84 resultados para 3-dimensional Structure


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The possibility of using a time sequence of surface pressure observations in four-dimensional data assimilation is being investigated. It is shown that a linear multilevel quasi-geostrophic model can be updated successfully with surface data alone, provided the number of time levels are at least as many as the number of vertical levels. It is further demonstrated that current statistical analysis procedures are very inefficient to assimilate surface observations, and it is shown by numerical experiments that the vertical interpolation must be carried out using the structure of the most dominating baroclinic mode in order to obtain a satisfactory updating. Different possible ways towards finding a practical solution are being discussed.

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With the introduction of new observing systems based on asynoptic observations, the analysis problem has changed in character. In the near future we may expect that a considerable part of meteorological observations will be unevenly distributed in four dimensions, i.e. three dimensions in space and one in time. The term analysis, or objective analysis in meteorology, means the process of interpolating observed meteorological observations from unevenly distributed locations to a network of regularly spaced grid points. Necessitated by the requirement of numerical weather prediction models to solve the governing finite difference equations on such a grid lattice, the objective analysis is a three-dimensional (or mostly two-dimensional) interpolation technique. As a consequence of the structure of the conventional synoptic network with separated data-sparse and data-dense areas, four-dimensional analysis has in fact been intensively used for many years. Weather services have thus based their analysis not only on synoptic data at the time of the analysis and climatology, but also on the fields predicted from the previous observation hour and valid at the time of the analysis. The inclusion of the time dimension in objective analysis will be called four-dimensional data assimilation. From one point of view it seems possible to apply the conventional technique on the new data sources by simply reducing the time interval in the analysis-forecasting cycle. This could in fact be justified also for the conventional observations. We have a fairly good coverage of surface observations 8 times a day and several upper air stations are making radiosonde and radiowind observations 4 times a day. If we have a 3-hour step in the analysis-forecasting cycle instead of 12 hours, which is applied most often, we may without any difficulties treat all observations as synoptic. No observation would thus be more than 90 minutes off time and the observations even during strong transient motion would fall within a horizontal mesh of 500 km * 500 km.

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Exact, finite-amplitude, local wave-activity conservation laws are derived for disturbances to steady flows in the context of the two-dimensional anelastic equations. The conservation laws are expressed entirely in terms of Eulerian quantities, and have the property that, in the limit of a small-amplitude, slowly varying, monochromatic wave train, the wave-activity density A and flux F, when averaged over phase, satisfy F = cgA where cg is the group velocity of the waves. For nonparallel steady flows, the only conserved wave activity is a form of disturbance pseudoenergy; when the steady flow is parallel, there is in addition a conservation law for the disturbance pseudomomentum. The above results are obtained not only for isentropic background states (which give the so-called “deep form” of the anelastic equations), but also for arbitrary background potential-temperature profiles θ0(z) so long as the variation in θ0(z) over the depth of the fluid is small compared with θ0 itself. The Hamiltonian structure of the equations is established in both cases, and its symmetry properties discussed. An expression for available potential energy is also derived that, for the case of a stably stratified background state (i.e., dθ0/dz > 0), is locally positive definite; the expression is valid for fully three-dimensional flow. The counterparts to results for the two-dimensional Boussinesq equations are also noted.

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An open-framework indium selenide, [C7H10N][In9Se14], has been prepared under solvothermal conditions in the presence of 3,5-dimethylpyridine, and characterized by single crystal diffraction, thermogravimetry, elemental analysis, FTIR spectroscopy and UV-Vis diffuse reflectance. The crystal structure of [C7H10N][In9Se14] contains an unusual building unit, in which corner-linked and edge-linked InSe45- tetrahedra coexist. The presence of one-dimensional circular channels, of ca. 6 Å diameter, results in approximately 25% of solvent accessible void space.

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The synthesis and characterization of five new indium selenides, [C9H17N2]3[In5Se8+x(Se2)1−x] (1–2), [C6H12N2]4[C6H14N2]3[In10Se15(Se2)3] (3), [C6H14N2][(C6H12N2)2NaIn5Se9] (4) and [enH2][NH4][In7Se12] (5), are described. These materials were prepared under solvothermal conditions, using 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) and 1,4-diazabicyclo[2.2.2]octane (DABCO) as structure-directing agents. Compounds 1–4 represent the first examples of ribbons in indium selenides, and 4 is the first example of incorporation of an alkali metal complex. Compounds 1, 2 and 4 contain closely related [In5Se8+x(Se2)1−x]3− ribbons which differ only in their content of (Se2)2− anions. These ribbons are interspaced by organic countercations in 1 and 2, while in 4 they are linked by highly unusual [Na(DABCO)2]+ units into a three-dimensional framework. Compound 3 contains complex ribbons, with a long repeating sequence of ca. 36 Å, and 4 is a non-centrosymmetric three-dimensional framework, formed as a consequence of the decomposition of DABCO into ethylenediamine (en) and ammonia.

