Hybrid Coordinate Ocean Model Research Articles

Upper-ocean changes with hurricane-strength wind events: a study using Argo profiles and an ocean reanalysis

Abstract. As the Earth's climate warms, the intensity and rain rate of tropical cyclones (TCs) is projected to increase. TCs intensify by extracting heat energy from the ocean; hence, a better understanding of upper-ocean changes with the TC passage is helpful to improve our understanding of air–sea interactions during and after the event. This work uses Argo float observations and the HYbrid Coordinate Ocean Model (HYCOM) ocean reanalysis to describe characteristics of upper-ocean changes with hurricane-strength wind events. We study the association of these changes with the vertical structure of the salinity profile before the event, i.e., increasing versus decreasing with depth. We also study the contribution of changes in salinity to upper-ocean density changes in each case. Results show that in regions where pre-event salinity increases with depth there is a corresponding statistically significant increase in upper-ocean salinity; vice versa, we observe a significant decrease in upper-ocean salinity in regions where pre-event salinity decreases with depth. Consistent with previous studies, temperature decreases in both regions. As near-surface temperature decreases, upper-ocean density increases, and the increase is larger where pre-event salinity increases with depth. Changes in upper-ocean properties from Argo and HYCOM are overall consistent with wind-driven vertical mixing of near-surface waters with colder and higher-salinity (or lower-salinity) waters below. Resulting changes in ocean stratification have implications for air–sea interactions during and after the event, with potential impacts on weather events that follow.

The Influence of Caribbean Current Eddies on Coastal Circulation in the Southwest Caribbean Sea

Abstract Westward-propagating Caribbean Current eddies modify the volume-integrated potential vorticity (PV) balance in the western Caribbean Sea, influencing the circulation of the Panamá–Colombia Gyre (PCG) and coastal currents hundreds of kilometers to the south of the eddies’ mean trajectory. Using 22 years of output from the Hybrid Coordinate Ocean Model, we apply a volume-integrated eddy phase-averaged 1.5-layer PV balance, showing that PV fluxes into the PCG region are balanced by frictional PV dissipation represented by linear drag along the coastline. Coastal currents in the PCG region vary by a factor of 2 in phase with the passage of a Caribbean Current eddy over the 116-day average eddy period. Flow separation at the Isthmus of Panamá results in a vortex shed from the Darien Gulf, which slows the coastal currents in the gyre region from their maximum during eddy events. An annual ensemble average PV balance in the gyre region shows that the mean PV influx to this region is higher from August to October. Correspondingly, the range of coastal currents in the gyre region over an eddy event is modestly influenced by the PV influx magnitude. Eddy-influenced reversals in the coastal current can occur between November and July at Bocas del Toro and year-round at Colón. Such coastal current reversals are important for the alongshore transport of larvae, freshwater, and chemical tracers.

Long-term variation of the eddy kinetic energy in the Northeastern South China sea

The seasonal to interannual variability of eddy kinetic energy (EKE) in the Northeastern South China Sea (NE-SCS) has been widely studied and it is recognized that they are strongly related to the state of the Kuroshio pathway in the Luzon Strait. While, due to the lack of long-term observations and high-resolution simulations, the decadal change of EKE in NE-SCS remains unexplored. In this study, we show the EKE trend in the past ∼ 30 years in the NE-SCS by using satellite observation and global HYbrid Coordinate Ocean Model reanalysis with the Navy Coupled Ocean Data Assimilation. It is found that due to the weakening of the Kuroshio in the Luzon Strait since 1990 s, the Kuroshio shows an enhanced looping path in the NE-SCS, inducing stronger EKE in this region. Further analysis confirms that the energy transfer by baroclinic instability is dominant for the increasing of EKE, when the Kuroshio intrudes into the NE-SCS and brings more potential energy inside the circulation. The Kuroshio state along the Luzon Strait is the key for modulating the EKE in the NE-SCS. Furthermore, the long-term weakening of Kuroshio current along the Luzon strait during 1993–2020 is determined by the decreasing of subtropical mode water, corresponding to the positive phase of the Atlantic Multidecadal Oscillation. This study provides insight into the interaction between marginal sea (i.e., the SCS) and the open ocean (i.e., the western Pacific Ocean), finally linking to the global climate change.

