shallow groundwater, evaluating its suitability for both drinking and irrigation purposes using a combined approach of geochemical methods, multivariate statistical analyses, and geospatial techniques. The hydrogeochemical analysis of 15 groundwater samples revealed a cation order of Ca2 + > Na+ > Mg2+ > K+ and an anion order of HCO3− > Cl− > SO42− > NO3−. The primary objective of this research is to assess the hydrogeochemical characteristics and water quality of shallow groundwater in Dhaka using a combination of graphical techniques, multivariate statistical analyses, and water quality indices. Fifteen groundwater samples were collected during the dry season and analyzed for major cations and anions. Piper, Gibbs, Durov, and Stiff diagrams were employed to identify dominant processes. Principal Component Analysis (PCA) and hierarchical clustering were used to distinguish geogenic and anthropogenic influences. Results revealed that groundwater is dominated by the calcium bicarbonate type, with cation order Ca²⁺ > Na⁺ > Mg²⁺ > K⁺ and anion order HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻. Cation exchange and silicate weathering were identified as the significant processes influencing water chemistry. PCA revealed that three principal components accounted for 86.4 % of the variance, indicating the influence of both natural mineral dissolution and localized anthropogenic inputs. According to the Water Quality Index (WQI), 5 samples were excellent, 6 were good, and 4 were poor for drinking purposes. All samples were suitable for irrigation based on SAR, RSC, SSP, EC, and TDS values. These findings provide a robust baseline for groundwater quality monitoring in Dhaka and similar urban areas. The integrated methodology can guide policy decisions on water resource protection and help communities prioritize safe groundwater use for both domestic and agricultural needs. The study offers valuable information for assessing water quality, monitoring contamination risks, and developing groundwater management strategies, particularly in rapidly urbanizing regions of Southeast Asia.

Qi Zhou, Jinghua Li, Xiaoyuan Wu et al.

Modular shipbuilding, as a cutting-edge ship construction paradigm, enables parallel manufacturing across workshops and stages—a core advantage that significantly shortens the total shipbuilding cycle, making it pivotal for modern shipyards to enhance productivity. However, this mode decomposes the integrated shipbuilding project into a large number of interdependent sub-activities spanning three key stages (fabrication, logistics, and assembly). Further, the duration of these sub-activities is inherently uncertain, primarily due to the extensive manual operations, variable on-site conditions, and supply chain fluctuations inherent in shipbuilding. These characteristics collectively pose a formidable challenge to project planning that pursues both high efficiency and low cost. To address this challenge, this paper proposes a Strategy-Group Evolution algorithm. First, the modular shipbuilding process scheduling problem is mathematically formulated as a resource-constrained three-stage multi-objective optimization model, where triangular fuzzy numbers are employed to characterize the uncertain sub-activity durations. Second, a two-layered Strategy-Group Evolution algorithm is designed for solving this model: the inner layer comprises 12 practical priority rules tailored to modular shipbuilding’s multi-stage features, while the outer layer adopts a genetic algorithm-based evolution policy to schedule and optimize the assignment of inner-layer rules to activity groups. The core of the Strategy-Group Evolution algorithm lies in dynamically assigning suitable strategies to different activity groups and evolving these assignments toward optimality—this avoids the limitation of a single priority rule for all stages, thereby facilitating the search for global optimal solutions. Finally, validation tests on real cruise ship construction projects and benchmark datasets demonstrate the efficacy and superiority of the proposed Strategy-Group Evolution algorithm.

Siqing Guo, Yubing Wang, Mingyuan Yue et al.

While battery-powered propulsion represents a promising pathway for inland waterway freight, its widespread adoption is hindered by range anxiety and high investment costs. Strategic energy replenishment has emerged as a critical and cost-effective solution to extend voyage endurance and mitigate these barriers. This paper introduces a novel approach to optimize energy replenishment strategies for inland electric ships that considers the possibility of adopting multiple technologies (charging and battery swapping) and partial replenishment. The proposed approach not only identifies optimal replenishment ports but also determines the technology to employ and the corresponding amount of energy to replenish for each operation, aimed at minimizing total replenishment costs. This problem is formulated as a mixed-integer linear programming model. A case study of a 700-TEU electric container ship operating on two routes along the Yangtze River validates the effectiveness of the proposed approach. The methodology demonstrates superior performance over existing approaches by significantly reducing replenishment costs and improving solution feasibility, particularly in scenarios with tight schedules and limited technology availability. Furthermore, a sensitivity analysis examines the impacts of key parameters, offering valuable strategic insights for industry stakeholders.

