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Northern Indian rivers are primarily fed by wintertime (December, January, February—DJF) precipitation, in the form of snow—yielded by eastward moving synoptic weather systems called Western Disturbances (WDs), over the western Himalayas (WH). This accumulated snow melts during ablation period. In the context of today’s warming atmosphere, it is imperative to study the changes in the temperature and precipitation patterns over the WH to assess the impact of global warming on climatic conditions of the region. Keeping that in mind, observational analysis of temperature and precipitation fields is planned. In the present study various climatic indices are analyzed based on wintertime (DJF) data of 30 years (1975–2006) obtained from the Snow and Avalanche Study Establishment (SASE), India. Results indicate enhancement in the surface air temperature across the WH. Percent number of warm (cold) days have increased (decreased) during 1975–2006 over the WH. Further analysis of precipitation reveals slightly decreasing but inconsistent trends.

In the context of climate change and its impact on sectors like agriculture and health, it is important to examine the changes in the characteristics of temperature extremes of different intensities and duration. In this study, an India Meteorological Department gridded temperature dataset is used to examine the changes in the frequency of occurrence of extreme temperatures over India and its seven homogeneous regions during the period 1969–2005. Results indicate a significant decrease in the frequency of occurrence of cold nights in the winter months in India and in its homogeneous regions in the north except in the western Himalaya. Southern regions show a drastic decrease in the frequency of cold nights relative to the period 1969–75. A significant increasing trend in the number of warm days in summer is noticed only in the interior peninsula. In the entire country and on the east coast and west coast, the maximum number of warm days in summer has been noticed only during the last decade, 1996–2005. Further, in the whole country the maximum number of intense warm days and nights in summer has been observed in the last decade. A significant increase in the number of cold days in winter is observed in the north-central and northeast regions. Changes in the frequency of warm and cold exceedances indicate maximum warming in the west coast as compared with all other regions. In sum, such spatial and temporal changes in the characteristics of all categories of temperature extremes broadly suggest warming trends in large parts of India.

Using data from 33 models from the CMIP5 historical and AMIP5 simulations, we have carried out a systematic analysis of biases in total precipitation and its convective and large-scale components over the south Asian region. We have used 23 years (1983–2005) of data, and have computed model biases with respect to the PERSIANN-CDR precipitation (with convective/large-scale ratio derived from TRMM 3A12). A clustering algorithm was applied on the total, convective, and large-scale precipitation biases seen in CMIP5 models to group them based on the degree of similarity in the global bias patterns. Subsequently, AMIP5 models were analyzed to conclude if the biases were primarily due to the atmospheric component or due to the oceanic component of individual models. Our analysis shows that the set of individual models falling in a given group is somewhat sensitive to the variable (total/convective/large-scale precipitation) used for clustering. Over the south Asian region, some of the convective and large-scale precipitation biases are common across groups, emphasizing that although on a global scale the bias patterns may be sufficiently different to cluster the models into different groups, regionally, it may not be true. In general, models tend to overestimate the convective component and underestimate the large-scale component over the south Asian region, although with spatially varying magnitudes depending on the model group. We find that the convective precipitation biases are largely governed by the closure and trigger assumptions used in the convection parameterization schemes used in these models, and to a lesser extent on details of the individual cloud models. Using two different methods: (i) clustering, (ii) comparing the bias patterns of models from CMIP5 with their AMIP5 counterparts, we find that, in general, the atmospheric component (and not the oceanic component through biases in SSTs and atmosphere-ocean feedbacks) plays a major role in deciding the convective and large-scale precipitation biases. However, the oceanic component has been found important for one of the convective groups in deciding the convective precipitation biases (over the maritime continent).

Daily gridded (1° × 1°) rainfall data prepared by the India Meteorological Department for the period 1951–2004 have been used in this study to examine possible changes in the frequency of rain events in India in terms of their duration and intensity per day. So far as the duration is concerned, a rain event is classified as short, long, dry, or prolonged dry spell. Similarly in terms of intensity, a rainy day is considered as low, moderate, or heavy. Changes in the frequency of these events have great relevance from the point of view of climate change. Threshold and limiting values for defining the heavy and moderate rain days are calculated in accordance with the gamma probability distribution. Results show that the frequencies of moderate and low rain days considered over the entire country have significantly decreased in the last half century. On the basis of the duration of rain events it is inferred that long spells show a significant decreasing trend over India as a whole while short and dry spells indicate an increasing tendency with 5% significance. The characteristics of rain events are also examined over six homogenous rainfall zones separately since the spatial distribution of rainfall over India shows large variability. In this study, the changes in the frequencies of different categories of rain events suggest weakening of the summer monsoon circulation over India. This hypothesis of a weakening of monsoon circulation is supported by significant reduction in the 850 hPa wind fields in the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalyzed data set.

