Scattered PKKP: Further evidence for scattering at a rough core-mantle boundary

PKKP signals from Novaya Zemlya recorded at LASA at distances around 60° show consistent anomalies in both slowness and azimuth. The observed anomaly suggests that the signal is a BC branch arrival, although the arrival time corresponds to the DF branch. The BC branch, however, does not extend back to this distance. The azimuth of approach is in the range 229–245°, instead of the expected 186°. These anomalies are associated only with PKKP; analysis of the core phases PKiKP and P′P′ (BC) from the same events show that they arrived at LASA with the appropriate slownesses and azimuths.The PKKP signals can be interpreted as “scattered” PKKP; the scattering occurs on underside reflection at the core-mantle boundary and is probably caused by topographic irregularities on the boundary itself. The calculated scattering region has a surface projection at about 60°S, 134°E, which is outside the diametral plane through source and receiver, and about 21° from the expected PKKP reflection point at 76°S, 95°E.Both the “direct” and “scattered” arms of the PKKP signal have a PK path close to that of the “C” end of the BC branch. The unexpectedly large amplitude of the arrival suggests that there may be a focusing of energy at C, which would indicate a change in velocity gradient just above the inner core boundary. The observations nevertheless require, on the scattering interpretation, lateral variations in the topography of the core-mantle boundary and a region of relatively large topography responsible for the anomalous PKKP observations.     

Similarity studies of entrainment in convective mixed layers

A similarity study of entrainment at the top of convectively driven mixed layer is presented. The similarity framework is used for a comparison between various parameterized models of mixed-layer growth rate and between closely related models for the ratio of heat fluxes at ground and inversion levels. These various models are also tested, in dimensionless form, against data from laboratory, field experiments and numerical higher-order-modeling of the convective layer. It is concluded that a rather accurate prediction of mixed-layer growth can be achieved with the simple constant flux ratio model, but that more refined studies of entrainment are required to account for the decrease of the heat flux ratio with increasing convective intensity.List of acronyms CRPE Centre de Recherches en Physique de l'Environnement, Issy-les-Moulineaux, France - EERM Etablissement d'Etudes et de Recherches Météorologiques, Boulogne, France - INRA Institut National de la Recherche Agronomique, Versailles, France - LAMP Laboratoire Associé de Météorologie Physique, Clermont-Ferrand, France - NCAR National Center for Atmospheric Research, Boulder, U.S.A. - NOAA National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Boulder, U.S.A.     

Entropy and spatial disorder

The majority of geostatistical estimation and simulation algorithms rely on a covariance model as the sole characteristic of the spatial distribution of the attribute under study. The limitation to a single covariance implicitly calls for a multivariate Gaussian model for either the attribute itself or for its normal scores transform. The Gaussian model could be justified on the basis that it is both analytically simple and it is a maximum entropy model, i.e., a model that minimizes unwarranted structural properties. As a consequence, the Gaussian model also maximizes spatial disorder (beyond the imposed covariance) which can cause flow simulation results performed on multiple stochastic images to be very similar; thus, the space of response uncertainty could be too narrow entailing a misleading sense of safety. The ability of the sole covariance to adequately describe spatial distributions for flow studies, and the assumption that maximum spatial disorder amounts to either no additional information or a safe prior hypothesis are questioned. This paper attempts to clarify the link between entropy and spatial disorder and to provide, through a detailed case study, an appreciation for the impact of entropy of prior random function models on the resulting response distributions.     

Geostatistics: Models and tools for the earth sciences

The probability construct underlying geostatistical methodology is recalled, stressing that stationary is a property of the model rather than of the phenomenon being represented. Geostatistics is more than interpolation and kriging(s) is more than linear interpolation through ordinary kriging. A few common misconceptions are addressed.     

