Tracer Leakage from Modeled Agulhas Rings

In a numerical, isopycnal, ocean model the mixing is investigated with the environment of two idealized Agulhas rings, one that splits, and one that remains coherent. The evolution of a passive tracer , initially contained within the rings, shows that tracer leakage is associated with the for mation of filaments in the early stage of ring evolution. These filaments reach down to the ther mocline. In the deepest layers leakage occurs on a larger scale. Self-advection of the rings is ver y irregular , and it is not possible to compute a Lagrangian boundar y i n order to estimate the transport of leakage from the rings. T o describe the processes that gover n tracer leakage, in a coordinate frame moving with the ring a kinematic separatrix is defined in the streamfunction field for the nondivergent flow . Initially , filaments arise because of the elongation of the ring, which is mainly gover ned by an m 5 2 instability that is collaborating with differential rotation. Because of beta, the symmetr y i s destroyed related to the separatrix associated with a stagnation point in the flow . The filament upstream of the stagnation point grows much faster and is associated with the bulk of tracer leakage. Mixing is enhanced by time dependence of the separatrix. As a result, there are no large differences between the leakage from a coherent ring, where the m 5 2 instability equilibrates, and from a splitting ring, where the m 5 2 instability keeps growing, which confir ms that the amount of leakage is mainly gover ned by the ring’ s initial defor mation combined with unsteady self-advection of the ring and not by the splitting of the ring. The decay of tracer content in the ther mocline shows that in the first months up to 40% of the ring water can be mixed with the environment. In deeper layers the decay of tracer content may reach up to 90%.

A Variance-Minimizing Filter for Large-Scale Applications

A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.

An Ensemble Smoother with Error Estimates

A smoother introduced earlier by van Leeuwen and Evensen is applied to a problem in which real obser vations are used in an area with strongly nonlinear dynamics. The derivation is new , but it resembles an earlier derivation by van Leeuwen and Evensen. Again a Bayesian view is taken in which the prior probability density of the model and the probability density of the obser vations are combined to for m a posterior density . The mean and the covariance of this density give the variance-minimizing model evolution and its errors. The assumption is made that the prior probability density is a Gaussian, leading to a linear update equation. Critical evaluation shows when the assumption is justified. This also sheds light on why Kalman filters, in which the same ap- proximation is made, work for nonlinear models. By reference to the derivation, the impact of model and obser vational biases on the equations is discussed, and it is shown that Bayes’ s for mulation can still be used. A practical advantage of the ensemble smoother is that no adjoint equations have to be integrated and that error estimates are easily obtained. The present application shows that for process studies a smoother will give superior results compared to a filter , not only owing to the smooth transitions at obser vation points, but also because the origin of features can be followed back in time. Also its preference over a strong-constraint method is highlighted. Further more, it is argued that the proposed smoother is more efficient than gradient descent methods or than the representer method when error estimates are taken into account

An Ensemble Kalman Smoother for Nonlinear Dynamics

It is for mally proved that the general smoother for nonlinear dynamics can be for mulated as a sequential method, that is, obser vations can be assimilated sequentially during a for ward integration. The general filter can be derived from the smoother and it is shown that the general smoother and filter solutions at the final time become identical, as is expected from linear theor y. Then, a new smoother algorithm based on ensemble statistics is presented and examined in an example with the Lorenz equations. The new smoother can be computed as a sequential algorithm using only for ward-in-time model integrations. It bears a strong resemblance with the ensemble Kalman filter . The difference is that ever y time a new dataset is available during the for ward integration, an analysis is computed for all previous times up to this time. Thus, the first guess for the smoother is the ensemble Kalman filter solution, and the smoother estimate provides an improvement of this, as one would expect a smoother to do. The method is demonstrated in this paper in an intercomparison with the ensemble Kalman filter and the ensemble smoother introduced by van Leeuwen and Evensen, and it is shown to be superior in an application with the Lorenz equations. Finally , a discussion is given regarding the properties of the analysis schemes when strongly non-Gaussian distributions are used. It is shown that in these cases more sophisticated analysis schemes based on Bayesian statistics must be used.