Present study attempts to project extreme precipitation indices over 34 different meteorological subdivisions and six homogeneous regions such as Northwest, Central Northeast, Northeast, West Central, Peninsular India and Hilly Region during summer monsoon season in the twenty-first century. For this purpose, the Regional Climate Model version4 (RegCM4) had been run at 50 km horizontal resolution forced with the global model GFDL-ESM2 M, during reference period 1976–2005 for the model validation, and the mid- (2031–2060) and far-future (2070–2099) for projections under RCP8.5 scenario over the South Asia CORDEX domain. In this paper, model simulated precipitation has been validated against IMD, APHRODITE and NCEP/NCAR data sets. The results indicate that RegCM4 captures the important features of seasonal precipitation and various extreme indices over the study area. The RegCM4 has projected an increase in the mean seasonal precipitation by 0.56 mm/day whereas in case of GFDL model the rate is 0.39 mm/day during the far-future relative to the reference period. The heavy precipitation indices are projected to increase more frequently (0.264/decade) than the mean precipitation rate (0.01/decade) over India. The correlations between the extreme precipitation indices and the seasonal mean precipitation are found to be strong. In addition, the consecutive dry days are projected to occur more frequently (3–5 days) over West Central (Telangana, Vidarbha and Marathwada) and west Rajasthan while consecutive wet days are projected to decrease over larger parts of India during far-future. Similarly, 1 day maximum precipitation and the simple daily intensity index are projected to increase consistently from mid- to far- futures over some sub-divisions of West coast, Hilly and Northeast regions. From a spatial probability perspective, model projection indicates more frequent severe drought and flood conditions over India.

An autonomous power generation system contains numerous autonomous generation units like diesel energy generator, solar photovoltaic units, wind turbine generator, fuel cells along with energy storing units such as the flywheel energy storage system and battery energy storage system. These renewable sources are typically varying in nature. Therefore, the system components either run at lower/higher power output or may turned on/off at different instant of their operation. Due to the above mentioned uncertainties, the conventional controllers are not able to provide desired performance under varied operating conditions. Owing to this challenge, this paper proposes an adaptive fuzzy logic PID controller (AFPID) optimized by improved sine cosine algorithm (ISCA) for the load frequency control (LFC) of an autonomous power generation system. Proposed ISCA algorithm is evaluated using standard test functions and compared with original sine cosine algorithm (SCA) to authenticate the competence of algorithm. It is found from the statistical results that the proposed ISCA algorithm outperform original SCA, Hybrid Improved Firefly-Pattern Search, gravitational search, and grey wolf optimization algorithms. The proposed AFPID controller optimized by ISCA is used for the load frequency control of the autonomous power generating system. The results show that the ISCA tuned AFPID controller has superior performance over conventional PID controller. The proposed AFPID controller is again examined by the sensitivity analysis by introducing different hybrid power system parameters and the robustness of the control approach with the dynamic change of power system parameters is evaluated. Finally, the stability of the proposed control system is tested using Eigen value analysis.

Effect of simultaneous Sm and Mn substitutions around half-doping level on the structural, magnetic and low temperature electronic behaviour of LaFeO 3 nanoparticle is extensively studied. The SXRD and FESEM data shows a single-phase nanoparticle of size 33 nm. A drastic magnetic phase change with a low temperature non-ergodic phase is seen compared to the parent LaFeO 3 (G-type antiferromagnetic) and this typical behaviour stems from the facts that, simultaneous presence of Sm and Mn alters the Fe crystal environment as well as its multiplicity which leads to improved exchange interactions among different ions. The doped nanoparticle shows a colossal dielectric response. Impedance, modulus spectra and ac conductivity analysis are used to find the conduction process involved in the system and it is related to the hopping conduction through grain and grain boundary resistances. The possibility of the polaronic part may arise from the interactions among mixed-valence state of Fe (Fe 3+ /Fe 2+ ), Mn (Mn 3+ /Mn 2+ ) and from the oxygen vacancies. Moreover, the ac-electrical conductivity is analysed using Jonscher’s double-power law and Jump relaxation model.

