Barotropic Ocean Research Articles

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.

Recirculation through western boundary currents varies nonlinearly with the ocean basin's aspect ratio

Recirculation gyres adjacent to western boundary currents (WBCs) in the ocean enhance the poleward transport of these currents. While it is well-established that the WBC in a barotropic ocean strengthens with increase in basin's aspect ratio (the meridional-to-zonal extent ratio), how intensity of the recirculation through the western boundary layer varies with this parameter remains unexplored. I address this using the non-dimensional form of the nonlinear, wind-driven Stommel–Munk model of westward intensification that comprises three parameters—the aspect ratio (δ), the damping coefficient (ϵ), and the β-Rossby number (Rβ). Here, ϵ is set by the ratio of Rayleigh friction coefficient (or eddy viscosity) to the meridional gradient of the Coriolis frequency and the basin's zonal dimension, while Rβ is proportional to wind stress amplitude and quantifies the strength of nonlinearity. In the weak-to-moderate nonlinearity limit (Rβ<∼ϵ), perturbation analysis reveals that recirculation varies concavely with aspect ratio, suggesting existence of an optimal aspect ratio (δopt) for which the recirculation is maximum and for typical values of ϵ (10−3−10−2), δopt follows the power-law relation δopt=4.3ϵ. Numerical simulations further validate the existence of δopt. For large ϵ (>5×10−3), the power-law predicts δopt for the numerical solutions rather accurately, but does not hold for smaller ϵ (2×10−3) due to increased importance of nonlinear terms. Nevertheless, the nonlinear variation in recirculation through the western boundary layer with aspect ratio is observed for all ϵ values and may contribute to the heterogeneous increase in the WBC's transport across different ocean basins in a warming climate.

Combining barotropic and baroclinic simplified models for drift trajectory predictions

ABSTRACT The shallow-water equations are often used as a classical simplified ocean model for barotropic ocean dynamics. The same equations can also be used to model simplified baroclinic dynamics through the reduced-gravity model. Herein, we propose to utilise a GPU-accelerated shallow-water simulation framework for representing two decoupled simplified ocean models for each of the barotropic and baroclinic dynamics, and use these models for ensemble prediction of short-term drift trajectories in coastal domains. This system can be used complementary to current operational systems as a lightweight tool for uncertainty quantification and in the future for ensemble-based data assimilation of in-situ observations. We show the relevance of our approach by demonstrating how the barotropic and baroclinic dynamical components are of varying importance at different geographical locations, and that one of the models can be used alone or in combination with the other. We benchmark our approach by showing the resulting ensemble trajectories in reference to deterministic trajectories produced by operational models for three Norwegian coastal regions.

Modeling and simulation of pollution transport in the Mediterranean Sea using enriched finite element method

This paper presents a novel numerical method for simulating the transport and dispersion of pollutants in the Mediterranean sea. The governing mathematical equations consist of a barotropic ocean model with friction terms, bathymetric forces, Coriolis and wind stresses coupled to an advection–diffusion equation with anisotropic dispersion tensor and source terms. The proposed numerical solver uses a multilevel adaptive semi-Lagrangian finite element method that combines various techniques, including the modified method of characteristics, finite element discretization, coupled projection scheme based on a rotational pressure correction algorithm, and an adaptive L2-projection. The approach employs the gradient of the concentration as an error indicator for enrichment adaptations and increasing the number of quadrature points where needed without refining the mesh. The method is shown to provide accurate and efficient simulations for pollution transport in the Mediterranean sea. The proposed approach distinguishes itself from the well-established adaptive finite element methods for incompressible viscous flows by retaining the same structure and dimension of linear systems during the adaptation process.

Uncertainties in the Arctic Ocean response to CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document}: a process-based analysis

