Forecasting rain for groundnut farmers�how good is good enough

: We illustrate how climatological information about adverse weather events and meteorological forecasts (when available) can be used to decide between alternative strategies so as to maximize the long-term average returns for rainfed groundnut in semi-arid parts of Karnataka, We show that until the skill of the forecast, i.e. probability of an adverse event occurring when it is forecast, is above a certain threshold, the forecast has no impact on the optimum strategy, This threshold is determined by the loss in yield due to the adverse weather event and the cost of the mitigatory measures, For the specific case of groundnut, it is found that while for combating some pests/diseases, climatological information is adequate, for others a forecast of sufficient skill would have a significant impact on the productivity.

A rain forest dusk chorus: cacophony or sounds of silence?

A rain forest dusk chorus consists of a large number of individuals of acoustically communicating species signaling at the same time. How different species achieve effective intra-specific communication in this complex and noisy acoustic environment is not well understood. In this study we examined acoustic masking interference in an assemblage of rain forest crickets and katydids. We used signal structures and spacing of signalers to estimate temporal, spectral and active space overlap between species. We then examined these overlaps for evidence of strategies of masking avoidance in the assemblage: we asked whether species whose signals have high temporal or spectral overlap avoid calling together. Whereas we found evidence that species with high temporal overlap may avoid calling together, there was no relation between spectral overlap and calling activity. There was also no correlation between the spectral and temporal overlaps of the signals of different species. In addition, we found little evidence that species calling in the understorey actively use spacing to minimize acoustic overlap. Increasing call intensity and tuning receivers however emerged as powerful strategies to minimize acoustic overlap. Effective acoustic overlaps were on average close to zero for most individuals in natural, multispecies choruses, even in the absence of behavioral avoidance mechanisms such as inhibition of calling or active spacing. Thus, call temporal structure, intensity and frequency together provide sufficient parameter space for several species to call together yet communicate effectively with little interference in the apparent cacophony of a rain forest dusk chorus.

A comparison of the fine-scale structure of the diurnal cycle of tropical rain and lightning

In this study, the fine-scale structure of the diurnal variability of ground-based lightning is systematically compared with satellite-based rain. At the outset, it is shown that tropical variability of lightning exhibits a prominent diurnal mode, much like rain. A comparison of the geographical distribution of the timing of the diurnal maximum shows that there is very good agreement between the two observables over continental and coastal regions throughout the tropics. Following this global tropical comparison, we focus on two regions, Borneo and equatorial South America, both of which show the interplay between oceanward and landward propagations of the phase of the diurnal maximum. Over Borneo, both rain and lightning clearly show a climatological cycle of ``breathing in'' (afternoon to early morning) and ``breathing out'' (morning to early afternoon). Over the equatorial east coast of South America, landward propagation is noticed in rain and lightning from early afternoon to early morning. Along the Pacific coast of South America, both rain and lightning show oceanward propagation. Though qualitatively consistent, over both regions the propagation is seen to extend further in rainfall. Additionally, given that lightning highlights vigorous convection, the timing of its diurnal maximum often precedes that of rainfall in the convective life cycle. (C) 2015 Elsevier B.V. All rights reserved.

Non-linear regression model for spatial variation in precipitation chemistry for South India

Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO3, NO3 and Mg do not change much from coast to inland while, SO4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent (R-2 similar to 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of similar to 5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India. (C) 2008 Elsevier Ltd. All rights reserved.

Cyclone-induced mixing does not cool SST in the post-monsoon north Bay of Bengal

High-resolution data from the TRMM satellite shows that sea surface temperature (SST) cools by 3 degrees C under the tracks of pre-monsoon tropical cyclones in the north Indian Ocean. However, even the strongest post-monsoon cyclones do not cool the open north Bay of Bengal. In this region, a shallow layer of freshwater from river runoff and monsoon rain caps a deep warm layer. Therefore, storm-induced mixing is not deep, and it entrains warm subsurface water. It is possible that the hydrography of the post-monsoon north Bay favours intense cyclones.

Inbreeding and the incidence of childhood genetic disorders in Karnataka, South India

Consanguineous marriages are strongly favoured among the populations of South India. In a study conducted on 407 infants and children, a total of 35 genetic diseases was diagnosed in 63 persons: 44 with single gene defects, 12 with polygenic disorders, and seven with Down's syndrome. The coefficient of inbreeding of the total study group, F = 0.0414, was significantly higher than that previously calculated for the general population, F = 0.0271, and autosomal recessive disorders formed the largest single disease category diagnosed. The results suggest that long term inbreeding may not have resulted in appreciable elimination of recessive lethals and sub-lethals from the gene pool.