Assessment of high-resolution regional ocean reanalysis K-ORA22 for the Northwest Pacific

The Korea Institute of Ocean Science and Technology developed the Korea Operational Oceanographic System-Ocean Predictability Experiment for Marine Environment (KOOS-OPEM), a high-resolution (1/24°, 51 vertical levels) ocean prediction model for the Northwest Pacific Ocean that incorporates ensemble optimal interpolation. In this study, we present KOOS-OPEM ReAnalysis version 2022 (K-ORA22), which covers the period from 2011 to 2022. We conducted a comparative analysis between K-ORA22 and other high-resolution (1/10°–1/12°) global reanalyses, including the Hybrid Coordinate Ocean Model, Global Ocean Reanalysis and Simulation (GLORYS), and Bluelink ReAnalysis (BRAN), to demonstrate the reproducibility and reliability of regional characteristics. Statistical comparisons revealed that while K-ORA22 exhibited some warm biases, its sea surface temperature (SST) anomaly correlation after removing the seasonal cycle was approximately 0.87, comparable to other reanalyses. Additionally, K-ORA22 effectively reproduced coastal upwelling, which is characterized by a sharp decrease in SST, as observed by marine meteorological buoys in the Southwest of the East/Japan Sea. K-ORA22 exhibits a warm bias of approximately 0.50 °C around 200 m, slightly higher than those of GLORYS and BRAN, while maintaining a low salinity bias in the subsurface. Notably, K-ORA22 outperformed the other reanalyses in accurately reproducing the unique characteristics of North Pacific and East Sea intermediate waters, characterized by a salinity minimum layer. In addition, K-ORA22 stands out in its ability to accurately reproduce the Yellow Sea Cold Water Mass with a low-temperature root-mean-square error (RMSE) of 0.76 °C in the Yellow Sea (YS) region. However, it exhibited the highest RMSE for salinity in the YS region and Korea/Tsushima Strait, indicating a potential overestimation of river discharge from Korea and China. While the sea surface height (SSH) anomaly correlation of K-ORA22 did not surpass 0.80 in the entire region because of limitations in the background error covariance used, its ability to reproduce the Kuroshio path was comparable to those of other reanalysis datasets. In conclusion, K-ORA22 excels in reproducing the unique characteristics of Korean marginal seas. Still, it exhibits weaknesses, such as the overestimation of river discharge and a somewhat limited ability to simulate SSH variability, compared with other global reanalyses. We plan to enhance K-ORA22 by updating background error covariance, addressing biases related to river discharge and assimilating the best available in situ observations and satellite data.

An Algorithm to Retrieve Range Ocean Current Speed under Tropical Cyclone Conditions from Sentinel-1 Synthetic Aperture Radar Measurements Based on XGBoost

In this study, a novel algorithm to retrieve the current speed along the range direction under extreme sea states is developed from C-band synthetic aperture radar imagery. To this aim, a Sentinel-1 (S-1) dual-polarized synthetic aperture radar (SAR) dataset consisting of 2300 images is collected during 200 tropical cyclones (TCs). The dataset is complemented with collocated wave simulations from the Wavewatch-III (WW3) model and reanalysis currents from the HYbrid Coordinate Ocean Model (HYCOM). The corresponding TC winds are officially released by IFRMER, while the Stokes drift following the wave propagation direction is estimated from the waves simulated by WW3. In this study, first the dependence of wind, Stokes drift, and range current on the Doppler centroid anomaly is investigated, and then the extreme gradient boosting (XGBoost) machine learning model is trained on 87% of the S-1 dataset for range current retrieval purposes. The rest of the dataset is used for testing the retrieval algorithm, showing a root mean square error (RMSE) and a correlation coefficient (r) of 0.11 m/s and 0.97, respectively, with the HYCOM outputs. A validation against measurements collected from two high-frequency (HF) phased-array radars is also performed, resulting in an RMSE and r of 0.12 m/s and 0.75, respectively. Those validation results are better than the 0.22 m/s RMSE and 0.28 r achieved by the empirical CDOP model. Hence, the experimental results confirm the soundness of the XGBoost, exhibiting a certain improvement over the empirical model.

