Discovery of Early Tonian Calc-alkaline and Shoshonitic Metamafic Rocks from the North Purulia Shear Zone, Chhotanagpur Gneissic Complex, Eastern India: Implications of Proterozoic Sub-continental Lithospheric Mantle

Reports of shoshonitic rocks in Precambrian terrains are relatively rare. Pl-Grt amphibolites and Hbl-Bt mafic granulites occurring in the migmatitic gneisses of the Chhotanagpur Gneissic Complex(CGC) show calc-alkaline and shoshonitic characteristics. Relict porphyritic, sub-ophitic and poikilitic textures are noted in these rocks. Their parent magma was emplaced during the waning phase of the regional metamorphism. Geochemically, these metamafics are similar to the Group Ⅲ potassic and ultrapo...     

Demarcation of fluoride vulnerability zones in granitic aquifer,semi-arid region,Telengana, India

This study has been carried out in the granitic aquifer of Maheshwaram watershed, Telengana, India. In this study, groundwater sample data of 8 years were analyzed for the fluoride content with other chemical quality parameters. The correlation and factor analysis were employed to understand the mechanisms for fluoride (F) enrichment as well as the hydrochemistry of the area. These analyses addressed that the observed groundwater quality was due to water-rock interaction in the aquifer and fluoride is coming from the dissolution of fluorite and other silicate minerals like biotite and hornblende by the groundwater. Land use/land cover (LULC) study from 2002 to 2008 revealed there were significant positive changes in build-up land and negative changes in vegetation cover after 2003. The main agriculture (paddy) has been reduced to 0.97 km² in 2008 from 2.39 km² in 2003. The studied watershed has been characterized on the basis of F concentration into safe, transition, and unsafe groups following the WHO and BIS guidelines. The temporal variation of the three groups showed that 57.6% area of the watershed was in unsafe zone in 2000–2003, but 69.2% of the area became safe in 2006–2009. It has been found that F concentration reduced in 12.59% of the area (became safe from unsafe) accompanied by the reduction of paddy field area. After validation with present (2016) fluoride concentrations, it was found that 16.28% are vulnerable in near future. The results of this study showed that (a) the safe and unsafe zones of fluoride concentrations vary with time with the changes in other parameters associated with it like crop pattern and (b) vulnerable zone can be identified based on the susceptibility to change of safe and unsafe zones. Such studies are useful for planning and management purposes.     

Comparative evaluation of performances of two versions of NCEP climate forecast system in predicting Indian summer monsoon rainfall

The operational prediction of climatic variables in monthly-to-seasonal scales has been issued by National Centers for Environmental Prediction (NCEP) through Climate Forecast System model (CFSv1) since 2004. After incorporating significant changes, a new version of this model (CFSv2) was released in 2011. The present study is based on the comparative evaluation of performances of CFSv2 and CFSv1 for the southwest monsoon season (June-July-August-September, JJAS) over India with May initial condition during 1982–2009. It was observed that CFSv2 has improved over CFSv1 in simulating the observed monsoon rainfall climatology and inter annual variability. The movement of the cell of Walker circulation in years of excessive and deficient rainfall is better captured in CFSv2, as well. The observed teleconnection pattern between ISMR-sea surface temperature (SST) is also better captured in CFSv2. The overall results suggest that the changes incorporated in CFSv1 through the development of CFSv2 have resulted in an improved prediction of ISMR.21     

On the Predictability of Northeast Monsoon Rainfall over South Peninsular India in General Circulation Models

In this study the predictability of northeast monsoon (Oct–Nov–Dec) rainfall over peninsular India by eight general circulation model (GCM) outputs was analyzed. These GCM outputs (forecasts for the whole season issued in September) were compared with high-resolution observed gridded rainfall data obtained from the India Meteorological Department for the period 1982–2010. Rainfall, interannual variability (IAV), correlation coefficients, and index of agreement were examined for the outputs of eight GCMs and compared with observation. It was found that the models are able to reproduce rainfall and IAV to different extents. The predictive power of GCMs was also judged by determining the signal-to-noise ratio and the external error variance; it was noted that the predictive power of the models was usually very low. To examine dominant modes of interannual variability, empirical orthogonal function (EOF) analysis was also conducted. EOF analysis of the models revealed they were capable of representing the observed precipitation variability to some extent. The teleconnection between the sea surface temperature (SST) and northeast monsoon rainfall was also investigated and results suggest that during OND the SST over the equatorial Indian Ocean, the Bay of Bengal, the central Pacific Ocean (over Nino3 region), and the north and south Atlantic Ocean enhances northeast monsoon rainfall. This observed phenomenon is only predicted by the CCM3v6 model.     

