Sea State Research Articles

Biotic transformation of methylmercury at the onset of the Arctic spring bloom

Despite the lack of local anthropogenic mercury sources, methylated mercury (MeHg) concentrations in Arctic biota are higher than in biota from lower latitudes. The main entry route occurs during the bioconcentration of seawater monomethylmercury (MMHg) into phytoplankton. Despite the known seasonal changes in biological activity in the region, little is known about the seasonal cycling of total mercury (THg) and MeHg in the Arctic Ocean. Here, we report the concentrations of THg and MeHg in seawater sampled from the northwestern Barents Sea water column during late winter and spring. In the upper 500 m, the THg concentrations are significantly higher in spring (0.64 ± 0.09 pmol L-1) compared to late winter (0.53 ± 0.07 pmol L-1), driven by seasonal inputs to surface waters from atmospheric deposition and the dynamics of changing sea ice conditions. Contrastingly, the MeHg concentrations in spring were significantly lower (41 ± 39 fmol L-1) compared to late winter (85 ± 42 fmol L-1). We suggest that most MeHg is biotically demethylated by both phytoplankton and bacteria, with additional losses from photodemethylation and evasion. Our observations highlight the importance of demethylation during potential uptake of methylmercury coinciding with the Arctic spring bloom. Lastly, we use our new data together with previously published seasonal data in the region to construct a simplified seasonal mercury cycle in an Arctic marginal ice zone.

A generating absorbing boundary condition for simulating wave interaction with maritime structures in current or at forward speed

The lack of suitable boundary conditions in practical surface wave simulations with maritime structures in current or at forward speed may cause energy in the computational domain to accumulate due to spurious wave reflection. The common way to prevent wave reflection is to use passive wave absorbers, such as damping zones or relaxation zones, which requires larger domains at the cost of computational effort. Our goal is to derive a local generating absorbing boundary condition (GABC) for long-crested irregular waves on top of a mean flow, using the flow to model the forward speed of a structure such as a ship. Earlier work has demonstrated that a local GABC for free surface waves has a performance similar to passive wave absorbers, but at a reduced computational effort. New in the present work is that we extend, verify and validate the GABC in the presence of a nonzero mean flow. The GABC is designed to be accurate for a range of wave components in irregular sea states, with the resulting reflection coefficients for each component lower than a chosen value, say 5%. Having used potential flow theory for its derivation means that the boundary should not be placed at the exact location where wave breaking is expected, such as very close to the structure in the domain, or in the surf zone in coastal modeling. For the application with ships in this article that does not pose a limitation. The performance is demonstrated for a range of dimensionless wave number between 0 and 6. Such a boundary condition is obtained through a rational approximation of the linear dispersion relation with a mean flow, in combination with vertical derivatives of the solution variables along the boundary. Local linearization means that the GABC incorrectly considers bound, nonlinear wave components to be freely propagating wave components. Bound components, however, tend to have smaller amplitudes and do not appear to affect performance for the considered cases. Results of simulations with regular and irregular waves, on top of flows with different magnitudes and directions, are found to agree with the theory. The main source of differences is the implementation of the second derivate in the GABC near the free surface. Simulations of a Wigley hull at forward speed in irregular waves are compared to an experiment that was conducted specifically for validating the ABC. The data of the experiment are available as open data through doi: 10.4121/21320604. The comparison between simulation and experiment demonstrates that the GABC with a mean flow can be applied not only for theoretical simulations with propagating waves, but also for more practical applications with a structure in the domain.

