Regional Ocean Modeling Research Articles

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.

Effects of open boundary bias correction and data assimilation in a regional ocean circulation model for the East Sea

Effects of open boundary bias correction and data assimilation in a regional ocean circulation model for the East Sea

Environmental controls and phenology of sea ice algal growth in a future Arctic

The future of Arctic sea ice algae is examined using a regional ocean and sea ice biogeochemical model, with a simulation from 1980 to 2085, considering a future scenario with strong warming. To analyze the impacts of climate change, we computed key dates in the development of sympagic blooms, corresponding to the occurrence of specific growth conditions, and designed diagnostics of ice algal phenology to estimate the onset and peak of blooms. These diagnostics help understand how the timing of light and nutrient availability governs the growth of ice algae and how environmental controls will be altered by climate change across regions. With thinner ice, photosynthetically active radiation in bottom ice will reach levels sufficient for growth earlier, resulting in a better synchrony of high levels of light and nutrients. Increases in snow cover can potentially offset the effect of thinner ice, leading to shorter periods of favorable growth conditions in certain regions. The loss of sea ice cover before the late 21st century only impacts sympagic blooms at lower latitudes, as the timing of sea ice break-up shows little change relative to other key dates at higher latitudes. In response to climate change, the model simulates a modified spatial distribution of blooms, with the emergence of highly productive areas and the loss of blooms in other regions. However, the changes in the timing of growth conditions do not substantially alter the timing of blooms, and both onset and peak ice algae see little change. The simulated lack of sensitivity of bloom onset is attributed to the delay in sea ice freeze-up projected by the model, causing a reduction of overwintering ice algae. The resulting lower initial biomass at the beginning of spring then causes a delay in the development of blooms, offsetting earlier light from thinner ice.

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.

Downscaling the ocean response to the Madden–Julian Oscillation in the Northwest Atlantic and adjacent shelf seas

Subseasonal-to-seasonal (S2S) prediction is a global effort to forecast the state of the atmosphere and ocean with lead times between two weeks and a season. This study explores the feasibility of S2S prediction of the ocean using a variety of tools including statistical analysis, a statistical-dynamical mixed layer model, and a regional, high-resolution ocean circulation model based on physical principles. Ocean predictability on S2S timescales is analyzed by compositing winter sea surface temperature (SST) anomalies in the North Atlantic with respect to the state of the Madden–Julian Oscillation (MJO). It is found that statistically significant, large-scale SST changes, particularly along the eastern seaboard of North America, can be related to the MJO. This signal is shown to be driven by anomalous air–sea heat fluxes caused by atmospheric perturbations in response to the MJO. The high-resolution model of the Gulf of Maine and Scotian Shelf is used to downscale the mean ocean response to the MJO. The model is able to capture the observed relationship between the MJO and SST in the northwest Atlantic. It is also shown that the anomalous atmospheric circulation in response to the MJO leads to anomalous upwelling on the Scotian Shelf. Overall, this study demonstrates that it is feasible, and of value, to use regional ocean models for S2S prediction.

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.

Using Shelf‐Edge Transport Composition and Sensitivity Experiments to Understand Processes Driving Sea Level on the Northwest European Shelf

AbstractVariability in ocean currents, temperature and salinity drive dynamic sea level (DSL) variability on the Northwest European Shelf (NWES). It is dominated by mass variations, with steric signals relatively small. A mechanistic explanation of how ocean dynamics relates to the mass component of NWES sea level variability is required. We use regional ocean model experiments to isolate sources of variability and then investigate the effect on monthly to‐interannual DSL variability together with the simulated momentum budgets along the shelfbreak. Regional (local) wind and non‐regional (remote) forcing are important on the NWES. For the local wind forcing, the net mass flux onto the shelf, which drives a shelf‐mean mode of DSL variability, results from a combination of surface Ekman, bottom Ekman and geostrophic flows and explains 73% of the variance in transport across the shelf‐edge. The geostrophic flow is closely related to wind stress with a flow about half that of surface Ekman transport but in the opposite direction. For the remotely forced mass‐flux across the shelf‐edge, the geostrophic component explains 62% of the variance and bottom friction plays an important indirect role. The remotely forced variability, while relatively spatially uniform, is more important for explaining DSL variance over the western NWES. This mode of variability is sensitive to signals propagating northward via a thin strip of the southern boundary near the Portuguese coast, consistent with coastal trapped wave signals. It also appears to drive steric height in the Bay of Biscay, which is related to DSL on the shelf.

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.