Filter-Based Classification of Training Image Patterns for Spatial Simulation

Multiple-point simulation, as opposed to simulation one point at a time, operates at the pattern level using a priori structural information. To reduce the dimensionality of the space of patterns we propose a multi-point filtersim algorithm that classifies structural patterns using selected filter statistics. The pattern filter statistics are specific linear combinations of pattern pixel values that represent directional mean, gradient, and curvature properties. Simulation proceeds by sampling from pattern classes selected by conditioning data.     

The Necessity of a Multiple-Point Prior Model

Any interpolation, any hand contouring or digital drawing of a map or a numerical model necessarily calls for a prior model of the multiple-point statistics that link together the data to the unsampled nodes, then these unsampled nodes together. That prior model can be implicit, poorly defined as in hand contouring; it can be explicit through an algorithm as in digital mapping. The multiple-point statistics involved go well beyond single-point histogram and two-point covariance models; the challenge is to define algorithms that can control more of such statistics, particularly those that impact most the utilization of the resulting maps beyond their visual appearance. The newly introduced multiple-point simulation (mps) algorithms borrow the high order statistics from a visually and statistically explicit model, a training image. It is shown that mps can simulate realizations with high entropy character as well as traditional Gaussian-based algorithms, while offering the flexibility of considering alternative training images with various levels of low entropy (organized) structures. The impact on flow performance (spatial connectivity) of choosing a wrong training image among many sharing the same histogram and variogram is demonstrated.     

ESR dating of sedimentary quartz: Possibilities and limitations of the single-grain approach

Usually, multiple-grain aliquots are used for electron spin resonance (ESR) dating of sediments. However, this approach excludes the ability of detecting insufficient bleaching, as would be the case when measuring several single aliquots or single grains. In this paper, we present preliminary results of single-grain ESR dating experiments on three different sedimentary deposits (fluvial, fluvio-aeolian and desert aeolian), ranging in age between 100 ka and 2 Ma. Titanium-related impurity centres (Ti–Li and Ti–H) were measured in a Q-band ESR spectrometer for estimating equivalent doses (D_e) of individual quartz grains (0.5–1 mm). Both additive and regenerative dose methods were used. The resulting D_e plots show a large scatter in D_e—from 100 Gy to more than 600 Gy—for the fluvial sample, probably reflecting different bleaching histories of the grains. On the contrary, a clear plateau can be observed in D_e for sands with a strong aeolian component. Preliminary single-grain ESR ages are in relatively good agreement with independent estimates, the best results being obtained for the desert aeolian sample (200 ka). It is concluded that ESR has a promising potential for estimating large naturally accumulated doses of well-bleached sediments. Nevertheless, the method is challenged by several experimental difficulties, such as long measurement times, excessive errors, and presumably a complex interrelationship between Ti–Li and Ti–H components.     

A novel experimental procedure to investigate the biodegradation of NAPL under unsaturated conditions

Soils need to be thoroughly investigated regarding their potential for the natural attenuation of non-aqueous phase liquids (NAPL). Laboratory investigations truly representative of degradation processes in field conditions are difficult to implement for porous media partially saturated with water, NAPL and air. We propose an innovative protocol to investigate degradation processes under steady-state vadose zone conditions. Experiments are carried out in glass columns filled with a sand and, as bacteria source, a soil from a diesel-fuel-polluted site. Water and NAPL (n-hexadecane diluted in heptamethylnonane (HMN)) are added to the porous medium in a two-step procedure using ceramic membranes placed at the bottom of the column. This procedure results, for appropriate experimental conditions, in a uniform distribution of the two fluids (water and NAPL) throughout the column. In a biodegradation experiment non-biodegradable HMN is used to provide NAPL mass, while keeping biodegradable n-hexadecane small enough to monitor its rapid degradation. Biodegradation is followed as a function of time by measuring oxygen consumption, using a respirometer. Degradative activity is controlled by diffusive transfers in the porous network, of oxygen from the gas phase to the water phase and of n-hexadecane from the NAPL phase to the water phase.