Using an ensemble of atmosphere–ocean general circulation models (AOGCMs) in an idealized climate change experiment, this study evaluates the contribution of different ocean processes to Arctic Ocean warming. On the AOGCM-mean, the Arctic Ocean warming is greater than the global ocean warming, both in the volume-weighted mean, and at most depths within the upper 2000 m. However, the uncertainty of Arctic Ocean warming is much larger than the uncertainty of global ocean warming. The Arctic warming is greatest a few 100 m below the surface and is dominated by the import of extra heat, which is added to the ocean at lower latitudes and is conveyed to the Arctic mostly by the large-scale barotropic ocean circulation. The change in strength of this circulation in the North Atlantic is relatively small and not correlated with the Arctic Ocean warming. The Arctic Ocean warming is opposed and substantially mitigated by the weakening of the Atlantic meridional overturning circulation (AMOC), though the magnitude of this effect has a large model spread. By reducing the northward transport of heat, the AMOC weakening causes a redistribution of heat from high latitudes to low latitudes. Within the Arctic Ocean, the propagation of heat anomalies is influenced by broadening of cyclonic circulation in the east and weakening of anticyclonic circulation in the west. On the model-mean, the Arctic Ocean warming is most pronounced in the Eurasian Basin, with large spread across the AOGCMs, and accompanied by subsurface cooling by diapycnal mixing and heat redistribution by mesoscale eddies.

Spatio‐Temporal Super‐Resolution Data Assimilation (SRDA) Utilizing Deep Neural Networks With Domain Generalization

AbstractDeep learning has recently gained attention in the atmospheric and oceanic sciences for its potential to improve the accuracy of numerical simulations or to reduce computational costs. Super‐resolution is one such technique for high‐resolution inference from low‐resolution data. This paper proposes a new scheme, called four‐dimensional super‐resolution data assimilation (4D‐SRDA). This framework calculates the time evolution of a system from low‐resolution simulations using a physics‐based model, while a trained neural network simultaneously performs data assimilation and spatio‐temporal super‐resolution. The use of low‐resolution simulations without ensemble members reduces the computational cost of obtaining inferences at high spatio‐temporal resolution. In 4D‐SRDA, physics‐based simulations and neural‐network inferences are performed alternately, possibly causing a domain shift, that is, a statistical difference between the training and test data, especially in offline training. Domain shifts can reduce the accuracy of inference. To mitigate this risk, we developed super‐resolution mixup (SR‐mixup)–a data augmentation method for domain generalization. SR‐mixup creates a linear combination of randomly sampled inputs, resulting in synthetic data with a different distribution from the original data. The proposed methods were validated using an idealized barotropic ocean jet with supervised learning. The results suggest that the combination of 4D‐SRDA and SR‐mixup is effective for robust inference cycles. This study highlights the potential of super‐resolution and domain‐generalization techniques, in the field of data assimilation, especially for the integration of physics‐based and data‐driven models.

Fortnightly variability of Chl a in the Indonesian seas

Abstract. Twenty years of daily MODIS-Aqua ocean color observations (2002–2022) are used to identify periodic variability of near-surface chlorophyll (Chl a) in the Indonesian seas. The frequency spectrum of Chl a is dominated by the mean and low-frequency monsoonal variability; however, a prominent peak around the fortnightly tidal period, MSf, is present. Harmonic analysis is used to quantify and map the fortnightly Chl a signal, which is discovered to be significant along the continental shelves of NW Australia and at several sites associated with narrow passages between the Lesser Sunda Islands, within the Sulu Archipelago, and at a few other sites in the Philippines Archipelago. Fortnightly variability at the shallow coastal sites is attributed to the spring–neap cycle of barotropic ocean currents, while we hypothesize that the variability in deeper water near the island passages is due to the modulation of vertical nutrient fluxes by baroclinic tidal mixing. The results document the significance of tidal mixing and highlight the heterogeneous character of biophysical processes within the Indonesian seas.

Synchronous Assimilation of Tidal Current-Related Data Obtained Using Coastal Acoustic Tomography and High-Frequency Radar in the Xiangshan Bay, China

To accurately reconstruct large-area three-dimensional current fields in coastal regions, simultaneous observations with ten coastal acoustic tomography (CAT) stations and two high-frequency radar (HFR) stations were performed in the Xiangshan Bay (XSB) on 4–5 December 2020. The section-averaged velocity that was observed by CAT and the radial velocity that was observed by HFR were, for the first time, synchronously assimilated into a three-dimensional barotropic ocean model. Compared with acoustic Doppler current profile data, the velocities of the model assimilating both CAT and HFR data had the highest accuracy according to root mean square differences (RMSDs), ranging from 0.05 to 0.08 m/s for all the vertical layers. For the models individually assimilating CAT and HFR, the values in the vertical layers ranged from 0.07 to 0.12 m/s and 0.08 to 0.13 m/s, respectively. A harmonic analysis of the model grid data showed that the spatial mean amplitudes of the M2, M4, and residual currents were 0.66, 0.14, and 0.09 m/s, respectively. Furthermore, the standing wave characteristics of the M2 current and M4 associated-oscillation in the inner XSB, mouth of the Xiangshan fjord, were better captured by the model assimilating both CAT and HFR. Our study demonstrates the advances in three-dimensional tidal current analysis using a model that assimilates both CAT and HFR data, especially in regions with complex coastal geography.

