Diurnal warm-layer events in the western Mediterranean and European shelf seas

We characterize near-surface ocean diurnal warm-layer events, using satellite observations and fields from numerical weather forecasting. The study covers April to September, 2006, over the area 11°W to 17°E and 35°N to 57°N, with 0.1° cells. We use hourly satellite SSTs from which peak amplitudes of diurnal cycles in SST (dSSTs) can be estimated with error ∼0.3 K. The diurnal excursions of SST observed are spatially and temporally coherent. The largest dSSTs exceed 6 K, affect 0.01% of the surface, and are seen in the Mediterranean, North and Irish Seas. There is an anti-correlation between the magnitude and the horizontal length scale of dSST events. Events wherein dSST exceeds 4 K have length scales of ≤40 km. From the frequency distribution of different measures of wind-speed minima, we infer that extreme dSST maxima arise where conditions of low wind speed are sustained from early morning to mid afternoon.

Diabatic balance model for the equatorial atmosphere

Using an asymptotic expansion, a balance model is derived for the shallow-water equations (SWE) on the equatorial beta-plane that is valid for planetary-scale equatorial dynamics and includes Kelvin waves. In contrast to many theories of tropical dynamics, neither a strict balance between diabatic heating and vertical motion nor a small Froude number is required. Instead, the expansion is based on the smallness of the ratio of meridional to zonal length scales, which can also be interpreted as a separation in time scale. The leading-order model is characterized by a semigeostrophic balance between the zonal wind and meridional pressure gradient, while the meridional wind v vanishes; the model is thus asymptotically nondivergent, and the nonzero correction to v can be found at the next order. Importantly for applications, the diagnostic balance relations are linear for winds when inferring the wind field from mass observations and the winds can be diagnosed without direct observations of diabatic heating. The accuracy of the model is investigated through a set of numerical examples. These examples show that the diagnostic balance relations can remain valid even when the dynamics do not, and the balance dynamics can capture the slow behavior of a rapidly varying solution.

Turbulent structure and scaling of the inertial subrange in a stratocumulus-topped boundary layer observed by a Doppler lidar

The turbulent structure of a stratocumulus-topped marine boundary layer over a 2-day period is observed with a Doppler lidar at Mace Head in Ireland. Using profiles of vertical velocity statistics, the bulk of the mixing is identified as cloud driven. This is supported by the pertinent feature of negative vertical velocity skewness in the sub-cloud layer which extends, on occasion, almost to the surface. Both coupled and decoupled turbulence characteristics are observed. The length and timescales related to the cloud-driven mixing are investigated and shown to provide additional information about the structure and the source of the mixing inside the boundary layer. They are also shown to place constraints on the length of the sampling periods used to derive products, such as the turbulent dissipation rate, from lidar measurements. For this, the maximum wavelengths that belong to the inertial subrange are studied through spectral analysis of the vertical velocity. The maximum wavelength of the inertial subrange in the cloud-driven layer scales relatively well with the corresponding layer depth during pronounced decoupled structure identified from the vertical velocity skewness. However, on many occasions, combining the analysis of the inertial subrange and vertical velocity statistics suggests higher decoupling height than expected from the skewness profiles. Our results show that investigation of the length scales related to the inertial subrange significantly complements the analysis of the vertical velocity statistics and enables a more confident interpretation of complex boundary layer structures using measurements from a Doppler lidar.

Theoretical insight into diagnosing observation error correlations using observation-minus-background and observation-minus-analysis statistics

To improve the quantity and impact of observations used in data assimilation it is necessary to take into account the full, potentially correlated, observation error statistics. A number of methods for estimating correlated observation errors exist, but a popular method is a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. The accuracy of the results it yields is unknown as the diagnostic is sensitive to the difference between the exact background and exact observation error covariances and those that are chosen for use within the assimilation. It has often been stated in the literature that the results using this diagnostic are only valid when the background and observation error correlation length scales are well separated. Here we develop new theory relating to the diagnostic. For observations on a 1D periodic domain we are able to the show the effect of changes in the assumed error statistics used in the assimilation on the estimated observation error covariance matrix. We also provide bounds for the estimated observation error variance and eigenvalues of the estimated observation error correlation matrix. We demonstrate that it is still possible to obtain useful results from the diagnostic when the background and observation error length scales are similar. In general, our results suggest that when correlated observation errors are treated as uncorrelated in the assimilation, the diagnostic will underestimate the correlation length scale. We support our theoretical results with simple illustrative examples. These results have potential use for interpreting the derived covariances estimated using an operational system.

