Regional Ocean Modeling System Research Articles

The vortex splitting process from interaction between a mesoscale vortex and two islands

Mesoscale vortices are major carriers of oceanic material and energy transfer, transporting large amounts of high-energy, temperature-anomalous water bodies during their movement. This significantly impacts both the ocean and the atmosphere. Based on the distribution of the North Brazil Curren rings and the Lesser Antilles in the eastern Caribbean Sea, we use the Regional Ocean Model System ocean circulation model to construct an idealized vortex. Simulations are conducted by varying the distances between the two islands and the scales of the islands to analyze how different parameters affect the vortex path and structural evolution. Using theoretical derivation and numerical simulation results, we construct a dimensionless parameter involving vortex diameter, island diameter, and the distance between the islands to determine the conditions under which vortex splitting occurs. The reliability of this dimensionless parameter is verified using experimental data and satellite data from St. Vincent and Barbados from April 6 to May 6, 2000.

The Role of Benthic Fluxes in Acidifying the Bottom Waters in the Northern Gulf of Mexico Hypoxic Zone Based on an Updated Water Column Biogeochemical‐Seabed Diagenetic and Sediment Transport Model

AbstractThe seabed and the water column are tightly coupled in shallow coastal environments. Numerical models of seabed‐water interaction provide an alternative to observational studies that require concurrent measurements in both compartments, which are hard to obtain and rarely available. Here, we present a coupled model that includes water column biogeochemistry, seabed diagenesis, sediment transport and hydrodynamics. Our model includes realistic representations of biogeochemical reactions in both seabed and water column, and fluxes at their interface. The model was built on algorithms for seabed‐water exchange in the Regional Ocean Modeling System and expanded to include carbonate chemistry in seabed. The updated model was tested for two sites where benthic flux and porewater concentration measurements were available in the northern Gulf of Mexico hypoxic zone. The calibrated model reproduced the porewater concentration‐depth profiles and benthic fluxes of O2, dissolved inorganic carbon (DIC), TAlk, NO3 and NH4. We used the calibrated model to explore the role of benthic fluxes in acidifying bottom water during fair weather and resuspension periods. Under fair weather conditions, model results indicated that bio‐diffusion in sediment, labile material input and sediment porosity have a large control on the importance of benthic flux to bottom water acidification. During resuspension, the model indicated that bottom water acidification would be enhanced due to the sharp increase of the DIC/TAlk ratio of benthic fluxes. To conclude, our model reproduced the seabed‐water column exchange of biologically important solutes and can be used for quantifying the role of benthic fluxes in driving bottom water acidification over continental shelves.

A Study on the Impact of Vertical Grid Parameter Perturbations in the Regional Ocean Modeling System

In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

A high resolution hydrodynamic-biogeochemical-oyster-filtration model predicts that the presence of oysters (Crassostrea virginica) can improve, or reduce, water quality depending upon oyster abundance and location

The eastern oyster (Crassostrea virginica) provides numerous ecosystem services such as building reef habitat, clarifying the water by filtering seston, and reducing excess nitrogen when their biodeposits are denitrified. Some of these ecosystem services have been extensively studied using two-dimensional and three-dimensional (3D) models. Yet, the relationship between oyster abundance, their filtration and biodeposition rates, and associated water quality metrics has not been estimated with high-resolution models that include biodeposit resuspension as well as simulation of 3D processes in the sub-tributaries where oysters are abundant. To undertake these estimates, a 3D Regional Ocean Modeling System (ROMS) framework, comprised of a coupled hydrodynamic-water quality model with an oyster filtration and biodeposition sub-model, was implemented over a fine-resolution model grid (120–150 m) of the Choptank River on the eastern shore of Chesapeake Bay, U.S.A. After validation with data from 20 cruises between May and September 2010, the model was used to predict seven variables associated with water quality in simulations with zero, recent, and 50x recent abundances of oysters. Results indicated that improvement in the seven water quality variables differed in response to the abundance of oysters and between regions in the Choptank River. In line with expectations, the water quality metrics improved with increasing oyster abundance in the shallow and retentive sub-tributaries of Broad and Harris Creeks. In contrast, in the deeper and more flushed mainstem of the Choptank River, some water quality metrics deteriorated when recent abundances of oysters were added to the model compared to the simulation with zero oysters and the same metrics improved when oyster abundances were increased by 50x. Overall, model results indicated that the many complex physical and biogeochemical processes that influence the effect of oysters on water quality resulted in differing responses to oysters across different systems. In addition, this study introduces a high-resolution, predictive tool that could be used to estimate the number of oysters needed to meet water quality thresholds in specific systems in support of ecosystem management.