Nautilus: An autonomous surface vehicle with a multilayer software architecture for offshore inspection

AbstractThe increasing adoption of robotic solutions for inspection tasks in challenging environments is becoming increasingly prevalent, particularly in the offshore wind energy industry. This trend is driven by the critical need to safeguard the integrity and operational efficiency of offshore infrastructure. Consequently, the design of inspection vehicles must comply with rigorous requirements established by the offshore Operation and Maintenance (O&M) industry. This work presents the design of an autonomous surface vehicle (ASV), named Nautilus, specifically tailored to withstand the demanding conditions of offshore O&M scenarios. The design encompasses both hardware and software architectures, ensuring Nautilus's robustness and adaptability to the harsh maritime environment. It presents a compact hull capable of operating in moderate sea states (wave height up to 2.5 m), with a modular hardware and software architecture that is easily adapted to the mission requirements. It has a perception payload and communication system for edge and real‐time computing, communicates with a Shore Control Center and allows beyond visual line‐of‐sight operations. The Nautilus software architecture aims to provide the necessary flexibility for different mission requirements to offer a unified software architecture for O&M operations. Nautilus's capabilities were validated through the professional testing process of the ATLANTIS Test Center, involving operations in both near‐real and real‐world environments. This validation process culminated in Nautilus's reaching a Technology Readiness Level 8 and became the first ASV to execute autonomous tasks at a floating offshore wind farm located in the Atlantic.

Simulation Study on Methods for Reducing Dynamic Cable Curvature in Floating Wind Power Platforms

As a key component connecting a floating wind turbine with static sea cables, dynamic cables undergo significant tensile and bending loads caused by hydrostatic pressure, self-weight, waves, and ocean currents during service, which can lead to fatigue failure. Thus, dynamic and fatigue analyses are necessary for the design and operation of dynamic cables. In this study, a fatigue analysis of the three-core four-layer armored dynamic cable used in a semisubmersible floating wind turbine was carried out at a water depth of 25 m. The Miner linear cumulative damage method, based on material S-N curves, was used to predict fatigue life. The results indicate that, at 10 times the safety factor, the dynamic cables meet the design requirement of a 30-year service life in the studied marine environment. The maximal curvature of the dynamic cable always appears at the exit of the bend stiffener, even beyond the allowed point. Adding weights to the section where the cable exits the bend stiffener and adjusting the bend stiffener’s hanging angle can both reduce the curvature at the bend stiffener exit. The scheme of adjusting the bend stiffener’s hanging angle is preferred, for it is easier for simultaneous adjusting and inducing much smaller extra stress in the cable. As the hanging angle increases, the curvature at the bend stiffener exit decreases, while the maximal effective tension and maximal von Mises stress gradually increase. For certain operating conditions, especially with higher waves, it is better to adjust the hanging angle to avoid excessive curvature and, meanwhile, ensure the increase in the stress within a reasonable range.

Motion-Based Wave Inference With Neural Networks: Transfer Learning From Numerical Simulation to Experimental Data

Abstract The directional wave spectrum, which describes the distribution of wave energy along frequencies and directions, can be estimated from the measured motions of a vessel subjected to a particular sea condition by resorting to the wave-buoy analogy. Several methods have been proposed to address the inverse estimation problem; recently, machine learning techniques have been assessed as further alternatives. However, it may be difficult to gather large datasets of in-service motion responses and the associated sea states to train effective data-driven models. In this work, an encoder–decoder neural network is trained with the synthetic responses of a station-keeping platform supply vessel (PSV) to estimate the directional wave spectrum. This estimation model is directly applied to perform wave inference from motion data of wave basin tests with a small-scale model of the same vessel. Furthermore, fine-tuning is also used to incorporate experimental data into the neural network model. Results show a satisfactory match between estimated and measured values, both with respect to the energy distribution and the integral spectrum parameters, indicating that the proposed approach can be employed to obtain data-driven wave inference models when there is little or no availability of measured motion records and the corresponding sea conditions.

