Studying local sources in the radio range based on the partial solar eclipse of January 4, 2011, at the Mountain Astronomical Station, Central Astronomical Observatory, Russian Academy of Sciences

Data are presented on a partial solar eclipse, which occurred on January 4, 2011, and was observed with RT-3 (?? = 4.9 cm) and RT-2 (?? = 3.2 cm) radio telescopes at the Mountain Astronomical Station, Central Astronomical Observatory, Russian Academy of Sciences (MAS CAO RAS). The radioemission flux in two channels was registered using digital methods with a time resolution of 0.5 s. Comparisons were performed with observations in the optical, UV, and X-ray ranges. The following local sources of increased radioemission on the solar disk have been identified: sunspot groups 1 (NOAA 1142) and 126 (NOAA 1141), unipolar sunspot 127 (NOAA 1140), facula areas, and polar and midlatitude coronal holes. It has been indicated that the brightness of a unipolar sunspot (for ?? = 4.9 cm, I _rel = 29.5; for ?? = 3.2 cm, I _rel = 10.1) and two sunspot groups (for ?? = 4.9 cm, I _rel = 10.1 and 14.2; for ?? = 3.2 cm, I _rel = 5.1 and 6.2) is maximal. The radioemission flux of all found coronal holes is decreased, and the decrease is more contrasting in the 4.9-cm range as compared to such a decrease in the 3.2-cm range. Radio maps of the Sun and changes in the radioemission flux of undisturbed solar regions from the center to the limb for ?? = 4.9 and 3.2 cm have been constructed based on the eclipse data.     

Geographical and Ecological Characteristics of the Caspian Sea and Modern Tendencies in the Evolution of Its Ecosystem

The Caspian Sea is characterized in the geographic and ecological aspects, and the state of its ecosystem is estimated. The natural and anthropogenic processes that control the formation of the environmental conditions in the Caspian Sea and the distribution of principal commercial hydrobionts and their food items are analyzed. Data on modern tendencies in changes in the abiotic and biotic parameters of the ecosystem, their causes and mechanisms are summarized. Prospects of further changes related to the development of shelf fields of petroleum hydrocarbons are assessed.     

Estimating the influence of seismic and meteorological factors on the accuracy of measurements by relative gravimeters

Continuous high-precision long-term gravity measurements are carried out at the geophysical observatory located in the experimental base of Vladimir State University. The long time series of gravity acceleration and its standard deviation are obtained. The factors responsible for the increases in the studied deviations are analyzed. The recommendations for improving the accuracy of relative gravity measurements are formulated.     

Separation of deterministic signals using independent component analysis (ICA)

Independent Component Analysis (ICA) represents a higher-order statistical technique that is often used to separate mixtures of stochastic random signals into statistically independent sources. Its benefit is that it only relies on the information contained in the observations, i.e. no parametric a-priori models are prescribed to extract the source signals. The mathematical foundation of ICA, however, is rooted in the theory of random signals. This has led to questions whether the application of ICA to deterministic signals can be justified at all? In this context, the possibility of using ICA to separate deterministic signals such as complex sinusoidal cycles has been subjected to previous studies. In many geophysical and geodetic applications, however, understanding long-term trend in the presence of periodical components of an observed phenomenon is desirable. In this study, therefore, we extend the previous studies with mathematically proving that the ICA algorithm with diagonalizing the 4th order cumulant tensor, through the rotation of experimental orthogonal functions, will indeed perfectly separate an unknown mixture of trend and sinusoidal signals in the data, provided that the length of the data set is infinite. In other words, we justify the application of ICA to those deterministic signals that are most relevant in geodetic and geophysical applications.     

Arc magmatism in eastern Kumaun Himalaya,India: A study based on geochemistry of granitoid rocks

Petrochemical studies of granitoid rocks from the eastern part of Kumaun region suggest that the leading edge of India represents an active arc during Late Paleoproterozoic times. It has been observed that melt generation for granodiorite rocks from the eastern Almora Nappe and Chhiplakot klippe along with the Askot klippe was caused through a subduction‐related process involving hydrous partial melting of a Paleoproterozoic amphibole‐ and/or garnet‐bearing mafic source with the involvement of sediments from the subduction zone. The medium‐ to high‐K basic rocks, common in subduction‐related magmatic arcs, can also explain the generation of the high‐K granodiorites of the Chhiplakot klippe. The augen gneisses from the eastern Almora nappe and Chhiplakot klippe along with the Askot klippe further show geochemical similarity with the associated granodiorites, suggesting there is a genetic linkage with one another.     

Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series

Two-station pairing approaches are routinely used to infill missing information in incomplete rainfall databases. We evaluated the performance of three simple methodologies to reconstruct incomplete time series in presence of variable nonlinear correlation between data pairs. Nonlinearity stems from the statistics describing the marginal peak-over-threshold (POT) values of rainfall events. A Monte Carlo analysis was developed to quantitatively assess expected errors from the use of chronological pairing (CP) with linear and nonlinear regression and frequency pairing (FP). CP is based on a priori selection of regression functions, while FP is based on matching the probability of non-exceedance of an event from one time series with the probability of non-exceedance of a similar event from another time series. We adopted a generalized Pareto (GP) model to describe POT events, and a t-copula algorithm to generate reference nonlinearly correlated pairs of random temporal distributions distributed according with the GP model. The results suggest that the optimal methodology strongly depends on GP statistics. In general, CP seems to provide the lowest errors when GP statistics were similar and correlation became linear; we found that a power-2 function performs well for the selected statistics when the number of missing points is limited. FP outperforms the other methods when POT statistics are different and variables are markedly nonlinearly correlated. Ensemble-based results seem to be supported by the analysis of observed precipitation at two real-world gauge stations.