Conditioning of the weak-constraint variational data assimilation problem for numerical weather prediction

4-Dimensional Variational Data Assimilation (4DVAR) assimilates observations through the minimisation of a least-squares objective function, which is constrained by the model flow. We refer to 4DVAR as strong-constraint 4DVAR (sc4DVAR) in this thesis as it assumes the model is perfect. Relaxing this assumption gives rise to weak-constraint 4DVAR (wc4DVAR), leading to a different minimisation problem with more degrees of freedom. We consider two wc4DVAR formulations in this thesis, the model error formulation and state estimation formulation. The 4DVAR objective function is traditionally solved using gradient-based iterative methods. The principle method used in Numerical Weather Prediction today is the Gauss-Newton approach. This method introduces a linearised `inner-loop' objective function, which upon convergence, updates the solution of the non-linear `outer-loop' objective function. This requires many evaluations of the objective function and its gradient, which emphasises the importance of the Hessian. The eigenvalues and eigenvectors of the Hessian provide insight into the degree of convexity of the objective function, while also indicating the difficulty one may encounter while iterative solving 4DVAR. The condition number of the Hessian is an appropriate measure for the sensitivity of the problem to input data. The condition number can also indicate the rate of convergence and solution accuracy of the minimisation algorithm. This thesis investigates the sensitivity of the solution process minimising both wc4DVAR objective functions to the internal assimilation parameters composing the problem. We gain insight into these sensitivities by bounding the condition number of the Hessians of both objective functions. We also precondition the model error objective function and show improved convergence. We show that both formulations' sensitivities are related to error variance balance, assimilation window length and correlation length-scales using the bounds. We further demonstrate this through numerical experiments on the condition number and data assimilation experiments using linear and non-linear chaotic toy models.

Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics

With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

Attenuation and damping of electromagnetic fields: influence of inertia and displacement current

New results for attenuation and damping of electromagnetic fields in rigid conducting media are derived under the conjugate influence of inertia due to charge carriers and displacement current. Inertial effects are described by a relaxation time for the current density in the realm of an extended Ohm`s law. The classical notions of poor and good conductors are rediscussed on the basis of an effective electric conductivity, depending on both wave frequency and relaxation time. It is found that the attenuation for good conductors at high frequencies depends solely on the relaxation time. This means that the penetration depth saturates to a minimum value at sufficiently high frequencies. It is also shown that the actions of inertia and displacement current on damping of magnetic fields are opposite to each other. That could explain why the classical decay time of magnetic fields scales approximately as the diffusion time. At very small length scales, the decay time could be given either by the relaxation time or by a fraction of the diffusion time, depending on whether inertia or displacement current, respectively, would prevail on magnetic diffusion.

Synchrotron X-ray imaging via ultra-small-angle scattering: principles of quantitative analysis and application in studying bone integration to synthetic grafting materials

Optimized experimental conditions for extracting accurate information at subpixel length scales from analyzer-based X-ray imaging were obtained and applied to investigate bone regeneration by means of synthetic beta-TCP grafting materials in a rat calvaria model. The results showed a 30% growth in the particulate size due to bone ongrowth/ingrowth within the critical size defect over a 1-month healing period.