Leveraging ecological indicators to improve short term forecasts of fish recruitment

AbstractForecasting the recruitment of fish populations with skill has been a challenge in fisheries for over a century. Previous large‐scale meta‐analyses have suggested linkages between environmental or ecosystem drivers and recruitment; however, applying this information in a management setting remains underutilized. Here, we use a well‐studied database of groundfish assessments from the West Coast of the USA to ask whether environmental variables or ecosystem indicators derived from long‐term monitoring datasets offer an improvement in our ability to skilfully forecast fish recruitment. A secondary question is which types of modelling approaches (ranging from linear models to non‐parametric methods) yield the best forecast skill. Third, we examine whether simultaneous forecasting of multiple species offers an advantage over generating species‐specific forecasts. We find that for approximately one third of the 29 assessed stocks, ecosystem indicators from juvenile surveys yields the highest out of sample predictive skill compared to other covariates (including environmental variables from Regional Ocean Modeling System output) or null models. Across modelling approaches, our results suggest that simpler linear modelling approaches do as well or better than more complicated approaches (reducing out of sample Root Mean Square Error by ~40% compared to null models), and that there appears to be little benefit to performing multispecies forecasts instead of single‐species forecasts. Our results provide a general framework for generating recruitment forecasts in other species and ecosystems, as well as a benchmark for future analyses to evaluate skill. The most promising applications are likely for species that are short lived, have relatively high recruitment variability, and moderate amounts of age or length data. Forecasts using our approach may be useful in identifying covariates or mechanisms to include in operational assessments but also provide qualitative advice to managers implementing ecosystem based fisheries management.

Improving the estimation of direct release rates and transport processes from the Fukushima Daiichi Nuclear Power Plant accident using higher-resolution oceanic dispersion model

A series of accidents at the Fukushima Daiichi Nuclear Power Station (F1NPS), following the 11 March 2011 earthquake and tsunami, resulted in the release of radioactive substances into the ocean. In particular, the release of large amounts of radioactive caesium has damaged the fishing industry, leading to voluntary restrictions on fishing and shipping. Oceanic dispersion simulations based on estimates of the pathways and fluxes of radioactive materials provide useful information for assessing the environmental impacts and formulating measures to mitigate the effects of the accident. For the direct release rate from the F1NPS site, an estimation method was developed using the results from nearby monitoring, and the seawater exchange rate was estimated in target volume using a numerical simulation. However, the influence of volume on the seawater exchange rate was not considered. Appropriate volumes must be considered when estimating the effects of future accidents. In addition, the directional coastal transport was underestimated in the simulations of the F1NPS accident because of the low resolution. To estimate the pathways and fluxes of radioactive material to the ocean and understand the distribution of the concentration of radioactive material based on ocean dispersion simulations, a study was conducted using a higher-resolution model. The horizontal resolution of the conventional ocean dispersion model Regional Ocean Modelling System (ROMS), was increased from 1 km to 200 m. The optimal settings of the seawater exchange rate were investigated, and the radioactive caesium transport process in the coastal direction was more accurately reflected. We found that the conventional volume for determining the seawater exchange rate, including the locations of release sources and observation points, is optimal. The validity of this finding was confirmed using experimental equations from previous oceanic tracer release experiments. To estimate future release rates, it an appropriate volume must be defined, for example, depending on the distance between the locations of the release sources and the observation point. In addition, improvements in the accuracy of the simulation of the coastal transport process were observed owing to the higher resolution, which increased reproducibility. However, with a horizontal resolution of 200 m, problems with repeatability near the harbours arose. A higher resolution, achieved using nesting or other methods, would be desirable to deal with releases smaller than those in the F1NPS accident.