Louis-Alexandre Couston

The meltwater mixing line (MML) model provides a theoretical prediction of near-ice water mass properties that is useful to compare with observations. If oceanographic measurements reported in a temperature-salinity diagram overlap with the MML prediction, then it is usually concluded that the local dynamics are dominated by the turbulent mixing of an ambient water mass with nearby melting ice. While the MML model is consistent with numerous observations, it is built on an assumption that is difficult to test with field measurements, especially near the ice boundary, namely that the effective (turbulent and molecular) salt and temperature diffusivities are equal. In this paper, this assumption is tested via direct numerical simulations of a canonical model for externally-forced ice-ocean boundary layers in a uniform ambient. We focus on the well-mixed regime by considering an ambient temperature close to freezing and run the simulations until a statistical steady state is reached. The results validate the assumption of equal effective diffusivities across most of the boundary layer. Importantly, the validity of the MML model implies a linear correlation between the mean salinity and temperature profiles normal to the interface that can be leveraged to construct a reduced ice-ocean boundary layer model based on a single scalar variable called thermal driving. We demonstrate that the bulk dynamics predicted by the reduced thermal driving model are in good agreement with the bulk dynamics predicted by the full temperature-salinity model. Then, we show how the results from the thermal driving model can be used to estimate the interfacial heat and salt fluxes, and the melt rate.

Barra Muzaffar Widayat, Delianis Pringgenies, Wilis Ari Setyati

This study aims to explore biosynthetic gene clusters and antibacterial activity in mangrove sediment bacteria at Tirang Beach, Semarang, Central Java. Research methods include isolating bacteria from seagrass sediments, antibacterial testing against S. aureus and E. coli bacteria, identifying bacteria using the DNA method, and testing the presence of biosynthetic gene clusters. The results showed that the mangrove sediment bacterial isolate with the isolate code B.26.ST.3.4 had the highest antibacterial activity with a value of 28.05 ± 0.9192 against the pathogen E. coli and 23.45 ± 10.2530 against the pathogen S. aureus. Apart from that, there are two other isolates that also have antibacterial activity. Based on bacterial DNA identification, mangrove sediment bacteria that have potential as antibacterials are Bacillus velezensis (B.9.ST.1.4), Bacillus subtilis (B.13.ST.2.2), and Bacillus amyloliquefaciens (B.26.ST.3.4). These three isolates have the NRPS gene, and isolate B.9.ST.1.4 also has the PKS-II gene, while isolate B.26.ST.3.4 has the PKS-I gene. This discovery provides a deeper understanding of the antibacterial potential of mangrove sediment bacteria at Tirang Beach, Semarang. This information can be used to develop natural antibiotics that are more effective and have the potential to fight bacterial infections that are increasingly resistant to conventional antibiotics. The conclusion is that bacteria have potential as antibacterials from mangrove sediment bacteria at Tirang Beach, Semarang through isolation and identification of bacteria. Isolate B.26.ST.3.4 has the highest antibacterial activity against E. coli and S. aureus pathogens. Apart from that, Bacillus velezensis, Bacillus subtilis, and Bacillus amyloliquefaciens also have antibacterial potential. The NRPS gene was found in all three isolates, while isolate B.9.ST.1.4 also had the PKS-II gene and isolate B.26.ST.3.4 had the PKS-I gene. This discovery can provide a deeper understanding of the natural antibiotic potential of mangrove sediment bacteria and can be the basis for further development in the pharmaceutical field.     Penelitian ini bertujuan untuk mengeksplorasi klaster gen biosintesis dan aktivitas antibakteri pada bakteri sedimen mangrove di Pantai Tirang, Semarang, Jawa Tengah. Metode penelitian meliputi isolasi bakteri dari sedimen lamun, uji antibakteri terhadap bakteri S. aureus dan E. coli, identifikasi bakteri dengan metode DNA, dan uji keberadaan klaster gen biosintesis. Hasil penelitian menunjukkan bahwa isolat bakteri sedimen mangrove dengan kode isolat B.26.ST.3.4 memiliki aktivitas antibakteri tertinggi dengan nilai 28,05±0,9192 terhadap patogen E. coli dan 23,45±10,2530 terhadap patogen S. aureus. Selain itu, terdapat dua isolat lain yang juga memiliki aktivitas antibakteri Berdasarkan identifikasi bakteri DNA, bakteri sedimen mangrove yang potensial sebagai antibakteri adalah Bacillus velezensis (B.9.ST.1.4), Bacillus subtilis (B.13.ST.2.2), dan Bacillus amyloliquefaciens (B.26.ST.3.4). Ketiga isolat ini memiliki gen NRPS, dan isolat B.9.ST.1.4 juga memiliki gen PKS-II, sedangkan isolat B.26.ST.3.4 memiliki gen PKS-I. Penemuan ini memberikan pemahaman yang lebih dalam tentang potensi antibakteri dari bakteri sedimen mangrove di Pantai Tirang Semarang. Informasi ini dapat digunakan untuk mengembangkan antibiotik alami yang lebih efektif dan memiliki potensi dalam melawan infeksi bakteri yang semakin resisten terhadap antibiotik konvensional. Kesimpulan bahwa bakteri potensi sebagai antibakteri dari bakteri sedimen mangrove di Pantai Tirang, Semarang melalui isolasi dan identifikasi bakteri. Isolat B.26.ST.3.4 memiliki aktivitas antibakteri tertinggi terhadap patogen E. coli dan S. aureus. Selain itu, Bacillus velezensis, Bacillus subtilis, dan Bacillus amyloliquefaciens juga memiliki potensi sebagai antibakteri. Gen NRPS ditemukan pada ketiga isolat tersebut, sedangkan isolat B.9.ST.1.4 juga memiliki gen PKS-II dan isolat B.26.ST.3.4 memiliki gen PKS-I. Penemuan ini dapat memberikan pemahaman yang lebih dalam tentang potensi antibiotik alami dari bakteri sedimen mangrove dan dapat menjadi dasar untuk pengembangan lebih lanjut dalam bidang farmasi.