A Novel Initialization Technique for Decadal Climate Predictions

Model initialization is a matter of transferring the observed information available at the start of a forecast to the model. An optimal initialization is generally recognized to be able to improve climate predictions up to a few years ahead. However, systematic errors in models make the initialization process challenging. When the observed information is transferred to the model at the initialization time, the discrepancy between the observed and model mean climate causes the drift of the prediction toward the model-biased attractor. Although such drifts can be generally accounted for with a posteriori bias correction techniques, the bias evolving along the prediction might affect the variability that we aim at predicting, and disentangling the small magnitude of the climate signal from the initial drift to be removed represents a challenge. In this study, we present an innovative initialization technique that aims at reducing the initial drift by performing a quantile matching between the observed state at the initialization time and the model state distribution. The adjusted initial state belongs to the model attractor and the observed variability amplitude is scaled toward the model one. Multi-annual climate predictions integrated for 5 years and run with the EC-Earth3 Global Coupled Model have been initialized with this novel methodology, and their prediction skill has been compared with the non-initialized historical simulations from CMIP6 and with the same decadal prediction system but based on full-field initialization. We perform a skill assessment of the surface temperature, the heat content in the ocean upper layers, the sea level pressure, and the barotropic ocean circulation. The added value of the quantile matching initialization is shown in the North Atlantic subpolar region and over the North Pacific surface temperature as well as for the ocean heat content up to 5 years. Improvements are also found in the predictive skill of the Atlantic Meridional Overturning Circulation and the barotropic stream function in the Labrador Sea throughout the 5 forecast years when compared to the full field method.

Generation and propagation of 21-day bottom pressure variability driven by wind stress curl in the East China Sea

Between June 2015 and June 2017, two pressure-recording inverted echo sounders (PIESs) and five current and pressure-recording inverted echo sounders (CPIESs) deployed along a section across the Kerama Gap acquired a dataset of ocean bottom pressure records in which there was significant 21-day variability (Pbot21). The Pbot21, which was particularly strong from July-December 2016, was coherent with wind stress curl (WSC) on the continental shelf of the East China Sea (ECS) with a squared coherence of 0.65 for a 3-day time lag. A barotropic ocean model demonstrated the generation, propagation, and dissipation of Pbot21. The modeled results show that the Pbot21 driven by coastal ocean WSC in the ECS propagated toward the Ryukyu Island Chain (RIC), while deep ocean WSC could not induce such variability. On the continental shelf, the Pbot21 was generated nearly synchronously with the WSC from the coastline to the southeast but dissipated within a few days due to the effect of bottom friction. The detection of Pbot21 by the moored array was dependent on the 21-day WSC patterns on the continental shelf. The Pbot21 driven southeast of the Changjiang Estuary by the WSC was detected while the Pbot21 generated northeast of the Changjiang Estuary was not.

Correcting GPS measurements for non-tidal loading

Non-tidal loading (NTL) deforms the earth’s surface, adding variability to the coordinates of geodetic sites. Yet, according to the IERS Conventions, there are no recommended surface-mass change models to account for NTL deformation in geodetic position time series. We investigate the NTL signal recorded at 585 GPS stations at different frequency bands, from day to years, by comparing GPS estimated displacements to modeled environmental loading. We used up-to-date and high-resolution (both temporal and spatial) models to account for NTL induced by mass changes in the atmosphere, oceans, and continental hydrology. Vertical land motions variability is reduced on average by up to 20% when correcting the series for non-tidal atmospheric and oceanic loading, employing either barotropic or baroclinic ocean models. We then focus on characterizing the ocean response to air-pressure variations, and we observe that there are no significant differences at seasonal timescales between a barotropic ocean model forced by air pressure and winds and a more classical baroclinic ocean model forced by wind, heat and freshwater fluxes. However, any of these choices further reduces the variability by 5% compared to the classical static inverted barometer ocean response. The variability of the vertical coordinate changes is further reduced by an additional 5% by also correcting for continental hydrology loading, especially at seasonal periods. For horizontal coordinate changes, the variability is reduced by less than 5% after correcting for all studied surface-mass changes.

