Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing nonlinearity

We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional methods (4DVAR and ETKF) and an ensemble transform Kalman smoother (ETKS) on the Lorenz 1963 model. We specifically investigated this performance with increasing nonlinearity and using a quasi-static variational assimilation algorithm as a comparison. Using the analysis root mean square error (RMSE) as a metric, these methods have been compared considering (1) assimilation window length and observation interval size and (2) ensemble size to investigate the influence of hybrid background error covariance matrices and nonlinearity on the performance of the methods. For short assimilation windows with close to linear dynamics, it has been shown that all hybrid methods show an improvement in RMSE compared to the traditional methods. For long assimilation window lengths in which nonlinear dynamics are substantial, the variational framework can have diffculties fnding the global minimum of the cost function, so we explore a quasi-static variational assimilation (QSVA) framework. Of the hybrid methods, it is seen that under certain parameters, hybrid methods which do not use a climatological background error covariance do not need QSVA to perform accurately. Generally, results show that the ETKS and hybrid methods that do not use a climatological background error covariance matrix with QSVA outperform all other methods due to the full flow dependency of the background error covariance matrix which also allows for the most nonlinearity.

Assessing the performance of dynamical trajectory estimates

Estimating trajectories and parameters of dynamical systems from observations is a problem frequently encountered in various branches of science; geophysicists for example refer to this problem as data assimilation. Unlike as in estimation problems with exchangeable observations, in data assimilation the observations cannot easily be divided into separate sets for estimation and validation; this creates serious problems, since simply using the same observations for estimation and validation might result in overly optimistic performance assessments. To circumvent this problem, a result is presented which allows us to estimate this optimism, thus allowing for a more realistic performance assessment in data assimilation. The presented approach becomes particularly simple for data assimilation methods employing a linear error feedback (such as synchronization schemes, nudging, incremental 3DVAR and 4DVar, and various Kalman filter approaches). Numerical examples considering a high gain observer confirm the theory.

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

A joint state and parameter estimation scheme for nonlinear dynamical systems

We present a novel algorithm for concurrent model state and parameter estimation in nonlinear dynamical systems. The new scheme uses ideas from three dimensional variational data assimilation (3D-Var) and the extended Kalman filter (EKF) together with the technique of state augmentation to estimate uncertain model parameters alongside the model state variables in a sequential filtering system. The method is relatively simple to implement and computationally inexpensive to run for large systems with relatively few parameters. We demonstrate the efficacy of the method via a series of identical twin experiments with three simple dynamical system models. The scheme is able to recover the parameter values to a good level of accuracy, even when observational data are noisy. We expect this new technique to be easily transferable to much larger models.

Implicit equal-weights particle filter

Filter degeneracy is the main obstacle for the implementation of particle filter in non-linear high-dimensional models. A new scheme, the implicit equal-weights particle filter (IEWPF), is introduced. In this scheme samples are drawn implicitly from proposal densities with a different covariance for each particle, such that all particle weights are equal by construction. We test and explore the properties of the new scheme using a 1,000-dimensional simple linear model, and the 1,000-dimensional non-linear Lorenz96 model, and compare the performance of the scheme to a Local Ensemble Kalman Filter. The experiments show that the new scheme can easily be implemented in high-dimensional systems and is never degenerate, with good convergence properties in both systems.

Microsatellite markers for hoop-petticoat daffodils (Narcissus sect. Bulbocodii; Amaryllidaceae)

• Premise of the study: Microsatellite markers were developed using hoop-petticoat daffodils ( Narcissus sect. Bulbocodii ; Amaryllidaceae) to aid in the taxonomic revision of the section, and further to evaluate their broad applicability for daffodil cultivar identification. • Methods and Results: Three hundred fifty-one primer pairs were developed using a commercial service. Nineteen polymorphic and repeatable markers were developed by screening 67 of these primer pairs. Of these, 11 chosen markers were used to screen 317 samples; the number of alleles per locus ranged from four to 21, and the observed heterozygosity ranged from 0.101 to 0.297. There were null genotypes in some samples for six of the markers. All the microsatellites were transferable to other Narcissus sections. • Conclusions: The results indicate that these new markers have sufficient potential variation to be used for taxonomic revision of the genus and to distinguish many commercial daffodil cultivars.

