The aerosol optical depth (AOD) is an important physical parameter and dimensionless number. The possible link between AOD and variability of summer monsoon rainfall and surface temperature over the densely populated Gangetic Plain may be used to assess change in weather and climate over the Plain. For examining the impact of AOD on summer monsoon rainfall and surface temperature, monthly data of AOD for the period of 2000–2015 are obtained from a remotely sensed moderate resolution imaging spectro-radiometer sensor at 550 nm and at a surface resolution of 1$^{\circ} \times$ 1$^{\circ}$. For the period of 2000–2015, rainfall and surface temperature data at a resolution of 1$^{\circ} \times$ 1$^{\circ}$ are obtained from Indian Meteorological Department (IMD) and surface wind data are obtained from National Centers for Environmental Prediction (NCEP). Summer monsoon rainfall and AOD are inversely related during 2000–2015. On an average, a difference in the mean monthly surface maximum and minimum temperatures increases (decreases) with a decrease (increase) of AOD. The high degree of correlation exists between AOD and a difference in $T_{\rm{max}}$ and $T_{\rm{min}}$ during January to June–July. In winter months, relative strength of negative vorticity over the Gangetic Plain and positive vorticity in the adjacent area may be cause of more dispersion of AOD in February in comparison with that in December and January and therefore more AOD is noticed in January and December.

The modern ‘machine-learning models’ are a section of artificially intelligent machines used to implement complex models, which can learn and improve from experience with respect to certain class of jobs, without being specifically programmed. In the present analysis, a comparative study is made of the popular machine-learning techniques regarding the prediction of auroral activity as reflected by the auroral electrojet index (AE index) during geomagnetically disturbed periods. The study also explores the suitability of the online sequential version of the best machine-learning algorithm, which has the potential for real-time forecast of the AE index from short-time input datasets with extremely fast convergence than batch-training methods. The study discusses the need for the correct choice of the input dataset that can be used for predicting the AE index from several combinations of input datasets which include coupling functions, geomagnetic indices and solar wind parameters. The study reveals that extreme learning machine and its online sequential version are promising models which could predict the AE index extremely fast with a high degree of accuracy even during disturbance periods. The study also shows that the choice of the polar cap index (PC index) as an input parameter is extremely important for an accurate prediction of the AE index.

Regional climate models are useful by downscaling from global climate model simulations for climate studies and climate applications at a regional scale. The South Asian monsoon region is one of the most challenging regions towards understanding the monsoon variability by implementing various climate simulations. A model version of the RegCM4 regional climate model provided by the International Centre for Theoretical Physics (ICTP) is used in this study to simulate the climate of Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) countries (India, Bangladesh, Bhutan, Nepal, Myanmar, Thailand and Sri Lanka) during the periods 1985–2000, which shows the present-day climate simulations. The simulation is carried out with RegCM4.3 with the lateral boundary forcing provided by the European Center for Medium Range Weather Forecast Reanalysis (Era-Interim) at 25 km horizontal resolution. The convective scheme Grell with closures Arakawa–Schubert is investigated during the south-west monsoon seasons (June–September, JJAS). The results indicate that the JJAS surface mean temperature has a large cold bias of 2–6$^{\circ}$C over the coastal regions near India, Myanmar, Thailand, Sri Lanka and Bangladesh when compared with the Climate Research Unit (CRU) observed dataset. The model is able to produce the spatial rainfall distribution pattern of the observed CRU and Global Precipitation Climatology Project (GPCP) averaged seasonal rainfall in most of the land regions over the BIMSTEC countries during this period, but with underestimation. Further, the south-westerly prevailing wind pattern at 850 hPa pressure level is also well captured by the model but with a higher intensity over Sri Lanka, Western India, Nepal and Thailand. The westerly is stronger over the Bay of Bengal in the model simulations than the observed Era-Reanalysis data sets obtained from ECMWF. Also, the model is able to capture the mean monsoon circulation features. This model may be used for a few of the BIMSTEC regions for climate study applications.