Analytic reconstruction of a two-dimensional velocity field from an observed diffusive scalar

Inverting an evolving diffusive scalar field to reconstruct the underlying velocity field is an underdetermined problem. Here we show, however, that for two-dimensional incompressible flows, this inverse problem can still be uniquely solved if high-resolution tracer measurements, as well as velocity measurements along a curve transverse to the instantaneous scalar contours, are available. Such measurements enable solving a system of partial differential equations for the velocity components by the method of characteristics. If the value of the scalar diffusivity is known, then knowledge of just one velocity component along a transverse initial curve is sufficient. These conclusions extend to the shallow-water equations and to flows with spatially dependent diffusivity. We illustrate our results on velocity reconstruction from tracer fields for planar Navier–Stokes flows and for a barotropic ocean circulation model. We also discuss the use of the proposed velocity reconstruction in oceanographic applications to extend localized velocity measurements to larger spatial domains with the help of remotely sensed scalar fields.

The Ability of Barotropic Models to Simulate Historical Mean Sea Level Changes from Coastal Tide Gauge Data

The nature of mean sea level variation over the global coastal ocean is considered based on 219 historical tide gauge records and three barotropic ocean circulation models forced by reanalysis surface air pressure and wind stress. The consistency of the models and their ability to reproduce the data are considered on nonseasonal timescales (seasonal cycles and linear trends removed) from bimonthly to multidecadal over 1900–2010. Models consistently simulate stronger sea level variability at higher latitude, higher frequency, between winters, and over broad shallow shelves and semi-enclosed marginal seas; standard deviations in modeled monthly sea level grow from 1–2 cm on average at low latitude (0°–30°) to 5–10 cm at high latitude (60°–90°), with larger values simulated over some shelf areas (e.g., North Sea). Models are more consistent over narrow shelf regions adjacent to deep basins and less consistent along the broad shallow continental shelf. On monthly timescales, discrepancies between models arise mostly from differences in model configuration (e.g., fine vs. coarse horizontal resolution), whereas model configuration and surface forcing (i.e., choice of atmospheric reanalysis) contribute comparably to model differences on annual timescales. Model solutions become more uncertain at earlier times (e.g., prior to 1950). The models show more skill explaining variance in tide gauge data at higher latitude, higher frequency, between winters, and over broad shallow shelves and within semi-enclosed marginal seas; at middle and high latitudes (poleward of 45°), model sea level solutions on average explain 30–50% of the monthly variance and 35–70% of the variance from one winter to the next in the tide gauge data records. Statistically significant relationships between the model solutions and observational data persist on long decadal periods. The relative skill of individual models is sensitive to region and timescale, such that no one model considered here consistently performs better than the others in all cases. Results suggest that barotropic models are useful for reducing noise in tide gauge records for studies of sea level rise and motivate additional model comparison studies in the context of sea level extremes.

A Simplified Model for the Baroclinic and Barotropic Ocean Response to Moving Tropical Cyclones: 2. Model and Simulations

AbstractA simplified analytical model is developed to describe the baroclinic and barotropic ocean response to moving tropical cyclones (TCs) and their associated pycnocline erosions. The model builds on classical mixed‐layer (ML) models and linear models of ocean response to transient events. As suggested, disturbances of the upper ocean stratification caused by the ML development shall not strongly impact the dynamics of baroclinic modes. Accordingly, the baroclinic response can be estimated using the prestorm ocean stratification condition. To the contrary, the ML is strongly coupled with these interior motions, through the TC‐induced upwelling response that affects the entrainment velocity. The ML temperature is then strongly dependent on the local temperature gradient in the upper layer. The model is represented by a set of analytical relationships providing rapid calculations for the ocean response to TC, given a prescribed wind velocity field traveling over an ocean with arbitrary stratification. Compared to satellite observations, simulations demonstrate the model ability to quantitatively reproduce the observed shape and magnitudes of the sea surface height and the sea surface temperature (SST) anomalies. Remarkably, the model is robust and efficient for a wide range of variability of TC characteristics (max wind speed, radius, shape of wind profile, and translation velocity), parameters of the ocean stratification, and Coriolis parameter. Simulations provide solid evidences about the key role of TC‐induced upwelling in the ML cooling and formation of SST wake. Cross‐track advection by wind‐driven currents, though small compared with TC translation velocity, can significantly contribute to broaden the shape and offset of the SST wake. Given its effectiveness and low computational burden, the proposed model can be introduced as a computational module into atmospheric numerical models of TC‐coupled evolution with the ocean, through the resulting local changes of surface enthalpy fluxes.