An integrated dataset of near-surface Eulerian fields and Lagrangian trajectories from an ocean model

A dataset consisting of numerically simulated oceanic velocities and sea surface height changes, provided conjointly from Eulerian and Lagrangian points of view, is made available as cloud-optimized archives on a cloud storage platform for unrestricted access. The Eulerian component of the dataset comprises oceanic velocity components at 0 m and 15 m depth, as well as total and steric sea surface height changes, obtained at hourly time steps for one year, with an approximate horizontal resolution of 1/25 degree on an irregular global geographical spatial grid, from the HYbrid Coordinate Ocean Model. The Lagrangian component of the dataset comprises the trajectories of particles advected in the Eulerian velocity field of the model. The particles were advected forward and backward for 30 days from a regular 1/4 degree grid in order to achieve 60-day long trajectories at 0 m and 15 m depths, with start times separated by 30 days, in 11 releases. This integrated dataset may help to link Eulerian and Lagrangian observational perspectives.

Enhancing the Resolution of Satellite Ocean Data Using Discretized Satellite Gridding Neural Networks

Ocean satellite data are often impeded by intrinsic limitations in resolution and accuracy. However, conventional data reconstruction approaches encounter substantial challenges when facing the nonlinear oceanic system and high-resolution fusion of variables. This research presents a Discrete Satellite Gridding Neural Network (DSGNN), a new machine learning method that processes satellite data within a discrete grid framework. By transforming the positional information of grid elements into a standardized vector format, the DSGNN significantly elevates the accuracy and resolution of data fusion through a neural network model. This method’s innovative aspect lies in its discretization and fusion technique, which not only enhances the spatial resolution of oceanic data but also, through the integration of multi-element datasets, better reflects the true physical state of the ocean. A comprehensive analysis of the reconstructed datasets indicates the DSGNN’s consistency and reliability across different seasons and oceanic regions, especially in its adept handling of complex nonlinear interactions and small-scale oceanic features. The DSGNN method has demonstrated exceptional competence in reconstructing global ocean datasets, maintaining small error variance, and achieving high congruence with in situ observations, which is almost equivalent to 1/12° hybrid coordinate ocean model (HYCOM) data. This study offers a novel and potent strategy for the high-resolution reconstruction and fusion of ocean satellite datasets.

Coupling of potential habitat models with particle tracking experiments to examine larval fish dispersal and connectivity in deep water regions.

Computing Lagrangian trajectories with ocean circulation models is a powerful way to infer larval dispersal pathways and connectivity. Defining release areas and timing of particles to represent larval habitat realistically is critical to obtaining representative dispersal pathways. However, it is challenging due to spatial and temporal variability in larval density. Forward-tracking particle experiments were conducted to study larval connectivity of four species (neritic or mesopelagic) in the Gulf of Mexico's (GoM) deep-water region. A seasonal climatology coupled with predicted potential larval habitat models based on generalized additive models was used to delimit the particle dispersal origin. Two contrasting mesoscale circulation patterns were examined: (1) high Loop Current (LC) intrusion, absence of recently detached LC anticyclonic eddies (LC-ACE), and no interaction between LC-ACEs and the semi-permanent cyclonic eddy (CE) in the Bay of Campeche (BoC), and (2) limited LC intrusion, a recently detached LC-ACE, and interaction between LC-ACEs and the BoC's CE. To simulate larval transport, virtual larvae were randomly released in the potential habitats and advected for 30 days with the velocity fields of the HYbrid Coordinate Ocean Model with hourly-resolution assimilation. Potential habitat location and size played a major role in dispersal and connectivity. A greater percentage of particles were retained in potential habitats restricted to the southern BoC, suggesting lower connectivity with other GoM regions than those encompassing most of the BoC or the central Gulf. Mesoscale feature interactions in the western GoM and BoC led to greater dispersion along the western basin. By contrast, the absence of ACE-CE interaction in the BoC led to greater retention and less connectivity between the southern and northern GoM. Under high LC intrusion, particles seeded north of the Yucatan Shelf were advected through the Florida Straits and dispersed within the GoM. Coupling potential habitat models with particle experiments can help characterize the dispersal and connectivity of fish larvae in oceanic systems.