Basin modelling, constrained by geochemical data from eight wells, was carried out, across the late Cretaceous and Early Palaeogene sediment packages of south-eastern Nigeria sedimentary basins. The study was aimed at establishing the sediment burial history, thermal maturation of the source rock and timing of hydrocarbon generation. The Late Cenomanian to Early Turonian Lokpanta Shale, which is the basal unit of the Eze-Aku Formation in the Eze-Aku Group, consists of alternating dark grey to black shales, marl and siltstones. The upper sections are mainly alternating sandstones, shales and limestones. This unit is the key petroleum source rock for the basin. Numerical 1D basin model of the study area revealed that the Cenomanian to Turonian times was the main phase of rifting in the Benue Trough evidenced by rapid subsidence. Subsidence rates varied widely in all the wells studied, ranging from 29–61 m/Mya (million years ago) and averaging 44 m/Mya. Subsidence rates also varied widely through geological time from the Cretaceous to the Palaeogene. The Cenomanian–Turonian and the Maastrichtian ages recorded the highest subsidence rates (169.75 and 168.28 m/Mya, respectively). These phases of rapid subsidence correspond to the main phase of rifting (Cenomanian–Turonian) and periods of increased sediment supply (Campanian and Maastrichtian), due to rapid erosion and unroofing of the structurally inverted Benue Trough, post-Santonian. Vitrinite reflectance values (1.87–4.78% Ro) indicated that the Lokpanta source rock (Late Cenomanian–Early Turonian) is mature to overmature. The vitrinite maturation profiles and the geochemical data suggested the generation of hydrocarbon before the Santonian compressional uplift of the Abakaliki–Benue Trough with its resultant sediment folding, which displaced the depo-centre from the Abakaliki Basin to the Anambra and Afikpo platforms. The subsequent erosion and non-deposition in the Abakaliki Basin raised the Lokpanta Shale above the oil generative window. The renewed sedimentation in the Campanian resulted in sagging due to sediment load creating the Anambra Basin. The lack of an effective trapping mechanism in the pre-Santonian may imply that hydrocarbon generated before the uplift migrated away, probably to upper and/or lower horizons (observed as oil shows in the region); some of which may be contributing to the Niger Delta crude. This is evidenced by the correlation of the Niger Delta deep sea samples to the Cretaceous (Lokpanta Shale) source rock and occurrence of biomarkers of Cretaceous origin (ab-hopanes and oleananes in the Opuama Channel complex, northern depobelt, Niger Delta).

Pan coefficients have been developed for the Sukhna lake region in Chandigarh, India that has a humid tropical monsoon climate, using the optimisation technique for annual, monthly and seasonal time scales. Evaporation estimated using the Bowen ratio energy budget method has been considered as actual evaporation. Results show that the pan coefficient for the study area varies significantly both by month and season. The month-wise variation is in the range of 0.72–1.40 and the seasonal variation is in the range of 0.81–1.16. Pan coefficients obtained using various existing models such as Cuenca, Snyder, Modified Snyder, Pereira, Orang, FAO-56 and Wahed–Snyder have also been compared with the developed coefficients. Comparative analysis indicates that the pan coefficients obtained using the Snyder model overestimate evaporation significantly, while the rest of the models significantly underestimate evaporation. The study concludes that the developed pan coefficients are observed to estimate the open-water surface evaporation with a fair degree of accuracy for the study area while the pan coefficient value of 0.7 being used by most field organisations in India give high errors. However, since pan coefficients vary spatially due to the variation in the relative significance of various meteorological parameters, the pan coefficients developed in the present study need to be further evaluated for their suitability to other similar climatic regions of India.

