Regional Ocean Modeling Research Articles

Optimal Precursors Triggering Sudden Shifts in the Antarctic Circumpolar Current Transport Through Drake Passage

AbstractDue to the high nonlinearity, the accurate prediction of the Antarctic circumpolar current (ACC) transport is still challenging. Using the eddy‐permitting regional ocean modeling system and the conditional nonlinear optimal perturbation approach, the sudden shift in the ACC transport through Drake Passage (DP) is investigated by exploring its optimal precursor (OPR). Here, the sudden shift in the ACC transport is defined as a fluctuation exceeding double STD (∼16 Sv; 1 Sv = 106 m3 s−1) within 30 days. The results indicate that the OPRs for all three cases exhibit specific structures in the middle DP (58°–62°S, 72°–64°W) at the depth of 1,000–3,000 m, implying that the ACC transport is most sensitive to the initial perturbations there. The OPRs' evolutions show similar features: the OPR for each case triggers an eddy‐like dipole perturbation with a northern cyclone and a southern anticyclone, leading to a sudden reduction in the ACC transport of ∼40 Sv. It is verified that the density components in the OPRs determine such evolution processes. Furthermore, baroclinic instability is diagnosed to play a dominant role in the development of OPRs by analyzing the perturbed kinetic energy budget. This study suggests that the deep‐layer density perturbations in the Southern Ocean should be carefully monitored when considering the short‐range prediction of the ACC transport.

Mechanisms of asymmetry in sea surface temperature anomalies associated with the Indian Ocean Dipole revealed by closed heat budget

The Indian Ocean Dipole (IOD) is an interannual climate mode of the tropical Indian Ocean. Although it is known that negative sea surface temperature (SST) anomalies in the eastern pole during the positive IOD are stronger than positive SST anomalies during the negative IOD, no consensus has been reached on the relative importance of various mechanisms that contribute to this asymmetry. Based on a closed mixed layer heat budget analysis using a regional ocean model, here we show for the first time that the vertical mixing plays an important role in causing such asymmetry in SST anomalies in addition to the contributions from the nonlinear advection and the thermocline feedback proposed by previous studies. A decomposition of the vertical mixing term indicates that nonlinearity in the anomalous vertical temperature gradient associated with subsurface temperature anomalies and anomalous vertical mixing coefficients is the main driver of such asymmetry. Such variations in subsurface temperature are induced by the anomalous southeasterly trade winds along the Indonesian coast that modulate the thermocline depth through coastal upwelling/downwelling. Thus, the thermocline feedback contributes to the SST asymmetry not through the vertical advection as previously suggested, but via the vertical mixing.

Seasonal-To-Interannual Variability of Sea-Surface Temperatures in The Inter-Americas Seas: Pattern-Dependent Biases in The Regional Ocean Modeling System

The Inter-Americas Seas (IAS), involving the Gulf of Mexico, the Caribbean and a section of the eastern tropical Pacific Ocean bordering Central America, Colombia and Ecuador, exhibits very active ocean-land-atmosphere interactions that impact socio-economic activities within and beyond the region, and that are still not well understood or represented in state-of-the-art models. On seasonal-to-interannual timescales, the main source of variability of this geographical area is related to interactions between the Pacific and the Atlantic oceans, involving to anomalous sea-surface temperature (SST) patterns like El Niño-Southern Oscillation (ENSO), and regional features in the Caribbean linked to the bi-modal seasonality of the Caribbean Low-Level Jet. This study investigates seasonal-to-interannual IAS surface-temperature anomalies in observations, and their representation in am eddy-permitting, 1/9o-resolution simulation using the Regional Ocean Modeling System (ROMS), interannually-forced by the Climate Forecast System Reanalysis. Here, rather than analyzing model biases locally (i.e., gridbox-by-gridbox), a non-local SST pattern-based diagnostic was conducted via a principal component analysis. The approach allowed to identify magnitude, variance and spatial systematic errors in SST patterns related to the Western Hemisphere Warm Pool, ENSO, the Inter-American Seas Dipole, and several other variability modes. These biases are mainly related to errors in surface heat fluxes, misrepresentation of air-sea interactions impacting surface latent cooling in the Caribbean, and too strong sub-surface thermal stratification, mostly off the coast of Ecuador and northern Peru.