Experimental and numerical study on the offshore adaptability of new FLH2 floating hydrogen liquefaction production storage and offloading unit

With the development of hydrogen production technology from offshore wind power and natural gas, the deep-sea energy interconnection system using hydrogen energy as the medium is constantly improving. The floating hydrogen liquefaction production storage and offloading unit (LH2-FPSO, FLH2) is an effective method for large-scale utilization of offshore hydrogen energy. By filling the heat exchanger with ortho-parahydrogen conversion catalyst, a new porous medium heat exchange channel is formed. Integrating the spiral wound heat exchanger with the ortho-parahydrogen catalytic conversion reactor can reduce the deck area of FLH2 process system and lower the investment cost of floating hydrogen liquefaction device. The performance of FLH2 can be influenced by the offshore wave and typhoon. In this paper, the methods of floating cryogenic visualization experiment, theoretical analysis and numerical simulation are conducted to study the coupled flow and heat transfer mechanism of working fluid applied in FLH2 under offshore conditions. The results show that the sea state has little influence on the ortho-parahydrogen conversion and cooling process of hydrogen in the porous heat exchange tube. The complex flow and heat transfer challenges brought by the integrated process of new floating hydrogen liquefaction and ortho-parahydrogen conversion have been overcome. With the effect of co-current shear of gas-phase mixed refrigerant, a large dry area will not appear on the outer wall surface of porous tube under offshore conditions. The FLH2 process system shows good adaptability at sea.

An experimental study on the aerodynamic loads of a floating offshore wind turbine under imposed motions

Abstract. The rotor of a floating wind turbine is subject to complex aerodynamics due to changes in relative wind speeds at the blades and potential local interactions between blade sections and the rotor near wake. These complex interactions are not yet fully understood. Lab-scale experiments are highly relevant for capturing these phenomena and provide means for the validation of numerical design tools. This paper presents a new wind tunnel experimental setup able to study the aerodynamic response of a wind turbine rotor when subjected to prescribed motions. The present study uses a 1:148 scale model of the DTU 10 MW reference wind turbine mounted on top of a 6 degrees of freedom parallel kinematic robotic platform. Firstly, the thrust variation of the turbine is investigated when single degree of freedom harmonic motions are imposed by the platform, with surge, pitch and yaw being considered in this study. For reduced frequencies greater than 1.2, it is found that the thrust variation is amplified by up to 150 % compared to the quasi-steady value when the turbine is subject to pitch and surge motions, regardless of the amplitude of motion. A similar behaviour is also noticed under yaw motions. Secondly, realistic 6 degrees of freedom motions are imposed by the platform. The motions are derived from FAST simulations performed on the full-scale turbine coupled with the TripleSpar floater, and the tests aim at exploring the thrust force dynamics for different sea states and wind conditions, obtaining reasonable agreement with the simulations. Finally, the work shows the capabilities of an off-the-shelf hexapod to conduct hybrid testing of floating offshore wind turbines in wind tunnels, as well as its limitations in performing such tests.

Cyanidation of tailings in artisanal small-scale gold mining at Arbaat Region in Red Sea State, Sudan

In this research, the processing of gold from artisanal small-scale gold mining was investigated by cyanidation using an agitation process. The sample's characterization shows that the silicate mineral exhibits the sample mineralogy, according to the results of the XRD examination. In XRF analysis, the mineralogical and chemical structure shows 77.1% SiO2, 8.08% Al2O3, 5.76% Fe2O3, 1.67% CaO, 0.97% K2O, 0.054% As2O3, 1.1% Na2O, 0.392% SO3, 0.454% TiO2, 0.049% MnO and 0.005% ZrO. The parameters of the experiments were stirring speed, NaCN concentration, solid-liquid ratio, temperature, and pH. The purpose of gold leaching in artisanal small-scale gold mining at Arbaat region is to find the appropriate conditions that will ensure maximum recovery. It was found that the gold dissolution decreases with increasing solid ratio. Furthermore, the cyanide concentration positively influences the range of 0.05–0.5 g/L. It is seen that the dissolution rate increases with the range of pH 10-10.30, while it starts to incline at pH after 10.30. However, the temperature and agitation speed have a significant effect on the gold dissolution. Cyanidation tests revealed that it is easy to apply the cyanidation process and recover about 87.52% Au content from the tailings of artisanal small-scale gold mining. The obtained recovery indicates the commercial and economic viability of the process that will be applied to extract Au from artisanal small-scale gold mining tailings in Arbaat.

