Six circumpolar currents—on the forcing of the Antarctic Circumpolar Current by wind and mixing

The transport of the Antarctic Circumpolar Current (ACC) is influenced by a variety of processes and parameters. A proper implementation of basin geometry, ocean topography and baroclinicity is known to be a fundamental requisite for a realistic simulation of the circulation and transport. Other, more subtle parameters are those of eddy-induced transports and diapycnal mixing of thermohaline tracers or buoyancy, either treated by eddy resolution or by a proper parameterization. Quite a number of realistic numerical simulations of the circulation in the Southern Ocean have recently been published. Many concepts on relations of the ACC transport to model parameters and forcing function are in discussion, however, without much generality and little success. We present a series of numerical simulations of circumpolar flow with a simplified numerical model, ranging from flat-bottom wind-driven flow to baroclinic flow with realistic topography and wind and buoyancy forcing. Analysis of the balances of momentum, vorticity, and baroclinic potential energy enables us to develop a new transport theory, which combines the most important mechanisms driving the circulation of the ACC and determining its zonal transport. The theory is based on the importance of the bottom vertical velocity in generating vorticity and shaping the baroclinic potential energy of the ACC. It explains the breaking of the -constraint by baroclinicity and brings together in one equation the wind and buoyancy forcing of the current. The theory emphasizes the role of Ekman pumping and eddy diffusion of buoyancy to determine the transport. It also demonstrates that eddy viscosity effects are irrelevant in the barotropic vorticity balance and that friction arises via eddy diffusion of density. In this regime, the classical Stommel model of vorticity balance is revived where the bottom friction coefficient is replaced by (with the Gent–McWilliams coefficient and the baroclinic Rossby radius ) and a modified wind curl forcing appears.     

Mapping nonlinear shallow-water tides: a look at the past and future

Overtides and compound tides are generated by nonlinear mechanisms operative primarily in shallow waters. Their presence complicates tidal analysis owing to the multitude of new constituents and their possible frequency overlap with astronomical tides. The science of nonlinear tides was greatly advanced by the pioneering researches of Christian Le Provost who employed analytical theory, physical modeling, and numerical modeling in many extensive studies, especially of the tides of the English Channel. Le Provost’s complementary work with satellite altimetry motivates our attempts to merge these two interests. After a brief review, we describe initial steps toward the assimilation of altimetry into models of nonlinear tides via generalized inverse methods. A series of barotropic inverse solutions is computed for the M tide over the northwest European Shelf. Future applications of altimetry to regions with fewer in situ measurements will require improved understanding of error covariance models because these control the tradeoffs between fitting hydrodynamics and data, a delicate issue in coastal regions. While M can now be robustly determined along the Topex/Poseidon satellite ground tracks, many other compound tides face serious aliasing problems. In memory of Christian Le Provost     

Internal and forced variability along a section between Greenland and Portugal in the CLIPPER Atlantic model

Numerical models are used to estimate the meridional overturning and transports along the paths of two hydrographic cruises, carried out in 1997 and 2002 from Greenland to Portugal. We have examined the influence of the different paths of the two cruises and found that it could explain 0.4 to 2 Sv of difference in overturning (the precise value is model-dependent). Models show a decrease in the overturning circulation between 1997 and 2002, with different amplitudes. The CLIPPER ATL6 model reproduces well the observed weakening of the overturning in density coordinates between the cruises; in the model, the change is due to the combination of interannual and high-frequency forcing and internal variability associated with eddies and meanders. Examination of the -coordinate overturning reveals model–data discrepancies: the vertical structure in the models does not change as much as the observed one. The East Greenland current variability is mainly wind-forced in the ATL6 model, while fluctuations due to eddies and instabilities explain a large part of the North Atlantic Current variability. The time-residual transport of dense water and heat due to eddy correlations between currents and properties is small across this section, which is normal to the direction of the main current.     

The Ensemble Kalman Filter: theoretical formulation and practical implementation

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.Responsible Editor: Jörg-Olaf Wolff     

Christian Le Provost on his way

This paper is an evocation of the scientific career of Christian Le Provost and of the different research topics in oceanography that have been of interest to him: tides, ocean modeling, altimetry, sea level, tidal dissipation, ...     