Seasonal Predictability of Sea Ice and Bottom Temperature Across the Eastern Bering Sea Shelf

AbstractSeasonal sea ice plays a key role in shaping the ecosystem dynamics of the eastern Bering Sea shelf. In particular, it leads to the formation of a characteristic pool of cold water that covers the bottom of the shelf from winter through summer; the extent of this cold pool is often used as a management index for distribution, productivity, recruitment, and survival of commercially important fish and shellfish species. Here, we quantify our ability to seasonally forecast interannual variability in Bering Sea bottom temperature and sea ice extent. Retrospective forecast simulations from two global forecast models are downscaled using a regional ocean model; the retrospective forecast simulations include 9‐month to 12‐month forecasts spanning 1982–2010. We find that dynamic forecasting can predict summer bottom temperatures across the eastern Bering Sea shelf with lead times of up to 4 months. The majority of the prediction skill derives from the persistence signal, and a persistence forecast is comparably skillful to the dynamic forecast at these lead times. However, forecast skill of sea ice advance and retreat is low when a forecast model is initialized before or during the ice season (October–February); this limits the ability of either dynamic or persistence models to predict summer bottom temperatures when initialized across the late fall to early spring months.

SEA-COApp: A web app to analyze, download, and visualize Regional Ocean Model (ROM) datasets in Southeast Asia

To provide weather and climate-related services for disaster management, public policymaking, and adaptation and mitigation efforts, the information regarding climate change is of high importance. However, obtaining or analyzing climate change datasets has been a challenge for those unfamiliar with coding. Therefore, to make the datasets easier to obtain and work with, we develop a "Southeast Asia – Climate-Ocean web App" (SEA-COApp). The SEA-COApp is a web app to aid people in obtaining, analyze, or visualize ROM datasets in Southeast Asia. It can obtain chunks of data from the InaROMS server and visualize it with an intuitive graphical user interface. Furthermore, it also has functionalities to calculate climatology, area average, anomaly, and trends. The tool can help those who are unfamiliar with climate change datasets to be able to use the datasets for their research. Thus, promoting cross-disciplinary research.

Artificial Intelligence powered forecast of oceanic mesoscale phenomena: A typhoon cold wake case occurring in Northwest Pacific Ocean

The phenomenon of typhoon cold wake has always been a key research object in the field of ocean–atmosphere interaction. Different from the physical equation-based numerical model which has long been dependent on, inspired by largely available forecasting and reanalyzed data and the advance of artificial intelligence technology, we build RC_ViT deep learning model for forecasting the typhoon cold wake. The total RMSE of grid points at each moment was between 0.5 and 0.9 °C, indicating that the model was accurate to forecast the sea surface temperature after the pass of typhoon. During the testing period of 11 years (2010–2020), using the deep learning method, our artificial intelligence model accurately and efficiently forecasts the sea surface temperature field. The cold wake of typhoon Megi (2010) was simulated by a Regional Ocean Model System (ROMS) and the artificial intelligence model separately. The results show that before the typhoon passing, the SST forecasted by the artificial intelligence model is more accurate, and after the typhoon passes, the ROMS forecast result has a smaller RMSE value. The reason may be that the intensity of typhoon Megi was too strong, and the artificial intelligence model training samples were few, resulting in artificial intelligence model forecast accuracy lower than traditional numerical models after the Megi passing. This study demonstrates the strong potential of the data-driven artificial intelligence model as an alternative to traditional numerical models for forecasting oceanic phenomena.

Support for the Slope Sea as a major spawning ground for Atlantic bluefin tuna: evidence from larval abundance, growth rates, and particle-tracking simulations

Atlantic bluefin tuna (Thunnus thynnus) are commercially and ecologically valuable, but management is complicated by their highly migratory lifestyle. Recent collections of bluefin tuna larvae in the Slope Sea off northeastern United States have opened questions about how this region contributes to population dynamics. We analyzed larvae collected in the Slope Sea and the Gulf of Mexico in 2016 to estimate larval abundance and growth rates and used a high-resolution regional ocean circulation model to estimate spawning locations and larval transport. We did not detect a regional difference in growth rates, but found that Slope Sea larvae were larger than Gulf of Mexico larvae prior to exogenous feeding. Slope Sea larvae generally backtracked to locations north of Cape Hatteras and would have been retained within the Slope Sea until the early juvenile stage. Overall, our results provide supporting evidence that the Slope Sea is a major spawning ground that is likely to be important for population dynamics. Further study of larvae and spawning adults in the region should be prioritized to support management decisions.

