Characterizing Observed Environmental Variability With HF Doppler Radar Surface Current Mappers and Acoustic Doppler Current Profilers: Environmental Variability in the Coastal Ocean

A network of high-frequency (HF) radars is deployed along the New Jersey coast providing synoptic current maps across the entire shelf. These data serve a variety of user groups from scientific research to Coast Guard search and rescue. In addition, model forecasts have been shown to improve with surface current assimilation. In all applications, there is a need for better definitions and assessment of the measurement uncertainty. During a summer coastal predictive skill experiment in 2001, an array of in situ current profilers was deployed near two HF radar sites, one long-range and one standard-range system. Comparison statistics were calculated between different vertical bins on the same current profiler, between different current profilers, and between the current profilers and the different HF radars. The velocity difference in the vertical and horizontal directions were then characterized using the observed root-mean-square (rms) differences. We further focused on two cases, one with relatively high vertical variability, and the second with relatively low vertical variability. Observed differences between the top bin of the current profiler and the HF radar were influenced by both system accuracy and the environment. Using the in situ current profilers, the environmental variability over scales based on the HF radar sampling was quantified. HF radar comparisons with the current profilers were on the same order as the observed environmental difference over the same scales, indicating that the environment has a significant influence on the observed differences. Velocity variability in the vertical and horizontal directions both contribute to these differences. When the potential effects of the vertical variability could be minimized, the remaining difference between the current profiler and the HF radar was similar to the measured horizontal velocity difference (~2.5 cm/s) and below the resolution of the raw radial data at the time of the deployment     

Change of Support for Estimating Local Block Grade Distributions

An important aspect in mineral resource evaluation is the reduction of variance when post-processing the grade distributions defined on the support (volume) of the available data into distributions defined on the support of the proposed selective mining units. Although the volume-variance relationship is well understood for the estimation of global grade distributions, it is still an unsolved issue for local estimation studies based on non-parametric geostatistical methods, such as indicator kriging, for which the support correction is not inherent to the method. To clarify this relationship, the local change of support problem is examined in the scope of two parametric models (multi-Gaussian and discrete Gaussian models). It is shown that the variance reduction factor between point and block-support local distributions depends on the block being considered and is less than the global variance reduction factor. As a consequence, post-processing the local point-support grade distributions on the basis of the latter systematically understates the importance of the change of support at the local scale and makes selective mining appear more economically attractive than it really is. In the light of these results, a methodology is proposed to post-process the local point-support distributions obtained via non-parametric (indicator) methods into block-support distributions. An application to simulated data indicates that this methodology provides an accurate estimation at the block support when dealing with diffusion-type random fields.     

Disjunctive Kriging with Hard and Imprecise Data

This paper presents a methodology for assessing local probability distributions by disjunctive kriging when the available data set contains some imprecise measurements, like noisy or soft information or interval constraints. The basic idea consists in replacing the set of imprecise data by a set of pseudohard data simulated from their posterior distribution; an iterative algorithm based on the Gibbs sampler is proposed to achieve such a simulation step. The whole procedure is repeated many times and the final result is the average of the disjunctive kriging estimates computed from each simulated data set. Being data-independent, the kriging weights need to be calculated only once, which enables fast computing. The simulation procedure requires encoding each datum as a pre-posterior distribution and assuming a Markov property to allow the updating of pre-posterior distributions into posterior ones. Although it suffers some imperfections, disjunctive kriging turns out to be a much more flexible approach than conditional expectation, because of the vast class of models that allows its computation, namely isofactorial models.     

Record of Late Pleistocene Glaciation and Deglaciation in the Southern Cascade Range. I. Petrological Evidence from Lacustrine Sediment in Upper Klamath Lake, Southern Oregon

