Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Ensemble clustering in deterministic ensemble Kalman filters

Ensemble clustering (EC) can arise in data assimilation with ensemble square root filters (EnSRFs) using non-linear models: an M-member ensemble splits into a single outlier and a cluster of M−1 members. The stochastic Ensemble Kalman Filter does not present this problem. Modifications to the EnSRFs by a periodic resampling of the ensemble through random rotations have been proposed to address it. We introduce a metric to quantify the presence of EC and present evidence to dispel the notion that EC leads to filter failure. Starting from a univariate model, we show that EC is not a permanent but transient phenomenon; it occurs intermittently in non-linear models. We perform a series of data assimilation experiments using a standard EnSRF and a modified EnSRF by a resampling though random rotations. The modified EnSRF thus alleviates issues associated with EC at the cost of traceability of individual ensemble trajectories and cannot use some of algorithms that enhance performance of standard EnSRF. In the non-linear regimes of low-dimensional models, the analysis root mean square error of the standard EnSRF slowly grows with ensemble size if the size is larger than the dimension of the model state. However, we do not observe this problem in a more complex model that uses an ensemble size much smaller than the dimension of the model state, along with inflation and localisation. Overall, we find that transient EC does not handicap the performance of the standard EnSRF.

Cooled infrared filters and dichroics for the sea and land surface temperature radiometer (SLSTR)

The Sea and Land Surface Temperature Radiometer (SLSTR) is a nine channel visible and infrared high precision radiometer designed to provide climate data of global sea and land surface temperatures. The SLSTR payload is destined to fly on the Ocean and Medium-Resolution Land Mission for the ESA/EU Global Monitoring for Environment and Security (GMES) Programme Sentinel-3 mission to measure the sea and land temperature and topography for near real-time environmental and atmospheric climate monitoring of the Earth. In this paper we describe the optical layout of infrared optics in the instrument, spectral thin-film multilayer design, and system channel throughput analysis for the combined interference filter and dichroic beamsplitter coatings to discriminate wavelengths at 3.74, 10.85 & 12.0 μm. The rationale for selection of thin-film materials, deposition technique, and environmental testing, inclusive of humidity, thermal cycling and ionizing radiation testing are also described.

Ensemble transform Kalman-Bucy filters

Two recent works have adapted the Kalman–Bucy filter into an ensemble setting. In the first formulation, the ensemble of perturbations is updated by the solution of an ordinary differential equation (ODE) in pseudo-time, while the mean is updated as in the standard Kalman filter. In the second formulation, the full ensemble is updated in the analysis step as the solution of single set of ODEs in pseudo-time. Neither requires matrix inversions except for the frequently diagonal observation error covariance. We analyse the behaviour of the ODEs involved in these formulations. We demonstrate that they stiffen for large magnitudes of the ratio of background error to observational error variance, and that using the integration scheme proposed in both formulations can lead to failure. A numerical integration scheme that is both stable and is not computationally expensive is proposed. We develop transform-based alternatives for these Bucy-type approaches so that the integrations are computed in ensemble space where the variables are weights (of dimension equal to the ensemble size) rather than model variables. Finally, the performance of our ensemble transform Kalman–Bucy implementations is evaluated using three models: the 3-variable Lorenz 1963 model, the 40-variable Lorenz 1996 model, and a medium complexity atmospheric general circulation model known as SPEEDY. The results from all three models are encouraging and warrant further exploration of these assimilation techniques.

The effect of (mis-specified) GARCH filters on the finite sample distribution of the BDS test

This paper considers the effect of using a GARCH filter on the properties of the BDS test statistic as well as a number of other issues relating to the application of the test. It is found that, for certain values of the user-adjustable parameters, the finite sample distribution of the test is far-removed from asymptotic normality. In particular, when data generated from some completely different model class are filtered through a GARCH model, the frequency of rejection of iid falls, often substantially. The implication of this result is that it might be inappropriate to use non-rejection of iid of the standardised residuals of a GARCH model as evidence that the GARCH model ‘fits’ the data.