High-order <Emphasis Type="Italic">h</Emphasis>-adaptive discontinuous Galerkin methods for ocean modelling

In this paper, we present an h-adaptive discontinuous Galerkin formulation of the shallow water equations. For a discontinuous Galerkin scheme using polynomials up to order , the spatial error of discretization of the method can be shown to be of the order of , where is the mesh spacing. It can be shown by rigorous error analysis that the discontinuous Galerkin method discretization error can be related to the amplitude of the inter-element jumps. Therefore, we use the information contained in jumps to build error metrics and size field. Results are presented for ocean modelling problems. A first experiment shows that the theoretical convergence rate is reached with the discontinuous Galerkin high-order h-adaptive method applied to the Stommel wind-driven gyre. A second experiment shows the propagation of an anticyclonic eddy in the Gulf of Mexico. An erratum to this article can be found at     

Empirische Untersuchung zur Frage der Beziehung zwischen durchschnittlicher und kennzeichnender Wellenperiode im Seegang

Zusammenfassung Als Zusammenhang zwischen der kennzeichnenden Wellenperiode und der durchschnittlichen Periode im Seegang wird die Formel angesetzt. Mit Hilfe empirischer Unterlagen wird nachgewiesen, daßc eine Funktion des von D. E. Cartwright und M. S. Longuet-Higgins [1956] eingeführten Spektralparameters ist. Es wird eine vorläufige quantitative Beziehung zwischenc und abgeleitet.

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Empirical investigations of the relation between the mean and the significant wave period in the sea

Summary It is supposed that the formula represents the relation between the significant wave period and the mean period in the sea. With the aid of empirical data it is demonstrated thatc is a function of the spectral parameter introduced by D. E. Cartwright and M. S. Longuet-Higgins [1956]. A preliminary quantitative relation betweenc and is derived.

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Etudes empiriques de la relation entre la période moyenne et la période significative des vagues dans la houle

Résumé On suppose que la formule représente la relation entre la période significative des vagues et la période moyenne dans la houle. A l'aide des données empiriques on montre quec est une fonction du paramètre spectral , introduit par D. E. Cartwright et M. S. Longuet-Higgins [1956]. Une relation quantitative préliminaire entrec et est dérivée.

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Validation and application of an ensemble Kalman filter in the Selat Pauh of Singapore

The effectiveness of an ensemble Kalman filter (EnKF) is assessed in the Selat Pauh of Singapore using observing system simulation experiment. Perfect model experiments are first considered. The perfect model experiments examine the EnKF in reducing the initial perturbations with no further errors than those in the initial conditions. Current velocity at 15 observational sites from the true ocean is assimilated every hour into the false ocean. While EnKF reduces the initial velocity error during the first few hours, it fails after one tidal cycle (approximately 12 h) due to the rapid convergence of the ensemble members. Successively, errors are introduced in the surface wind forcing. A random perturbation ε is applied independently to each ensemble member to maintain the ensemble spread. The assimilation results showed that the success of EnKF depends critically on the presence of ε, yet it is not sensitive to the magnitude of ε, at least in the range of weak to moderate perturbations. Although all experiments were made with EnKF only, the results could be applicable in general to all other ensemble-based data assimilation methods.     

Das Spektrum der internen Bewegungsvorgänge der westlichen Ostsee im Periodenbereich von 0,3 bis 60 Minuten

Zusammenfassung Für ein Beobachtungsbeispiel (Stromgeschwindigkeit, Dichte) aus der Kieler Bucht wird eine Deutung ausgeprägter Maxima der zugehörigen Spektren zwischen 0,3 und 60 Minuten durch interne Wellen gegeben. Mit einer beobachteten Periode von zwei Minuten durchgeführte Rechnungen ergeben eine starke Abhängigkeit der Wellenlänge von der mittleren Strömung . Im Falle erhält man bei 23,5 m Wassertiefe eine Wellenlänge von etwa 70 m, im Falle von etwa 85 m. Die berechneten Schwingungen stellen uneigentliche interne Wellen dar (W. Krauß [1966]). Die Interpretation durch eine Grenzflächenwelle führt auf eine Wellenlänge von 86 m, die nur geringfügig von denen der internen Wellen 1. Ordnung in stetig sich ändernder Strömung abweicht.In einer theoretischen Untersuchung werden kleinräumige Anfangsstörungen (z. B. momentane Druckänderungen an der Meeresoberfläche) als mögliche Ursache für die Entstehung kurzperiodischer interner Wellen erkannt. Es zeigt sich, daß kurzzeitig wirksame Anfangsbeschleunigungen in ihrem Einwirkungsbereich stehende, allmählich abklingende interne Wellen erzeugen, während in der Umgebung gleichzeitig fortschreitende Wellen entstehen, deren Amplituden mit wachsender Entfernung vom Erregungsgebiet abnehmen. Die Perioden der Schwingungen haben größere Werte als die zu einer exponentiellen Schichtung gehörige Väisäläperiode und verändern sich in Abhängigkeit von der Größe des Anregungsgebietes wie die zellularer Stabilitätsschwingungen.