Petrological and textural properties of lacustrine sediments from Upper Klamath Lake, Oregon, reflect changing input volumes of glacial flour and thus reveal a detailed glacial history for the southern Cascade Range between about 37 and 15 ka. Magnetic properties vary as a result of mixing different amounts of the highly magnetic, glacially generated detritus with less magnetic, more weathered detritus derived from unglaciated parts of the large catchment. Evidence that the magnetic properties record glacial flour input is based mainly on the strong correlation between bulk sediment particle size and parameters that measure the magnetite content and magnetic mineral freshness. High magnetization corresponds to relatively fine particle size and lower magnetization to coarser particle size. This relation is not found in the Buck Lake core in a nearby, unglaciated catchment. Angular silt-sized volcanic rock fragments containing unaltered magnetite dominate the magnetic fraction in the late Pleistocene sediments but are absent in younger, low magnetization sediments. The finer grained, highly magnetic sediments contain high proportions of planktic diatoms indicative of cold, oligotrophic limnic conditions. Sediment with lower magnetite content contains populations of diatoms indicative of warmer, eutrophic limnic conditions. During the latter part of oxygen isotope stage 3 (about 37–25 ka), the magnetic properties record millennial-scale variations in glacial-flour content. The input of glacial flour was uniformly high during the Last Glacial Maximum, between about 21 and 16 ka. At about 16 ka, magnetite input, both absolute and relative to hematite, decreased abruptly, reflecting a rapid decline in glacially derived detritus. The decrease in magnetite transport into the lake preceded declines in pollen from both grass and sagebrush. A more gradual decrease in heavy mineral content over this interval records sediment starvation with the growth of marshes at the margins of the lake and dilution of detrital material by biogenic silica and other organic matter.     

Histogram and variogram inference in the multigaussian model

Several iterative algorithms are proposed to improve the histogram and variogram inference in the framework of the multigaussian model. The starting point is the variogram obtained after a traditional normal score transform. The subsequent step consists in simulating many sets of gaussian values with this variogram at the data locations, so that the ranking of the original values is honored. The expected gaussian transformation and the expected variogram are computed by an averaging operation over the simulated datasets. The variogram model is then updated and the procedure is repeated until convergence. Such an iterative algorithm can adapt to the case of tied data and despike the histogram. Two additional issues are also examined, referred to the modeling of the empirical transformation function and to the optimal pair weighting when computing the sample variogram.     

Geostatistical simulation of random fields with bivariate isofactorial distributions by adding mosaic models

This work deals with the geostatistical simulation of a family of stationary random field models with bivariate isofactorial distributions. Such models are defined as the sum of independent random fields with mosaic-type bivariate distributions and infinitely divisible univariate distributions. For practical applications, dead leaf tessellations are used since they provide a wide range of models and allow conditioning the realizations to a set of data via an iterative procedure (simulated annealing). The model parameters can be determined by comparing the data variogram and madogram, and enable to control the spatial connectivity of the extreme values in the realizations. An illustration to a forest dataset is presented, for which a negative binomial model is used to characterize the distribution of coniferous trees over a wooded area.     

Conditional Simulation of Random Fields with Bivariate Gamma Isofactorial Distributions

This work focuses on a random function model with gamma marginal and bivariate isofactorial distributions, which has been applied in mining geostatistics for estimating recoverable reserves by disjunctive kriging. The objective is to widen its use to conditional simulation and further its application to the modeling of continuous attributes in geosciences. First, the main properties of the bivariate gamma isofactorial distributions are analyzed, with emphasis in the destructuring of the extreme values, the presence of a proportional effect (higher variability in high-valued areas), and the asymmetry in the spatial correlation of the indicator variables with respect to the median threshold. Then, we provide examples of stationary random functions with such bivariate distributions, for which the shape parameter of the marginal distribution is half an integer. These are defined as the sum of squared independent Gaussian random fields. An iterative algorithm based on the Gibbs sampler is proposed to perform the simulation conditional to a set of existing data. Such ‘multivariate chi-square’ model generalizes the well-known multigaussian model and is more flexible, since it allows defining a shape parameter which controls the asymmetry of the marginal and bivariate distributions.     