The combination of detection and simulation for the distribution and sourcing of microplastics in Shing Mun River estuary, Hong Kong

For the first time, combined detection and simulation was performed on microplastic (MP) debris in surface water, sediment, and oyster samples at ten coastal sites of Shing Mun River estuary, Hong Kong at different tidal conditions. The MP debris were extracted and detected using Fourier transform infrared (FT-IR) spectroscopy, and the simulation was conducted using Weather Research & Forecasting Model (WRF) / Regional Ocean Modelling System (ROMS) coupled hydro-dynamic modelling and the subsequent Lagrangian particle tracking.The results demonstrated the majority of polyethylene (with partial chlorine substitution) debris among all the MPs found, and great spatial and tidal variabilities of MP concentrations were observed. The combination of MP observation and simulations referred to the interpretation that a considerable percentage of MPs found in this study originated from South China Sea. Those MPs were probably transported to Tolo Harbour through sea currents and drifted inshore and offshore with tides. This study provided baseline measures of MP concentrations in Shing Mun River estuary and comprehensive understanding for how MPs transport and distribute within a dynamic estuarine system.

Impact of Satellite Wind on Improving Simulation of the Upper Ocean Response to Tropical Cyclones

Accurate modeling of the ocean response to tropical cyclones (TCs) requires high-quality wind fields to force ocean models. In this study, blended wind fields are generated using multi-source satellite data and the Climate Forecast System Reanalysis (CFSR) wind data. We utilize the hybrid wind fields to drive the Regional Ocean Modeling System (ROMS) for simulating oceanic dynamic and thermodynamic parameters. The model’s simulated ocean surface and sub-surface temperatures, as well as current speeds, are generally consistent with satellite and in situ observations collected during TC Winston and Freddy. The results are significantly better than those simulated by ROMS using wind forcing from CFSR alone. These results suggest that incorporating satellite wind data into the atmospheric forcing has the potential to enhance vertical mixing and improve simulations of the upper ocean response to TCs.

On the evidence of helico-spiralling recirculation within coherent cores of eddies using Lagrangian approach

Oceanic eddies exhibit remarkable coherence and longevity compared to other transient features in the surrounding flow. They possess the ability to transport properties over extensive distances while maintaining their material identity intact. The Lagrangian Coherent Structure (LCS) framework has proven effective in capturing these coherent eddies, where they display a solid-body-like rotation. Although various LCS approaches have been employed to investigate different facets of coherent eddies, a comprehensive understanding of their three-dimensional structures and internal dynamics remains elusive. This study aims to advance our comprehension of coherent eddies’ structural characteristics and delve into the precise nature of their internal dynamics by utilizing the Lagrangian Averaged Vorticity Deviation approach. Two eddies, one cyclonic and the other anti-cyclonic, were chosen from a high-resolution simulation carried out in the Bay of Bengal using the Regional Ocean Modeling System (ROMS). The findings unveil that these eddies have three-dimensional coherent cores resembling gently tapered cones that are broader at the surface and gradually narrow towards the bottom. Intriguingly, the dynamically coherent core of these eddies exhibits simultaneous upwelling and downwelling while maintaining their volumes during advection due to persistent material coherence. The three-dimensional trajectories followed by the fluid parcels inside the coherent core are helical. Their two-dimensional horizontal projections show alternating spiral bands of upwelling and downwelling which are the manifestations of Vortex Rossby Waves. These observations lead to a conceptual framework of a three-dimensional helico-spiralling recirculation pattern within the coherent cores of eddies.