Seasonal variation in material exchange through the Bohai Strait

The seasonal variation in material exchange through the Bohai Strait (BS) was examined using the climatological mean outputs from the Regional Ocean Modelling Systems and in-situ observations from two acoustic Doppler current profilers at two typical stations in the Strait from July 2017 to June 2018. The suspended sediment concentration (SSC) was retrieved from ocean color remote sensing data. The long-term mean numerical results and the one-year observations suggest that the volume and suspended sediment flux in the BS section exhibit distinct seasonal variations. The annual mean net outflow of the suspended sediment through the BS section is estimated to be 15.8 Mt/yr in the climatological state. The observations further reveal the circulation structure, with inflow in the north and outflow in the south. Freshwater from the Yellow Sea discharged sediment into the Bohai Sea in the deep northern channel at a rate of 0.4 Mt/yr, whereas turbid water discharged sediment into the Yellow Sea in the shallow southern channel at a rate of 0.19 Mt/yr. Several factors determine the seasonal variation in the sediment flux. In the winter half-year, variation in SSC plays a dominant role, while in summer, the primary influence on sediment flux is current velocity. Moreover, SSC significantly influences the southern shallow and deep northern channels, while the current velocity is dominant in the central channel. In addition, the meridional wind displays a close relationship with the seasonal variation of the sediment exchange through the BS by dominating both the current and SSC.

Ocean Modeling in the Makassar Strait and Balikpapan Bay Using Online Nesting Method

Nur, A.A.; Suprijo, T.; Mandang, I.; Radjawane, I.M.; Park, H., and Khadami, F., 2021. Ocean modeling in the Makassar Strait and Balikpapan Bay using online nesting method. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 206–210. Coconut Creek (Florida), ISSN 0749-0208. This study had applied offline nesting method (one-way interaction) by using Regional Ocean Modeling System (ROMS) to simulate currents circulation in the Balikpapan Bay and showing good results with a high agreement between model output and observational measurement for water level data. It proves that even using the offline nesting method is the better option than increasing grid resolution on the entire model domain that will be demanding more computational cost, while the area of interest is a small-scale application. Therefore, this study aims to improve the model solution by using the online nesting method (two-way interaction) with a refinement ratio of 1:5 from the larger domain to a smaller domain. Three domains which include larger domain (L1) with spatial resolution 2.5 km that encompasses almost the entire Makassar Strait and acted as parent grid for the model. Coarser model of domain L2 with 500 m resolution becomes the buffer zone between the parent model (L1) and smaller domain (L3) in the Balikpapan Bay that has 100 m resolution. Initial and boundary conditions (IC/BC) for the L1 domain consisting of water levels, currents, temperature, and salinity were derived from the Hybrid Coordinate Ocean Model (HyCOM) re-analysis dataset. By using this method, there is only IC needed to be prepared for the other domain by interpolating IC data from the L1 domain and the BC would be provided directly from their larger domain during the simulation. Surface forcing for all domains extracted from the European Centre for Medium-Range Weather Forecast (ECMWF) ERA5 hourly dataset. Statistical methods such as Root Mean Square Error (RMSE) and model skill were used to validate model results for each model domain and found the improvement of the model solution when comparing observational data by model results for the larger and smaller domain at the same location, respectively.

A New Open Source Implementation of Lagrangian Filtering: A Method to Identify Internal Waves in High‐Resolution Simulations

AbstractIdentifying internal waves in complex flow fields is a long‐standing problem in fluid dynamics, oceanography and atmospheric science, owing to the overlap of internal waves temporal and spatial scales with other flow regimes. Lagrangian filtering—that is, temporal filtering in a frame of reference moving with the flow—is one proposed methodology for performing this separation. Here we (a) describe an improved implementation of the Lagrangian filtering methodology and (b) introduce a new freely available, parallelized Python package that applies the method. We show that the package can be used to directly filter output from a variety of common ocean models including MITgcm, Regional Ocean Modeling System and MOM5 for both regional and global domains at high resolution. The Lagrangian filtering is shown to be a useful tool to both identify (and thereby quantify) internal waves, and to remove internal waves to isolate the non‐wave flow field.