Pre-Processing of Simulated Synthetic Aperture Radar Image Scenes Using Polarimetric Enhancement for Improved Ship Wake Detection

Ship wake detection using synthetic aperture radar (SAR) imagery provides a way to obtain small marine ship information, but it often becomes unavailable and unreliable during a high sea state. Polarimetric information provides a potential way to solve this problem, which can enhance the ship target as well as the ship wake features. However, three challenges still exist in ship wake detection in polarimetric SAR imagery: the unwanted influences of bright and singular points on ship wake detection, the lack of performance analysis of wake detection by new-type polarimetric enhancement methods, and the difficulty of using the assessment criteria for ship wake detection. In this paper, we try to solve the above problems. Firstly, fully polarized SAR imagery of both ship turbulent and Kelvin wake is simulated based on the two-scale composite model, and the Polarimetric Whitening Filter (PWF) and Polarimetric Detection Optimization Filter (PDOF) are applied to the simulated fully polarized SAR imagery to enhance the ship wake features. Secondly, since the bright and singular points resulting from the ship echoes and the polarimetric enhancement methods may lead to misdetections, a logarithm process and z-score normalization pre-processing has been applied to the images. Then, a new assessment criterion for wake detection performance has been formulated, and the probability of missing detections (PMDs) and the probability of false alarms (PFAs) have been defined for two different requirements. And a Radon transform-based ship wake detection method for both ship turbulence and Kelvin wake has been carried out in horizontal–horizontal (HH), vertical–vertical (VV), horizontal–vertical (HV), PWF and PDOF SAR imagery. Finally, an analysis of the wake detection performance has been carried out. The PWF and PDOF can improve the wake detection performance by an average of nearly 50 percent compared with the HH and VV.

Study on Cable Tension Characteristics of Shore-Based Constant Tension Mooring Systems Under the Coupling Effect of Wind, Wave, and Current

Abstract This paper proposes a shore-based constant tension mooring system, which improves the cable tension distribution by adjusting the length of the cable to maintain the constant tension of the cable between the ship and the mooring pile in order to solve the problem of poor safety and reliability of the traditional mooring system in the mooring process. First, based on the three-dimensional potential flow theory, this paper uses the hydrodynamic software AQWA to numerically simulate the dynamic response of the traditional mooring system under the coupling of wind, wave, and current in different sea states. Subsequently, a shore-based constant tension mooring system using the principle of volume-varying hydraulic control was studied. On the basis of a comprehensive analysis of the working principle of the constant tension hydraulic control mooring system, a mathematical model of the main working circuit is established. The system was numerically simulated by relying on matlab/Simulink simulation software. Finally, by comparing with traditional mooring systems, the results show that the maximum cable tension of the shore-based constant tension mooring system is significantly reduced so that the tension is controlled within a fixed range, and the safety factor of the mooring cable is significantly improved, thus reducing the risk of mooring system failure and improving the ship's survivability.

Latitudinal distribution of biomarkers across the western Arctic Ocean and the Bering Sea: an approach to assess sympagic and pelagic algal production

Abstract. The drastic decline of Arctic sea ice due to global warming and polar amplification of environmental changes in the Arctic basin profoundly alter primary production with consequences for polar ecosystems and the carbon cycle. In this study, we use highly branched isoprenoids (HBIs), brassicasterol, dinosterol and terrestrial biomarkers (n-alkanes and campesterol) in surface sediments to assess sympagic and pelagic algal production with changing sea-ice conditions along a latitudinal transect from the Bering Sea to the high latitudes of the western Arctic Ocean. Suspended particulate matter (SPM) was also collected in surface waters at several stations of the Chukchi Sea to provide snapshots of phytoplankton communities under various sea-ice conditions for comparison with underlying surface sediments. Our results show that sympagic production (IP25 and HBI-II) increased northward between 62 and 73∘ N, with maximum values at the sea-ice edge in the Marginal Ice Zone (MIZ) between 70 and 73∘ N in the southeastern Chukchi Sea and along the coast of Alaska. It was consistently low at northern high latitudes (>73∘ N) under extensive summer sea-ice cover and in the Ice-Free Zone (IFZ) of the Bering Sea. Enhanced pelagic sterols and HBI-III occurred in the IFZ across the Bering Sea and in the southeastern Chukchi Sea up to 70–73∘ N in MIZ conditions, which marks a shift of sympagic over pelagic production. In surface water SPM, pelagic sterols display similar patterns as chlorophyll a, increasing southward with higher amounts found in the Chukchi shelf, pointing to the dominance of diatom production. Higher cholesterol values were found in the mid-Chukchi Sea shelf where phytosterols were also abundant. This compound prevailed over phytosterols in sediments, compared to SPM, reflecting efficient consumption of algal material in the water column by herbivorous zooplankton.

