Full Sphere Axisymmetric Simulations of the Solar Dynamo

We explore a full sphere (2D axisymmetric) kinematic solar dynamo model based on the Babcock-Leighton idea that the poloidal field is generated in the surface layers from the decay of tilted bipolar solar active regions. This model incorporates the helioseismically deduced solar rotation profile and an algorithm for buoyancy motivated from simulations of flux tube dynamics. A prescribed deep meridional circulation plays an important role in the advection of magnetic flux. We specifically address the parity issue and show that – contrary to some recent claims – the Babcock-Leighton dynamo can reproduce solar-like dipolar parity if certain reasonable conditions are satisfied in the solar interior, the most important requirement being that the poloidal field of the two hemispheres be efficiently coupled across the equator.

Numerical Modelling of the Observed Diurnal Cycle of Indian Monsoon Rainfall

We have analysed the diurnal cycle of rainfall over the Indian region (10S-35N, 60E-100E) using both satellite and in-situ data, and found many interesting features associated with this fundamental, yet under-explored, mode of variability. Since there is a distinct and strong diurnal mode of variability associated with the Indian summer monsoon rainfall, we evaluate the ability of the Weather Research and Forecasting Model (WRF) to simulate the observed diurnal rainfall characteristics. The model (at 54km grid-spacing) is integrated for the month of July, 2006, since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST), by using two different SST datasets, namely, Final Analyses (FNL) and Real-time Global (RTG). It was found that with RTG SST the rainfall simulation over central India (CI) was significantly better than that with FNL. On the other hand, over the Bay of Bengal (BoB), rainfall simulated with FNL was marginally better than with RTG. However, the overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the role of the convective parameterization scheme on the simulation of diurnal cycle of rainfall. We found that the Kain-Fritsch (KF) scheme performs significantly better than Betts-Miller-Janjić (BMJ) and Grell-Devenyi schemes. We also studied the impact of other physical parameterizations, namely, microphysics, boundary layer, land surface, and the radiation parameterization, on the simulation of diurnal cycle of rainfall, and identified the “best” model configuration. We used this configuration of the “best” model to perform a sensitivity study on the role of various convective components used in the KF scheme. In particular, we studied the role of convective downdrafts, convective timescale, and feedback fraction, on the simulated diurnal cycle of rainfall. The “best” model simulations, in general, show a good agreement with observations. Specifically, (i) Over CI, the simulated diurnal rainfall peak is at 1430 IST, in comparison to the observed 1430-1730 IST peak; (ii) Over Western Ghats and Burmese mountains, the model simulates a diurnal rainfall peak at 1430 IST, as opposed to the observed peak of 1430-1730 IST; (iii) Over Sumatra, both model and observations show a diurnal peak at 1730 IST; (iv) The observed southward propagating diurnal rainfall bands over BoB are weakly simulated by WRF. Besides the diurnal cycle of rainfall, the mean spatial pattern of total rainfall and its partitioning between the convective and stratiform components, are also well simulated. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over CI and BoB. While, the 54km and 18km simulations were conducted for the whole of July, 2006, the 6km simulation was carried out for the period 18 - 24 July, 2006. The results of our coarse- and fine-scale numerical simulations of the diurnal cycle of monsoon rainfall will be discussed.

Size-dependent and strain rate effects in quantum dot nanostructures with molecular dynamic simulations

Size and strain rate effects are among several factors which play an important role in determining the response of nanostructures, such as their deformations, to the mechanical loadings. The mechanical deformations in nanostructure systems at finite temperatures are intrinsically dynamic processes. Most of the recent works in this context have been focused on nanowires [1, 2], but very little attention has been paid to such low dimensional nanostructures as quantum dots (QDs). In this contribution, molecular dynamics (MD) simulations with an embedded atom potential method(EAM) are carried out to analyse the size and strain rate effects in the silicon (Si) QDs, as an example. We consider various geometries of QDs such as spherical, cylindrical and cubic. We choose Si QDs as an example due to their major applications in solar cells and biosensing. The analysis has also been focused on the variation in the deformation mechanisms with the size and strain rate for Si QD embedded in a matrix of SiO2 [3] (other cases include SiN and SiC matrices).It is observed that the mechanical properties are the functions of the QD size, shape and strain rate as it is in the case for nanowires [2]. We also present the comparative study resulted from the application of different EAM potentials in particular, the Stillinger-Weber (SW) potential, the Tersoff potentials and the environment-dependent interatomic potential (EDIP) [1]. Finally, based on the stabilized structural properties we compute electronic bandstructures of our nanostructures using an envelope function approach and its finite element implementation.