Long-Lead Prediction Skill of Indian Summer Monsoon Rainfall Using Outgoing Longwave Radiation (OLR): an Application of Canonical Correlation Analysis

There is a statistical linkage between tropical outgoing longwave radiation (OLR) and all-India summer monsoon rainfall (AISMR). A positive and significant correlation is observed over the surrounding areas of northeast Australia and the Arafura Sea during the months of January and February (J&F) which drops down as the lead month decreases. The OLR index as an area average over the surrounding areas of northeast Australia and the Arafura Sea is found to have 0.4 correlation with AISMR. The index is also found to be strongly correlated with the Indian monsoon index. In view of the teleconnection pattern, the OLR index is used for the development of statistical models using the concept of linear regression (LR) and canonical correlation analysis (CCA). Potential of CCA over LR is observed for the prediction of seasonal rainfall over the northwest, west central and over the whole country as well. The seasonal rainfall predictability basically comes from the months of June and September.     

Performance of general circulation models and their ensembles for the prediction of drought indices over India during summer monsoon

The drought during the months of June to September (JJAS) results in significant deficiency in the annual rainfall and affects the hydrological planning, disaster management, and the agriculture sector of India. Advance information on drought characteristics over the space may help in risk assessment over the country. This issue motivated the present study which deals with the prediction of drought during JJAS through standardized precipitation index (SPI) using nine general circulation models (GCM) product. Among these GCMs, three are the atmospheric and six are atmosphere–ocean coupled models. The performance of these GCM’s predicted SPI is examined against the observed SPI for the time period of 1982–2010. After a rigorous analysis, it can be concluded that the skill of prediction by GCM is not satisfactory, whereas the ability of the coupled models is better than the atmospheric models. An attempt has been made to improve the accuracy of predicted SPI using two different multi-model ensemble (MME) schemes, viz., arithmetic mean and weighted mean using singular value decomposition-based multiple linear regressions (SVD-MLR) of GCMs. It is found that among these MME techniques, SVD-MLR-based MME has more skill as compared to simple MME as well as individual GCMs.     

Effect of spatial correlation on regional trends in rain events over India

The regional trends are evaluated in the frequency of various rain events using the daily gridded (1°?×?1°) rainfall dataset for the time period 1901–2004, prepared by the India Meteorological Department (IMD). In terms of intensity, the events are classified as low, moderate, heavy and extreme heavy, while short and long spells are classified on the basis of duration of rainfall. The analytical (parametric) and the empirical (bootstrap) techniques were used to incorporate the impact of spatial correlation in regional trends. It is observed that, consideration of spatial correlation reduces the significance level of the trends and the effective number of grid points falling under each category. Especially, the noticeable cross-correlation have reduced the significance of the trends in moderate and long spell rain events to a large extent, while the significance of trends in the extreme heavy and short spell events is not highly affected because of small cross-correlation.     

Performance of Multi Model Canonical Correlation Analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output

The emerging advances in the field of dynamical prediction of monsoon using state-of-the-art General Circulation Models (GCMs) have led to the development of various multi model ensemble techniques (MMEs). In the present study, the concept of Canonical Correlation Analysis is used for making MME (referred as Multi Model Canonical Correlation Analysis or MMCCA) for the prediction of Indian summer monsoon rainfall (ISMR) during June-July-August-September (JJAS). This method has been employed on the rainfall outputs of six different GCMs for the period 1982 to 2008. The prediction skill of ISMR by MMCCA is compared with the simple composite method (SCM) (i.e. arithmetic mean of all GCMs), which is taken as a benchmark. After a rigorous analysis through different skill metrics such as correlation coefficient and index of agreement, the superiority of MMCCA over SCM is illustrated. Performance of both models is also evaluated during six typical monsoon years and the results indicate the potential of MMCCA over SCM in capturing the spatial pattern during extreme years.     

Meso-scale flanking structure and micro-scale push up structure within migmatitic biotite granite,Peninsular Gneissic Complex,Southern India

International Journal of Earth Sciences -