Monitoring ocean currents during the passage of Typhoon Muifa using optical-fiber distributed acoustic sensing

In situ observations under typhoon conditions are sparse and limited. Distributed acoustic sensing (DAS) is an emerging technology that uses submarine optical-fiber (OF) cables to monitor the sea state. Here, we present DAS-based ocean current observations when a super typhoon passed overhead. The microseismic noise induced by ocean surface gravity waves (OSGWs) during Typhoon Muifa (2022) is observed in the ~0.08–0.38 Hz frequency band, with high-frequency (>0.3 Hz) component being tidally modulated. The OSGW propagation along the entire cable is successfully revealed via frequency–wavenumber analysis. Further, a method based on the current-induced Doppler shifts of DAS-recorded OSGW dispersions is proposed to calculate both speeds and directions of horizontal ocean currents. The measured current is consistent with the tidally induced sea-level fluctuations and sea-surface winds observed at a nearby ocean buoy. These observations demonstrate the feasibility of monitoring the ocean current under typhoon conditions using DAS-instrumented cables.

Arctic Sea Ice Loss Modulates the Surface Impact of Autumn Stratospheric Polar Vortex Stretching Events

AbstractThe cold Eurasia has been proposed to be closely linked to the weakening of the stratospheric polar vortex (SPV), however, how the Arctic sea ice modulates the surface impacts of the weak SPV is unclear. This study explores the critical modulating role of reduced Arctic sea ice in the surface cooling response to SPV stretching events in autumn. Here, through ERA5 reanalysis and Whole Atmosphere Community Climate Model simulations, we show that Eurasian cold events are more likely (45%) to occur in days 30–50 after the onset of SPV stretching events under lower Barents‐Kara Seas (BKS) sea ice conditions, in contrast to under heavy BKS sea ice conditions when robust surface cooling is absent. The stratospheric and tropospheric pathways explain 46.8% and 53.2% of the total variance of Siberian coldness, respectively. The downward extension of anomalous stratospheric wave‐2 ridge to the troposphere intensifies the Arctic‐North European high, favoring the subsequent colder Siberia.

Environmental Risk Analysis of Different Segments of The Arctic Northeast Route

There are huge differences in the sea ice conditions, climate and environment, geographical conditions and communication conditions in the Arctic waters, and the equipment and navigation requirements of ships are also different. In order to ensure the safety and success of the ships, through the route, this paper using fuzzy level analysis (Fuzzy Analytic Hierarchy Process, FAHP), build the northeast arctic route risk evaluation index system, targeted analysis of different segments, the results show that: (1) although the sea risk point is different but the natural environment risk has a significant impact on the arctic waters.(2) The risk coefficient of Arctic route is higher than that of traditional ordinary routes. Among the five sea areas in this study, Chukchi Sea is the highest, followed by East Belia Sea. The crew need to pay more attention when sailing.(3) The research in this paper can provide a reference for the navigation safety of the northeast Arctic shipping route.