Ocean component of the first operational version of Hurricane Analysis and Forecast System: Evaluation of HYbrid Coordinate Ocean Model and hurricane feedback forecasts

The first operational version of the coupled Hurricane Analysis and Forecast System (HAFSv1) launched in 2023 consists of the HYbrid Coordinate Ocean Model (HYCOM) and finite-volume cubed-sphere (FV3) dynamic atmosphere model. This system is a product of efforts involving improvements and updates over a 4-year period (2019–2022) through extensive collaborations between the Environmental Modeling Center at the US National Centers for Environmental Prediction (NCEP) and NOAA Atlantic Oceanography and Meteorology Laboratory. To provide two sets of numerical guidance, the initial operational capability of HAFSv1 was configured to two systems—HFSA and HFSB. In this study, we present in-depth analysis of the forecast skills of the upper ocean that was co-evolved by the HFSA and HFSB. We chose hurricane Laura (2020) as an example to demonstrate the interactions between the storm and oceanic mesoscale features. Comparisons performed with the available in situ observations from gliders as well as Argos and National Data Buoy Center moorings show that the HYCOM simulations have better agreement for weak winds than high winds (greater than Category 2). The skill metrics indicate that the model sea-surface temperature (SST) and mixed layer depth (MLD) have a relatively low correlation. The SST, MLD, mixed layer temperature (MLT), and ocean heat content (OHC) are negatively biased. For high winds, SST and MLT are more negative, while MLD is closer to the observations with improvements of about 8%–19%. The OHC discrepancy is proportional to predicted wind intensity. Contrarily, the mixed layer salinity (MLS) uncertainties are smaller and positive for higher winds, probably owing to the higher MLD. The less-negative bias of MLD for high winds implies that the wind-force mixing is less effective owing to the higher MLD and high buoyancy stability (approx. 1.5–1.7 times) than the observations. The heat budget analysis suggests that the maximum heat loss by hurricane Laura was O(< 3°C per day). The main contributor here is advection, followed by entrainment, which act against or with each other depending on the storm quadrant. We also found relatively large unaccountable heat residuals for the in-storm period, and the residuals notably led the heat tendency, meaning that further improvements of the subscale simulations are warranted. In summary, HYCOM simulations showed no systematic differences forced by either HFSA or HFSB.

Estimating effects of wind and waves on the Doppler centroid frequency shift for the SAR retrieval of ocean currents

Estimating the effects of wind and waves (EWW) on the Doppler centroid frequency shift is a key step in the Synthetic Aperture Radar (SAR) retrieval of ocean currents. However, available models for estimating EWW may exhibit errors as they fail to fully consider the wave and current effects or uncorrected electromagnetic pointing errors. In this study, we corrected the electromagnetic pointing error of Sentinel-1A. In particular, by matching the current data provided by the high-frequency (HF) radar, we accurately obtained the EWW from July 2020 to June 2023. By using the wind and wave parameters provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), the variation characteristics of EWW were analyzed and four geophysical model functions (GMFs) were established using different wave parameters. The application of these GMFs to the retrieval of currents was validated using the HF radar. The optimal current retrieval accuracy in terms of the time series and statistical results was then achieved using the model containing the most comprehensive wave parameters, with a bias of 0.01 m/s and a root mean square error of 0.19 m/s. The proposed model demonstrates the ability to retrieve 100 km scale eddy currents in the Gulf Stream, exhibiting a high agreement with HYbrid Coordinate Ocean Model (HYCOM) reanalysis data, with a bias and root mean square error of approximately −0.03–0.13 m/s and 0.2–0.32 m/s, respectively. The results fully demonstrate that the GMFs established in this study can facilitate the improvement of the SAR retrievals of ocean currents. Moreover, the ability of the proposed model to capture the velocity variations of subscale eddy currents is proved, providing an important tool for oceanographic research.