Interconnection between the Southern South China Sea and the Java Sea through the Karimata Strait

This study aims to investigate the interconnection between the southern South China Sea (SSCS) and Java Sea (JS) by simulating seasonal circulations and associated transports using the Regional Ocean Modelling System (ROMS). The seasonal circulation was predominantly driven by monsoonal wind stress and water exchanges between the SSCS and the JS. During the boreal winter, cooler and saltier waters from the SSCS were advected into the JS, while during the boreal summer, cooler waters from the JS were advected into the SSCS, with the advection of fresher water onto the Peninsular Malaysia’s east coast in the SSCS being the new finding provided by this study. The various water transports were driven southward into the JS during the boreal winter and northward into the SSCS during the boreal summer. The various water transports estimated by ROMS peaked in May during the inflow months from the JS into the SSCS, which was attributed to the simulated anticyclonic eddy in the SSCS, which differed from previous studies that peaked between June and August. The annual mean volume, freshwater, heat, and salt transports were 0.96 Sv, 0.04 Sv, 0.10 PW, and 0.03 × 109 kg s−1, respectively, directed from the SSCS into the JS.

Coupled regional Earth system modeling in the Baltic Sea region

Abstract. Nonlinear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross-compartmental feedback loops in the Earth system. These feedbacks are less well represented in the traditional stand-alone atmosphere and ocean models on which many of today's regional climate assessments rely (e.g., EURO-CORDEX, NOSCCA and BACC II). This has promoted the development of regional climate models for the Baltic Sea region by coupling different compartments of the Earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed on the region by prescribed boundary conditions and, thus, permit more degrees of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress on model systems that allow two-way communication between atmosphere and ocean models; models for the land surface, including the terrestrial biosphere; and wave models at the air–sea interface and hydrology models for water cycle closure. However, several processes that have mostly been realized by one-way coupling to date, such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g., aerosols), are not considered here. In contrast to uncoupled stand-alone models, coupled Earth system models can modify mean near-surface air temperatures locally by up to several degrees compared with their stand-alone atmospheric counterparts using prescribed surface boundary conditions. The representation of small-scale oceanic processes, such as vertical mixing and sea-ice dynamics, appears essential to accurately resolve the air–sea heat exchange over the Baltic Sea, and these parameters can only be provided by online coupled high-resolution ocean models. In addition, the coupling of wave models at the ocean–atmosphere interface allows for a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large-scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land-use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes such as heavy precipitation, storms, or tropical nights (defined as nights where the daily minimum temperature does not fall below 20 ∘C), and these parameters appear to be sensitive to coupling. For the present-day climate, many coupled atmosphere–ocean and atmosphere–land surface models have demonstrated the added value of single climate variables, in particular when low-quality boundary data were used in the respective stand-alone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models to close the water cycle remains problematic, as the accuracy of precipitation provided by atmosphere models is, in most cases, insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments. Many regional stand-alone ocean and atmosphere models are tuned to suitably represent present-day climatologies rather than to accurately simulate climate change. Therefore, more research is required into how the regional climate sensitivity (e.g., the models' response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared with uncoupled ones.

