Stratal composition and stratigraphic organization of stratal elements in an ancient deep‐marine basin‐floor succession,Neoproterozoic Windermere Supergroup,British Columbia,Canada

Despite a globally growing seismic and outcrop analogue data set, the detailed (centimetre to decametre) internal stratal make up of deep‐marine basin‐floor ‘channelized‐lobe’ strata remain poorly known. An ancient analogue for modern, mixed‐sediment, passive margin, deep‐marine basin‐floor fans is the well‐preserved Neoproterozoic Upper and Middle Kaza groups in the southern Canadian Cordillera. This succession is a few kilometres thick and comprises six sedimentary facies representing deposition from different kinds of sediment‐gravity flows. Representative lateral and vertical assemblages of one or more of these facies comprise six stratal elements, including: isolated scours, avulsion splays, feeder channels, distributary channels, terminal splays, and distal and off‐axis fine‐grained turbidite units. The internal characteristics of the various stratal elements do not differ from more distal to more proximal settings, but the relative abundance of the various stratal elements does. The difference in relative abundance of stratal elements in the kilometre‐scale stratigraphy of the Kaza Group results in a systematic upward change in architecture. The systematic arrangement of the stratal elements within the interpreted larger bodies, or lobes, and then lobes within the basin‐floor fan, suggests a hierarchical organization. In this article a hierarchy is proposed that is based on avulsion but, also importantly, the location of avulsion. The proposed avulsion‐based hierarchical scheme will be a useful tool to bridge the scalar gap between outcrop and seismic studies by providing a single stratigraphic framework and terminology for basin‐floor stratal elements.     

Using terrestrial LiDAR to measure water erosion on stony plots under simulated rainfall

Terrestrial LiDAR scanning (TLS) technology is widely used to detect terrain elevation changes. This study examines the potential use of terrestrial LiDAR to measure erosion on small experimental plots at high resolution. Multitemporal TLS scans were conducted at six positions around plots (12 m²) with three slope treatments through 11 simulated rainfall applications. Surface elevation changes were quantified by comparing scans between rainfall simulations, and elevation changes greater than the level of detection were used to obtain volumetric change estimations. Erosion mass was estimated both by using soil bulk density and the density of sediment collected in runoff, and then compared to the erosion estimated from the runoff samples. Results showed: (1) with the aid of fixed reference controls in the form of concrete target surfaces of varying roughness, registration accuracy was better than 1 mm and mean level of change detection was less than 2.2 mm; (2) the average absolute relative errors of TLS-estimated eroded mass ranged from 6.8% to 31.8%, with greater values on 5% slope; (3) the TLS-estimated erosion accuracy was affected by erosion magnitude, the utilized material density and number of scan positions, and a grid size of 10 mm was found to be appropriate for this scale to estimate the volumetric changes; (4) the number of scan positions could be reduced to three while not significantly impacting volumetric change estimations; and (5) elevating the scanner resulted in much better accuracy for eroded mass estimations. This study suggests that using LiDAR to monitor soil erosion at the plot scale is feasible, and provides guidance about the level of accuracy one might expect in doing so. © 2019 John Wiley & Sons, Ltd.     

On the computation of area probabilities based on a spatial stochastic model for precipitation cells and precipitation amounts

A main task of weather services is the issuing of warnings for potentially harmful weather events. Automated warning guidances can be derived, e.g., from statistical post-processing of numerical weather prediction using meteorological observations. These statistical methods commonly estimate the probability of an event (e.g. precipitation) occurring at a fixed location (a point probability). However, there are no operationally applicable techniques for estimating the probability of precipitation occurring anywhere in a geographical region (an area probability). We present an approach to the estimation of area probabilities for the occurrence of precipitation exceeding given thresholds. This approach is based on a spatial stochastic model for precipitation cells and precipitation amounts. The basic modeling component is a non-stationary germ-grain model with circular grains for the representation of precipitation cells. Then, we assign a randomly scaled response function to each precipitation cell and sum these functions up to obtain precipitation amounts. We derive formulas for expectations and variances of point precipitation amounts and use these formulas to compute further model characteristics based on available sequences of point probabilities. Area probabilities for arbitrary areas and thresholds can be estimated by repeated Monte Carlo simulation of the fitted precipitation model. Finally, we verify the proposed model by comparing the generated area probabilities with independent rain gauge adjusted radar data. The novelty of the presented approach is that, for the first time, a widely applicable estimation of area probabilities is possible, which is based solely on predicted point probabilities (i.e., neither precipitation observations nor further input of the forecaster are necessary). Therefore, this method can be applied for operational weather predictions.     

Are There Differences in the Response of Natural Stand and Plantation Biomass to Changes in Temperature and Precipitation? A Case for Two-needled Pines in Eurasia

A comparative discussion of the advantages and disadvantages of natural stands and plantations, including in terms of their productivity and stability, began from the moment of the first forest plantings and continues to this day. In the context of the progressive replacement of natural forests by plantations due to deforestation, the question of how will change the carbon storage capacity of forest cover when replacing natural forests with artificial ones in a changing climate becomes extremely relevant. This article presents the first attempt to answer this question at the transcontinental level on a special case for two-needled pine trees (subgenus Pinus L.). The research was carried out using the database compiled by the authors on the single-tree biomass structure of forest-forming species of Eurasia, in particular, data of 1880 and 1967 of natural and plantation trees, respectively. Multi-factor regression models are calculated after combining the matrix of initial data on the structure of tree biomass with the mean January temperature and mean annual precipitation, and their adequacy indices allow us to consider them reproducible. It is found that the aboveground and stem biomass of equal-sized and equal-aged natural and plantation trees increases as the January temperature and precipitation rise. This pattern is only partially valid for the branches biomass, and it has a specific character for the foliage one. The biomass of all components of plantation trees is higher than that of natural trees, but the percent of this excess varies among different components and depends on the level of January temperatures, but does not depend at all on the level of annual precipitation. A number of uncertainties that arose during the modeling process, as well as the preliminary nature of the obtained regularities, are noted.     