Tropical Atmospheric Intraseasonal Oscillations Leading to Sea Level Extremes in Coastal Indonesia during Recent Decades

Abstract Coastal flooding induced by sea surface high extreme (HEX) events is an increasing risk to human society and infrastructure as both urban growth in coastal areas and anthropogenic sea level rise continue, especially for island nations like Indonesia. This paper investigates the role of atmospheric intraseasonal oscillations (ISOs), which are dominated by the Madden–Julian oscillation (MJO), in forcing HEXs on the coasts of Indonesia bordering the Indian Ocean. We use satellite altimetry data from 1993 to 2021 and tide gauge observations to detect HEXs, and modeling experiments using both the Regional Ocean Modeling System and a Bayesian dynamic linear model to understand the forcing and processes. We find that HEXs exhibit strong seasonality, with most events occurring during boreal winter (December–February) and spring (March–May) that are dominated by seasonal-to-decadal and intraseasonal variability respectively. In 32% of the 56 HEX events detected, the amplitude of ISO-induced sea level anomalies (SLAs) exceeds that of seasonal-to-decadal SLAs. Surface wind stress associated with atmospheric ISOs is the major forcing for intraseasonal SLAs, and both the remote westerly wind stress from the Indian Ocean equator and northwesterly longshore wind stress at the Indonesian coasts play important roles in driving the HEXs. The MJO is the dominant cause of ISO-dominated HEXs and its impact shows strong seasonal differences. Spring MJOs are associated with stronger convective anomalies over the eastern Indian Ocean equator that drive stronger zonal winds across the equatorial basin that lead to more HEX events compared to winter MJOs when the convection is shifted southward.

Interannual Variability of Marine Nitrogen Fixation in the Western Tropical Atlantic

AbstractN2 fixation is a central process of the marine nitrogen cycle, yet little is known about how this process varies from year‐to‐year. Here, we investigate this variability in the Western Tropical Atlantic (WTA), a region where N2 fixation is prevalent, fueled, in part, by the nutrient input from the Amazon River. We use hindcast simulations from 1983 through 2019 with the Regional Oceanic Modeling System (ROMS) coupled to the Biogeochemical Elemental Cycling (BEC) model expanded to include Diatom‐Diazotroph Assemblages (DDAs). Throughout the WTA, we find a substantial level of interannual variability of N2 fixation, altering it by up to 33%, and locally by up to nearly 60%. Part of this interannual variability is driven by variations in the Amazon River discharge, which during high discharge events leads to reduced rates in the upper parts of the plume and strongly enhanced rates in the downstream part. This dipole pattern is a consequence of the riverine inputs of phosphorus and the competition with non‐diazotrophs for this limiting resource. Another part of the N2 fixation variability is driven by the Atlantic Meridional Mode (AMM), and the El Niño‐Southern Oscillation (ENSO). These processes alter N2 fixation primarily through the supply of the limiting nutrients phosphorus and iron by vertical mixing, while the role of top‐down control through grazing is relatively limited in our model. The high, and so far not well recognized interannual N2 fixation variability can lead to erroneous extrapolation of field measurements and inaccuracies in the marine nitrogen budget, if unaccounted for.

Model validation and applications of wave and current forecasts from the Hong Kong Observatory's Operational Marine Forecasting System

The Hong Kong Observatory has been running an Operational Marine Forecasting System (OMFS) adapted from the Regional Ocean Modelling System (ROMS) coupled with the WaveWatch III and SWAN wave models to provide wave, current and sea temperature forecasts up to 144 h twice a day since December 2021. To facilitate users’ interpretation of model forecasts of significant wave height and current speed in coastal predictions and open seas which are of particular significance in high wind situations, model forecasts were validated against moored buoy observations and wave recorder measurements near the shores of Hong Kong and drifting buoy data over the South China Sea, as well as Mercator Ocean model reanalysis in 2022. The validation results showed that the wave forecasts generally agreed well with the buoy observations with coefficient of determination (R2) of around 0.7 and root-mean-square error (RMSE) of less than 0.2 m up to 72 h ahead. The R2 for sea current forecasts ranged between 0.4 and 0.6, and the RMSE was around 8 to 11 cm/s in near shores up to T + 144 forecast hours. Validation against drifting buoy demonstrated that the trend of current forecasts generally agreed well with the measurements. RMSE of surface current forecasts over open seas ranged from 19 cm/s for 24-hour forecast to around 30 cm/s for 144-hour forecast when compared against Mercator Ocean reanalysis. Results from the current downscaling approach could serve as a benchmark reference for HKO to enhance OMFS in the future. In this paper, applications of model forecasts in the provision of marine weather services in Hong Kong are also introduced.