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We study the scaling properties and Kraichnan–Leith–Batchelor (KLB) theory of forced inverse cascades in generalized two-dimensional (2D) fluids (α-turbulence models) simulated at resolution 8192x8192. We consider α=1 (surface quasigeostrophic flow), α=2 (2D Euler flow) and α=3. The forcing scale is well resolved, a direct cascade is present and there is no large-scale dissipation. Coherent vortices spanning a range of sizes, most larger than the forcing scale, are present for both α=1 and α=2. The active scalar field for α=3 contains comparatively few and small vortices. The energy spectral slopes in the inverse cascade are steeper than the KLB prediction −(7−α)/3 in all three systems. Since we stop the simulations well before the cascades have reached the domain scale, vortex formation and spectral steepening are not due to condensation effects; nor are they caused by large-scale dissipation, which is absent. One- and two-point p.d.f.s, hyperflatness factors and structure functions indicate that the inverse cascades are intermittent and non-Gaussian over much of the inertial range for α=1 and α=2, while the α=3 inverse cascade is much closer to Gaussian and non-intermittent. For α=3 the steep spectrum is close to that associated with enstrophy equipartition. Continuous wavelet analysis shows approximate KLB scaling ℰ(k)∝k−2 (α=1) and ℰ(k)∝k−5/3 (α=2) in the interstitial regions between the coherent vortices. Our results demonstrate that coherent vortex formation (α=1 and α=2) and non-realizability (α=3) cause 2D inverse cascades to deviate from the KLB predictions, but that the flow between the vortices exhibits KLB scaling and non-intermittent statistics for α=1 and α=2.

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The new thiogallate Na5(Ga4S)(GaS4)3·6H2O has been prepared solvothermally, using 3,5-dimethyl pyridine as a solvent, and characterised by powder and single crystal X-ray diffraction. This material, which exhibits a three-dimensional crystal structure, crystallises in the cubic space group View the MathML sourceF4¯3c (a = 17.557(4) Å). The crystal structure contains octahedral building blocks [Ga4S (GaS4)6]20−, linked into a three-dimensional network with a perovskite-type topology, and sodium hydrate clusters, [Na5(H2O)6]5+, filling the cavities in the [Ga4S(GaS4)6/2]5− framework. UV–Vis diffuse reflectance measurements indicate that this material is a wide band gap semiconductor, with a band gap of ca. 4.4 eV.

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The synthesis and crystal structure of four gallium sulphide open frameworks, built from supertetrahedral clusters, are described. The structures of [C4NH12]6[Ga10S18][C4NH12]6[Ga10S18](1) and [C4NH12]12[Ga20S35.5(S3)0.5O](2) contain supertetrahedral T3 clusters, while in the isostructural compounds [C4NH12]16[Ga10S18M4Ga16S33][C4NH12]16[Ga10S18M4Ga16S33] (M=CoM=Co(3), Zn (4)), T3 and T4 clusters alternate. These materials exhibit three-dimensional frameworks, with topologies consisting of two interpenetrating diamond lattices, and contain over 50% of solvent accessible void space. UV–Vis diffuse reflectance measurements indicate that these compounds are semiconducting, with band gaps over the range 3.4–4.1 eV.

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Observers generally fail to recover three-dimensional shape accurately from binocular disparity. Typically, depth is overestimated at near distances and underestimated at far distances [Johnston, E. B. (1991). Systematic distortions of shape from stereopsis. Vision Research, 31, 1351–1360]. A simple prediction from this is that disparity-defined objects should appear to expand in depth when moving towards the observer, and compress in depth when moving away. However, additional information is provided when an object moves from which 3D Euclidean shape can be recovered, be this through the addition of structure from motion information [Richards, W. (1985). Structure from stereo and motion. Journal of the Optical Society of America A, 2, 343–349], or the use of non-generic strategies [Todd, J. T., & Norman, J. F. (2003). The visual perception of 3-D shape from multiple cues: Are observers capable of perceiving metric structure? Perception and Psychophysics, 65, 31–47]. Here, we investigated shape constancy for objects moving in depth. We found that to be perceived as constant in shape, objects needed to contract in depth when moving toward the observer, and expand in depth when moving away, countering the effects of incorrect distance scaling (Johnston, 1991). This is a striking example of the failure of shape con- stancy, but one that is predicted if observers neither accurately estimate object distance in order to recover Euclidean shape, nor are able to base their responses on a simpler processing strategy.