The sorption of uranium onto mullite influenced by pH, initial adsorbate concentration, sorption dose and reaction duration was probed utilising batch techniques. X-ray powder diffraction was used to characterise mullite. Sorption isotherms, sorption kinetics and thermodynamic characteristics were also investigated. The Freundlich isotherm model could best depict experimental data, suggesting that the sorption mechanism of uranium onto mullite may be multi-layer adsorption. The E value obtained from the Dubinin–Radushkevich model implied that uranium sorption onto mullite is a chemical process. The pseudo-second-order model successfully depicted uranium sorption onto mullite, indicating that the sorption rate is mainly controlled by chemical sorption. The thermodynamic parameters computed showed that entropy and enthalpy under the trial conditions were positive and that values of ${\Delta}G$$^{\Theta}$ were negative. Thermodynamics illustrated that the sorption process was endothermic and spontaneous. The results achieved in this study are intended to further a deeper comprehension of uranium migration in silicate minerals.

Variability of an ocean biological response induced by tropical cyclones and the factors responsible for the differential response is relatively unexplored in the Indian ocean. The aim of the current study is to analyse and identify the difference in the amplitude of chlorophyll blooms induced by tropical cyclones during the period of 1999–2016. The relationship of the amplitude of chlorophyll blooms to the cyclone characteristics (cyclone intensity and translation speed) and the oceanographic parameters (mixed layer depth and nutricline depth) is assessed. Analysis of chlorophyll blooms induced by 28 cyclones during the study period indicated that the amplitude of the chlorophyll concentration varies irrespective of the intensity of the cyclones. The results suggest that the translation speed exhibited by the cyclone is the key factor which controls the amplitude of blooms. The slower translation speed of the cyclone enhances the bloom intensity. Another factor which controls the bloom amplitude is the pre-existing shallow mixed layer depth. A shallow mixed layer modulates the light and nutrient availability which is essential in increasing the chlorophyll concentration. It is observed that shallower nutricline depth also favours an increase in the post-cyclone chlorophyll concentration. In-situ chlorophyll observations from Bio-Argo float during cyclones Hudhud and Vardah revealed that with its slower translation speed and shallower mixed layer depth, cyclone Hudhud could induce stronger bloom than cyclone Vardah, though the intensities of both the cyclones are the same at the location of float. This study implies that relatively weaker tropical cyclones can also induce strong chlorophyll blooms under favourable conditions and not all stronger cyclones induce blooms in the Indian Ocean.

The natural system of the drainage basin is interrupted by sub-surface faults and active tectonic processes. The anomalous nature of the drainage network and its basic morphological characteristics produce significant geomorphometric anomalies of the drainage basins which are an indicator of seismotectonic activity. In recent years, the increasing frequency of earthquakes and the subsequent damage in the Indian sub-continent necessitates a study of the seismotectonic significance with special reference to morphometric analysis. Hence, the present research is focused on studying the geomorphometric anomalies at a micro basin level and their impact on seismotectonic activity using geoinformatics. The study area is the lower Tista sub-basin which belongs to the Himalayan mountain in the northern part, whereas the southern part represents a peneplain surface. The quantitative databases of various morphometric parameters have been generated using digital elevation model data and satellite images to identify the geomorphic anomalies at the micro basin level which have been compared with past seismological databases to understand the impact on seismotectonic activity. The result shows that the drainage bifurcation, anomalous drainage network, drainage compression along the mountain front, narrow steep valleys in the high resistance surface, neotectonic deformation and the asymmetric valley shape are probable geomorphometric anomalies which coincide with past seismic activity in the study region. The present study also shows that the tectonic tilt, compressed meanders in the uplifted surface and the linear valley in the alluvial surface are also equivalently significant for past earthquake occurrences in the foothill zone. It is also observed that the elongated and linear micro basins and the presence of a strike–slip fault with major lineaments in the Quaternary surface are great indicators of geomorphometric anomalies which have no resemblance with any significant earthquake in the past and are equally important signatures of seismotectonic activity. The study concludes that the geomorphometric anomaly is an important parameter of seismotectonic activity which can be used for studying seismic hazards in the future.