Assessing the impact of subsurface temperature observations from fishing vessels on temperature and heat content estimates in shelf seas: a New Zealand case study using Observing System Simulation Experiments

We know that extremes in ocean temperature often extend below the surface, and when these extremes occur in shelf seas they can significantly impact ecosystems and fisheries. However, a key knowledge gap exists around the accuracy of model estimates of the ocean’s subsurface structure, particularly in continental shelf regions with complex circulation dynamics. It is well known that subsurface observations are crucial for the correct representation of the ocean’s subsurface structure in reanalyses and forecasts. While Argo floats sample the deep waters, subsurface observations of shelf seas are typically very sparse in time and space. A recent initiative to instrument fishing vessels and their equipment with temperature sensors has resulted in a step-change in the availability of in situ data in New Zealand’s shelf seas. In this study we use Observing System Simulation Experiments to quantify the impact of the recently implemented novel observing platform on the representation of temperature and ocean heat content around New Zealand. Using a Regional Ocean Modelling System configuration of the region with 4-Dimensional Variational Data Assimilation, we perform a series of data assimilating experiments to demonstrate the influence of subsurface temperature observations at two different densities and of different data assimilation configurations. The experiment period covers the 3 months during the onset of the 2017-2018 Tasman Sea Marine Heatwave. We show that assimilation of subsurface temperature observations in concert with surface observations results in improvements of 44% and 38% for bottom temperature and heat content in shelf regions (water depths< 400m), compared to improvements of 20% and 28% for surface-only observations. The improvement in ocean heat content estimates is sensitive to the choices of prior observation and background error covariances, highlighting the importance of the careful development of the assimilation system to optimize the way in which the observations inform the numerical model estimates.

Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System

Abstract. Particle tracking is widely utilized to study transport features in a range of physical, chemical, and biological processes in oceanography. In this study, a new offline particle-tracking package, Tracker v1.1, is introduced, and its performance is evaluated in comparison to an online Eulerian dye, one online particle-tracking software package, and three offline particle-tracking software packages in a small, high-resolution model domain and a large coarser model domain. It was found that both particle and dye approaches give similar results across different model resolutions and domains when they were tracking the same water mass, as indicated by similar mean advection pathways and spatial distributions of dye and particles. The flexibility of offline particle tracking and its similarity against online dye and online particle tracking make it a useful tool to complement existing ocean circulation models. The new Tracker was shown to be a reliable particle-tracking package to complement the Regional Ocean Modeling System (ROMS) with the advantages of platform independence and speed improvements, especially in large model domains achieved by the nearest-neighbor search algorithm. Lastly, trade-offs of computational efficiency, modifiability, and ease of use that can influence the choice of which package to use are explored. The main value of the present study is that the different particle and dye tracking codes were all run on the same model output or within the model that generated the output. This allows some measure of intercomparison between the different tracking schemes, and we conclude that all choices that make each tracking package unique do not necessarily lead to very different results.

