Geology and geochemistry of metabasalts of Shimoga schist belt,Dharwar Craton: implications for the late Archean basin development

The late Archaean Shimoga schist belt in the Western Dharwar Craton, with its huge dimensions and varied lithological associations of different age groups, is an ideal terrane to study Archean crustal evolution. The rock types in this belt are divided into Bababudhan Group and Chitradurga Group. The Bababudhan Group is dominated by mafic volcanic rocks followed by shallow marine sedimentary rocks while the Chitradurga Group is dominated by greywackes, pillowed basalts, and deep marine sedimentary rocks with occasional felsic volcanics. The Nb/Th and Nb/La ratios of the studied metabasalts of the Bababudhan Group indicate crustal contamination. They were extruded onto the vast Peninsular Gneisses through the rifting of the basement gneiss. The Nb/Yb ratios of high-magnesium basalts and tholeiitic basalts of Chitradurga Group suggest the enrichment of their source magma. Based on the flat primitive mantle-normalized multi-element plot with negative Nb anomalies and Th/Ta-La/Yb ratios, the high-magnesium basalts and tholeiitic basalts are considered to have erupted in an oceanic plateau setting with minor crustal contamination. The high-magnesium basalts and tholeiitic basalts formed two different pulses of same magma type, in which the first pulse of magma gave rise to high-magnesium basalts which were derived from deep mantle sources and underwent minor crustal contamination en route to the surface, while the second pulse of magma gave rise to tholeiitic basalts formed at similar depths to that of high-magnesium basalts and escaped crustal contamination. The associated lithological units found with the studied metavolcanic rock types of Bababudan and Chitradurga Groups of Dharwar Supergroup of rocks in Shimoga schist belt of Western Dharwar Craton confirm the mixed-mode basin development with a transition from shallow marine to deep marine settings.     

Forecasting quantitative rainfall over India using multi-model ensemble technique

A new approach to ensemble forecasting of rainfall over India based on daily outputs of four operational numerical weather prediction (NWP) models in the medium-range timescale (up to 5 days) is proposed in this study. Four global models, namely ECMWF, JMA, GFS and UKMO available on real-time basis at India Meteorological Department, New Delhi, are used simultaneously with adequate weights to obtain a multi-model ensemble (MME) technique. In this technique, weights for each NWP model at each grid point are assigned on the basis of unbiased mean absolute error between the bias-corrected forecast and observed rainfall time series of 366 daily data of 3 consecutive southwest monsoon periods (JJAS) of 2008, 2009 and 2010. Apart from MME, a simple ensemble mean (ENSM) forecast is also generated and experimented. The prediction skill of MME is examined against observed and corresponding outputs of each constituent model during monsoon 2011. The inter-comparison reveals that MME is able to provide more realistic forecast of rainfall over Indian monsoon region by taking the strength of each constituent model. It has been further found that the weighted MME technique has higher skill in predicting daily rainfall compared to ENSM and individual member models. RMSE is found to be lowest in MME forecasts both in magnitude and area coverage. This indicates that fluctuations of day-to-day errors are relatively less in the MME forecast. The inter-comparison of domain-averaged skill scores for different rainfall thresholds further clearly demonstrates that the MME algorithm improves slightly above the ENSM and member models.     

Analysis and very short range forecast of cyclone “AILA” with radar data assimilation with rapid intermittent cycle using ARPS 3DVAR and cloud analysis techniques

In this study, both reflectivity and radial velocity are assimilated into the Weather Research and Forecasting (WRF) model using ARPS 3DVAR technique and cloud analysis procedure for analysis and very short range forecast of cyclone ÁILA. Doppler weather radar (DWR) data from Kolkata radar are assimilated for numerical simulation of landfalling tropical cyclone. Results show that the structure of cyclone AILA has significantly improved when radar data is assimilated. Radar reflectivity data assimilation has strong influence on hydrometeor structures of the initial vortex and precipitation pattern and relatively less influence is observed on the wind fields. Divergence/convergence conditions over cyclone inner-core area in the low-to-middle troposphere (600–900 hPa) are significantly improved when wind data are assimilated. However, less impact is observed on the moisture field. Analysed minimum sea level pressure (SLP) is improved significantly when both reflectivity and wind data assimilated simultaneously (RAD-ZVr experiment), using ARPS 3DVAR technique. In this experiment, the centre of cyclone is relocated very close to the observed position and the system maintains its intensity for longer duration. As compared to other experiments track errors are much reduced and predicted track is very much closer to the best track in RAD-ZVr experiment. Rainfall pattern and amount of rainfall are better captured in this experiment. The study also reveals that cyclone structure, intensification, direction of movement, speed and location of cyclone are significantly improved and different stages of system are best captured when both radar reflectivity and wind data are assimilated using ARPS 3DVAR technique and cloud analysis procedure. Thus optimal impact of radar data is realized in RAD-ZVr experiment. The impact of DWR data reduces after 12 h forecast and it is due to the dominance of the flow from large-scale global forecast system model. Successful coupling of data assimilation package ARPS 3DVAR with WRF model for Indian DWR data is also demonstrated.