The Cone-in-Cone Structure and Its Origin

Morphostructural investigation of carbonate cone-in-cone formations allows to conclude that they belong to self-organizing (dissipative, according to I. Prigogine's terminology) systems of the geological past formed in a thermogradient field at the expense of energy of heat and mass transfer (Prigogine and Stengers, 1984). First, the fluid-convective metasomatic hypothesis unites and reconciles the most well-known hypotheses that previously seemed to be incompatible and transforms them to rather consistent particular cases of a more intricate multistage geological phenomenon. Second, it helps to identify the morphologically and genetically analogous noncarbonate structures that mimic biogenic ones. The probable indicative role of cone-in-cone structure in the mapping of fluid-conducting systems is a consequence of the proposed hypothesis.     

Rare earth elements in the clay fraction of coaliferous sediments of the Arkagalinskoe (Magadan district) and Dolinskoe (Sakhalin Island) coalfields

The study of REE distribution in the clay fraction of sedimentary rocks from two coalfields made it possible to distinguish several types of REE distribution, which correlate with their mineral composition. It is shown that the REE fractionation was related to the mineral reconstruction of the primary clay fraction and some detrital minerals in the course of postsedimentary transformations of rocks during diagenesis, early catagenesis, and beginning of late catagenesis. These transformations were governed by several factors, such as the composition of sediments; hydrochemical features of accumulation environment; the chemical composition, dynamics, and feeding sources of pore solutions; the porosity and permeability of sediments and rocks; and the content of organic matter and its reaction ability.     

A 2D finite volume model for bebris flow and its application to events occurred in the Eastern Pyrenees

FLATModel is a 2D finite volume code that contains several original approaches to improve debris-flow simulation. Firstly, FLATModel incorporates a ＂stop-and-go＂ technique in each cell to allow continuous collapses and remobilizations of the debris-flow mass. Secondly, flow velocity and consequently yield stress is directly associated with the type of rheology to improve boundary accuracy. Thirdly, a simple approach for entrainment is also included in the model to analyse the effect of basal erosion of debris flows. FLATMODEL was tested at several events that occurred in the Eastern Pyrenees and simulation results indicated that the model can represent rather well the different characteristics observed in the field.     

Diurnal variation of deep cloud systems over the Indian region using INSAT-1B pixel data

Summary Among the various time scales of deep clouds, diurnal variation is found to be prominent over the tropics. The present study examines the diurnal variation in the number and area cover associated with the cloud systems over the tropical Indian region using INSAT-1B pixel data. Three periods, namely, April–May 1988, July–August 1988, and January–February 1989 are considered. The dependence of diurnal characteristics on the temperature threshold, life duration and size of cloud systems, and land-sea contrast has been explored. The diurnal characteristics of cloud systems living for more than a day have been studied for the first time. It is shown that cloud systems exhibit strong diurnal dependence at the coldest temperature threshold used (201 K). Also, the diurnal variation is more for larger cloud systems and for longer living systems. In general, more deep cloud activity is found from the satellite data during the pre-dawn and early morning hours. Precipitation is enhanced during morning to early noon hours. Further, using data from a recent field experiment, clear evidence of diurnal variation in precipitation over the Bay of Bengal is also presented. Received March 20, 2000/Revised October 3, 2000     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

Possible representation for discovery observations of stellar flares

It is shown that the chronology of flare star discoveries in the Pleiades cluster and the Orion association can be described satisfactorily by various distribution functions (gamma, binomial, decreasing exponential, and delta) for the mean frequencies of stellar flares. However, it has been found that this is due to the uncertainty in the observationally derived distribution function for the mean frequency of stellar flares. The most likely function is that derived by Ambartsumian, which has a physical basis.Translated fromAstrofizika, Vol. 38, No. 1, pp. 25–32, January–March, 1995.