TYPHOON KARDING (NORU) STORM SURGE ANALYSIS USING THE COAWST MODELING SYSTEM

Abstract. The Philippines, frequently affected by typhoons, faces the hazard of storm surges. This study examined the Coupled-Ocean-Atmosphere-Wave-Sediment Transport Modeling System (COAWST) to simulate Typhoon Karding's September 2022 storm surge. COAWST integrates the Regional Ocean Modeling System (ROMS), Simulating WAves Nearshore (SWAN), and Weather Research and Forecasting (WRF) coupled using the Model Coupling Toolkit (MCT). Four setups were analyzed: i. ROMS only, ii. ROMS-SWAN, iii. ROMS-WRF, and iv. ROMS-SWAN-WRF, focusing on four variables: a. Surface air pressure, b. Wind speed, c. Free-surface elevation, and d. Significant wave height. Results show that the ROMS-WRF and ROMS-SWAN-WRF setups accurately simulated Typhoon Karding's track with minimal positional error and wind speed. However, the models overestimated the typhoon's minimum air pressure with p-biases of 7.74% (i and ii), 4.1% (iii), and 3.9% (iv), and RMSE values of 68.529 hPa (i and ii), 36.744 hPa (iii), and 36.789 hPa (iv). Additionally, water levels were underestimated, with RMSE ranging from 0.31 to 0.35 meters and p-biases from −72.56% to −154.89% at Baler, Aurora validation point. At the Real, Quezon validation point, RMSE and p-bias ranged from 0.30 to 0.34 meters and −84.80% to −166.44%, respectively. Nonetheless, the models were able to simulate the storm surge and significant wave height at Baler and Real points similar to recorded data, with setup iv performing best in storm surge simulation. In summary, COAWST may be employed for typhoon simulations, with coupling being able to increase accuracy.

Dynamical systems for remote validation of very high-resolution ocean models

This paper presents and investigates a novel methodology for validating high-resolution ocean models using satellite imagery. High-resolution ocean models provide detailed information in coastal areas where other available data products are too coarse. Models are usually fitted by comparing them with observations; However, accessing in situ data in all small coastal areas is not feasible, as in situ observations are scarce and obtained through dedicated ships or instruments in limited and selected regions. Our work aims to use alternative remote sensing information to overcome this challenge. The approach involves establishing connections between the satellite observations and the outcomes of various computational experiments carried out using the Regional Ocean Modeling System, which allows the selection of different parameters to run the ocean model. These choices are not fully determined a priori and each one produces distinct outputs, which are then linked to the images through dynamical systems objects. By defining a performance index, we are able to quantify which experiment provides a better representation of the local ocean state.

Assimilation of satellite swaths versus daily means of sea ice concentration in a regional coupled ocean–sea ice model

Abstract. Operational forecasting systems routinely assimilate daily means of sea ice concentration (SIC) from microwave radiometers in order to improve the accuracy of the forecasts. However, the temporal and spatial averaging of the individual satellite swaths into daily means of SIC entails two main drawbacks: (i) the spatial resolution of the original product is blurred (especially critical in periods with strong sub-daily sea ice movement), and (ii) the sub-daily frequency of passive microwave observations in the Arctic are not used, providing less temporal resolution in the data assimilation (DA) analysis and, therefore, in the forecast. Within the SIRANO (Sea Ice Retrievals and data Assimilation in NOrway) project, we investigate how challenges (i) and (ii) can be avoided by assimilating individual satellite swaths (level 3 uncollated) instead of daily means (level 3) of SIC. To do so, we use a regional configuration of the Barents Sea (2.5 km grid) based on the Regional Ocean Modeling System (ROMS) and the Los Alamos Sea Ice Model (CICE) together with the ensemble Kalman filter (EnKF) as the DA system. The assimilation of individual swaths significantly improves the EnKF analysis of SIC compared to the assimilation of daily means; the mean absolute difference (MAD) shows a 10 % improvement at the end of the assimilation period and a 7 % improvement at the end of the 7 d forecast period. This improvement is caused by better exploitation of the information provided by the SIC swath data, in terms of both spatial and temporal variance, compared to the case when the swaths are combined to form a daily mean before assimilation.

Dispersion and fate of methane emissions from cold seeps on Hikurangi Margin, New Zealand