Spatially constrained regionalization with multilayer perceptron

In this article, multilayer perceptron (MLP) network models with spatial constraints are proposed for regionalization of geostatistical point data based on multivariate homogeneity measures. The study focuses on non‐stationarity and autocorrelation in spatial data. Supervised MLP machine learning algorithms with spatial constraints have been implemented and tested on a point dataset. MLP spatially weighted classification models and an MLP contiguity‐constrained classification model are developed to conduct spatially constrained regionalization. The proposed methods have been tested with an attribute‐rich point dataset of geological surveys in Ukraine. The experiments show that consideration of the spatial effects, such as the use of spatial attributes and their respective whitening, improve the output of regionalization. It is also shown that spatial sorting used to preserve spatial contiguity leads to improved regionalization performance.     

Magnetism and mineralogy of Almahata Sitta polymict ureilite (= asteroid 2008 TC3): Implications for the ureilite parent body magnetic field

Abstract– The Almahata Sitta meteorite is the first case of recovered extraterrestrial material originating from an asteroid that was detected in near Earth space shortly before entering and exploding in the high atmosphere. The aims of our project within the 2008 TC₃ consortium were investigating Almahata Sitta’s (AS) magnetic signature, phase composition and mineralogy, focussing on the opaque minerals, and gaining new insights into the magnetism of the ureilite parent body (UPB). We report on the general magnetic properties and behavior of Almahata Sitta and try to place the results in context with the existing data set on ureilites and ureilite parent body models. The magnetic signature of AS is dominated by a set of low‐Ni kamacites with large grain sizes. Additional contributions come from micron‐sized kamacites, suessite, (Cr) troilite, and daubreelite, mainly found in the olivine grains adjacent to carbon‐rich veins. Our results show that the paleomagnetic signal is of extraterrestrial origin as can be seen by comparing with laboratory produced magnetic records (IRM). Four types of kamacite (I–IV) have been recognized in the sample. The elemental composition of the ureilite vein metal Kamacite I (particularly Co) clearly differs from the other kamacites (II‐IV), which are considered to be indigenous. Element ratios of kamacite I indicate that it was introduced into the UPB by an impactor, supporting the conclusions of Gabriel and Pack (2009) .     

Another Record: Ocean Warming Continues through 2021 despite La Ni?a Conditions

The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate system and increases ocean heat content (O...     

Murmanite and lomonosovite as Ag-selective ionites: kinetics and products of ion exchange in aqueous AgNO3 solutions

Products and kinetics of ion exchange of heterophyllosilicate minerals lomonosovite and murmanite with aqueous AgNO₃ solutions under low-temperature conditions have been studied using scanning electron microscopy, electron microprobe analysis, single-crystal X-ray diffraction, infrared spectroscopy, ²³Na nuclear magnetic resonance spectroscopy and dynamic calorimetry. Both minerals show strong affinity for silver in cation exchange. Simplified formulae of Ag-exchanged forms of murmanite and lomonosovite are (Ag_3.0Ca_0.5Na_0.5) (Ti,Nb,Mn,Fe)_3.7?4 (Si₂O₇)₂O₄·4(H₂O,OH) and (Ag_8.2Na_1.2Ca_0.3) (Ti,Nb,Mn,Fe)_3.9?4 (Si₂O₇)₂ (PO₄)_1.9O₄·xH₂O, respectively. The reaction of ion exchange for murmanite follows the first-order kinetic model up to ca. 70–80 % conversion. The rate of the process is described by the equation k(h^?1) = 10^7.64±0.60 exp[?(12.2 ± 0.9)·10³/RT]. The average heat release value in the temperature range 39.4–72 °C is 230 J g^?1. The cation exchange is limited by processes in solid state, most probably binding of silver.     

Removal of topographic effects from lunar images using Kaguya (LALT) and Earth-based observations

Lunar images acquired at non-zero phase angles show brightness variations caused by both albedo heterogeneities and local topographic slopes of the surface. To distinguish between these two factors, altimetry measurements or photoclinometry data can be used. The distinction is especially important for imagery of phase-function parameters of the Moon. The imagery is a new tool that can be used to study structural anomalies of the lunar surface. To illustrate the removal of the topographic effects from photometric images, we used Earth-based telescopic observations, altimetry measurements carried out with the Kaguya (JAXA) LALT instrument, and a new photoclinometry technique that includes analysis of several images of the same scenes acquired at different phase angles. Using this technique we have mapped the longitudinal component of lunar topography slopes (the component measured along the lines of constant latitude). We have found good correlations when comparing our map with the corresponding data from Kaguya altimetry. The removal of the topographic surface properties allows for the study of the phase-function parameters of the lunar surface, not only for flat mare regions, but for highlands as well.