We are facing the water shortage crisis. To realise sustainable development, we should improve water-use efficiency (WUE). In this study, a cloud–compound fuzzy matter element–entropy combined model was constructed to evaluate WUE. The Huai river basin (HRB) was selected as the study area. The cloud model was used to select some indices and build the comprehensive evaluation index system (CEIS), which included the overall, agricultural, industrial, domestic and environmental categories. The compound fuzzy matter element model was used to calculate the comprehensive indicators of WUE of the HRB and its regions. The weight of each index in the CEIS was determined using the entropy model. The results showed that WUE of the HRB had an upward trend on the whole because of the enhanced emphasis on water resources by the international and national governments. However, the regional difference was obvious. The WUE of Henan province was higher than that of Jiangsu province. The imbalance of regional WUE is an international problem. By analysing the difference among regions, research can provide a reference for the decision making of the water resources management department.

The impacts of elevation, terrain slope and vegetation cover on lightning activity are investigated for contrasting environments in the north-east (NE) (21–29$^{\circ}$N; 86–94$^{\circ}$E) and the north-west (NW) (28–36$^{\circ}$N; 70–78$^{\circ}$E) regions of the Himalayan range. Lightning activity is more at a higher terrain slope/elevation in the dry NW region where vegetation cover is less, whereas it is more at a lower terrain slope/elevation in the moist NE region where vegetation cover is more. In the wet NE, 86% (84%) of the annual lightning flash rate density (LFRD) occurs at an elevation < 500 m (terrain slope < 2%) and then sharply falls off at a higher elevation (terrain slope). However, only 49% (47%) of LFRD occurs at an elevation of < 500 m (terrain slope < 2%) and then rather gradually falls off at a higher elevation (terrain slope) in the dry NW. The ratio of the percentages of LFRD and elevation points is much higher in the NW than in the NE above an elevation of ${\sim}$1000 m. The impacts of terrain slope and elevation in enhancing the lightning activity are stronger in the dry NW than in the moist NE. The correlation coefficient of the LFRD with the normalised difference vegetation index is higher in the NW than in the NE on both the regional and annual scales. Results are discussed as a caution in using any single climate variable as a proxy for projecting a change in the lightning–climate relationships in the scenario of global warming.

This study investigates the attenuation of the seismic Rayleigh waves propagating in an elastic crustal layer of the Earth over its viscoelastic mantle. The exact equations of motion of the theory of linear viscoelasticity are used and the complex dispersion equation is obtained for an arbitrary type of hereditary operator of the viscoelastic materials. The viscoelasticity of the materials is described by the fractional-exponential operators of Rabotnov, and a solution algorithm is developed to obtain numerical results for the attenuation of the considered waves. Attenuation curves are obtained and discussed, and in particular, the influence of the rheological parameters of the materials on this attenuation is studied. It is established that a decrease in the creep time of the viscoelastic materials leads to an increase in the attenuation coefficient.

This study examines skill of the Monsoon Mission Climate Forecasting System (MMCFS) model simulations of monthly and seasonal maximum, minimum and mean temperatures of hot weather season (April, May and June) for the period 1982–2008 over India. The hindcast skill at the sub-division and all India scales were computed. The hindcasts were prepared using initial conditions (ICs) pertaining to January, February and March. The bias-corrected forecast for the 2016 AMJ season was also verified with the high resolution gridded temperature data of the India Meteorological Department (IMD). Standard verification skill scores, namely correlation coefficient (CC) and root mean square error (RMSE) have been used to assess the hindcast skill at various lead times. The grid point level statistical bias-correction was successful in reducing the bias and RMSE of the MMCFS model hindcast at the sub-division and all India scales. The hindcast analysis showed that for all the considered ICs and during all the months (April, May and June) and AMJ season for maximum, minimum and mean temperature bias of four sub-divisions Jammu & Kashmir (J&K), Himachal Pradesh, Uttarakhand, and Arunachal Pradesh showed bias ${\leq} {-}$2.0$^{\circ}$C and four sub-divisions Saurashtra and Kutch, Bihar, Gangetic West Bengal, Sub-Himalayan West Bengal (SHWB) and Sikkim showed bias ${\geq}$2$^{\circ}$C. Hindcast based on the February and March ICs showed the best skill both in sub-division scale as well as in all India scale. Similarly, among the three months of the AMJ season, model skills based on considered ICs were best for the April month. Many of the sub-divisions from northwest India and neighboring central India and along the west coast showed significant hindcast skill for simulations based on February and March ICs. For the all India averaged temperature, March IC based forecast showed the highest skill for all the months and AMJ season followed by February IC. The MMCFS model forecasts for the 2016 monthly and seasonal temperatures were able to indicate correct signs of the observed temperature anomalies in most of the sub-divisions. The pattern anomaly correlations for the May and June forecasts based on March IC were significant at ${\geq}$ 95% level.

