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.     

Climatic response of thick leaf spruce (Picea crassifolia) tree-ring width at different elevations over Qilian Mountains, northwestern China

Tree-ring cores of thick leaf spruce (Picea crassifolia) taken from four sites at different elevations, in the middle of the Qilian Mountains, in the arid and semi-arid region of northwestern China, were used to develop four tree-ring width chronologies using standard dendrochronological methods. Results indicate that with increasing altitude the chronologies’ year-to-year variations decreased. Hence, the sensitivity of the tree-ring chronologies to climate decreases with altitude. Further analysis showed that the significant limiting factor on tree growth is spring precipitation. Measurements of stomata density and leaf dry weight suggest the species’ ecological adaptation strategy changes with elevation. At high elevation the metabolic rate of thick leaf spruce decreases, thus showing the effect of the climate.     

基于CEI的飞船交会对接远程导引段的轨道确定方案

探讨了CEI技术在飞船交会对接远程导引段的高精度定轨与实时监控的能力。仿真结果表明:精密定轨中采用可视弧段较长的单站可使相对位置精度达百米以内,速度达厘米/秒级。采用单一绝对扩展卡尔曼滤波器的方案进行实时轨道计算,采用滤波稳定后固定模糊度的方法可以使相对轨道位置精度达十米级,速度精度达厘米/秒级,事后及实时的轨道精度均满足远程导引段的精度指标。     

High-efficiency calculation method for watershed rainfall-runoff routing using one-dimensional dynamic wave equations

Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations (HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictor-corrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.     

摩擦作用对西南低涡扰动的影响

西南低涡是对流层下层的中尺度扰动。本文在零级近似条件下,采用p坐标系的基本方程组,在边界层内设计两层模式。通过一定的简化方程组后,得到:当Z≤1/2[kL~2/(μ~2Knu~*)] 时,摩擦效应具有二重性,一方面使扰动减弱;另一方面使扰动增强,而前者的影响略大于后者,最终使扰动消失。频率随高度Z的降低而增加。当Z>1/2[kL~2/(μ~2Knμ~*)]时,摩擦作用甚微,几乎可以忽略不计。频率虽然有两个值,但随高度Z的增加,他们趋于一个常值。     

Observational evidence for solar coronal decimetric radio pulsations with very short periods

Using the decimetric (700–1500 MHz) radio spectrometer and the synchronous observational system with high temporal resolution at four frequencies (1420, 2130, 2840 and 4260 MHz) of Yunnan Observatory, two rare events were observed on 2001 June 24 and 1990 July 30. The former was a small radio burst exhibiting pulsations with short periods (about 29, 40 and 100 ms) in the impulsive phase. The latter was a large radio burst, which at 2840 MHz produced radio pulsations with period of about 30 ms. This paper focuses on pulsations with very short periods in the range of 29–40 ms. The mechanism of generation of such pulsations may be modulation of radio radiation by the periodic trains of whistler packets originating in unstable regions of the corona. Alternatively, these pulsations can be attributed to wave-wave non-linear interactions of electrostatic upper hybrid waves driven by beams of precipitating electrons in flaring loops.     

Identification of Gleissberg Cycles and a Rising Trend in a 315-Year-Long Series of Sunspot Numbers

We show in this short note that the method of singular spectrum analysis (SSA) is able to clearly extract a strong, clean, and clear component from the longest available sunspot (International Sunspot Number, ISN) time series (1700?–?2015) that cannot be an artifact of the method and that can be safely identified as the Gleissberg cycle. This is not a small component, as it accounts for 13% of the total variance of the total original signal. Almost three and a half clear Gleissberg cycles are identified in the sunspot number series. Four extended solar minima (XSM) are determined by SSA, the latest around 2000 (Cycle 23/24 minimum). Several authors have argued in favor of a double-peaked structure for the Gleissberg cycle, with one peak between 55 and 59 years and another between 88 and 97 years. We find no evidence of the former: solar activity contains an important component that has undergone clear oscillations of \(\approx90\) years over the past three centuries, with some small but systematic longer-term evolution of “instantaneous” period and amplitude. Half of the variance of solar activity on these time scales can be satisfactorily reproduced as the sum of a monotonous multi-secular increase, a \(\approx90\)-year Gleissberg cycle, and a double-peaked (\(\approx10.0\) and 11.0 years) Schwabe cycle (the sum amounts to 46% of the total variance of the signal). The Gleissberg-cycle component definitely needs to be addressed when attempting to build dynamo models of solar activity. The first SSA component offers evidence of an increasing long-term trend in sunspot numbers, which is compatible with the existence of the modern grand maximum.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.