On using peak amplitude and rise time for AE source characterization

Acoustic Emission (AE) signals, which are electrical version of acoustic emissions, are usually analysed using a set of signal parameters. The major objective of signal analysis is to study the characteristics of the sources of emissions. Peak amplitude (P-a) and rise time (R-t) are two such parameters used for source characterization. In this paper, we theoretically investigate the efficiency of P-a and R-t to classify and characterize AE sources by modelling the input stress pulse and transducer. Analytical expressions obtained for P-a and R-t clearly indicate their use and efficiency for source characterization. It is believed that these results may be of use to investigators in areas like control systems and signal processing also.

A waveguide problem involving a thick iris in the theory of electromagnetism

The problem of electromagnetic wave propagation in a rectangular waveguide containing a thick iris is considered for its complete solution by reducing it to two suitable integral equations, one of which is of the first kind and the other is of the second kind. These integral equations are solved approximately, by using truncated Fourier series for the unknown functions. The reflection coefficient is computed numerically from the two integral equation approaches, and almost the same numerical results are obtained. This is also depicted graphically against the wave number and compared with thin iris results, which are computed by using complementary formulations coupled with Galerkin approximations. While the reflection coefficient for a thin iris steadily increases with the wave number, for a thick iris it fluctuates and zero reflection occurs. The number of zeros of the reflection coefficient for a thick iris increases with the thickness. Thus a thick iris becomes completely transparent for some discrete wave numbers. This phenomenon may be significant in the modelling of rectangular waveguides.

The Untouchable Soldier: Caste, Politics, and the Indian Army

Military establishments are omnipresent if not everywhere omnipotent. While these costly bureaucracies are the bane of finance ministers around the world, they do provide an important opportunity for comparative analysis. This paper examines a military system—the Indian one—through time, and attempts to demonstrate the changing relationship of that system to Indian politics and society in general, and to the low-caste communities of India in particular. We select the low-caste untouchables because they represent an extreme challenge to the integrative capacity of both political and social systems, and because they have recently been the subject of intensive political and academic concern.Stephen P. Cohen is Assistant Professor of Political Science in Asian Studies at the University of Illinois. Research for this paper was supported by a fellowship from the American Institute of Indian Studies in 1964–65.

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.

On breaks of the Indian monsoon

For over a century, the term break has been used for spells in which the rainfall over the Indian monsoon zone is interrupted. The phenomenon of 'break monsoon' is of great interest because long intense breaks are often associated with poor monsoon seasons. Such breaks have distinct circulation characteristics (heat trough type circulation) and have a large impact on rainfed agriculture. Although interruption of the monsoon rainfall is considered to be the most important feature of the break monsoon, traditionally breaks have been identified on the basis of the surface pressure and wind patterns over the Indian region. We have defined breaks (and active spells) on the basis of rainfall over the monsoon zone. The rainfall criteria are chosen so as to ensure a large overlap with the traditional breaks documented by Ramamurthy (1969) and De et al (1998). We have identified these rainbreaks for 1901-89. We have also identified active spells on the basis of rainfall over the Indian monsoon zone. We have shown that the all-India summer monsoon rainfall is significantly negatively correlated with the number of rainbreak days (correlation coefficient -0.56) and significantly positively correlated with the number of active days (correlation coefficient 0.47). Thus the interannual variation of the all-India summer monsoon rainfall is shown to be related to the number of days of rainbreaks and active spells identified here. There have been several studies of breaks (and also active spells in several cases) identified on the basis of different criteria over regions differing in spatial scales (e.g., Webster et al 1998; Krishnan et al 2000; Goswami and Mohan 2000; and Annamalai and Slingo 2001). We find that there is considerable overlap between the rainbreaks we have identified and breaks based on the traditional definition. There is some overlap with the breaks identified by Krishnan et al (2000) but little overlap with breaks identified by Webster et al (1998). Further, there are three or four active-break cycles in a season according to Webster et al (1998) which implies a time scale of about 40 days for which Goswami and Mohan (2000), and Annamalai and Slingo'(2001) have studied breaks and active minus break fluctuations. On the other hand, neither the traditional breaks (Ramamurthy 1969; and De et al 1998) nor the rainbreaks occur every year. This suggests that the 'breaks' in these studies axe weak spells of the intraseasonal variation of the monsoon, which occur every year. We have derived the OLR and circulation patterns associated with rainbreaks and active spells and compared them with the patterns associated with breaks/active minus break spells from these studies. Inspite of differences in the patterns over the Indian region, there is one feature which is seen in the OLR anomaly patterns of breaks identified on the basis of different criteria as well as the rainbreaks identified in this paper viz., a quadrapole over the Asia-west Pacific region arising from anomalies opposite (same) in sign to those over the Indian region occurring over the equatorial Indian Ocean and northern tropical (equatorial) parts of the west Pacific. Thus it appears that this quadrapole is a basic feature of weak spells of the intraseasonal,variation over the Asia-west Pacific region. Since the rainbreaks are intense weak spells, this basic feature is also seen in the composite patterns of these breaks. We find that rainbreaks (active spells) are also associated with negative (positive) anomalies over a part of the cast Pacific suggesting that the convection over the Indian region is linked to that over the east Pacific not only on the interannual scale (as evinced by the link between the Indian summer monsoon rainfall and ENSO) but on the intraseasonal scale as well.

