Late Cretaceous mafic dykes in the Dharwar craton

Palaeomagnetic, geochemical and geochronological studies have been conducted on a set of dolerite dykes intruding the Peninsular gneisses near Huliyurdurga town, Karnataka, as a reconnaissance survey indicated a Cretaceous age for them. The dykes are mainly tholeiitic in composition with their 87Sr/86Sr ratios tightly clustered around 0·7045. Their palaeomagnetic data (D _m =329°,I _m =−55°) and the corresponding palaeopole coordinates (λ _p = 34°S,L _p =108°E) are strikingly close to those of the Deccan Traps to the north. Whole rock K-Ar ages of these dykes ranging between 69 and 84 Ma are also similar to the range of K-Ar ages of the Deccan basalts. The chemical, palaeomagnetic and temporal coherence between the dykes and the Deccan basalts indicate that they may indeed be tectonically related events.     

Forecasting monthly precipitation using sequential modelling

In the hydrological cycle, rainfall is a major component and plays a vital role in planning and managing water resources. In this study, new generation deep learning models, recurrent neural network (RNN) and long short-term memory (LSTM), were applied for forecasting monthly rainfall, using long sequential raw data for time series analysis. “All-India” monthly average precipitation data for the period 1871–2016 were taken to build the models and they were tested on different homogeneous regions of India to check their robustness. From the results, it is evident that both the trained models (RNN and LSTM) performed well for different homogeneous regions of India based on the raw data. The study shows that a deep learning network can be applied successfully for time series analysis in the field of hydrology and allied fields to mitigate the risks of climatic extremes.     

Sensitivity of tropical cyclone intensification to boundary layer and convective processes

This study examines the role of the parameterization of convection, planetary boundary layer (PBL) and explicit moisture processes on tropical cyclone intensification. A high-resolution mesoscale model, National Center for Atmospheric Research (NCAR) model MM5, with two interactive nested domains at resolutions 90 km and 30 km was used to simulate the Orissa Super cyclone, the most intense Indian cyclone of the past century. The initial fields and time-varying boundary variables and sea surface temperatures were taken from the National Centers for Environmental Prediction (NCEP) (FNL) one-degree data set. Three categories of sensitivity experiments were conducted to examine the various schemes of PBL, convection and explicit moisture processes. The results show that the PBL processes play crucial roles in determining the intensity of the cyclone and that the scheme of Mellor-Yamada (MY) produces the strongest cyclone. The combination of the parameterization schemes of MY for planetary boundary layer, Kain-Fritsch2 for convection and Mixed-Phase for explicit moisture produced the best simulation in terms of intensity and track. The simulated cyclone produced a minimum sea level pressure of 930 hPa and a maximum wind of 65 m s⁻¹ as well as all of the characteristics of a mature tropical cyclone with an eye and eye-wall along with a warm core structure. The model-simulated precipitation intensity and distribution were in good agreement with the observations. The ensemble mean of all 12 experiments produced reasonable intensity and the best track.     

Evolution of model systematic errors in the Tropical Atlantic Basin from coupled climate hindcasts

Significant systematic errors in the tropical Atlantic Ocean are common in state-of-the-art coupled ocean–atmosphere general circulation models. In this study, a set of ensemble hindcasts from the NCEP coupled forecast system (CFS) is used to examine the initial growth of the coupled model bias. These CFS hindcasts are 9-month integrations starting from perturbed real-time oceanic and atmospheric analyses for 1981–2003. The large number of integrations from a variety of initial states covering all months provides a good opportunity to examine how the model systematic errors grow. The monthly climatologies of ensemble hindcasts from various initial months are compared with both observed and analyzed oceanic and atmospheric datasets. Our analyses show that two error patterns are dominant in the hindcasts. One is the warming of the sea surface temperature (SST) in the southeastern tropical Atlantic Ocean. This error grows faster in boreal summer and fall and peaks in November–December at round 2°C in the open ocean. It is caused by an excessive model surface shortwave radiative flux in this region, especially from boreal summer to fall. The excessive radiative forcing is in turn caused by the CFS inability to reproduce the observed amount of low cloud cover in the southeastern ocean and its seasonal increase. According to a comparison between the seasonal climatologies from the CFS hindcasts and a long-term simulation of the atmospheric model forced with observed SST, the CFS low cloud and radiation errors are inherent to its atmospheric component. On the other hand, the SST error in CFS is a major cause of the model’s southward bias of the intertropical convergence zone (ITCZ) in boreal winter and spring. An analysis of the SST errors of the 6-month ensemble hindcasts by seven coupled models in the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction project shows that this SST error pattern is common in coupled climate hindcasts. The second error pattern is an excessive deepening of the model thermocline depth to the north of the equator from the western coast toward the central ocean. This error grows fastest in boreal summer. It is forced by an overly strong local anticyclonic surface wind stress curl and is in turn related to the weakened northeast trade winds in summer and fall. The thermocline error in the northwest delays the annual shoaling of the equatorial thermocline in the Gulf of Guinea remotely through the equatorial waveguide.     