The impact of ocean data assimilation on the simulation of mesoscale eddies at São Paulo plateau (Brazil) using the regional ocean modeling system

This work presents simulations of ocean circulation in the southwestern South Atlantic Ocean with emphasis on the São Paulo Plateau region, a unique physiographic feature at the foot of the continental slope offshore southeast Brazil, where the flow is dominated by ocean eddies and dipoles. Surface dynamics south of 23°S presents a heterogeneous circulation pattern intimately related to the presence of mesoscale features, such as meanders of the Brazil Current along the continental slope, and eddies that interacts with deep ocean features. The reproduction of these eddies at the correct time and spatial structure are quite challenging in the context of a non-assimilative model, considering the limitations imposed by the model’s numerical schemes, physical parameterizations, boundary conditions and surface forcing. In this sense, the Regional Ocean Modeling System (ROMS) 4-dimensional Variational Data Assimilation (4D-Var) module was used to increase model skill and minimize deviations from oceanic observations. Weekly observations of Sea Surface Height (SSH), daily Sea Surface Temperature (SST) fields and in situ vertical profiles of temperature and salinity from multiple sources were used in consecutive assimilation cycles to produce an accurate representation of ocean features and their variability. Both the assimilative and free run were evaluated against observations, including in situ current measurements. Results showed significant improvements of the assimilation procedure on both assimilated and non-assimilated variables, with RMSE reductions of 27% and 47% for SST and SSH, respectively, and 51% for current speed measurements during a dipole event in the São Paulo Plateau. The assimilative run was able to reproduce a remarkable event of mesoscale eddies interaction (dipole) and consequent current intensification, leading to important improvements on model skill. The correct use of observational information of open ocean surface features through data assimilation is a key factor for a proper simulation of such eddy dipole events.

Modulation of ocean acidification by decadal climate variability in the Gulf of Alaska

Uptake of anthropogenic carbon dioxide from the atmosphere by the surface ocean is leading to global ocean acidification, but regional variations in ocean circulation and mixing can dampen or accelerate apparent acidification rates. Here we use a regional ocean model simulation for the years 1980 to 2013 and observational data to investigate how ocean fluctuations impact acidification rates in surface waters of the Gulf of Alaska. We find that large-scale atmospheric forcing influenced local winds and upwelling strength, which in turn affected ocean acidification rate. Specifically, variability in local wind stress curl depressed sea surface height in the subpolar gyre over decade-long intervals, which increased upwelling of nitrate- and dissolved inorganic carbon-rich waters and enhanced apparent ocean acidification rates. We define this sea surface height variability as the Northern Gulf of Alaska Oscillation and suggest that it can cause extreme acidification events that are detrimental to ecosystem health and fisheries.

Sensitivity of marine fish thermal habitat models to fishery data sources.

Statistical models built using different data sources and methods can exhibit conflicting patterns. We used the northern stock of black sea bass (Centropristis striata) as a case study to assess the impacts of using different fisheries data sources and laboratory‐derived physiological metrics in the development of thermal habitat models for marine fishes. We constructed thermal habitat models using generalized additive models (GAMs) based on various fisheries datasets as input, including the NOAA Northeast Fisheries Science Center (NEFSC) bottom trawl surveys, various inshore fisheries‐independent trawl surveys (state waters), NEFSC fisheries‐dependent observer data, and laboratory‐based physiological metrics. We compared each model's GAM response curve and coupled them to historical ocean conditions in the U.S. Northeast Shelf using bias‐corrected ocean temperature output from a regional ocean model. Thermal habitat models based on shelf‐wide data (NEFSC fisheries‐dependent observer data and fisheries‐independent spring and fall surveys) explained the most variation in black sea bass presence/absence data at ~15% deviance explained. Models based on a narrower range of sampled thermal habitat from inshore survey data in the Northeast Area Monitoring and Assessment Program (NEAMAP) and the geographically isolated Long Island Sound data performed poorly. All models had similar lower thermal limits around 8.5℃, but thermal optima, when present, ranged from 16.7 to 24.8℃. The GAMs could reliably predict habitat from years excluded from model training, but due to strong seasonal temperature fluctuations in the region, could not be used to predict habitat in seasons excluded from training. We conclude that survey data source can greatly impact development and interpretation of thermal habitat models for marine fishes. We suggest that model development be based on data sources that sample the widest range of ocean temperature and physical habitat throughout multiple seasons when possible, and encourage thorough consideration of how data gaps may influence model uncertainty.