Snow water equivalent (SWE) is important for understanding the hydrological significance of glaciers. In this study, the spatial and temporal variability in SWE and its impact over the Vestre Broggerbreen and Feiringbreen glaciers around Ny-Alesund in Svalbard (high Arctic) were investigated in the early snow season for the period 2012–2017. The physical properties like depth and density were measured directly in the field and spatial characteristics curvature, slope and aspect were extracted from the digital elevation model. The Vestre Broggerbreen (4.1 km$^{2}$) is a NE flowing glacier, situated around 3 km SW to Ny-Alesund village while the Feiringbreen (7.5 km$^{2}$) is a SW flowing glacier, situated around 14 km NE across the Kongsfjorden. The SWE for the studied period (2012–2017) varied from 141 to 1188 mm. The significant (R$^{2}$ = 0.97) correlation indicated a possible control of snow depth over SWE compared to altitude (R$^{2}$ = 0.65) and other spatial characteristics. The glaciers have experienced negative balance and lost a significant amount of ice ($\sim$4 m.w.e.) since 2012. The observations suggest that the increased liquid precipitation and temperature in the early snow season have reduced SWE over both these valley glaciers. The reduced SWE has also contributed to decreases in the mass balance of these glaciers.

The capability of the regional climate model RegCM4.5 to simulate land surface climate in dense vegetation areas is improved by changing the empirical parameter $\alpha$ in the canopy interception coefficient in the Community Land Model, version 4.5 (CLM4.5). It is found that $\alpha$ is a very important and sensitive parameter. After increasing the value of $\alpha$, the simulation biases of latent and sensible heat flux in the wet season as well as the evaporation of intercepted water from the vegetation canopy ($E_{\rm{c}}$) and vegetation transpiration ($E_{\rm{t}}$) are significantly reduced. In addition, the simulated 2 m air temperature and surface run-off in the wet season are improved obviously. However, surface soil moisture and temperature are not sensitive to the change of $\alpha$. When regional climate simulation is conducted by RegCM4.5, the value of $\alpha$ can be increased to 0.5 if the annual average sum of the leaf area index and the stem area index is more than 2.5, which could enhance the capability of the model, to a certain extent, to simulate the land surface climate.

Crystalline aquifers are present in most parts of southern India with limited resources of groundwater. The groundwater storage map in the Maheshwaram watershed has been estimated from the product of specific yield (Sy) and saturate aquifer thickness as a system being an unconfined weathered–fractured combined aquifer. Land-use data has been used for the estimation of groundwater abstraction at a spatial scale. Storage and scarcity mapping demonstrate that the watershed is clearly vulnerable to drought in some areas because of significant pumping. Therefore, the result shows that on average, the availability of groundwater storage corresponds to 1.5 yr of the present groundwater abstraction rate with successive low monsoons (i.e., insignificant recharge). Additionally, 13% of the area shows no storage at present, 28% of the area has less than 1 yr, 40% area has less than 2 yr and 12% area has less than 3% of storage. Very few cells can sustain for more than 3 yr. Additionally, the Sy of the aquifer ranges from 0.2% to 5% with a mean value of 1.8%. A geo-statistical technique has been applied for the estimation of Sy at unknown cells where either the cell was dry or no pumping occurred. This estimated two-dimensional Sy value can also be used in classical groundwater numerical modelling for a better understanding of groundwater resource management.