The Indian monsoon and its variability

For over 300 years, the monsoon has been viewed as a gigantic land-sea breeze. It is shown in this paper that satellite and conventional observations support an alternative hypothesis, which considers the monsoon as a manifestation of seasonal migration of the intertropical convergence zone (ITCZ). With the focus on the Indian monsoon, the mean seasonal pattern is described, and why it is difficult to simulate it is discussed. Some facets of the intraseasonal variation, such as active-weak cycles; break monsoon; and a special feature of intraseasonal variation over the region, namely, poleward propagations of the ITCZ at intervals of 2-6 weeks, are considered. Vertical moist stability is shown to be a key parameter in the variation of monthly convection over ocean and land as well as poleward propagations. Special features of the Bay of Bengal and the monsoon brought out by observations during a national observational experiment in 1999 are briefly described.

Climate change and Indian forests

An assessment of the impact of projected climate change on forest ecosystems in India based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the global dynamic vegetation model IBIS for A1B scenario is conducted for short-term (2021-2050) and long-term (2071-2100) periods. Based on the dynamic global vegetation modelling, vulnerable forested regions of India have been identified to assist in planning adaptation interventions. The assessment of climate impacts showed that at the national level, about 45% of the forested grids is projected to undergo change. Vulnerability assessment showed that such vulnerable forested grids are spread across India. However, their concentration is higher in the upper Himalayan stretches, parts of Central India, northern Western Ghats and the Eastern Ghats. In contrast, the northeastern forests, southern Western Ghats and the forested regions of eastern India are estimated to be the least vulnerable. Low tree density, low biodiversity status as well as higher levels of fragmentation, in addition to climate change, contribute to the vulnerability of these forests. The mountainous forests (sub-alpine and alpine forest, the Himalayan dry temperate forest and the Himalayan moist temperate forest) are susceptible to the adverse effects of climate change. This is because climate change is predicted to be larger for regions that have greater elevations.

Optimal local polynomial regression of noisy time varying signals

We address the problem of local-polynomial modeling of smooth time-varying signals with unknown functional form, in the presence of additive noise. The problem formulation is in the time domain and the polynomial coefficients are estimated in the pointwise minimum mean square error (PMMSE) sense. The choice of the window length for local modeling introduces a bias-variance tradeoff, which we solve optimally by using the intersection-of-confidence-intervals (ICI) technique. The combination of the local polynomial model and the ICI technique gives rise to an adaptive signal model equipped with a time-varying PMMSE-optimal window length whose performance is superior to that obtained by using a fixed window length. We also evaluate the sensitivity of the ICI technique with respect to the confidence interval width. Simulation results on electrocardiogram (ECG) signals show that at 0dB signal-to-noise ratio (SNR), one can achieve about 12dB improvement in SNR. Monte-Carlo performance analysis shows that the performance is comparable to the basic wavelet techniques. For 0 dB SNR, the adaptive window technique yields about 2-3dB higher SNR than wavelet regression techniques and for SNRs greater than 12dB, the wavelet techniques yield about 2dB higher SNR.

Modeling Indian Ocean circulation: Bay of Bengal fresh water plume and the Arabian Sea Mini Warm Pool

The Indian subcontinent divides the north Indian Ocean into two tropical basins, namely the Arabian Sea and the Bay of Bengal. The Arabian Sea has high salinity whereas the salinity of the Bay of Bengal is much lower due to the contrast in freshwater forcing of the two basins. The freshwater received by the Bay in large amounts during the summer monsoon through river discharge is flushed out annually by ocean circulation. After the withdrawal of the summer monsoon, the Ganga – Brahmaputra river plume flows first along the Indian coast and then around Sri Lanka into the Arabian Sea creating a low salinity pool in the southeastern Arabian Sea (SEAS). In the same region, during the pre-monsoon months of February – April, a warm pool, known as the Arabian Sea Mini Warm Pool (ASMWP), which is distinctly warmer than the rest of the Indian Ocean, takes shape. In fact, this is the warmest region in the world oceans during this period. Simulation of the river plume and its movement as well as its implications to thermodynamics has been a challenging problem for models of Indian Ocean. Here we address these issues using an ocean general circulation model – first we show that the model is capable of reproducing fresh plumes in the Bay of Bengal as well as its movement and then we use the model to determine the processes that lead to formation of the ASMWP. Hydrographic observations from the western Bay of Bengal have shown the presence of a fresh plume along the northern part of the Indian coast during summer monsoon. The Indian Ocean model when forced by realistic winds and climatological river discharge reproduces the fresh plume with reasonable accuracy. The fresh plume does not advect along the Indian coast until the end of summer monsoon. The North Bay Monsoon Current, which flows eastward in the northern Bay, separates the low salinity water from the more saline southern parts of the bay and thus plays an important role in the fresh water budget of the Bay of Bengal. The model also reproduces the surge of the fresh-plume along the Indian coast, into the Arabian Sea during northeast monsoon. Mechanisms that lead to the formation of the Arabian Sea Mini Warm Pool are investigated using several numerical experiments. Contrary to the existing theories, we find that salinity effects are not necessary for the formation of the ASMWP. The orographic effects of the Sahyadris (Western Ghats) and resulting reduction in wind speed leads to the formation of the ASMWP. During November – April, the SEAS behave as a low-wind heatdominated regime where the evolution of sea surface temperature is solely determined by atmospheric forcing. In such regions the evolution of surface layer temperature is not dependent on the characteristics of the subsurface ocean such as the barrier layer and temperature inversion.