A Simplified Model for the Baroclinic and Barotropic Ocean Response to Moving Tropical Cyclones: 1. Satellite Observations

AbstractChanges of sea surface temperature and height, derived from 20‐day passive microwave and altimeter measurements for three tropical cyclones (TCs), Jimena, Ignacio and Kilo, during the 2015 Pacific hurricane season, sampling different stages of intensification, wind speeds, radii, Coriolis parameter, translation velocities, and ocean stratification conditions, are reported and analyzed. As triggered along the path of moving TCs, very large interior ocean displacements can occur to leave prominent sea surface height (SSH) anomalies in the TC wake. Resulting surface depressions can reach 0.3–0.5 m, depending upon size, translation speed, and ocean stratification conditions. These signatures can be quite persistent, that is, more than few weeks, to possibly be intercepted with satellite altimeters. To interpret sea surface temperature (SST) and SSH anomalies, a semiempirical framework is adopted, based on the heat and momentum conservations laws for the upper wind driven mixed layer. As interpreted, SSH anomalies provide direct estimates to evaluate the upwelling impact, that is, the upwelling amplification on the SST wake. For the reported cases, the influence of the upwelling is found rather moderate, of order 10–40%. More promising, the proposed bottom‐up approach can help document the resulting wind forcing and practical drag coefficient under extreme TC conditions. As found for these three TCs, a marked drag reduction for wind speed higher than 35 m/s is inferred to ensure consistency with the measured SSH and SST anomalies.

Seafloor Crustal Deformation on Ocean Bottom Pressure Records With Nontidal Variability Corrections: Application to Hikurangi Margin, New Zealand

AbstractOcean bottom pressure (OBP) observations are a powerful tool for determining vertical crustal displacements, especially due to earthquakes and slow earthquakes, with centimeter‐level resolution. In these studies, removal of oceanographic noise (tens of centimeters) is required to identify centimeter‐level crustal deformation. We undertake barotropic modeling to remove oceanographic signals from data from an OBP array deployed offshore New Zealand in 2014/2015. We show that removing the nontidal component calculated from a barotropic ocean model reduces the variance in the data by about 66% and provides a feasible means to resolve pressure changes due to crustal deformation during the slow slip events. We also discuss the vertical displacements from slow slip events that occurred in late September to mid‐October 2014, and we outline our procedure for processing OBP data.

Nonlinear tidal dissipation in the subsurface oceans of Enceladus and other icy satellites

Subsurface ocean tides act as a mechanism to dissipate tidal energy in icy satellite interiors. We numerically model the effect of an ice shell on ocean tides using non-linear bottom drag for the first time. We demonstrate that subsurface oceans experience tidal pressurization due to the confining nature of the ice shell, and find that Enceladus’ eccentricity forcing can generate up to 2.2 kPa of pressure excess at the ocean surface. Existing free-surface oceanic energy dissipation scaling laws are extended to subsurface oceans, and are benchmarked against our numerical results to within 10 %. We show that for the large bodies Ganymede, Europa and Titan, an ice shell increases eccentricity tidal heating due to self-gravity, whereas the shell’s suppressive mechanical forcing reduces eccentricity tide dissipation on Enceladus and Dione by several orders of magnitude due to their high effective rigidities. In contrast, the ice shell enhances obliquity-forced dissipation in all satellites investigated, except Triton, because the largely divergence-free ocean response is unaffected by the shell’s rigidity but is still enhanced by self-gravity. We conclude that the fundamental difference in ocean response to obliquity and eccentricity forcing, combined with self-gravity, results in increased obliquity heating and suppressed eccentricity heating in small satellites. For large satellites with low effective rigidities, the type of ocean response is less important because the shell’s mechanical forcing has little impact on the flow, whereas self-gravity will enhance the response, and consequently dissipation, regardless of the forcing. Overall, obliquity tides are likely to dominate the tidal heating budget of icy satellite oceans, remaining the most prominent source of fluid dissipation in subsurface barotropic ocean tides.