Transients in GPS time series can occur due to post-seismic deformation, seasonal hydrological loads, sea-level changes, flood and drought conditions, excessive groundwater withdrawal and recharge, etc. We report two new cases where the application of external loading, namely, earthquake loading and surface loading due to impoundment of hydroelectric reservoir, probably altered the local hydrological conditions to cause anomalous transients in the surface displacement. In the first case, moderate shaking due to the 2015 Gorkha earthquake at Patna (Bihar, India) caused transients in ground deformation in the following 50–60 days of the earthquake which are recorded by a continuous GPS site at Patna. In the second case, impoundment of the Tehri reservoir and its seasonal variations in the Garhwal Himalaya probably altered the local hydrological conditions which is causing anomalous biannual cyclic deformation at a site KUNR, near the reservoir.

The Greenland ice sheet (GrIS) is one of the drivers of global sea level rise and plays a crucial role in understanding the global climate changes. Here, we have estimated and analysed the decadal (between 2013–2016 and 2003–2005) and annual (2014–2015, 2015–2016) volume discharge of ice from the entire GrIS. The 40 Hz Geophysical Data Record product of the unique Ka band (AltiKa) radar altimeter were utilised to derive the elevation, elevation changes and volume changes over the GrIS. To test the first-level accuracy of the result, AltiKa and NASA’s ice, cloud and land elevation satellite digital elevation model (ICESat DEM)-derived elevation were compared, which yielded a correlation value of 0.95. Thereafter, decadal volume changes obtained over the entire GrIS, from the differencing of the AltiKa and ICESat DEM elevation revealed a decreasing rate of 247 km$^{3}$/year. Moreover, basin-wise analysis indicated the maximum decrease in elevation of basin located in the north and north-west region of GrIS. Annual changes obtained by differencing the AltiKa cycle of the same month (so that the surface condition will remain same) between the two consecutive years, specifically during 2014–2015 and 2015–2016 over the entire GrIS contributed volume loss of 187 and 210 km$^{3}$, respectively, indicating an enhanced decrease for a later period.

The present study focuses on the chemical modification of a Cr-spinel from the Suru Valley ophiolitic peridotites exposed near Trespone Village of Kargil district, Ladakh Himalaya. The Suru Valley peridotite is partially serpentinised with the preservation of the spinel and relics of olivine and pyroxene. These peridotites contain characteristic red-brown spinel grains of corroded grain boundaries. While analysing these grains for mineral chemistry, compositional variation was observed with Cr-rich cores rimmed by Cr-poor compositions. Secondary spinel compositions, i.e., ferritchromite and magnetite were observed along the margins and cracks of primary Cr-spinel grains. The primary Cr-spinel cores are identified as Cr-rich and are characterised by higher values of Cr$^{3+}$# (0.5–0.6) and lower values of Al$^{3+}$# (0.42–0.54). From primary spinel cores to altered rims it was observed that Cr$^{3+}$# and Fe$^{3+}$# increase while Mg$^{2+}$# decreases due to Mg$^{2+}$–Fe$^{2+}$ and Al$^{3+}$–Fe$^{3+}$ exchange with surrounding silicates of host peridotite during alteration. On the basis of present spinel mineral chemistry, metamorphic alteration conditions were transitional between greenschist and lower amphibolite similar to most of the Neo-Tethyan ophiolite peridotites.

In the alpine ecosystem of the Himalaya, an observation of species diversity with habitat heterogeneity predicts some important factors that govern them. Information theory-based species biodiversity at the community level and habitat heterogeneity at the landscape level were studied. Resourcesat-2 linear imaging self-scanning sensor (LISS-III and LISS-IV)-based spectral diversity indices and species diversity indices of four summits with increasing elevation gradients were estimated. The species richness decreased with an increase in elevation. The southern aspect of the sub-alpine zone has the highest biodiversity having a 3.5 Shannon’ entropy (H). Despite receiving higher insolation, the increase in elevation leading to coldness and dominance of a few species make the southern aspects less diverse at the higher elevation. Both elevational gradients and microclimatic conditions define biodiversity in the Himalaya. Resolution from coarser (LISS-III) to finer (LISS-IV) to micro (field) scale showed an increasing range of values, H = 0.1, 0.2 and 2.1, respectively. There is significantly less correlation between field and satellite measured biodiversity indices (r, −0.5 to 0.3). To go closer to the field level of biodiversity assessment, there is a need to use satellite data having a higher spatial resolution. Spectral variation hypothesis does not hold good in the alpine ecosystem of the Himalaya.