Effect of rodents on seed fate of five hornbill-dispersed tree species in a tropical forest in north-east India

Hornbills are important dispersers of a wide range of tree species. Many of these species bear fruits with large, lipid-rich seeds that could attract terrestrial rodents. Rodents have multiple effects on seed fates, many of which remain poorly understood in the Palaeotropics. The role of terrestrial rodents was investigated by tracking seed fate of five horn bill-dispersed tree species in a tropical forest in north-cast India. Seeds were marked inside and outside of exclosures below 6-12 parent fruiting trees (undispersed seed rain) and six hornbill nest trees (a post-dispersal site). Rodent visitors and seed removal ere monitored using camera traps. Our findings suggest that several rodent species. especially two species of porcupine were major on-site seed predators. Scatter-hoarding was rare (1.4%). Seeds at hornbill nest trees had lower survival compared with parent fruiting trees, indicating that clumped dispersal by hornbills may not necessarily improve seed survival. Seed survival in the presence and absence of rodents varied with tree species. Some species (e.g. Polyalthia simiarum) showed no difference, others (e.g. Dysoxylum binectariferum) experienced up to a 64%. decrease in survival in the presence of rodents. The differing magnitude of seed predation by rodents can have significant consequences at the seed establishment stage.

Variability of Indian summer monsoon rainfall in daily data from gauge and satellite

It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

System integration design in MEMS - A case study of micromachined load cell

One of the critical issues in large scale commercial exploitation of MEMS technology is its system integration. In MEMS, a system design approach requires integration of varied and disparate subsystems with one of a kind interface. The physical scales as well as the magnitude of signals of various subsystems vary widely. Known and proven integration techniques often lead to considerable loss in advantages the tiny MEMS sensors have to offer. Therefore, it becomes imperative to think of the entire system at the outset, at least in terms of the concept design. Such design entails various aspects of the system ranging from selection of material, transduction mechanism, structural configuration, interface electronics, and packaging. One way of handling this problem is the system-in-package approach that uses optimized technology for each function using the concurrent hybrid engineering approach. The main strength of this design approach is the fast time to prototype development. In the present work, we pursue this approach for a MEMS load cell to complete the process of system integration for high capacity load sensing. The system includes; a micromachined sensing gauge, interface electronics and a packaging module representing a system-in-package ready for end characterization. The various subsystems are presented in a modular stacked form using hybrid technologies. The micromachined sensing subsystem works on principles of piezo-resistive sensing and is fabricated using CMOS compatible processes. The structural configuration of the sensing layer is designed to reduce the offset, temperature drift, and residual stress effects of the piezo-resistive sensor. ANSYS simulations are carried out to study the effect of substrate coupling on sensor structure and its sensitivity. The load cell system has built-in electronics for signal conditioning, processing, and communication, taking into consideration the issues associated with resolution of minimum detectable signal. The packaged system represents a compact and low cost solution for high capacity load sensing in the category of compressive type load sensor.

Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

Lifting the singular nature of a model for peeling of an adhesive tape

We investigate the dynamics of peeling of an adhesive tape subjected to a constant pull speed. Due to the constraint between the pull force, peel angle and the peel force, the equations of motion derived earlier fall into the category of differential-algebraic equations (DAE) requiring an appropriate algorithm for its numerical solution. By including the kinetic energy arising from the stretched part of the tape in the Lagrangian, we derive equations of motion that support stick-slip jumps as a natural consequence of the inherent dynamics itself, thus circumventing the need to use any special algorithm. In the low mass limit, these equations reproduce solutions obtained using a differential-algebraic algorithm introduced for the earlier singular equations. We find that mass has a strong influence on the dynamics of the model rendering periodic solutions to chaotic and vice versa. Apart from the rich dynamics, the model reproduces several qualitative features of the different waveforms of the peel force function as also the decreasing nature of force drop magnitudes.

Urban satellite image classification using biologically inspired techniques

This paper focuses on optimisation algorithms inspired by swarm intelligence for satellite image classification from high resolution satellite multi- spectral images. Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to satisfactorily classify all the basic land cover classes of an urban region. In both supervised and unsupervised classification methods, the evolutionary algorithms are not exploited to their full potential. This work tackles the land map covering by Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) which are arguably the most popular algorithms in this category. We present the results of classification techniques using swarm intelligence for the problem of land cover mapping for an urban region. The high resolution Quick-bird data has been used for the experiments.