Spectral design of temperature-invariant narrow bandpass filters for the mid-infrared

The ability of narrow bandpass filters to discriminate wavelengths between closely-separated gas absorption lines is crucial in many areas of infrared spectroscopy. As improvements to the sensitivity of infrared detectors enables operation in uncontrolled high-temperature environments, this imposes demands on the explicit bandpass design to provide temperature-invariant behavior. The unique negative temperature coefficient (dn/dT<0) of Lead-based (Pb) salts, in combination with dielectric materials enable bandpass filters with exclusive immunity to shifts in wavelength with temperature. This paper presents the results of an investigation into the interdependence between multilayer bandpass design and optical materials together with a review on invariance at elevated temperatures.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

In vitro osteogenesis on fluorcanasite glass-ceramic with three different chemical compositions

This study aimed at investigating in vitro osteogenesis on three fluorcanasite glass-ceramic compositions with different solubilities (K3, K5, and K8). Osteoblastic cells were obtained from human alveolar bone fragments and cultured under standard osteogenic condition until subconfluence. First passage cells were cultured on K3, K5, and K8 and on Bioglass (R) 45S5 (45S5-control). Cell adhesion was evaluated at 24 h. For proliferation and viability, cells were cultured for 1, 4, and 10 days. Total protein content and alkaline phosphatase (ALP) activity were measured at 7, 14, and 21 days. Cultures were stained with Alizarin red at 21 days, for detection of mineralized matrix. Data were compared by ANOVA followed by Duncan`s test. Cell adhesion, cell proliferation, viability, total protein content, and ALP activity were not affected by fluorcanasite glass-ceramic composition and solubility. Bone-like formation was similar on all fluorcanasite-glass ceramics and was reduced compared to 45S5. The changes in the chemical composition and consequently solubility of the fluorcanasite glass-ceramics tested here did not significantly alter the in vitro osteogenesis. Further modifications of the chemical composition of the fluorcanasite glass-ceramic would be required to improve bone response, making this biomaterial a good candidate to be employed as a bone substitute.

Untangling associations between chironomid taxa in Neotropical streams using local and landscape filters

1. Analyses of species association have major implications for selecting indicators for freshwater biomonitoring and conservation, because they allow for the elimination of redundant information and focus on taxa that can be easily handled and identified. These analyses are particularly relevant in the debate about using speciose groups (such as the Chironomidae) as indicators in the tropics, because they require difficult and time-consuming analysis, and their responses to environmental gradients, including anthropogenic stressors, are poorly known. 2. Our objective was to show whether chironomid assemblages in Neotropical streams include clear associations of taxa and, if so, how well these associations could be explained by a set of models containing information from different spatial scales. For this, we formulated a priori models that allowed for the influence of local, landscape and spatial factors on chironomid taxon associations (CTA). These models represented biological hypotheses capable of explaining associations between chironomid taxa. For instance, CTA could be best explained by local variables (e.g. pH, conductivity and water temperature) or by processes acting at wider landscape scales (e.g. percentage of forest cover). 3. Biological data were taken from 61 streams in Southeastern Brazil, 47 of which were in well-preserved regions, and 14 of which drained areas severely affected by anthropogenic activities. We adopted a model selection procedure using Akaike`s information criterion to determine the most parsimonious models for explaining CTA. 4. Applying Kendall`s coefficient of concordance, seven genera (Tanytarsus/Caladomyia, Ablabesmyia, Parametriocnemus, Pentaneura, Nanocladius, Polypedilum and Rheotanytarsus) were identified as associated taxa. The best-supported model explained 42.6% of the total variance in the abundance of associated taxa. This model combined local and landscape environmental filters and spatial variables (which were derived from eigenfunction analysis). However, the model with local filters and spatial variables also had a good chance of being selected as the best model. 5. Standardised partial regression coefficients of local and landscape filters, including spatial variables, derived from model averaging allowed an estimation of which variables were best correlated with the abundance of associated taxa. In general, the abundance of the associated genera tended to be lower in streams characterised by a high percentage of forest cover (landscape scale), lower proportion of muddy substrata and high values of pH and conductivity (local scale). 6. Overall, our main result adds to the increasing number of studies that have indicated the importance of local and landscape variables, as well as the spatial relationships among sampling sites, for explaining aquatic insect community patterns in streams. Furthermore, our findings open new possibilities for the elimination of redundant data in the assessment of anthropogenic impacts on tropical streams.