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The powerspectrum of internal motions in the western baltic between the periods 0.3 and 60 minutes. Part 1: Interpretation of the wavelike component of the internal unrest in the sea

Summary The powerspectra of the internal unrest in the sea show marked peaks in the range of periods between 0.3 and 60 minutes. An interpretation of these phenomena is given in terms of internal waves for a specific example obtained from short periodic current and density variations in the Kieler Bucht. The numerical calculations for an observed period of two minutes show an important influence of the vertical distribution of the current on the wavelength. In the case of the wavelength amounts to about 70 m, where as in the case of the length is about 85 m, assuming a depth of the sea of 23.5 m. The computed oscillations represent improper internal waves (W. Krauß [1966]). Interpretation by internal boundary waves yields a wavelength of 86 m, which is slightly different only from those of the first mode of internal waves in the case of continuously varying .By a theoretical investigation it is shown that short periodic internal waves may be caused by local initial perturbations (for instance by sudden variations of pressure at the surface). The solution of the problem describes slowly decreasing standing internal waves, which are generated within the area upon which short-dated initial accelerations have acted. At the same time a train of progressive waves is developed in the environment travelling away from the centre of the excitation. The amplitudes of these waves diminish with increasing distance from the origin. The periods of the computed oscillations yield higher values than the Väisäläperiod belonging to an exponential stratification. The variability in these periods is caused by variations in depth, by variations in stability, and by changes in the horizontal dimensions of the area of initial perturbation. This dependence is similar to that of cellular oscillations of stability.

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Spectre des oscillations internes de la mer Baltique Ouest pour des périodes comprises entre 0,3 et 60 minutes. 1ère Partie: Interprétation des éléments ondulatoires de mouvement

Résumé Pour un cas d'observation (vitesse de courant, densité) en baie de Kiel, des maximums bien marqués des spectres correspondants entre 0,3 et 60 minutes s'expliquent par des ondes internes. Des calculs effectués avec une période de deux minutes montrent que la longueur d'onde dépend beaucoup du courant moyen, . Pour , par 23,5 m de profondeur, on obtient une longueur d'onde environ 70 m; pour , une longueur d'environ 85 m. Les oscillations calculées représentent des ondes internes qui ne sont pas des ondes propres. L'interprétation par une onde de surface limite conduit à une longueur d'onde de 86 m très peu différente de celles des ondes internes du premier ordre dans un courant constamment variable.Une étude théorique montre que des perturbations initiales peu étendues (par exemple variations momentanées de la pression à la surface de la mer) peuvent être à l'origine d'ondes internes à courte période. Il apparaît que des accélérations initiales, agissant brièvement, font naître dans leur zone d'action des ondes internes stationnaires qui s'amortissent peu à peu, tandis qu'en même temps aux alentours se produisent des ondes progressives dont l'amplitude décroît à mesure qu'elles s'éloignent de la région où elles ont pris naissance. Les périodes des oscillations ont des valeurs plus grandes que celle de la période de Väisälä rapportée à une stratification exponentielle, et elles varient suivant la grandeur de la zone où elles ont pris naissance comme les oscillations de stabilité cellulaire.

     

Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF): A data assimilation scheme for memory intensive,high performance computing

Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF) is introduced as a variant on the Ensemble Kalman Filter (EnKF). RumEnKF differs from EnKF in that it does not store the entire ensemble, but rather only saves the first two moments of the ensemble distribution. In this way, the number of ensemble members that can be calculated is less dependent on available memory, and mainly on available computing power (CPU). RumEnKF is developed to make optimal use of current generation super computer architecture, where the number of available floating point operations (flops) increases more rapidly than the available memory and where inter-node communication can quickly become a bottleneck. RumEnKF reduces the used memory compared to the EnKF when the number of ensemble members is greater than half the number of state variables. In this paper, three simple models are used (auto-regressive, low dimensional Lorenz and high dimensional Lorenz) to show that RumEnKF performs similarly to the EnKF. Furthermore, it is also shown that increasing the ensemble size has a similar impact on the estimation error from the three algorithms.     