Gap-filling techniques applied to the GOCI-derived daily sea surface salinity product for the Changjiang diluted water front in the East China Sea

Abstract. The spatial and temporal resolutions of contemporary microwave-based sea surface salinity (SSS) measurements are insufficient. Thus, we developed a gap-free gridded daily SSS product with higher spatial and temporal resolutions, which can provide information on short-term variability in the East China Sea (ECS), such as the front changes by Changjiang diluted water (CDW). Specifically, we conducted gap-filling for daily SSS products based on the Geostationary Ocean Color Imager (GOCI) with a spatial resolution of 1 km (0.01°), using a machine learning approach during the summer seasons from 2015 to 2019. The comparison of the Soil Moisture Active Passive (SMAP), Copernicus Marine Environment Monitoring Service (CMEMS), and Hybrid Coordinate Ocean Model (HYCOM) SSS products with the GOCI-derived SSS over the entire SSS range showed that the SMAP SSS was highly consistent, whereas the HYCOM SSS was the least consistent. In the < 31 psu range, the SMAP SSS was still the most consistent with the GOCI-derived SSS (R2=0.46; root mean squared error: RMSE = 2.41 psu); in the > 31 psu range, the CMEMS and HYCOM SSS products showed similar levels of agreement with that of the SMAP SSS. We trained and tested three machine learning models – the fine trees, boosted trees, and bagged trees models – using the daily GOCI-derived SSS as output, including the three SSS products, environmental variables, and geographical data. We combined the three SSS products to construct input datasets for machine learning. Using the test dataset, the bagged trees model showed the best results (mean R2=0.98 and RMSE = 1.31 psu), and the models that used the SMAP SSS as input had the highest level. For the dataset in the > 31 psu range, all the models exhibited similarly reasonable performances (RMSE = 1.25–1.35 psu). The comparison with in situ SSS data, time series analysis, and the spatial SSS distribution derived from models showed that all the models had proper CDW distributions with reasonable RMSE levels (0.91–1.56 psu). In addition, the CDW front derived from the model gap-free daily SSS product clearly demonstrated the daily oceanic mechanism during the summer season in the ECS at a detailed spatial scale. Notably, the CDW front in the zonal direction, as captured by the Ieodo Ocean Research Station (I-ORS), moved approximately 3.04 km d−1 in 2016, which is very fast compared with the cases in other years. Our model yielded a gap-free gridded daily SSS product with reasonable accuracy and enabled the successful recognition of daily SSS fronts at the 1 km level, which was previously not possible with ocean color data. Such successful application of machine learning models can further provide useful information on the long-term variation of daily SSS in the ECS. The gridded gap-free SSS dataset at 0.01°×0.01° spatial resolution is freely available at https://doi.org/10.22808/DATA-2023-2 (Shin et al., 2023).