Crossover between macroscopic and mesoscopic regimes of vortex interactions in type-II superconductors

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Studying nonlinear effects on the early stage of phase ordering using a decomposition method

Nonlinear effects on the early stage of phase ordering are studied using Adomian's decomposition method for the Ginzburg-Landau equation for a nonconserved order parameter. While the long-time regime and the linear behavior at short times of the theory are well understood, the onset of nonlinearities at short times and the breaking of the linear theory at different length scales are less understood. In the Adomians decomposition method, the solution is systematically calculated in the form of a polynomial expansion for the order parameter, with a time dependence given as a series expansion. The method is very accurate for short times, which allows to incorporate the short-time dynamics of the nonlinear terms in a analytical and controllable way. (c) 2005 Elsevier B.V. All rights reserved.

Interface morphology snapshots of vertically segregated thin films of semiconducting polymer/polystyrene blends

We present atomic force microscopic images of the interphase morphology of vertically segregated thin films spin coated from two-component mixtures of poly[2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenylene-vinylene] (MEH-PPV) and polystyrene (PS). We investigate the mechanism leading to the formation of wetting layers and lateral structures during spin coating using different PS molecular weights, solvents and blend compositions. Spinodal decomposition competes with the formation of surface enrichment layers. The spinodal wavelength as a function of PS molecular weight follows a power-law similar to bulk-like spinodal decomposition. Our experimental results indicate that length scales of interface topographical features can be adjusted from the nanometer to micrometer range. The importance of controlled arrangement of semiconducting polymers in thin film geometries for organic optoelectronic device applications is discussed. (c) 2007 Elsevier Ltd. All rights reserved.

Bacterial nanocellulose for medical implants

Bacterial cellulose (BC) has established to be a remarkably versatile biomaterial and can be used in wide variety of applied scientific endeavours, especially for medical devices. In fact, biomedical devices recently have gained a significant amount of attention because of an increased interest in tissue-engineered products for both wound care and the regeneration of damaged or diseased organs. Due to its unique nanostructure and properties, microbial cellulose is a natural candidate for numerous medical and tissue-engineered applications. Hydrophilic bacterial cellulose fibers of an average diameter of 50 nm are produced by the bacterium Acetobacter xylinum, using a fermentation process. The microbial cellulose fiber has a high degree of crystallinity. Using direct nanomechanical measurement, determined that these fibers are very strong and when used in combination with other biocompatible materials, produce nanocomposites particularly suitable for use in human and veterinary medicine. Moreover, the nanostructure and morphological similarities with collagen make BC attractive for cell immobilization and cell support. The architecture of BC materials can be engineered over length scales ranging from nano to macro by controlling the biofabrication process. The chapter describes the fundamentals, purification and morphological investigation of bacterial cellulose. This chapter deals with the modification of microbial cellulose and how to increase the compatibility between cellulosic surfaces and a variety of plastic materials. Furthermore, provides deep knowledge of fascinating current and future applications of bacterial cellulose and their nanocomposites especially in the medical field, materials with properties closely mimic that of biological organs and tissues were described. © Springer-Verlag Berlin Heidelberg 2013.

High Dispersivity Bacterial Cellulose/Carbon Nanotube Nanocomposite for Sensor Applications

Bacterial cellulose (BC) has established to be a remarkably versatile biomaterial and can be used in wide variety of applied scientific endeavors, especially for medical devices. In fact, biomedical devices recently have gained a significant amount of attention because of increased interesting tissue-engineered products for both wound care and the regeneration of damaged or diseased organs. The architecture of BC materials can be engineered over length scales ranging from nano to macro by controlling the biofabrication process, besides, surface modifications bring a vital role in in vivo performance of biomaterials. In this work, bacterial cellulose fermentation was modified with carbon nanotubes for sensor applications and diseases diagnostic. SEM images showed that polymer modified-carbon nanotube (PVOH-carbon nanotube) produced well dispersed system and without agglomeration. Influences of carbon nanotube in bacterial cellulose were analyzed by FTIR. TGA showed higher thermal properties of developed bionanocomposites.

Mass and surface fractal in supercritical dried silica aerogels prepared with additions of sodium dodecyl sulfate

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multiscale sensing of antibody - antigen interactions by organic transistors and single-molecule force spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)