Quasi-sure existence of Gaussian rough paths and large deviation principles for capacities

We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated with a Gaussian process with long-time memory. As an application we establish a large deviation principle (LDP) for capacities for such Gaussian rough paths. Together with Lyons' universal limit theorem, our results yield immediately the corresponding results for pathwise solutions to stochastic differential equations driven by such Gaussian process in the sense of rough paths. Moreover, our LDP result implies the result of Yoshida on the LDP for capacities over the abstract Wiener space associated with such Gaussian process.

The signature of a rough path: uniqueness

In the context of controlled differential equations, the signature is the exponential function on paths. B. Hambly and T. Lyons proved that the signature of a bounded variation path is trivial if and only if the path is tree-like. We extend Hambly–Lyons' result and their notion of tree-like paths to the setting of weakly geometric rough paths in a Banach space. At the heart of our approach is a new definition for reduced path and a lemma identifying the reduced path group with the space of signatures.

Sparse density estimator with tunable kernels

A new sparse kernel density estimator with tunable kernels is introduced within a forward constrained regression framework whereby the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Based on the minimum integrated square error criterion, a recursive algorithm is developed to select significant kernels one at time, and the kernel width of the selected kernel is then tuned using the gradient descent algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing very sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

Spherical nonparametric estimators applied to the UGAMP model integration for AMIP

The aim of this paper is essentially twofold: first, to describe the use of spherical nonparametric estimators for determining statistical diagnostic fields from ensembles of feature tracks on a global domain, and second, to report the application of these techniques to data derived from a modern general circulation model. New spherical kernel functions are introduced that are more efficiently computed than the traditional exponential kernels. The data-driven techniques of cross-validation to determine the amount elf smoothing objectively, and adaptive smoothing to vary the smoothing locally, are also considered. Also introduced are techniques for combining seasonal statistical distributions to produce longer-term statistical distributions. Although all calculations are performed globally, only the results for the Northern Hemisphere winter (December, January, February) and Southern Hemisphere winter (June, July, August) cyclonic activity are presented, discussed, and compared with previous studies. Overall, results for the two hemispheric winters are in good agreement with previous studies, both for model-based studies and observational studies.

Structure of turbulent flow over arrays of cubical roughness

The structure of turbulent flow over large roughness consisting of regular arrays of cubical obstacles is investigated numerically under constant pressure gradient conditions. Results are analysed in terms of first- and second-order statistics, by visualization of instantaneous flow fields and by conditional averaging. The accuracy of the simulations is established by detailed comparisons of first- and second-order statistics with wind-tunnel measurements. Coherent structures in the log region are investigated. Structure angles are computed from two-point correlations, and quadrant analysis is performed to determine the relative importance of Q2 and Q4 events (ejections and sweeps) as a function of height above the roughness. Flow visualization shows the existence of low-momentum regions (LMRs) as well as vortical structures throughout the log layer. Filtering techniques are used to reveal instantaneous examples of the association of the vortices with the LMRs, and linear stochastic estimation and conditional averaging are employed to deduce their statistical properties. The conditional averaging results reveal the presence of LMRs and regions of Q2 and Q4 events that appear to be associated with hairpin-like vortices, but a quantitative correspondence between the sizes of the vortices and those of the LMRs is difficult to establish; a simple estimate of the ratio of the vortex width to the LMR width gives a value that is several times larger than the corresponding ratio over smooth walls. The shape and inclination of the vortices and their spatial organization are compared to recent findings over smooth walls. Characteristic length scales are shown to scale linearly with height in the log region. Whilst there are striking qualitative similarities with smooth walls, there are also important differences in detail regarding: (i) structure angles and sizes and their dependence on distance from the rough surface; (ii) the flow structure close to the roughness; (iii) the roles of inflows into and outflows from cavities within the roughness; (iv) larger vortices on the rough wall compared to the smooth wall; (v) the effect of the different generation mechanism at the wall in setting the scales of structures.

Estimating surface CO2 fluxes from space-borne dry air mole fraction observations using an Ensemble Kalman filter

We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

A groove-ploughing theory for the production of mega-scale glacial lineations, and implications for ice-stream mechanics

Mega-scale glacial lineations (MSGLs) are longitudinally aligned corrugations (ridge-groove structures 6-100 km long) in sediment produced subglacially. They are indicators of fast flow and a common signature of ice-stream beds. We develop a qualitative theory that accounts for their formation, and use numerical modelling, and observations of ice-stream beds to provide supporting evidence. Ice in contact with a rough (scale of 10-10(3) m) bedrock surface will mimic the form of the bed. Because of flow acceleration and convergence in ice-stream onset zones, the ice-base roughness elements experience transverse strain, transforming them from irregular bumps into longitudinally aligned keels of ice protruding downwards. Where such keels slide across a soft sedimentary bed, they plough through the sediments, carving elongate grooves, and deforming material up into intervening ridges. This explains MSGLs and has important implications for ice-stream mechanics. Groove ploughing provides the means to acquire new lubricating sediment and to transport large volumes of it downstream. Keels may provide basal drag in the force budget of ice streams, thereby playing a role in flow regulation and stability We speculate that groove ploughing permits significant ice-stream widening, thus facilitating high-magnitude ice discharge.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