Wind‐Induced Quasi‐Seasonal and Quasi‐Monthly Variations of Near‐Bottom Temperature on the Chukchi Slope of the Southwestern Canada Basin

AbstractThe time series of near‐bottom temperatures collected from September 2018 until August 2020 from an array of three current‐ and pressure‐recording inverted echo sounders showed quasi‐seasonal and quasi‐monthly (∼28 days) variations at a depth of ∼1,300 m near the Chukchi slope in the western Arctic Ocean. They revealed an increase of ∼0.1°C during the winter‐spring period compared with the summer‐fall period. These variations were observed in the data‐assimilated Hybrid Coordinate Ocean Model (HYCOM) outputs near the observation site (correlation coefficient >0.7). They confirmed that variations in near‐bottom temperature are related to changes in the intensity of the Atlantic Water (AW) boundary current, concurrent with the deepening of the lower AW layer by approximately 50 m. The difference in sea surface height (SSH) between the Canada Basin and the Chukchi Shelf increased because of the negative wind stress curl (WSC) and retarded the AW boundary current according to the geostrophic effect. When the near‐bottom temperature increased during the winter‐spring period, the SSH in the Chukchi Shelf was lower than that in the summer‐fall period because of the less negative WSC. Quasi‐monthly variations were related to SSH on the Chukchi Shelf owing to the negative WSC. HYCOM outputs from 1994 to 2015 showed that the AW boundary current weakened more recently than in the past due to the increased melting of sea ice. The results imply that a longer sea‐ice‐free season in the Arctic amplifies changes in the AW boundary current and deep ocean temperature owing to increased atmospheric forcing.

Evaluation of a 4DVAR Assimilation System in the California Current at the SWOT Calibration/Validation Site

Abstract This study evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean (ECCO) data assimilation (DA) framework to a submesoscale-resolving model [Massachusetts Institute of Technology General Circulation Model (MITgcm), at 1-km grid resolution]. This is in preparation for future studies to understand and assimilate the novel swath measurements of sea surface height from the Surface Water and Ocean Topography (SWOT) satellite mission. The model domain is centered at the SWOT calibration/validation (CalVal) site, located 300 km offshore of Monterey Bay, California. We assimilate vertical profiles of temperature and salinity from a linear array of three SWOT prelaunch CalVal moorings, between September and December 2019. Two model solutions are analyzed: 1) a nonassimilating forward simulation termed “first-guess” and 2) an optimized solution that assimilates the in situ observations. Both runs are nested within the global 1/12° Hybrid Coordinate Ocean Model that uses Navy Coupled Ocean Data Assimilation (HYCOM/NCODA) analysis. We evaluate the performance by comparing the two model solutions against assimilated and withheld in situ observations. We show that by assimilating hydrographic data, the model performance over the first-guess solution is improved with an error-to-observation reduction of 30%–45% for temperature, 14%–41% for salinity, and 44%–56% for steric height. Over the study period, the average steric height error at the three assimilated moorings was 1.27 cm for the optimized solution versus 2.6 cm for the first-guess solution. A comparison to withheld glider observations shows that the optimized solution outperforms the first-guess solution with an error-to-observation reduction of approximately 38% in steric height (1.5 versus 2.4 cm). This study indicates, for the first time, that the MITgcm–ECCO framework can be successfully applied to the reconstruction of submesoscale ocean variability, via the nesting of a high-resolution regional domain into a global outer domain.

Surface and Sub‐Surface Kinetic Energy Wavenumber‐Frequency Spectra in Global Ocean Models and Observations

AbstractThis paper examines spectra of horizontal kinetic energy (HKE) in the surface and sub‐surface ocean, with an emphasis on internal gravity wave (IGW) motions, in global high‐resolution ocean simulations. Horizontal wavenumber‐frequency spectra of surface HKE are computed over seven oceanic regions from two global simulations of the HYbrid Coordinate Ocean Model (HYCOM) and three global simulations of the Massachusetts Institute of Technology general circulation model (MITgcm). In regions with high IGW activity, high surface HKE variance in the horizontal wavenumber‐frequency spectra is aligned along IGW linear dispersion curves. For both HYCOM and MITgcm, and in almost all regions, finer horizontal resolution yields more energetic supertidal IGW continuum spectra. The ratio of high‐horizontal‐wavenumber variance in semi‐diurnal and supertidal motions relative to lower‐frequency motions, a quantity of great interest for swath altimetry, depends on the model employed and the horizontal resolution within the model, implying that quantitative predictions of the partition between low‐ and high‐frequency motions taken from particular simulations should be treated with care. The frequency‐vertical wavenumber spectra, frequency spectra, and vertical wavenumber spectra from the models are compared to spectra computed from McLane profilers at nine locations. In general, MITgcm spectra match the McLane profiler spectra more closely at high frequencies (|ω| > 4.5 cpd). In both models, vertical wavenumber spectra roll off more steeply than observations at high vertical wavenumbers (m > 10−2 cpm). The vertical wavenumber spectra in such models is an important target for improvement, due to turbulence production and dissipation that takes place at high vertical wavenumbers.