Yuan Wang, Zhenbin Du

This paper studies the trajectory tracking issue for an underactuated autonomous underwater vehicle (AUV) in the horizontal plane. The desired velocity–tracking error relationship (DVTER) is constructed according to the kinematics and kinetic equation, which means that the expected velocities are built so that the position tracking errors converge to 0. Moreover, the limitation of obtaining the expected velocity by directly differentiating the desired position values is avoided. Then, the nonsingular fast terminal sliding mode (TSM) controller is developed to ensure that the velocities converge to the designed expected values in finite time, and tracking speed is improved by comparing with the traditional nonsingular terminal sliding mode method. It turns out that the expected trajectory can be tracked by an underactuated AUV. Finally, the efficiency of the constructed control mechanism is confirmed by simulation results.

Wenda Zhang, Christopher L. P. Wolfe

Abstract Mixing along isopycnals plays an important role in the transport and uptake of oceanic tracers. Isopycnal mixing is commonly quantified by a tracer diffusivity. Previous studies have estimated the tracer diffusivity using the rate of dispersion of surface drifters, subsurface floats, or numerical particles advected by satellite‐derived velocity fields. This study shows that the diffusivity can be more efficiently estimated from the dispersion of coherent mesoscale eddies. Coherent eddies are identified and tracked as the persistent sea surface height extrema in both a two‐layer quasigeostrophic (QG) model and an idealized primitive equation (PE) model. The Lagrangian diffusivity is estimated using the tracks of these coherent eddies and compared to the diagnosed Eulerian diffusivity. It is found that the meridional coherent eddy diffusivity approaches a stable value within about 20–40 days in both models. In the QG model, the coherent eddy diffusivity is a good approximation to the upper‐layer tracer diffusivity in a broad range of flow regimes, except for small values of bottom friction or planetary vorticity gradient, where the motions of same‐sign eddies are correlated over long distances. In the PE model, the tracer diffusivity has a complicated vertical structure and the coherent eddy diffusivity is correlated with the tracer diffusivity at the e‐folding depth of the energy‐containing eddies where the intrinsic speed of the coherent eddies matches the rms eddy velocity. These results suggest that the oceanic tracer diffusivity at depth can be estimated from the movements of coherent mesoscale eddies, which are routinely tracked from satellite observations.