Generation and Evolution of Natal Pulses: Solitary Meanders in the Agulhas Current

Solitar y meanders of the Agulhas Current, so-called Natal pulses, may play an important role in the overall dynamics of this current system. Several hypotheses concer ning the triggering of these pulses are tested using sea sur face height and temperature data from satellites. The data show the for mation of pulses in the Natal Bight area at irregular inter vals ranging from 50 to 240 days. Moving downstream at speeds between 10 and 20 km day 2 1 they sometimes reach sizes of up to 300 km. They seem to play a role in the shedding of Agulhas rings that penetrate the South Atlantic. The inter mittent for mation of these solitar y meanders is argued to be most probably related to barotropic instability of the strongly baroclinic Agulhas Current in the Natal Bight. The vorticity structure of the obser ved basic flow is argued to be stable anywhere along its path. However , a proper perturbation of the jet in the Natal Bight area will allow barotropic instability , because the bottom slope there is considerably less steep than elsewhere along the South African east coast. Using satellite altimetr y these perturbations seem to be related to the inter mittent presence of offshore anticyclonic anomalies, both upstream and eastward of the Natal Bight.

Impact of Interbasin Exchange on the Atlantic Overturning Circulation

The ther mohaline exchange between the Atlantic and the Souther n Ocean is analyzed, using a dataset based on WOCE hydrographic data. It is shown that the salt and heat transports brought about by the South Atlantic subtropical gyre play an essential role in the Atlantic heat and salt budgets. It is found that on average the exported North Atlantic Deep W ater (NADW) is fresher than the retur n flows (basically composed of ther mocline and inter mediate water), indicating that the overtur ning circulation (OC) exports freshwater from the Atlantic. The sensitivity of the OC to interbasin fluxes of heat and salt is studied in a 2 D model, representing the Atlantic between 60 8 N and 30 8 S. The model is forced by mixed boundar y conditions at the sur face, and by realistic fluxes of heat and salt at its 30 8 S boundar y. The model circulation tur ns out to be ver y sensitive to net buoyancy fluxes through the sur face. Both net sur face cooling and net sur face saltening are sources of potential energy and impact positively on the circulation strength. The vertical distributions of the lateral fluxes tend to stabilize the stratification, and, as they extract potential energy from the system, tend to weaken the flow . These results imply that a change in the composition of the NADW retur n transports, whether by a change in the ratio ther mocline/inter mediate water , o r by a change in their ther mohaline characteristics, might influence the Atlantic OC considerably . It is also shown that the circulation is much more sensitive to changes in the shape of the lateral buoyancy flux than to changes in the shape of the sur face buoyancy flux, as the latter does not explicitly impact on the potential energy of the system. It is concluded that interocean fluxes of heat and salt are important for the strength and operation of the Atlantic ther mohaline circulation, and should be correctly represented in models that are used for climate sensitivity studies.

Analysis Scheme in the Ensemble Kalman Filter

This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter . I t i s shown that the obser vations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the obser vations and generate an ensemble of obser vations that then is used in updating the ensemble of model states. T raditionally , this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low . This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach

Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation

The weak-constraint inverse for nonlinear dynamical models is discussed and derived in terms of a probabilistic formulation. The well-known result that for Gaussian error statistics the minimum of the weak-constraint inverse is equal to the maximum-likelihood estimate is rederived. Then several methods based on ensemble statistics that can be used to find the smoother (as opposed to the filter) solution are introduced and compared to traditional methods. A strong point of the new methods is that they avoid the integration of adjoint equations, which is a complex task for real oceanographic or atmospheric applications. they also avoid iterative searches in a Hilbert space, and error estimates can be obtained without much additional computational effort. the feasibility of the new methods is illustrated in a two-layer quasigeostrophic model.