Flooding a landscape: impact of Holocene transgression on coastal sedimentology and underwater archaeology in Kiladha Bay (Greece)

Franchthi Cave, bordering Kiladha Bay, in Greece, is a key archaeological site, due to its long occupation time, from?~?40,000 to?~?5000 year BP. To date, no clear evidence of Neolithic human dwellings in the cave was found, supporting the assumption that Neolithic people may have built a village where there is now Kiladha Bay. During the Neolithic period/Early Holocene, wide areas of the bay were indeed emerged above sea level. Bathymetric and seismic data identified a terrace incised by a valley in?~?1 to 2 m sediment depth. Eight sediment cores, up to 6.3-m-long, were retrieved and analysed using petrophysical, sedimentological, geochemical, and chronostratigraphic methods. The longest core extends into the exposure surface, consisting of a layer of carbonate rubble in a finer matrix, representing weathering processes. Dated organic remains place this unit at?~?8500 cal year BP. It is overlain by stiff silty mud representing an estuarine environment. This mud is capped by reduced sediments with roots marking an exposure surface. A shell-layer, dated to?~?6300 cal year BP, overlies this terrestrial sequence, reflecting the marine transgression. This layer occurs at 10.8 mbsl, 7.7 m deeper than the global sea level at that time, suggesting tectonic subsidence in the area. It is overlain by finer-grained marine carbonate-rich sediments. The top of the core shows traces of eutrophication, pebbles and marine shells, all likely a result of modern anthropogenic processes. These results are interpreted in the context of human occupation: the exposed surface contains pottery sherds, one dating to the Early to Middle Neolithic period, indicating that Neolithic people were present in this dynamic landscape interacting with a migrating coastline. Even if the artefacts are isolated, future investigations of the submerged landscape off Franchthi Cave might lead to the discovery of a Neolithic village, which eventually became buried under marine sediments.     

Carbonaceous chondrites as analogs for the composition and alteration of Ceres

The mineralogy and geochemistry of Ceres, as constrained by Dawn's instruments, are broadly consistent with a carbonaceous chondrite (CM/CI) bulk composition. Differences explainable by Ceres’s more advanced alteration include the formation of Mg‐rich serpentine and ammoniated clay; a greater proportion of carbonate and lesser organic matter; amounts of magnetite, sulfide, and carbon that could act as spectral darkening agents; and partial fractionation of water ice and silicates in the interior and regolith. Ceres is not spectrally unique, but is similar to a few other C‐class asteroids, which may also have suffered extensive alteration. All these bodies are among the largest carbonaceous chondrite asteroids, and they orbit in the same part of the Main Belt. Thus, the degree of alteration is apparently related to the size of the body. Although the ammonia now incorporated into clay likely condensed in the outer nebula, we cannot presently determine whether Ceres itself formed in the outer solar system and migrated inward or was assembled within the Main Belt, along with other carbonaceous chondrite bodies.     

Uranium in Holocene valley-fill sediments,and uranium,radon, and helium in waters,Lake Tahoe—Carson Range area,Nevada and California,U.S.A.

Uraniferous Holocene sediments occur in the Carson Range of Nevada and California, U.S.A., between Lake Tahoe and Carson Valley. The hosts for the uranium include peat and interbedded organic-rich sand, silt, and mud that underly valley floors, fens, and marshes along stream valleys between the crest of the range and the edge of Lake Tahoe. The known uranium accumulations extend along the Carson Range from the area just southeast of South Lake Tahoe northward to the area just east of Carson City; however, they almost certainly continue beyond the study area to the north, west, and south. Due to the young age of the accumulations, uranium in them is in gross disequilibrium with its highly radioactive daughter products. These accumulations have thus escaped discovery with radiation detection equipment in the past. The uranium content of these sediments approaches 0.6 percent; however, the average is in the range of 300–500 ppm. Waters associated with these sediments locally contain as much as 177 ppb uranium. Modest levels of helium and radon also occur in these waters.Uraniferous waters are clearly entering the private and public water supply systems in some parts of the study area; however, it is not known how much uranium is reaching users of these water supplies. Many of the waters sampled in the study area exceed the published health effects guidance level of the Environmental Protection Agency. Regulatory standards for uranium in waters have not been published, however.Much uranium is stored in the sediments along these stream valleys. Estimates for a marsh and a fen along one drainage are 24,000 and 15,000 kg, respectively. The potential effects of man-induced environmental changes on the uranium are uncertain. Laboratory studies of uraniferous sediment rich in organic matter may allow us to evaluate the potential of liberating uranium from such sediments and creating transient increases in the level of uranium moving in water in the natural environment.