Are mortgage lenders guilty of the housing bubble? A UK perspective

Existing theoretical models of house prices and credit rely on continuous rationality of consumers, an assumption that has been frequently questioned in recent years. Meanwhile, empirical investigations of the relationship between prices and credit are often based on national-level data, which is then tested for structural breaks and asymmetric responses, usually with subsamples. Earlier author argues that local markets are structurally different from one another and so the coefficients of any estimated housing market model should vary from region to region. We investigate differences in the price–credit relationship for 12 regions of the UK. Markov-switching is introduced to capture asymmetric market behaviours and turning points. Results show that credit abundance had a large impact on house prices in Greater London and nearby regions alongside a strong positive feedback effect from past house price movements. This impact is even larger in Greater London and the South East of England when house prices are falling, which are the only instances where the credit effect is more prominent than the positive feedback effect. A strong positive feedback effect from past lending activity is also present in the loan dynamics. Furthermore, bubble probabilities extracted using a discrete Kalman filter neatly capture market turning points.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Multiple camera people detection and tracking using support integration

This paper proposes a method to locate and track people by combining evidence from multiple cameras using the homography constraint. The proposed method use foreground pixels from simple background subtraction to compute evidence of the location of people on a reference ground plane. The algorithm computes the amount of support that basically corresponds to the ""foreground mass"" above each pixel. Therefore, pixels that correspond to ground points have more support. The support is normalized to compensate for perspective effects and accumulated on the reference plane for all camera views. The detection of people on the reference plane becomes a search for regions of local maxima in the accumulator. Many false positives are filtered by checking the visibility consistency of the detected candidates against all camera views. The remaining candidates are tracked using Kalman filters and appearance models. Experimental results using challenging data from PETS`06 show good performance of the method in the presence of severe occlusion. Ground truth data also confirms the robustness of the method. (C) 2010 Elsevier B.V. All rights reserved.

Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt.

Extração de informação sobre bases de dados textuais

Com a crescente popularização dos microcomputadores e da rede mundial de informação, Internet, uma enorme variedade e quantidade de informações estão se tornando acessíveis a um número cada vez maior de pessoas. Desta forma, também cresce a importância de se extrair a informação útil que está no grande conjunto das informações disponibilizadas. Hoje há muito mais dados na forma de textos eletrônicos do que em tempos passados, mas muito disto é ignorado. Nenhuma pessoa pode ler, entender e sintetizar megabytes de texto no seu cotidiano. Informações perdidas, e conseqüentemente oportunidades perdidas, estimularam pesquisas na exploração de várias estratégias para a administração da informação, a fim de estabelecer uma ordem na imensidão de textos. As estratégias mais comuns são recuperação de informações, filtragem de informações e outra relativamente nova, chamada de extração de informações. A extração de informações tem muitas aplicações potenciais. Por exemplo, a informação disponível em textos não-estruturados pode ser armazenada em bancos de dados tradicionais e usuários podem examiná-las através de consultas padrão. Para isso, há um complexo trabalho de gerenciamento, que é conseqüência da natureza não estruturada e da difícil análise dos dados. Os dados de entrada, que são os textos semi ou não-estruturados, são manipulados por um processo de extração configurado através de bases de conhecimento criadas pelo usuário do sistema. Esta dissertação tem como objetivo a definição de uma linguagem, com base em uma arquitetura de múltiplos níveis, para extrair satisfatoriamente as informações desejadas pelo usuário, presentes em bases de dados textuais. Também faz parte deste trabalho a implementação de um protótipo que utiliza a linguagem proposta.

Estudo, proposta e previsão de desempenho de um filtro de energia para experimentos com alta resolução de comprimento de onda em fontes pulsantes de nêutrons