Eastern Boundary Upwelling Systems in Ocean–Sea Ice Simulations Forced by CORE and JRA55-do: Mean State and Variability at the Surface

Abstract In this paper we summarize improvements in climate model simulation of eastern boundary upwelling systems (EBUS) when changing the forcing dataset from the Coordinated Ocean-Ice Reference Experiments (CORE; ∼2° winds) to the higher-resolution Japanese 55-year Atmospheric Reanalysis for driving ocean–sea ice models (JRA55-do, ∼0.5°) and also due to refining ocean grid spacing from 1° to 0.1°. The focus is on sea surface temperature (SST), a key variable for climate studies, and which is typically too warm in climate model representation of EBUS. The change in forcing leads to a better-defined atmospheric low-level coastal jet, leading to more equatorward ocean flow and coastal upwelling, both in turn acting to reduce SST over the upwelling regions off the west coast of North America, Peru, and Chile. The refinement of ocean resolution then leads to narrower and stronger alongshore ocean flow and coastal upwelling, and the emergence of strong across-shore temperature gradients not seen with the coarse ocean model. Off northwest Africa the SST bias mainly improves with ocean resolution but not with forcing, while in the Benguela, JRA55-do with high-resolution ocean leads to lower SST but a substantial bias relative to observations remains. Reasons for the Benguela bias are discussed in the context of companion regional ocean model simulations. Finally, we address to what extent improvements in mean state lead to changes to the monthly to interannual variability. It is found that large-scale SST variability in EBUS on monthly and longer time scales is largely governed by teleconnections from climate modes and less sensitive to model resolution and forcing than the mean state.

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.

Impact of bathymetry on Indian Ocean circulation in a nested regional ocean model

The Regional Indian Ocean model based on Modular Ocean Model (MOM4p1) was used to understand the importance of a realistic representation of bathymetry on Ocean General Circulation. The model has 1/4° uniform horizontal resolution and is forced with Coordinated Ocean-Ice Reference Experiments (CORE-II) inter-annual forcing with two simulations named BLND (realistic bathymetry) and OM3 (smoothed bathymetry), which only differ in the representation of bathymetry for the years 1992–2005. We also used recent reanalysis products from ORAS5 and SODA3 and ADCP observation to compare the subsurface currents. We show that by the inclusion of realistic bathymetry, there is a significant improvement in the upper ocean salinity, temperature, and currents, particularly near the coast. The salinity and temperature of the upper ocean are very close to the observed value near the coast. The bias in the salinity and temperature was reduced to half in BLND simulation compared to OM3, which led to a more realistic East India Coastal Current (EICC). We show the first evidence of a basin-wide cyclonic gyre over the Bay of Bengal at 1000 m depth during spring, which is just opposite to that of a basin-wide anti-cyclonic gyre at the surface. We found the presence of poleward EICC during spring at 1000 m and 2000 m depth, which is opposite to that of the surface. The presence of this deeper EICC structure is completely absent during fall. We show the presence of a boundary current along the coast of Andaman and Nicobar Island at a depth of 2000 m. The observed Wyrtki Jet (WJ) magnitude and spatial structure are most realistically reproduced in BLND simulation as compared to OM3 simulations. Both ORAS5 and SODA reanalysis products underestimate the WJ magnitude. The presence of the Maldives Islands is responsible for the westward extent of Equatorial Under Current (EUC). The presence of Maldives also creates wakes on the leeward side in the EUC zonal current. During fall, EUC is better defined in the eastern Equatorial Indian Ocean and lies at a depth of between 50 and 100 m, unlike its spring counterpart, in which its core is located slightly deeper, between 100 and 150 m depth. During peak summer months, June–July, a strong eastward zonal jet is present at 1000 m depth, similar to Wyrtki Jet (WJ). Inter-monsoon Jets, i.e., spring and fall jets, are also seen but are in the opposite direction, i.e., westward, unlike eastward in WJ.

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.

An interactive visualization and data portal tool (PALTIDE) for relative sea level and palaeotidal simulations of the northwest European shelf seas since the Last Glacial Maximum

ABSTRACTRelative sea level (RSL) predictions based on glacial isostatic adjustment (GIA) simulations and palaeotidal predictions generated by hydrodynamic models using GIA‐generated palaeotopographies are available in the published literature, and datasets are available via data repositories. However, these data are often difficult to extract for specific locations or timeslices, requiring users to request datasets from corresponding authors. To overcome the intractability of these data and to enable users to interrogate datasets themselves without requiring offline requests, we have developed PALTIDE, an online visualization tool with intuitive user interface accessible at https://shiny.bangor.ac.uk/paleotidal/. The model domain for this interactive visualization tool is the northwest European continental shelf, covering the period from the Last Glacial Maximum (LGM) to the present day, and is based on previous GIA simulations by Bradley and colleagues and hydrodynamic simulations using Regional Ocean Modelling System (ROMS) published by Ward and colleagues. The tool is developed in R and utilizes a number of packages including shiny and bslib for the frontend, and arrow, raster and the tidyverse for backend data processing. The tool enables visualizations and data downloads for RSL, tidal amplitude and tide‐dependent parameters for any location within the model domain over 1000‐year timesteps from the LGM to the present.