Photoluminescence behavior of Eu(3+) ion doped into gamma- and alpha-alumina systems prepared by combustion, ceramic and Pechini methods

Al(2)O(3):Eu(3+)(1%) samples were prepared by combustion, ceramic, and Pechini methods annealed from 400 to 1400 degrees C. XRD patterns indicate that samples heated up to 1000 degrees C present disordered character of activated alumina (gamma-Al(2)O(3)). However, alpha-Al(2)O(3) phase showed high crystallinity and thermostability at 1200-1400 degrees C. The sample characterizations were also carried out by means of infrared spectroscopy (IR), scanning electron microscopy (SEM) and specific surface areas analysis (BET method). Excitation spectra of Al(2)O(3):Eu(3+) samples present broaden bands attributed to defects of Al(2)O(3) matrices and to LMCT state of O -> Eu(3+), however, the narrow bands are assigned to (7)F(0) -> (5)D(J),(5)H(J) and (5)L(J) transitions of Eu(3+) ion. Emission spectra of samples calcined up to 1000 degrees C show broaden bands for (5)D(0) -> (7)F(J) transitions of Eu(3+) ion suggesting that the rare earth ion is in different symmetry sites showed by inhomogeneous line broadening of bands, confirming the predominance of the gamma-alumina phase. For all samples heated from 1200 to 1400 degrees C the spectra exhibit narrow (5)D(0) -> (7)F(J) transitions of Eu(3+) ion indicating the conversion of gamma to alpha-Al(2)O(3) phases, a high intensity narrow peak around 695 nm assigned to R lines of Cr(3+) ion is shown. Al(2)O(3):Eu(3+) heated up to 1100 degrees C presents an increase in the Omega(2) intensity parameter with the increase of temperatures enhancing the covalent character of metal-donor interaction. The disordered structural systems present the highest values of emission quantum efficiencies (eta). CIE coordinates of Al(2)O(3):Eu(3+) are also discussed. (C) 2007 Elsevier Inc. All rights reserved.

Synthesis and characterization of glass-ceramic microspheres for thermotherapy

Glass microspheres containing radionuclides are used to treat liver cancer. A promising alternative therapy is being developed based on the magnetic hyperthermia which is related to the heat supplied by a magnetic material under an alternating current magnetic field. The advantage of this option is that most of killed cells are cancer cells which are more susceptible to the temperature raise. In the present work aluminum iron silicate glasses containing minor glass modifiers and nucleating agents were synthesized as irregular shape particles which were further transformed in microspheres by using a petrol liquefied gas-oxygen torch. The optimized processing parameters which lead to microspheres that give a response to the magnetic field were determined. The dissolution rate in water at 90 degrees C was determined to be 3 x 10(-8) g cm(-2) min(-1). The microsphere size distribution was determined by laser scattering. The crystalline phase responsible for the ferromagnetic response was identified as magnetite. Since this phase has a high saturation magnetization and high Curie temperature, it is potentially useful for biomedical applications. The hysteresis magnetic loop was measured for materials produced in different conditions, and some of them showed to be appropriated for thermotherapy. The ratio Fe(3+)/Fe(total) was determined by Mossbauer spectroscopy. (C) 2010 Elsevier B.V. All rights reserved.

Intergranular properties of uniaxially pressed YBa(2)Cu(3)O(7-delta) ceramic samples

We performed measurements of electrical resistivity as a function of temperature, rho(T), in polycrystalline samples of YBa(2)Cu(3)O(7-delta) (Y-123) subjected to different uniaxial compacting pressures. We observed by using X-ray diffractometry that samples have a very similar composition. Most of the identified peaks are related to the superconducting Y-123 phase. Also, from the X-ray diffraction patterns performed, in powder and pellet samples, we estimated the Lotgering factor along the (00l) direction, F((00l)). The results indicate that F((00l)) increases from 0.13 to 0.16. From electrical resistivity measurements as a function of temperature, we were able to separate contributions arising from both the grain misalignment and microstructural defects. We found appreciable degradation in the normal-state transport properties of samples with an increase in uniaxial compacting pressure. It seems that this type of behavior is associated with an increase in the influence of microstructural defects at the intergranular level. The experimental results are analyzed in the framework of a current conduction model of granular samples.