Low-altitude small target detection in sea clutter background based on improved CEEMDAN-IZOA-ELM

To effectively detect low-altitude small targets under complex sea surface environment, an innovative method has been developed. This method harnesses the chaotic characteristics of sea clutter and employs a combination of Adaptive Noise Complete Ensemble Empirical Modal Decomposition (CEEMDAN), Adaptive Wavelet Thresholding (AWT), and Polynomial Fitting Filtering (SG) for denoising sea clutter data. Subsequently, the Improved Zebra Optimization Algorithm-Extreme Learning Machine (IZOA-ELM) detector is utilized to identify low-altitude small targets amidst the sea clutter background. To begin, the CEEMDAN method is applied to disentangle the measured sea clutter data into a set of Intrinsic Mode Functions (IMFs). Afterwords, the Refined Composite Multiscale Dispersion Entropy (RCMDE) is computed for each individual IMF. This process categorizes the IMFs into three distinct components: noise-dominant, signal-noise mixture, and signal-dominant segments. The noise-dominate of IMF component is subjected to denoising through AWT, the signal-noise mixture of IMF components are processed using SG filtering, while the signal-dominant of IMF remains unaltered. The denoised sea clutter signal is reconstructed by concatenating the denoised and unprocessed IMFs. Based on the chaotic nature of sea clutter signals, first-order sea clutter data is transformed into high-dimensional data through phase space reconstruction. The initial weights and thresholds of the ELM are optimized through the IZOA to establish an optimal prediction model. This model is then used to detect small, low-altitude targets by analyzing the prediction error. The algorithm's effectiveness in noise removal is validated using IPIX and SPRR measured sea clutter data, demonstrating a significant improvement in the root mean square of prediction error (RMSE) by one order of magnitude after denoising compared to the pre-denoising state. Furthermore, we observed that the IZOA-ELM method can be effectively applied to detect small targets at low altitudes across various sea conditions. However, when the sea state is complex and greatly affected by the surrounding noise, an effective approach is to first employ CEEMDAN-AWT-SG to denoise the original signal, and then utilize IZOA-ELM for target detection.

Operation failure of risk analysis on floating storage and offloading

The need for petroleum in daily life is increasing. The oil comes from the seabed, so it is necessary to have adequate facilities during the exploration and exploitation of crude oil. The process of distributing crude oil to FSO is assisted by the Product Transfer System pipeline. In this process there is a possibility of failure that occurs form several factors, namely tools, weather and sea conditions, and human. In this study, the analysis of the risk of operational failure during loading-unloading of crude oil is discussed. The analysis was carried out using the HAZOP Analysis and Bow-Tie Analysis methods. HAZOP Analysis for hazard identification, and Bow-Tie Analysis for finding the appropriate mitigation. From this method, an overview of the risks than can occur can be obtained so that the risk control required by FSO can be implemented. From the results of this study, it was found that there are 41 potential hazards on the process of loading-unloading crude oil FSO, with the highest risk is inadequate quality of the transfer equipment components with the likelihood rank is 4 and severity rank is 4. The results of Bow-Tie visualization of dominant risk found five causes, namely corrosion, inadequate material quality, eroded material, service life, and material degradation, and five consequences, namely property damage, delayed operational activities, oil spills, environmental damage due to oil spill, and corrosion occurs on the product transfer equipment.

Analysis of deck house height and center of gravity in anti-capsize patrol boat

The design of patrol boats, especially in Indonesian waters which have extreme sea conditions, requires fairly good stability capabilities and special self-righting capabilities. Designing a self-righting ship will be closely related to the ship stability because the center of gravity (G) is affected by the load and the height of the deckhouse of a ship, which has implications for the ship’s self-righting. Present study was carried out with experimental study for patrol boat design that has capability self-righting moment. The patroal boat has 4 deckhouse height variations with 2.01 m, 2.11 m, 2.21 m, and 2.31 m, respectively. There are 4 variations of the load conditions, i.e., the condition with 50% of the maximum amount of cargo, the condition 50% the passengers and cargo, full load condition without passengers, and the last one is the condition of the passenger baggage is only 50%. The results showed that a deckhouse with a height of 2.01 m has the worst GZ curve analysis, where in some conditions the results touch a negative number before heeling to 180°. The results showed by trial and error that the minimum deckhouse height is 2.07 m to have a self-righting moment in all conditions.