Assimilation of Geosat Altimeter Data for the Agulhas Current Using the Ensemble Kalman Filter with a Quasigeostrophic Model

The ring-shedding process in the Agulhas Current is studied using the ensemble Kalman filter to assimilate geosat altimeter data into a two-layer quasigeostrophic ocean model. The properties of the ensemble Kalman filter are further explored with focus on the analysis scheme and the use of gridded data. The Geosat data consist of 10 fields of gridded sea-surface height anomalies separated 10 days apart that are added to a climatic mean field. This corresponds to a huge number of data values, and a data reduction scheme must be applied to increase the efficiency of the analysis procedure. Further, it is illustrated how one can resolve the rank problem occurring when a too large dataset or a small ensemble is used.

Biofilm on the apical region of roots in primary teeth with vital and necrotic pulps with or without radiographically evident apical pathosis

Aim To evaluate, by scanning electron microscopy (SEM), the presence of biofilms on the external surfaces of the apical third of roots of human primary teeth with vital or necrotic pulps with and without radiographically evident periradicular pathosis. Methodology Eighteen teeth were selected: group I - normal pulp (n = 5), group II - pulp necrosis without radiographic evidence of periapical pathosis (n = 7) and group III - pulp necrosis with well-defined radiographic periapical pathosis (n = 6). After extraction, the teeth were washed with saline and immersed in 0.03 g mL(-1) trypsin solution for 20 min. The teeth were then washed in sodium cacodilate buffer and stored in receptacles containing modified Karnovsky solution. The teeth were sectioned, dehydrated in an ethanol series, critical-point dried with CO(2), sputter coated with gold and the external root surface in the apical third examined by SEM. Results In the teeth of groups I and II, the apical root surfaces were covered by collagen fibres, with no evidence of bacteria (100%). In the teeth of group III, the root apices had no collagen fibres but revealed resorptive areas containing microorganisms (cocci, bacilli, filaments and spirochetes) in all cases (100%). Conclusion Microorganisms organized as biofilms on the external root surface (extraradicular infection) were detected in primary teeth with pulp necrosis and radiographically visible periapical pathosis.

Insight into Anopheles (Nyssorhynchus) (Diptera: Culicidae) Species from Brazil

Anopheles (Nyssorhynchus) benarrochi s.l., Anopheles (Nyssorhynchus) oswaldoi s.l., and Anopheles (Nyssorhynchus) konderi s.l. collected in Acrelandia, state of Acre, Brazil, were identified based on morphological characters of the male genitalia, fourth-instar larvae, and pupae. Morphological variation was observed in the male genitalia of these species in comparison with specimens from other localities in Brazil. DNA sequence from the nuclear ribosomal second internal transcribed spacer of individuals identified as An. benarrochi s.l. by using male genitalia characteristics showed that the various morphological forms are conspecific but are distinct from An. benarrochi B from Colombia. Anopheles konderi s.l. and An. oswaldoi s.l. both misidentified as An. oswaldoi s.s. (Peryassu) throughout Brazil, may actually comprise at least two undescribed species. Diagnostic morphological characteristics of the male genitalia are provided to distinguish Anopheles benarrochi s.l., Anopheles oswaldoi s.l., and Anopheles konderi s.l. from morphologically similar species. Incrimination of An. oswaldoi s.s. in malaria transmission in Brazil needs further investigation because other undescribed species from Acre may have been confounded with this taxon.

Extracts from pitanga (Eugenia uniflora L.) leaves: Influence of extraction process on antioxidant properties and yield of phenolic compounds

Different extraction processes were employed to extract the polyphenolic compounds from pitanga (Eugenia uniflora L) leaves: a one-step process using water, ethanol or supercritical CO(2) as solvents, and a two-step process using supercritical CO(2) followed by either water or ethanol. The total polyphenolic compounds, total flavonoids and antioxidant activity were determined in all the extracts obtained. The process performance was evaluated with respect to three variables: global extraction yield, concentration and yield of both polyphenols and flavonoids in the extracts. For the one-step extraction, the results showed that the extraction yield increased with solvent polarity. For the two-step process, the results suggested that water was more efficient in extracting the phenolic compounds from E. uniflora when the matrix was previously extracted with scCO(2). With respect to the antioxidant activity, the ethanolic extracts obtained from both processes, using either the DPPH radical scavenging method or the beta-carotene bleaching method, presented high antioxidant activities. (C) 2010 Elsevier B.V. All rights reserved.