Volume and Heat Transport in the South China Sea and Maritime Continent at Present and the End of the 21st Century

AbstractOcean transports through the Southeast Asian Seas connect the western tropical Pacific and Indian Oceans, thereby exerting an important role in regional and global climate. High‐resolution regional ocean model simulations over the South China Sea (SCS) and maritime continent are used to study the mean and seasonally varying thermohaline structure and volume transport through the straits surrounding the SCS. Diversity in the vertical structure of these straits is not only indicative of the role of widely varying bathymetry but also strong seasonality associated with monsoonal currents. The presence of a Pacific water mass in intermediate and deep layers of the Luzon Strait points to a key pathway between the Pacific and Indian Oceans. Further, examining a suite of global, high‐resolution model simulations reveals the projected changes in the regional upper ocean transports due to anthropogenic radiative forcing by the end of the 21st century. The global models predict an increase in heat and volume transport through the Luzon and Karimata Straits, and a decrease thereof through the Makassar and Lombok Straits by the end of the century. Overall, these changes impute additional net convergence of heat and volume in the SCS, a significant reduction of sea surface salinity and mixed layer depth, and an increase in the upper‐ocean heat content of the region. As the SCS serves as a regional heat capacitor and is impacted by the global thermohaline circulation locally via Indonesian Throughflow, these predicted changes have the potential to impact climate over the Indo‐Pacific region and globally.

Introducing the New Regional Community Earth System Model, R-CESM

AbstractThe development of high-resolution, fully coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) Model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include 1) assessing the skill of R-CESM in a multiyear, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean–atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean–atmosphere interactions. We also discuss capabilities under development such as (i) regional refinement using a high-resolution ROMS nested within global CESM and (ii) “online” coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS.

Numerical Simulation of Deep-Sea Sediment Transport Induced by a Dredge Experiment in the Northeastern Pacific Ocean

Predictability of the dispersion of sediment plumes induced by potential deep-sea mining activities is still very limited due to operational limitations on in-situ observations required for a thorough validation and calibration of numerical models. Here we report on a plume dispersion experiment carried out in the German license area for the exploration of polymetallic nodules in the northeastern tropical Pacific Ocean in 4,200 m water depth. The dispersion of a sediment plume induced by a small-scale dredge experiment in April 2019 was investigated numerically by employing a sediment transport module coupled to a high-resolution hydrodynamic regional ocean model. Various aspects including sediment characteristics and ocean hydrodynamics were examined to obtain the best statistical agreement between sensor-based observations and model results. Results show that the model is capable of reproducing suspended sediment concentration and redeposition patterns observed during the dredge experiment. Due to a strong southward current during the dredging, the model predicts no sediment deposition and plume dispersion north of the dredging tracks. The sediment redeposition thickness reaches up to 9 mm directly next to the dredging tracks and 0.07 mm in about 320 m away from the dredging center. The model results suggest that seabed topography and variable sediment release heights above the seafloor cause significant changes especially for the low sedimentation pattern in the far-field area. Near-bottom mixing is expected to strongly influence vertical transport of suspended sediment.

Propagation of a Meteotsunami from the Yellow Sea to the Korea Strait in April 2019

A meteotsunami with a wave height of 0.1–0.9 m and a period of 60 min was observed at tide gauges along the Korea Strait on 7 April 2019, while a train of two to four atmospheric pressure disturbances with disturbance heights of 1.5–3.9 hPa moved eastward from the Yellow Sea to the Korea Strait. Analysis of observational data indicated that isobar lines of the atmospheric pressure disturbances had angles of 75–83° counterclockwise due east and propagated with a velocity of 26.5–31.0 m/s. The generation and propagation process of the meteotsunami was investigated using the Regional Ocean Modeling System. The long ocean waves were amplified due to Proudman resonance in the southwestern Yellow Sea, where the water is deeper than 75 m; here, the long ocean waves were refracted toward the coast on the shallow coastal region of the northern Korea Strait. Refraction and reflection by offshore islands significantly affect the wave heights at the coast. To investigate the effects of an eastward-moving velocity and angle of atmospheric pressure disturbance on the height of a long ocean wave, sensitivity simulations were performed. This result will be useful for the real-time prediction system of meteotsunamis in the Korea Strait.

A numerical study on the role of atmospheric forcing on mixed layer depth variability in the Bay of Bengal using a regional ocean model

A numerical study on the role of atmospheric forcing on mixed layer depth variability in the Bay of Bengal using a regional ocean model