On integral equation and least squares methods for scattering by diffraction gratings

In this paper we consider the scattering of a plane acoustic or electromagnetic wave by a one-dimensional, periodic rough surface. We restrict the discussion to the case when the boundary is sound soft in the acoustic case, perfectly reflecting with TE polarization in the EM case, so that the total field vanishes on the boundary. We propose a uniquely solvable first kind integral equation formulation of the problem, which amounts to a requirement that the normal derivative of the Green's representation formula for the total field vanish on a horizontal line below the scattering surface. We then discuss the numerical solution by Galerkin's method of this (ill-posed) integral equation. We point out that, with two particular choices of the trial and test spaces, we recover the so-called SC (spectral-coordinate) and SS (spectral-spectral) numerical schemes of DeSanto et al., Waves Random Media, 8, 315-414 1998. We next propose a new Galerkin scheme, a modification of the SS method that we term the SS* method, which is an instance of the well-known dual least squares Galerkin method. We show that the SS* method is always well-defined and is optimally convergent as the size of the approximation space increases. Moreover, we make a connection with the classical least squares method, in which the coefficients in the Rayleigh expansion of the solution are determined by enforcing the boundary condition in a least squares sense, pointing out that the linear system to be solved in the SS* method is identical to that in the least squares method. Using this connection we show that (reflecting the ill-posed nature of the integral equation solved) the condition number of the linear system in the SS* and least squares methods approaches infinity as the approximation space increases in size. We also provide theoretical error bounds on the condition number and on the errors induced in the numerical solution computed as a result of ill-conditioning. Numerical results confirm the convergence of the SS* method and illustrate the ill-conditioning that arises.

Mean flow and turbulence statistics over groups of urban-like cubical obstacles

Direct numerical simulations of turbulent flow over regular arrays of urban-like, cubical obstacles are reported. Results are analysed in terms of a formal spatial averaging procedure to enable interpretation of the flow within the arrays as a canopy flow, and of the flow above as a rough wall boundary layer. Spatial averages of the mean velocity, turbulent stresses and pressure drag are computed. The statistics compare very well with data from wind-tunnel experiments. Within the arrays the time-averaged flow structure gives rise to significant 'dispersive stress' whereas above the Reynolds stress dominates. The mean flow structure and turbulence statistics depend significantly on the layout of the cubes. Unsteady effects are important, especially in the lower canopy layer where turbulent fluctuations dominate over the mean flow.

A critical assessment of unbalanced surface stresses: Some complementary considerations

The wide-ranging survey of twisted growth in polymers by Lotz and Cheng cites extensive evidence consistent with the relief of surface stress being the underlying cause. This complementary note contributes to the discussion by making three main points. First, it is necessary to go further and explain the key issue of how a consistent twist is maintained when, as commonly, this habit has a lower symmetry than the crystallographic lattice. Detailed study has shown that, in polyethylene, this occurs by reorganization of the initial fold surfaces. Second, the suggested explanation by Keith and Padden that. in polyethylene, the asymmetric habit derives from molecules adding to lamellae with inclined fold surfaces is invalid being doubly inconsistent with observation. Third, twisting has now been linked to faster growth by study of row structures in polyethylene. This produces inherently rough fold surfaces in Regime II whose internal stresses drive reorganization and twisting. For slower (Regime I) growth, fold surfaces form with and maintain ordered packing so providing no basis for twisting. These new insights radically alter the context of twisted growth and provide a firm factual basis for further work. (c) 2005 Elsevier Ltd. All rights reserved.