Eddy-mixing entropy and its maximization in forced-dissipative geostrophic turbulence

An equilibrium, or maximum entropy, statistical mechanics theory can be derived for ideal, unforced and inviscid, geophysical flows. However, for all geophysical flows which occur in nature, forcing and dissipation play a major role. Here, a study of eddy-mixing entropy in a forced-dissipative barotropic ocean model is presented. We heuristically investigate the temporal evolution of eddy-mixing entropy, as defined for the equilibrium theory, in a strongly forced and dissipative system. It is shown that the eddy-mixing entropy provides a descriptive tool for understanding three stages of the turbulence life cycle: growth of instability; formation of large scale structures; and steady state fluctuations. The fact that the eddy-mixing entropy behaves in a dynamically balanced way is not a priori clear and provides a novel means of quantifying turbulent disorder in geophysical flows. Further, by determining the relationship between the time evolution of entropy and the maximum entropy principle, evidence is found for the action of this principle in a forced-dissipative flow. The maximum entropy potential vorticity statistics are calculated for the flow and are compared with numerical simulations. Deficiencies of the maximum entropy statistics are discussed in the context of the mean-field approximation for energy. This study highlights the importance of entropy and statistical mechanics in the study of geostrophic turbulence.

Odessa Tsunami of 27 June 2014: Observations and Numerical Modelling

On 27 June, a 1–2-m high wave struck the beaches of Odessa, the third largest Ukrainian city, and the neighbouring port-town Illichevsk (northwestern Black Sea). Throughout the day, prominent seiche oscillations were observed in several other ports of the Black Sea. Tsunamigenic synoptic conditions were found over the Black Sea, stretching from Romania in the west to the Crimean Peninsula in the east. Intense air pressure disturbances and convective thunderstorm clouds were associated with these conditions; right at the time of the event, a 1.5-hPa air pressure jump was recorded at Odessa and a few hours earlier in Romania. We have utilized a barotropic ocean numerical model to test two hypotheses: (1) a tsunami-like wave was generated by an air pressure disturbance propagating directly over Odessa (“Experiment 1”); (2) a tsunami-like wave was generated by an air pressure disturbance propagating offshore, approximately 200 km to the south of Odessa, and along the shelf break (“Experiment 2”). Both experiments decisively confirm the meteorological origin of the tsunami-like waves on the coast of Odessa and imply that intensified long ocean waves in this region were generated via the Proudman resonance mechanism while propagating over the northwestern Black Sea shelf. The “Odessa tsunami” of 27 June 2014 was identified as a “beach meteotsunami”, similar to events regularly observed on the beaches of Florida, USA, but different from the “harbour meteotsunamis”, which occurred 1–3 days earlier in Ciutadella (Baleares, Spain), Mazara del Vallo (Sicily, Italy) and Vela Luka (Croatia) in the Mediterranean Sea, despite that they were associated with the same atmospheric system moving over the Mediterranean/Black Sea region on 23–27 June 2014.

Spatiotemporal Tracking of Ocean Current Field With Distributed Acoustic Sensor Network

A distributed networked underwater sensor (DNUS) system can provide ocean measurements over a wide area with a large number of sensors. This paper studies the estimation of the ocean current field observed by a DNUS system. Considering that the current field is correlated in time and space, we present a statistically-based acoustic travel time difference tomography method based on a Kalman filter (KF) to reconstruct and track the ocean current field. A spatiotemporal autoregressive (AR) model is used to describe the time evolution of the current field. In the spatiotemporal AR model, the observation region is divided into subtriangle grids. The subtriangles are partitioned into clusters and each cluster is assigned with one AR coefficient. Moreover, the AR coefficients are updated adaptively with the past estimated current velocities. The proposed method is verified with the synthetic observational data generated by a barotropic ocean model. Compared with the regular distributed processing method, the proposed ocean current field reconstruction and tracking method achieves a lower region-integrated root-mean-square error (RMSE). In addition, by making use of the spatiotemporal correlation, the proposed method is robust to the measurement link failure and burst errors in the DNUS system.