Gulf Stream Effects on Sea Level Oscillations: Enhancing Performance of a Coastal and Estuarine Model Nested into Global Model through Modified Boundary Conditions

This study investigates the effects of the gulf stream (GS) on sea-level oscillations across various time scales and assesses the performance of a coastal and estuarine model nested within a global model in simulating these variations. It aims to improve boundary conditions to simulate sea-level oscillations more accurately by considering the influence of GS flow. An inverse correlation is observed between observed sea-level oscillation and GS flow, which becomes more pronounced over longer time scales. Using Delft3D, a high-resolution coastal and estuarine model is developed to simulate circulation dynamics in the central Indian River Lagoon (IRL), FL, and adjacent coastal areas on the Florida east coast. The model is nested into the HYCOM (Hybrid Coordinate Ocean Model), and meteorological forcings are derived from the NARR (North American Regional Reanalysis) model. The model demonstrates satisfactory performance across key parameters, including tide, salinity, water temperature, and currents. However, there remains a noticeable difference between the modeled and observed data. To address this, the model is executed with modified flow boundary conditions at eastern boundary nodes, integrating HYCOM tide, and observing low-frequency sea-level variations. The implementation of the new boundary conditions results in an improved simulation of sea-level oscillations. This study presents the conceptual framework and detailed methodologies employed in the creation of a high-resolution model tailored for estuarine and coastal areas nested into global models capable of satisfactorily simulating sea-level oscillations even when the global model does not represent GS effects.

A Technique for SAR Significant Wave Height Retrieval Using Azimuthal Cut-Off Wavelength Based on Machine Learning

A Technique for SAR Significant Wave Height Retrieval Using Azimuthal Cut-Off Wavelength Based on Machine Learning

Mesoscale eddies in the Gulf of Mexico: A three-dimensional characterization based on global HYCOM

The Gulf of Mexico (GoM) is characterized by strong mesoscale eddy activities that have been studied extensively, yet the comprehensive three-dimensional (3-D) kinematic properties of GoM eddies are still not well documented. In this study, the 3-D mesoscale eddy activities in the upper layer (0–800 m) of the GoM are characterized using 14-year (1997–2010) global Hybrid Coordinate Ocean Model (HYCOM) outputs. Most eddies in the upper layer (both cyclonic and anticyclonic) have radii of ∼30–60 km and lifespans shorter than 30 days. The spatial distributions of GoM eddies do not vary much with depth, while their intensity decreases with depth. The size of cyclonic eddies does not vary much with depth, while the size of anticyclonic eddies decreases slightly with depth. Cyclonic eddies are often found to be generated in the eastern GoM (especially in the Loop Current region), the Bay of Campeche, and on the continental slope of the Campeche Bank, while anticyclonic eddies are often generated on the northeastern and northwestern GoM continental slopes, and in the central GoM (near 24°N) and the Bay of Campeche (92–94°W). In addition, long-lived GoM eddies (e.g., lifespan >150 days) tend to have intermediate eddy intensity (e.g., 0.13–0.32 for cyclonic eddies at the 10 m level). Both cyclonic and anticyclonic eddies are found to play an important role in the horizontal and vertical transport of heat and salt, and eddy-induced anomalies of water temperature and salinity at both surface and subsurface are generally more pronounced in the eastern GoM than in the western GoM.