A comparative study of the effects of metal contamination on collembola in the field and in the laboratory

We examined the species diversity and abundance of Collembola at 32 sampling points along a gradient of metal contamination in a rough grassland site ( Wolverhampton, England), formerly used for the disposal of metal-rich smelting waste. Differences in the concentrations of Cd, Cu, Pb and Zn between the least and most contaminated part of the 35 metre transect were more than one order of magnitude. A gradient of Zn concentrations from 597 to 9080 mug g(-1) dry soil was found. A comparison between field concentrations of the four metals and previous studies on their relative toxicities to Collembola, suggested that Zn is likely to be responsible for any ecotoxicological effects on springtails at this site. Euedaphic ( soil dwelling) Collembola were extracted by placing soil cores into Tullgren funnels and epedaphic ( surface dwelling) species were sampled using pitfall traps. There was no obvious relationship between the total abundance, or a range of commonly used diversity indices, and Zn levels in soils. However, individual species showed considerable differences in abundance. Metal "tolerant'' (e.g., Ceratophysella denticulata) and metal "sensitive'' (e.g., Cryptopygus thermophilus) species could be identified. Epedaphic species appeared to be influenced less by metal contamination than euedaphic species. This difference is probably due to the higher mobility and lower contact with the soil pore water of epedaphic springtails in comparison to euedaphic Collembola. In an experiment exposing the standard test springtail, Folsomia candida, to soils from all 32 sampling points, adult survival and reproduction showed small but significant negative relationships with total Zn concentrations. Nevertheless, juveniles were still produced from eggs laid by females in the most contaminated soils with 9080 mug g(-1) Zn. Folsomia candida is much more sensitive to equivalent concentrations of Zn in the standard OECD soil. Thus, care should be taken in extrapolating the results of laboratory toxicity tests on metals in OECD soil to field soils, in which, the biological availability of contaminants is likely to be lower. Our studies have shown the importance of ecotoxicological effects at the species level. Although there may be no differences in overall abundance, sensitive species that are numerous in contaminated sites, and which may play important roles in decomposition("keystone species'') can be greatly reduced in numbers by pollution.

A comparative study of the effects of metal contamination on collembola in the field and in the laboratory

We examined the species diversity and abundance of Collembola at 32 sampling points along a gradient of metal contamination in a rough grassland site ( Wolverhampton, England), formerly used for the disposal of metal-rich smelting waste. Differences in the concentrations of Cd, Cu, Pb and Zn between the least and most contaminated part of the 35 metre transect were more than one order of magnitude. A gradient of Zn concentrations from 597 to 9080 mug g(-1) dry soil was found. A comparison between field concentrations of the four metals and previous studies on their relative toxicities to Collembola, suggested that Zn is likely to be responsible for any ecotoxicological effects on springtails at this site. Euedaphic ( soil dwelling) Collembola were extracted by placing soil cores into Tullgren funnels and epedaphic ( surface dwelling) species were sampled using pitfall traps. There was no obvious relationship between the total abundance, or a range of commonly used diversity indices, and Zn levels in soils. However, individual species showed considerable differences in abundance. Metal "tolerant'' (e.g., Ceratophysella denticulata) and metal "sensitive'' (e.g., Cryptopygus thermophilus) species could be identified. Epedaphic species appeared to be influenced less by metal contamination than euedaphic species. This difference is probably due to the higher mobility and lower contact with the soil pore water of epedaphic springtails in comparison to euedaphic Collembola. In an experiment exposing the standard test springtail, Folsomia candida, to soils from all 32 sampling points, adult survival and reproduction showed small but significant negative relationships with total Zn concentrations. Nevertheless, juveniles were still produced from eggs laid by females in the most contaminated soils with 9080 mug g(-1) Zn. Folsomia candida is much more sensitive to equivalent concentrations of Zn in the standard OECD soil. Thus, care should be taken in extrapolating the results of laboratory toxicity tests on metals in OECD soil to field soils, in which, the biological availability of contaminants is likely to be lower. Our studies have shown the importance of ecotoxicological effects at the species level. Although there may be no differences in overall abundance, sensitive species that are numerous in contaminated sites, and which may play important roles in decomposition("keystone species'') can be greatly reduced in numbers by pollution.

Comparative characterisation by atomic force microscopy and ellipsometry of soft and solid thin films

Ellipsometry and atomic force microscopy (AFM) were used to study the film thickness and the surface roughness of both 'soft' and solid thin films. 'Soft' polymer thin films of polystyrene and poly(styrene-ethylene/butylene-styrene) block copolymer were prepared by spin-coating onto planar silicon wafers. Ellipsometric parameters were fitted by the Cauchy approach using a two-layer model with planar boundaries between the layers. The smooth surfaces of the prepared polymer films were confirmed by AFM. There is good agreement between AFM and ellipsometry in the 80-130 nm thickness range. Semiconductor surfaces (Si) obtained by anisotropic chemical etching were investigated as an example of a randomly rough surface. To define roughness parameters by ellipsometry, the top rough layers were treated as thin films according to the Bruggeman effective medium approximation (BEMA). Surface roughness values measured by AFM and ellipsometry show the same tendency of increasing roughness with increased etching time, although AFM results depend on the used window size. The combined use of both methods appears to offer the most comprehensive route to quantitative surface roughness characterisation of solid films. Copyright (c) 2007 John Wiley & Sons, Ltd.