Em fontes de nêutrons por spallation para pesquisa de materiais, o comprimento de onda dos nêutrons é geralmente determinado pelos tempos de percurso (TOF) dos nêutrons desde a fonte até o detector. A precisão atingível é limitada pelo fato de o tempo de emissão do pulso característico do sistema alvo/moderador ser diferente de zero (a situação ideal fictícia seria a emissão se ocorresse na forma de um impulso). “Moderadores acoplados” (elementos usados para produzir feixes de alta intensidade com nêutrons de baixa energia) apresentam um decaimento de intensidade em função do tempo muito longo, ao longo de todo o espectro usado nos experimentos. Por este motivo, “moderadores desacoplados”, os quais produzem feixes com intensidade mais reduzida, são freqüentemente usados para instrumentos que requerem alta resolução. Neste trabalho, propusemos e analisamos uma nova técnica de filtragem dinâmica de feixes de nêutrons polarizados de baixa energia para experimentos que utilizam TOF na determinação do comprimento de onda. O dispositivo consiste de um sistema ótico polarizador/analisador e um inversor de spin seletivo em energia, o qual funciona por ressonância espacial do spin. Variando a condição de ressonância em sincronia com a estrutura temporal do pulso de nêutrons (através do controle de campos magnéticos), o filtro pode ajustar a resolução de energia (ou de comprimento de onda) de pulsos de banda larga em tais experimentos, separando os nêutrons com a correta relação “TOF/comprimento de onda” dos demais Um método para o cálculo de desempenho do sistema foi apresentado em um Trabalho Individual (TI) (PARIZZI et al., 2002 - i), do qual se fará aqui uma breve revisão além de amplo uso na otimização dos parâmetros a serem ajustados para o projeto do filtro. Os resultados finais mostram que ganhos consideráveis em resolução podem ser obtidos com a aplicação desta técnica em experimentos de reflectometria por tempo de percurso, sem que para tal seja necessário comprometer a intensidade do feixe usado pelo mesmo instrumento quando operado em um modo de baixa resolução, dando ao usuário do instrumento a opção de escolher a relação ótima entre intensidade e resolução para seu experimento. Como parte da conclusão desta dissertação, é apresentada uma proposta de parâmetros para a construção deste tipo de filtro e previsão de desempenho da configuração proposta, baseada no software de modelamento desenvolvido.

Análise numérica de escoamentos turbulentos tridimensionais empregando o método de elementos finitos e simulação de grandes escalas

O presente trabalho apresenta o estudo e implementação de um algoritmo numérico para análise de escoamentos turbulentos, tridimensionais, transientes, incompressíveis e isotérmicos, através da Simulação de Grande Escalas, empregando o Método de Elementos Finitos. A modelagem matemática do problema baseia-se nas equações de conservação de massa e quantidade de movimento de um fluido quase-incompressível. Adota-se um esquema de Taylor-Galerkin, com integração reduzida e fórmulas analíticas das funções de interpolação, para o elemento hexaédrico de oito nós, com funções lineares para as componentes de velocidade e constante no elemento para a pressão. Para abordar o problema da turbulência, emprega-se a Simulação de Grandes Escalas, com modelo para escalas inferiores à resolução da malha. Foram implementados o modelo clássico de Smagorinsky e o modelo dinâmico de viscosidade turbulenta, inicialmente proposto por Germano et al, 1991. Uma nova metodologia, denominada filtragem por elementos finitos independentes, é proposta e empregada, para o processo de segunda filtragem do modelo dinâmico. O esquema, que utiliza elementos finitos independentes envolvendo cada nó da malha original, apresentou bons resultados com um baixo custo computacional adicional. São apresentados resultados para problemas clássicos, que demonstram a validade do sistema desenvolvido. A aplicabilidade do esquema utilizado, para análise de escoamentos caracterizados por elevados números de Reynolds, é discutida no capítulo final. São apresentadas sugestões para aprimorar o esquema, visando superar as dificuldades encontradas com respeito ao tempo total de processamento, para análise de escoamentos tridimensionais, turbulentos e transientes .

Medição de deslocamento através de sensores magnetoresistivos aplicada ao movimento mandibular

Neste trabalho é apresentado um método para medição de deslocamentos sem contato, utilizando sensores magnetoresistivos, os quais são sensibilizados pela variação do campo magnético produzido por um imã permanente em deslocamento no espaço. Os sensores magnetoresistivos possuem, internamente, uma ponte de Wheathestone, onde a resistência varia conforme varia o campo magnético, de modo que o circuito mais indicado para este caso é um amplificador e um filtro para cada sensor. O principal objetivo do trabalho é a obtenção de uma técnica para medir deslocamentos sem contato, e estender os resultados para medida de movimentos mandibulares. A montagem consiste de duas placas de celeron, distantes 30mm uma da outra e unidas por parafusos de polietileno. Em cada uma destas placas foram dispostos quatro sensores, num total de oito, sendo que para cada um deles existe um circuito de amplificação e filtragem do sinal de saída. Sob uma chapa de alumínio foi fixado este equipamento e uma mesa de calibração em 3D, a qual, após a obtenção da matriz de calibração, foi substituída por um emulador de movimento mandibular. Os parâmetros do modelo foram estimados através do método dos mínimos quadrados com auxílio do software Matlab, Release 12. Este software também foi utilizado para o sistema de aquisição de dados durante a realização dos experimentos. A imprecisão dos resultados obtidos na determinação dos deslocamentos, está na ordem de décimos de milímetros. O trabalho apresenta, também, o mapeamento do campo magnético do magneto utilizado nos experimentos através do software FEM2000 – Método de elementos finitos aplicado ao eletromagnetismo.