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.     

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.     

Jet Deflection by a Quasi-Steady-State Side Wind in the Laboratory

We present experimental data on the steady state deflection of a highly supersonic jet by a side-wind in the laboratory. The use of a long interaction region enables internal shocks to fully cross the jet, leading to the development of significantly more structure in the jet than in previous work with a similar setup (Lebedev et al., 2004). The ability to control the length of the interaction region in the laboratory allows the switch between a regime representing a clumpy jet or wind and a regime similar to a slowly varying mass loss rate. The results indicate that multiple internal oblique shocks develop in the jet and the possible formation of a second working surface as the jet attempts to tunnel through the ambient medium.     

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.     

Improving efficiency in radio surveys for gravitational lenses

Many lens surveys have hitherto used observations of large samples of background sources to select the small minority which are multiply imaged by lensing galaxies along the line of sight. Recently surveys such as SLACS and OLS have improved the efficiency of surveys by pre-selecting double-redshift systems from SDSS. We explore other ways to improve survey efficiency by optimum use of astrometric and morphological information in existing large-scale optical and radio surveys. The method exploits the small position differences between FIRST radio positions of lensed images and the SDSS lens galaxy positions, together with the marginal resolution of some larger gravitational lens systems by the FIRST beam. We present results of a small pilot study with the VLA and MERLIN, and discuss the desirable criteria for future surveys.     

Long-wavelength MHD instability in the prefront of collisionless shocks with accelerated particles

Collisionless shocks in turbulent space plasmas accelerate particles by the Fermi mechanism to ultrarelativistic energies. The interaction of accelerated particles with the plasma inflow produces extended supersonic MHD flows of multicomponent plasma. We investigate the instabilities of a flow of three-component turbulent plasma with relativistic particles against long-wavelength perturbations with scales larger than the accelerated particle transport mean free path and the initial turbulence scales. The presence of turbulence allows us to formulate the system of single-fluid equations, the equation of motion for the medium as a whole, and the induction equation for the magnetic field with turbulent magnetic and kinematic viscosities. The current of accelerated particles enters into the induction equation with an effective magnetic diffusion coefficient. We have calculated the local growth rates of the perturbations related to the nonresonant long-wavelength instability of the current of accelerated particles for MHD perturbations in the WKB approximation. The amplification of long-wavelength magnetic field perturbations in the flow upstream of the shock front can affect significantly the maximum energies of the particles accelerated by a collisionless shock and can lead to the observed peculiarities of the synchrotron X-ray radiation in supernova remnants.