On ensemble representation of the observation-error covariance in the Ensemble Kalman Filter

Evensen (2003) presents a modification of the Ensemble Kalman Filter (EnKF), in which the observation-error and background-error covariance matrices are both represented by ensembles, in contrast to the usual practice, where only the background error is so represented. It is shown that this modification can cause the ensemble to collapse to a single member, in the common situation where the number of observations is more than twice the number of ensemble members, and to be rank-deficient when the number of observations is greater than or equal to the ensemble size. It is also shown that some further modifications to the scheme, presented by Evensen as offering numerical efficiencies, can prevent this collapse. However, these latter modifications are shown in some simple numerical examples to require tuning to produce acceptable results, which are nevertheless inferior to those of the standard EnKF.Acknowledgements The author acknowledges useful discussions with Peter Steinle, and other participants at the EnKF workshop held in BMRC in November, 2003.     

Open and coastal seas interactions south of Japan represented by an ensemble Kalman filter

We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have adopted the local ensemble transformation Kalman filter algorithm based on 20 members’ ensemble simulations of the parallelized Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36°. By assimilating satellite sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability.     

Sampling strategies and square root analysis schemes for the EnKF

The purpose of this paper is to examine how different sampling strategies and implementations of the analysis scheme influence the quality of the results in the EnKF. It is shown that by selecting the initial ensemble, the model noise and the measurement perturbations wisely, it is possible to achieve a significant improvement in the EnKF results, using the same number of members in the ensemble. The results are also compared with a square root implementation of the EnKF analysis scheme where the analyzed ensemble is computed without the perturbation of measurements. It is shown that the measurement perturbations introduce sampling errors which can be reduced using improved sampling schemes in the standard EnKF or fully eliminated when the square root analysis algorithm is used. Further, a new computationally efficient square root algorithm is proposed which allows for the use of a low-rank representation of the measurement error covariance matrix. It is shown that this algorithm in fact solves the full problem at a low cost without introducing any new approximations.     

Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model

This paper describes an application of the ensemble Kalman filter (EnKF) in which streamflow observations are used to update states in a distributed hydrological model. We demonstrate that the standard implementation of the EnKF is inappropriate because of non-linear relationships between model states and observations. Transforming streamflow into log space before computing error covariances improves filter performance. We also demonstrate that model simulations improve when we use a variant of the EnKF that does not require perturbed observations. Our attempt to propagate information to neighbouring basins was unsuccessful, largely due to inadequacies in modelling the spatial variability of hydrological processes. New methods are needed to produce ensemble simulations that both reflect total model error and adequately simulate the spatial variability of hydrological states and fluxes.     

State estimation of tidal hydrodynamics using ensemble Kalman filter

This paper presents a coupling of an ensemble Kalman filter (EnKF) with a discontinuous Galerkin-based, two-dimensional circulation model (DG ADCIRC-2DDI) to improve the state estimation of tidal hydrodynamics including water surface elevations and depth-integrated velocities. The methodology in this paper using EnKF perturbs the modeled hydrodynamics and bottom friction parameterization in the model while assimilating data with inherent error, and demonstrates a capability to apply EnKF within DG ADCIRC-2DDI for data assimilation. Parallel code development presents a unique aspect of the approach taken and is briefly described in the paper, followed by an application to a real estuarine system, the lower St. Johns River in north Florida, for the state estimation of tidal hydrodynamics. To test the value of gauge observations for improving state estimation, a tide modeling case study is performed for the lower St. Johns River successively using one of the four available tide gauging stations in model-data comparison. The results are improved simulations of water surface elevations and depth-integrated velocities using DG ADCIRC-2DDI with EnKF, both locally where data are available and non-locally where data are not available. The methodology, in general, is extensible to other modeling and data applications, for example, the use of remote sensing data, and specifically, can be readily applied as is to study other tidal systems.     

