Dynamical aspects of atmospheric data assimilation in the tropics

A faithful depiction of the tropical atmosphere requires three-dimensional sets of observations. Despite the increasing amount of observations presently available, these will hardly ever encompass the entire atmosphere and, in addition, observations have errors. Additional (background) information will always be required to complete the picture. Valuable added information comes from the physical laws governing the flow, usually mediated via a numerical weather prediction (NWP) model. These models are, however, never going to be error-free, why a reliable estimate of their errors poses a real challenge since the whole truth will never be within our grasp. The present thesis addresses the question of improving the analysis procedures for NWP in the tropics. Improvements are sought by addressing the following issues: - the efficiency of the internal model adjustment, - the potential of the reliable background-error information, as compared to observations, - the impact of a new, space-borne line-of-sight wind measurements, and - the usefulness of multivariate relationships for data assimilation in the tropics. Most NWP assimilation schemes are effectively univariate near the equator. In this thesis, a multivariate formulation of the variational data assimilation in the tropics has been developed. The proposed background-error model supports the mass-wind coupling based on convectively-coupled equatorial waves. The resulting assimilation model produces balanced analysis increments and hereby increases the efficiency of all types of observations. Idealized adjustment and multivariate analysis experiments highlight the importance of direct wind measurements in the tropics. In particular, the presented results confirm the superiority of wind observations compared to mass data, in spite of the exact multivariate relationships available from the background information. The internal model adjustment is also more efficient for wind observations than for mass data. In accordance with these findings, new satellite wind observations are expected to contribute towards the improvement of NWP and climate modeling in the tropics. Although incomplete, the new wind-field information has the potential to reduce uncertainties in the tropical dynamical fields, if used together with the existing satellite mass-field measurements. The results obtained by applying the new background-error representation to the tropical short-range forecast errors of a state-of-art NWP model suggest that achieving useful tropical multivariate relationships may be feasible within an operational NWP environment.

Crystallization on the Mesoscale : Self-Assembly of Iron Oxide Nanocubes into Mesocrystals

Self-assembly of nanoparticles is a promising route to form complex, nanostructured materials with functional properties. Nanoparticle assemblies characterized by a crystallographic alignment of the nanoparticles on the atomic scale, i.e. mesocrystals, are commonly found in nature with outstanding functional and mechanical properties. This thesis aims to investigate and understand the formation mechanisms of mesocrystals formed by self-assembling iron oxide nanocubes. We have used the thermal decomposition method to synthesize monodisperse, oleate-capped iron oxide nanocubes with average edge lengths between 7 nm and 12 nm and studied the evaporation-induced self-assembly in dilute toluene-based nanocube dispersions. The influence of packing constraints on the alignment of the nanocubes in nanofluidic containers has been investigated with small and wide angle X-ray scattering (SAXS and WAXS, respectively). We found that the nanocubes preferentially orient one of their {100} faces with the confining channel wall and display mesocrystalline alignment irrespective of the channel widths.  We manipulated the solvent evaporation rate of drop-cast dispersions on fluorosilane-functionalized silica substrates in a custom-designed cell. The growth stages of the assembly process were investigated using light microscopy and quartz crystal microbalance with dissipation monitoring (QCM-D). We found that particle transport phenomena, e.g. the coffee ring effect and Marangoni flow, result in complex-shaped arrays near the three-phase contact line of a drying colloidal drop when the nitrogen flow rate is high. Diffusion-driven nanoparticle assembly into large mesocrystals with a well-defined morphology dominates at much lower nitrogen flow rates. Analysis of the time-resolved video microscopy data was used to quantify the mesocrystal growth and establish a particle diffusion-based, three-dimensional growth model. The dissipation obtained from the QCM-D signal reached its maximum value when the microscopy-observed lateral growth of the mesocrystals ceased, which we address to the fluid-like behavior of the mesocrystals and their weak binding to the substrate. Analysis of electron microscopy images and diffraction patterns showed that the formed arrays display significant nanoparticle ordering, regardless of the distinctive formation process.  We followed the two-stage formation mechanism of mesocrystals in levitating colloidal drops with real-time SAXS. Modelling of the SAXS data with the square-well potential together with calculations of van der Waals interactions suggests that the nanocubes initially form disordered clusters, which quickly transform into an ordered phase.