Numerical Model Test of Spilled Oil Transport Near the Korean Coasts Using Various Input Parametric Models

Oil spills pose significant threats to marine ecosystems, human health, socioeconomic aspects, and coastal communities. Accurate real-time predictions of oil slick transport along coastlines are paramount for quick preparedness and response efforts. This study used an open-source OpenOil numerical model to simulate the fate and trajectories of oil slicks released during the 2007 Hebei Spirit accident along the Korean coasts. Six combinations of input parameters, derived from a five-day met-ocean dataset incorporating various hydrodynamic, meteorological, and wave models, were investigated to determine the input variables that lead to the most reasonable results. The predictive performance of each combination was evaluated quantitatively by comparing the dimensions and matching rates between the simulated and observed oil slicks extracted from synthetic aperture radar (SAR) data on the ocean surface. The results show that the combination incorporating the Hybrid Coordinate Ocean Model (HYCOM) for hydrodynamic parameters exhibited more substantial agreement with the observed spill areas than Copernicus Marine Environment Monitoring Service (CMEMS), yielding up to 88% and 53% similarity, respectively, during a more than four-day oil transportation near Taean coasts. This study underscores the importance of integrating high-resolution met-ocean models into oil spill modeling efforts to enhance the predictive accuracy regarding oil spill dynamics and weathering processes.

Extraction of persistent lagrangian coherent structures for the pollutant transport prediction in the Bay of Bengal

Lagrangian Coherent Structures (LCS) are the hidden fluid flow skeletons that provide meaningful information about the Lagrangian circulation. In this study, we computed the monthly climatological LCSs (cLCS) maps utilizing 24 years (1994–2017) of HYbrid Coordinate Ocean Model (HYCOM) currents and ECMWF re-analysis winds in the Bay of Bengal (BoB). The seasonal reversal of winds and associated reversal of currents makes the BoB dynamic. Therefore, we primarily aim to reveal the cLCSs associated with seasonal monsoon currents and mesoscale (eddies) processes over BoB. The simulated cLCS were augmented with the complex empirical orthogonal functions to confirm the dominant lagrangian transport pattern features better. The constructed cLCS patterns show a seasonal accumulation zone and the transport pattern of freshwater plumes along the coastal region of the BoB. We further validated with the satellite imagery of real-time oil spill dispersion and modelled oil spill trajectories that match well with the LCS patterns. In addition, the application of cLCSs to study the transport of hypothetical oil spills occurring at one of the active oil exploration sites (Krishna-Godavari basin) was described. Thus, demonstrated the accumulation zones in the BoB and confirmed that the persistent monthly cLCS maps are reasonably performing well for the trajectory prediction of pollutants such as oil spills. These maps will help to initiate mitigation measures in case of any occurrence of oil spills in the future.

Acoustic tomographic inversion of 3D temperature fields with mesoscale anomaly in the South China Sea

Acoustic tomographic inversion is based on travel times measured along the transmission paths between all station pairs to reconstruct three-dimensional temperature structures with mesoscale anomalies. In this study, tomographic simulation experiments were designed based on the Hybrid Coordinate Ocean Model (HYCOM) reanalysis data to reconstruct mesoscale phenomena from travel time data obtained from five, seven, and nine stations in the South China Sea over a domain of 100 × 100 km. The travel times for each station pair were calculated in the vertical section using the Bellhop acoustic ray simulation method. Six Empirical orthogonal function (EOF) modes of sound speed along the sound transmission paths in a vertical slice were used to formulate the inversion equations. The horizontal-slice distributions of temperature in the tomography domain were reconstructed using the grid-segmented method for each depth layer. For station-to-station distances greater than 100 km, the performance of inversion was best for the seven-station case rather than for the nine-station case, with the highest horizontal resolution of the three cases. This case study concluded that the seven-station case rather than the nine-station case provided an optimal station number for reconstructing the three-dimensional temperature fields.