The influence of cold seep methane on the surrounding benthos is well-documented but the fate of dissolved methane and its impact on water column biogeochemistry remains less understood. To address this, the distribution of dissolved methane was determined around three seeps on the south-east Hikurangi Margin, south-east of New Zealand, by combining data from discrete water column sampling and a towed methane sensor. Integrating this with bottom water current flow data in a dynamic Gerris model determined an annual methane flux of 3 x 105 kg at the main seep. This source was then applied in a Regional Ocean Modelling System (ROMS) simulation to visualize lateral transport of the dissolved methane plume, which dispersed over ∼100 km in bottom water within 1 year. Extrapolation of this approach to four other regional seeps identified a combined plume volume of 3,500 km3 and annual methane emission of 0.4–3.2 x 106 kg CH4 y-1. This suggests a regional methane flux of 1.1–10.9 x 107 kg CH4 y-1 for the entire Hikurangi Margin, which is lower than previous hydroacoustic estimates. Carbon stable isotope values in dissolved methane indicated that lateral mixing was the primary determinant of methane in bottom water, with potential methane oxidation rates orders of magnitude lower than the dilution rate. Calculations indicate that oxidation of the annual total methane emitted from the five seeps would not significantly alter bottom water dissolved carbon dioxide, oxygen or pH; however, superimposition of methane plumes from different seeps, which was evident in the ROMS simulation, may have localized impacts. These findings highlight the value of characterizing methane release from multiple seeps within a hydrodynamic model framework to determine the biogeochemical impact, climate feedbacks and connectivity of cold seeps on continental shelf margins.

Exploring temporal and spatial SST patterns and their impact in the Arabian Sea: Insights from the regional ocean modeling system

The Regional Ocean Modeling System (ROMS) is integrated across the Arabian Sea (AS) from 1992 to 2021 and covers 33°E to 80°E and 5°N to 32°N at high horizontal resolutions of 1/4°(∼25 km). The study demonstrates that the variability is controlled by a seasonal high-resolution setup, with superior performance for various seasons during the months of December-January-February (DJF), March-April-May (MAM), June-July-August-September (JJAS) and October–November (ON). The Sea Surface Temperature (SST) anomalies in the JJAS season werestudied. SST dominates the seasonal variability of the Indian summer monsoon (ISM). Our results show that the ROMS can simulate seasonal variability and its effects on the upper ocean properties over the AS. In addition, the impact of monthly variation is controlled. In recreating the spatio-temporal distribution of surface as well as subsurface hydrographic parameters such as surface and subsurface temperature, the simulation results are reasonable like observation and reanalysis.

Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system

Abstract. Ocean models must be regularly updated through the assimilation of observations (data assimilation) in order to correctly represent the timing and locations of eddies. Since initial conditions play an important role in the quality of short-term ocean forecasts, an effective data assimilation scheme to produce accurate state estimates is key to improving prediction. Western boundary current regions, such as the East Australia Current system, are highly variable regions, making them particularly challenging to model and predict. This study assesses the performance of two ocean data assimilation systems in the East Australian Current system over a 2-year period. We compare the time-dependent 4-dimensional variational (4D-Var) data assimilation system with the more computationally efficient, time-independent ensemble optimal interpolation (EnOI) system, across a common modelling and observational framework. Both systems assimilate the same observations: satellite-derived sea surface height, sea surface temperature, vertical profiles of temperature and salinity (from Argo floats), and temperature profiles from expendable bathythermographs. We analyse both systems' performance against independent data that are withheld, allowing a thorough analysis of system performance. The 4D-Var system is 25 times more expensive but outperforms the EnOI system against both assimilated and independent observations at the surface and subsurface. For forecast horizons of 5 d, root-mean-squared forecast errors are 20 %–60 % higher for the EnOI system compared to the 4D-Var system. The 4D-Var system, which assimilates observations over 5 d windows, provides a smoother transition from the end of the forecast to the subsequent analysis field. The EnOI system displays elevated low-frequency (>1 d) surface-intensified variability in temperature and elevated kinetic energy at length scales less than 100 km at the beginning of the forecast windows. The 4D-Var system displays elevated energy in the near-inertial range throughout the water column, with the wavenumber kinetic energy spectra remaining unchanged upon assimilation. Overall, this comparison shows quantitatively that the 4D-Var system results in improved predictability as the analysis provides a smoother and more dynamically balanced fit between the observations and the model's time-evolving flow. This advocates the use of advanced, time-dependent data assimilation methods, particularly for highly variable oceanic regions, and motivates future work into further improving data assimilation schemes.