Thomas Röckmann, Maarten van Herpen, Chloe Brashear et al.

The reaction of CH _4 with chlorine (Cl) radicals in the atmosphere is associated with an extraordinarily strong isotopic fractionation, where ^12 CH _4 reacts about 70 ‰ faster with Cl than ^13 CH _4 . Therefore, although the Cl-based sink of CH _4 constitutes only a small contribution to its total removal rate, the uncertainty in this small sink has been identified as one of the two largest uncertainties of isotope-based CH _4 source apportionment at the global scale. The uncertainty arises from the fact that Cl levels in the atmosphere are so low that they cannot be detected directly. One very sensitive indirect method to identify and quantify the CH _4 + Cl reaction in the atmosphere is the detection of the extremely ^13 C-depleted reaction product carbon monoxide (CO) from this reaction. This article reviews the concept of this approach, its successful application in the atmosphere, its challenges and opportunities for identifying and quantifying Cl-based removal of CH _4 at the regional and global scale and its potential to detect and evaluate possible attempts to enhance CH _4 removal from the atmosphere.

Hans van Haren

The propagation of inertio-gravity waves (IGW) into the deep-sea is relevant for energy transfer to turbulence where waves break, and thus for redistribution of nutrients, oxygen and suspended matter. In constant stratification, vertical IGW-propagation is readily modelled. In varying stratification, where homogeneous layers alternate with stratified layers, transmission and reflection cause complex patterns. Half-year long moored acoustic Doppler current profiler (ADCP) observations midway between the Balearic Islands and Sardinia in the 2800-m deep Western-Mediterranean Sea occasionally demonstrate a distinct transition, between weakly stratified (N>=2f) and homogeneous (N=<f) layers, of IGW at near-inertial frequencies. Here, N denotes the buoyancy frequency and f the local inertial frequency (vertical Coriolis parameter). The transition in stratification is rather abrupt, within Deltaz=25 m and provides an amplitude-reduction of 1.3 for super-inertial motions. Simulations with non-traditional momentum equations involving the horizontal Coriolis parameter fh qualitatively confirm observed IGW-refraction. The observational area is marked by variations in hydrographic characteristics, with abundant mesoscale eddies to the south and dense-water formation to the north of the site during the previous winter. Thus, also transitions occur from deep homogeneous layers into deeper, recently formed stratified ones. Polarization spectra of shear are bound by IGW-limits related to N=f, while current-polarization to 2fh. These frequencies coincide with large-scale buoyancy frequencies independently observed in various layers using shipborne CTD-profiling.

G. Fu, Z.‐S. Wang, X.‐Y. Zhang et al.

Abstract The fundamental features of one kind of rarely known stratocumulus, which was termed as “Millipede Cloud,” occurred over the Eastern Pacific Ocean in 2017 were first documented by using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. These clouds had long and meandering “central axes” extending from several hundreds to thousands kilometers, and a number of “radical cloud arms” extending several tens of kilometers in its two sides. Total 59 “Millipede Clouds,” 4 and 55 of them, were formed over the Northern and the Southern Hemispheres, respectively. Their environmental backgrounds were analyzed by using ERA5 reanalysis data and MODIS sensor Level‐2 data. The cloud top pressures of these “Millipede Clouds” were between 850 and 800 hPa, and their top heights were about 1–2 km. There existed “inversion layer” of air temperature near the cloud tops at 800 hPa, which strongly suggested that these clouds were lower stratocumulus in essence.

Lauren A. Bolotin, Betsy M. Summers, Philip Savoy et al.

Abstract Freshwater salinization of rivers is occurring across the globe because of nonpoint source loading of salts from anthropogenic activities such as agriculture, urbanization, and resource extraction that accelerate weathering and release salts. Multidecadal trends in river salinity are well characterized, yet our understanding of annual regimes of salinity in rivers draining diverse central and western U.S. landscapes and their associated catchment attributes is limited. We classified annual salinity regimes in 242 stream locations through dynamic time warping and fuzzy c‐medoids clustering of salinity time series. We found two dominant regimes in salinity characterized by an annual summer–fall peak or spring decline. Using random forest regression, we found that precipitation amount, stream slope, and soil salinity were the most important predictors of salinity regime classification. Advancing our understanding of salinity regimes in rivers will improve our ability to predict and mitigate the effects of salinization in freshwater ecosystems through management interventions.