Refinement of predictive reaeration equations for a typical Indian river

Dissolved oxygen mass balance has been computed for different reaches of River Kali in western Uttar Pradesh (India) to obtain the reaeration coefficient (K₂). A total of 270 field data sets have been collected during the period from March 1999 to February 2000. Eleven most popular predictive equations, used for reaeration prediction and utilizing mean stream velocity, bed slope, flow depth, friction velocity and Froude number, have been tested for their applicability in the River Kali using data generated during field survey. The K₂ values computed from these predictive equations have been compared with the K₂ values observed from dissolved oxygen balance measurements in the field. The performance of predictive equations have been evaluated using error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and correlation statistics. The equations developed by Smoot and by Cadwallader and McDonnell showed comparatively better results. Moreover, a refined predictive equation has been developed using a least‐squares algorithm for the River Kali that minimizes error estimates and improves correlation between observed and computed reaeration coefficients. Copyright © 2001 John Wiley & Sons, Ltd.     

Itawa Bhopji (L3–5) chondrite regolith breccia: Fall,classification, and cosmogenic records

Abstract— A stony meteorite fell at Itawa Bhopji, Rajasthan, India on 2000 May 30. This is the fifth recorded fall in a small area of Rajasthan during the past decade. The meteorite is an ordinary chondrite with light clasts in a dark matrix, consisting of a mixture of equilibrated (mainly type 5) and unequilibrated components. Olivine is Fa_24–26 and pyroxene Fs_20–22 but, within the unequilibrated components, olivine (Fa_5–29) and low calcium pyroxene (Fs_5–37) are highly variable. Based on petrographic studies and chemical analyses, it is classified as L(3–5) regolith breccia. Studies of various cosmogenic records, including several gamma‐emitting radionuclides varying in half‐life from 5.6 day ⁵²Mn to 0.73 Ma ²⁶Al, tracks and rare gases have been carried out. The exposure age of the meteorite is estimated from cosmogenic components of rare gases to be 19.6 Ma. The track density varies by a factor of ?3 (from 4 to 12 times 10⁶/cm²) within the meteorite, indicating a preatmospheric body of ?9 cm radius (corresponding to a meteoroid mass of ?11 kg) and small ablation (1.5 to 3.6 cm). Trapped components in various rare gases are high and the solar component is present in the dark portion of the meteorite. Large excess of neutron‐produced ⁸²Kr and ¹²⁸Xe in both the light and the dark lithology but very low ⁶⁰Co, indicating low neutron fluxes received by the meteoroid in the interplanetary space, are clear signatures of an additional irradiation on the parent body.     

A first estimate of ground water ages for the deep aquifer of the Kathmandu Basin, Nepal, using the radioisotope chlorine-36

The Kathmandu Basin in Nepal contains up to 550 m of Pliocene-Quaternary fluvio-lacustrine sediments which have formed a dual aquifer system. The unconfined sand and gravel aquifer is separated by a clay aquitard, up to 200 m thick, from the deeper, confined aquifer, comprised of Pliocene sand and gravel beds, intercalated with clay, peat, and lignite. The confined aquifer currently provides an important water supply to the central urban area but there are increasing concerns about its sustainability due to overexploitation. A limited number of determinations of the radioisotope 36Cl have been made on bore waters in the basin, allowing us to postulate on the age of ground water in the deeper, confined aquifer. Ground water evolution scenarios based on radioisotope decay, gradual dissolution of formational salts as the ground waters move downgradient, and flow velocity estimations produce comparable ground water ages for the deep waters, ranging from 200,000 to 400,000 years. From these ages, we deduce a mean ground water flow velocity of only 45 mm/year from recharge in the northeast to the main extraction region 15 km to the southwest. We thus estimate current recharge at about 5 to 15 mm/year, contributing 40,000 to 1.2 million m3/year to the ground water system. Current ground water extraction is estimated to be 20 times this amount. The low specific discharge confirms that the resource is being mined, and, based on current projections, reserves will be used up within 100 years.