Novel Algorithm for estimation of Swell Pressure of Fine Grained Soils Based on Diffuse Double Layer (DDL) Theory

Use of engineered landfills for the disposal of industrial wastes is currently a common practice. Bentonite is attracting a greater attention not only as capping and lining materials in landfills but also as buffer and backfill materials for repositories of high-level nuclear waste around the world. In the design of buffer and backfill materials, it is important to know the swelling pressures of compacted bentonite with different electrolyte solutions. The theoretical studies on swell pressure behaviour are all based on Diffuse Double Layer (DDL) theory. To establish a relation between the swell pressure and void ratio of the soil, it is necessary to calculate the mid-plane potential in the diffuse part of the interacting ionic double layers. The difficulty in these calculations is the elliptic integral involved in the relation between half space distance and mid plane potential. Several investigators circumvented this problem using indirect methods or by using cumbersome numerical techniques. In this work, a novel approach is proposed for theoretical estimations of swell pressures of fine-grained soil from the DDL theory. The proposed approach circumvents the complex computations in establishing the relationship between mid-plane potential and diffused plates’ distances in other words, between swell pressure and void ratio.

Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.

Laboratory simulations show diabatic heating drives cumulus-cloud evolution and entrainment

Clouds are the largest source of uncertainty in climate science, and remain a weak link in modeling tropical circulation. A major challenge is to establish connections between particulate microphysics and macroscale turbulent dynamics in cumulus clouds. Here we address the issue from the latter standpoint. First we show how to create bench-scale flows that reproduce a variety of cumulus-cloud forms (including two genera and three species), and track complete cloud life cycles-e.g., from a ``cauliflower'' congestus to a dissipating fractus. The flow model used is a transient plume with volumetric diabatic heating scaled dynamically to simulate latent-heat release from phase changes in clouds. Laser-based diagnostics of steady plumes reveal Riehl-Malkus type protected cores. They also show that, unlike the constancy implied by early self-similar plume models, the diabatic heating raises the Taylor entrainment coefficient just above cloud base, depressing it at higher levels. This behavior is consistent with cloud-dilution rates found in recent numerical simulations of steady deep convection, and with aircraft-based observations of homogeneous mixing in clouds. In-cloud diabatic heating thus emerges as the key driver in cloud development, and could well provide a major link between microphysics and cloud- scale dynamics.

Redundancy resolution using a tractrix and its application to real-time simulations of hyper-redundant manipulators, snakes and tying of knots

To realistically simulate the motion of flexible objects such as ropes, strings, snakes, or human hair,one strategy is to discretise the object into a large number of small rigid links connected by rotary or spherical joints. The discretised system is highly redundant and the rotations at the joints (or the motion of the other links) for a desired Cartesian motion of the end of a link cannot be solved uniquely. In this paper, we propose a novel strategy to resolve the redundancy in such hyper-redundant systems.We make use of the classical tractrix curve and its attractive features. For a desired Cartesian motion of the `head'of a link, the `tail' of the link is moved according to a tractrix,and recursively all links of the discretised objects are moved along different tractrix curves. We show that the use of a tractrix curve leads to a more `natural' motion of the entire object since the motion is distributed uniformly along the entire object with the displacements tending to diminish from the `head' to the `tail'. We also show that the computation of the motion of the links can be done in real time since it involves evaluation of simple algebraic, trigonometric and hyperbolic functions. The strategy is illustrated by simulations of a snake, tying of knots with a rope and a solution of the inverse kinematics of a planar hyper-redundant manipulator.