Dual sensitized phosphors owing to their efficient energy transfer and wide spectral range have grabbed the attention of the scientific community to sort out the issue of poor luminous efficacy and simultaneously improve their applicability. Herein, a series of doubly sensitized (Bi 3+ /Mn 2+ ) and Dy 3+ activated YVO 4 phosphors have been synthesized adopting the high temperature solid state reaction route and characterized through various analytical techniques. The tetragonal zircon type structure is confirmed from the XRD patterns supported by quantitative Reitveld refinement. The emission spectral profile reveals a wide spectral range of Dy 3+ covering blue, green and red region with two-fold enhancement in the luminescence intensity due to double sensitization by Bi 3+ /Mn 2+ . The underlying energy transfer mechanism is also discussed in detail to showcase the dual sensitization of the activator ions. The CIE coordinates indicate the spectral tuning towards the white region and the low color purity percentage shows its purity towards white color. Furthermore, the CCT value favours cool white feature of the phosphor. Thus, Bi 3+ and Mn 2+ doping reflects in enhancing the emission intensity, thereby increasing the applicability of these Dy 3+ activated phosphors in the field of solid state lighting.

Optimized concentration of reduced graphene oxide (rGO) in the lube is one of the important factors for effective lubrication of solid body contacts. At sufficiently lower concentration, the lubrication is ineffective and friction/wear is dominated by base oil. In contrast, at sufficiently higher concentration, the rGO sheets aggregates in the oil and weak interlayer sliding characteristic of graphene sheets is no more active for providing lubrication. However, at optimized concentration, friction coefficient and wear is remarkably reduced to 70% and 50%, respectively, as compared to neat oil. Traditionally, such lubrication is described by graphene/graphite particle deposited in contact surfaces that provides lower shear strength of boundary tribofilm. In the present investigation, graphene/graphite tribofilm was absent and existing traditional lubrication mechanism for the reduction of friction and wear is ruled out. It is demonstrated that effective lubrication is possible, if rGO is chemically linked with PEG molecules through hydrogen bonding and PEG intercalated graphene sheets provide sufficiently lower shear strength of freely suspended composite tribofilm under the contact pressure. The work revealed that physical deposition and adsorption of the graphene sheets in the metallic contacts is not necessary for the lubrication.

The study of climate changes in India and search for robust evidences are issues of concern specially when it is known that poor people are very vulnerable to climate changes. Due to the vast size of India and its complex geography, climate in this part of the globe has large spatial and temporal variations. Important weather events affecting India are floods and droughts, monsoon depressions and cyclones, heat waves, cold waves, prolonged fog and snowfall. Results of this comprehensive study based on observed data and model reanalyzed fields indicate that in the last century, the atmospheric surface temperature in India has enhanced by about 1 and 1.1°C during winter and post-monsoon months respectively. Also decrease in the minimum temperature during summer monsoon and its increase during post-monsoon months have created a large difference of about 0.8°C in the seasonal temperature anomalies which may bring about seasonal asymmetry and hence changes in atmospheric circulation. Opposite phases of increase and decrease in the minimum temperatures in the southern and northern regions of India respectively have been noticed in the interannual variability. In north India, the minimum temperature shows sharp decrease of its magnitude between 1955 and 1972 and then sharp increase till date. But in south India, the minimum temperature has a steady increase. The sea surface temperatures (SST) of Arabian Sea and Bay of Bengal also show increasing trend. Observations indicate occurrence of more extreme temperature events in the east coast of India in the recent past. During summer monsoon months, there is a decreasing (increasing) trend in the frequency of depressions (low pressure areas). In the last century the frequency of occurrence of cyclonic storms shows increasing trend in the month of November. In addition there is increase in the number of severe cyclonic storms crossing Indian Coast. Analysis of rainfall amount during different seasons indicate decreasing tendency in the summer monsoon rainfall over Indian landmass and increasing trend in the rainfall during pre-monsoon and post-monsoon months.