Review of Intelligent Ship Path Planning Algorithms

Intelligent ship route planning has become an important research direction in the field of shipping in recent years. This paper first provides an overview of the basic theory of intelligent ship route planning. Secondly, various intelligent ship route planning algorithms are introduced, including methods based on A* algorithm, artificial potential field algorithm, RRT algorithm, and reinforcement learning. These algorithms analyze information such as ocean environment, predict sea conditions and traffic conditions, and consider ship dynamics and navigation safety constraints to provide efficient and safe navigation routes for ships. Finally, this paper points out the key issues and future development directions in intelligent ship route planning. The continuous innovation and application of intelligent ship route planning algorithms will provide more intelligent and efficient ship transportation services for the shipping industry, promoting the sustainable development of the shipping industry.

The Influence of Time-Varying Sea Ice Concentration on Antarctic and Southern Ocean Numerical Weather Prediction

Abstract Although operational weather forecasting centers are increasingly using global coupled atmosphere–ocean–ice models to replace atmosphere-only models for short- and medium-range (10 day) weather forecasting, the influence of sea ice on such forecasting has yet to be fully quantified, especially in the Southern Ocean. To address this gap, a polar-specific version of the Weather Research and Forecasting Model is implemented with a circumpolar Antarctic domain to investigate the impact of daily updates of sea ice concentration on short- and medium- range weather forecasting. A statistically significant improvement in near-surface atmospheric temperature and humidity is shown from +24 to +192 h when updating the daily sea ice concentration in the model. The forecast skill improvements for 2-m temperature and dewpoint temperature are enhanced from June to September, which is the period of late sea ice advance. Regionally, model improvement is shown to occur in most sea ice regions, although the improvement is strongest in the Ross Sea and Weddell Sea sectors. The surface heat budget also shows remarkable improvement in outgoing radiative heat fluxes and both sensible and latent heat fluxes. This idealized research demonstrates the nonnegligible effect of including more accurate time-varying sea ice concentration in numerical weather forecasting. Significance Statement The purpose of this study is to understand how a more realistic Antarctic sea ice field may influence the skill of short- and medium-range weather forecasts. Many operational atmospheric numerical weather prediction (NWP) models use a static forecast field through the time frame of the model’s forecast—often 3–10 days. In this study, we updated the sea ice concentration field daily and compared the forecast outcomes with those from model runs using a static sea ice concentration field. We found the forecast skill of near-surface temperature and humidity show the most significant improvements in our idealized experiments. This indicates the importance of incorporating improved dynamic sea ice representation in Antarctic short- to medium-range operational weather forecasting.

Short-term ship roll motion prediction using the encoder–decoder Bi-LSTM with teacher forcing

The safety of maritime operations has become a paramount concern with the advancement of intelligent ships. Ship stability and safety are directly impacted by roll motion, making the prediction of short-term ship roll motion pivotal for assisting navigators in making timely adjustments and averting hazardous roll conditions. However, predicting ship roll motion poses challenges due to nonlinear dynamics. This study aims to predict short-term ship roll motion by leveraging the encoder–decoder structure of Bidirectional Long Short-Term Memory Networks (Bi-LSTM) with teacher forcing. The model is accomplished by employing an encoder–decoder structure to map input sequences to output sequences of varying lengths, and employing teacher forcing to enhance the network’s ability to extract information. To refine and analyze the prediction model, aspects such as the quantity of training data to guarantee model generalization, establishing apposite length relationships between input and output sequences, and assessing the model performance in various sea states are investigated. Additionally, comparative experiments assessing roll motion prediction for intervals of 10s, 30 s, 60 s, and 120 s are conducted to substantiate the necessity and effectiveness of the proposed network. The dataset originates from a commercial professional simulator developed by the Norwegian company Offshore Simulator Center AS (OSC).