The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations

The local ensemble transform Kalman filter (LETKF) is implemented with the Weather Research and Forecasting (WRF) model, and real observations are assimilated to assess the newly-developed WRF-LETKF system. The WRF model is a widely-used mesoscale numerical weather prediction model, and the LETKF is an ensemble Kalman filter (EnKF) algorithm particularly efficient in parallel computer architecture. This study aims to provide the basis of future research on mesoscale data assimilation using the WRF-LETKF system, an additional testbed to the existing EnKF systems with the WRF model used in the previous studies. The particular LETKF system adopted in this study is based on the system initially developed in 2004 and has been continuously improved through theoretical studies and wide applications to many kinds of dynamical models including realistic geophysical models. Most recent and important improvements include an adaptive covariance inflation scheme which considers the spatial and temporal inhomogeneity of inflation parameters. Experiments show that the LETKF successfully assimilates real observations and that adaptive inflation is advantageous. Additional experiments with various ensemble sizes show that using more ensemble members improves the analyses consistently.     

Assimilating transient groundwater flow data via a localized ensemble Kalman filter to calibrate a heterogeneous conductivity field

A localized ensemble Kalman filter (EnKF) method is developed to assimilate transient flow data to calibrate a heterogeneous conductivity field. To update conductivity value at a point in a study domain, instead of assimilating all the measurements in the study domain, only limited measurement data in an area around the point are used for the conductivity updating in the localized EnKF method. The localized EnKF is proposed to solve the problems of the filter divergence usually existing in a data assimilation method without localization. The developed method is applied, in a synthetical two dimensional case, to calibrate a heterogeneous conductivity field by assimilating transient hydraulic head data. The simulations by the data assimilation with and without localized EnKF are compared. The study results indicate that the hydraulic conductivity field can be updated efficiently by the localized EnKF, while it cannot be by the EnKF. The covariance inflation and localization are found to solve the problem of the filter divergence efficiently. In comparison with the EnKF method without localization, the localized EnKF method needs smaller ensemble size to achieve stabilized results. The simulation results by the localized EnKF method are much more sensitive to conductivity correlation length than to the localization radius. The developed localized EnKF method provides an approach to improve EnKF method in conductivity calibration.     

Review of the Kalman-type hydrological data assimilation

ABSTRACT

There is great potential in Data Assimilation (DA) for the purposes of uncertainty identification, reduction and real-time correction of hydrological models. This paper reviews the latest developments in Kalman filters (KFs), particularly the Extended KF (EKF) and the Ensemble KF (EnKF) in hydrological DA. The hydrological DA targets, methodologies and their applicability are examined. The recent applications of the EKF and EnKF in hydrological DA are summarized and assessed critically. Furthermore, this review highlights the existing challenges in the implementation of the EKF and EnKF, especially error determination and joint parameter estimation. A detailed review of these issues would benefit not only the Kalman-type DA but also provide an important reference to other hydrological DA types.

Editor D. Koutsoyiannis; Associate editor F. Pappenberger     

Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter

Catchment scale hydrological models are critical decision support tools for water resources management and environment remediation. However, the reliability of hydrological models is inevitably affected by limited measurements and imperfect models. Data assimilation techniques combine complementary information from measurements and models to enhance the model reliability and reduce predictive uncertainties. As a sequential data assimilation technique, the ensemble Kalman filter (EnKF) has been extensively studied in the earth sciences for assimilating in-situ measurements and remote sensing data. Although the EnKF has been demonstrated in land surface data assimilations, there are no systematic studies to investigate its performance in distributed modeling with high dimensional states and parameters. In this paper, we present an assessment on the EnKF with state augmentation for combined state-parameter estimation on the basis of a physical-based hydrological model, Soil and Water Assessment Tool (SWAT). Through synthetic simulation experiments, the capability of the EnKF is demonstrated by assimilating the runoff and other measurements, and its sensitivities are analyzed with respect to the error specification, the initial realization and the ensemble size. It is found that the EnKF provides an efficient approach for obtaining a set of acceptable model parameters and satisfactory runoff, soil water content and evapotranspiration estimations. The EnKF performance could be improved after augmenting with other complementary data, such as soil water content and evapotranspiration from remote sensing retrieval. Sensitivity studies demonstrate the importance of consistent error specification and the potential with small ensemble size in the data assimilation system.