Mafic granulites from key localities of the Eastern Ghats Province preserve Fe–Ti oxides, Cu–Fe sulphides and traces of sulphate minerals along with silicate phases. Two different varieties of mafic granulite exhibit slightly contrasting mineral assemblages. While the massive type of mafic granulite contains minerals assemblage orthopyroxene $+$ clinopyroxene $+$ plagioclase $+$ magnetite $+$ ilmenite $+$ pyrite $+$ pyrrhotite, the migmatitic variety contains garnet as an additional phase. Both oxide and sulphide minerals show contrasting textural characters. Textural analysis and construed mineral reactions imply that the variation of oxide–silicate, oxide–sulphide and sulphate relations is linked to variation of $f$O$_{2}$ during the pre-peak, peak and post-peak stages of metamorphism. The calculated $f$O$_{2}$ values range up to +4 log units relative to the QFM (quartz-fayalite-magnetite) buffer among the samples, except for one sample which shows lower values ($−$10 log units relative to the FMQ (fayalite-magnetite-quartz) buffer). The consistently high $f$O$_{2}$ condition at the lower crust could result from several factors, but the role of the externally derived fluid appears to be plausible. Hot brine solution with CaCl$_{2}$ species can explain the oxidation as well as local metasomatism of the mafic lower crust even though its presence is not verified from direct characterisation like fluid inclusion analysis.

Independent component analysis (ICA) is a blind source signal separation method which can effectively estimate high-order information and thus can effectively extract the common mode errors (CMEs) of a regional global navigation satellite system (GNSS) observation network. In this paper, ICA is used for the weighted filtering (WICA) and the extraction of CMEs of a regional GNSS observation network with the root mean square error (RMSE) of daily solution taken as the weighting factor. Through an analysis of the observed data from 19 valid stations of the Crustal Movement Observation Network of China (CMONOC) in North China, it is shown that the coordinate series precision of 13, 16 and 12 stations in the N, E and U directions, respectively, after filtering by WICA is higher than that by the traditional ICA method. The average correlation coefficient of the coordinate time series for each station after filtering is obviously decreased. Two simulation experiments are designed to extract known CMEs. It is shown that CMEs can be recovered better by WICA and that the standard deviations of most stations after filtering are smaller than those by ICA. The results from the real data and simulation experiments suggest that the RMSE of coordinate series be considered in spatio-temporal filtering.

The Deccan trap basaltic lava flows host a plethora of secondary minerals, notably zeolites, quartz and calcite. These minerals occupy the vesicles and cavities that are formed during the solidification of the lava flows. Much attention has been given to beautifully developed zeolites of the Deccan traps and well-crystallised quartz varieties such as rosy quartz and amethyst. However, a group of minerals consisting of cryptocrystalline and amorphous silica did not receive much attention despite their consistent occurrence in all parts of the Deccan large igneous province. The freshly exposed samples of the chalcedonic silica occurring in the vesicular basalt at the Laxminarayan Institute of Technology (LIT) hill, Nagpur University Campus, were studied, one of which was studied in detail using X-ray diffraction analysis, differential thermal analysis, thermogravimetric analysis, Fourier transform infrared and scanning electron microscope–energy dispersive spectroscopy. The present study has demonstrated that the secondary silica occupying vesicles in the basaltic lava flows was length-fast chalcedony showing fibrous morphology overprinted by grainy morphology. It was concluded that the mother fluid was a hot ($\sim$100–300$^{\circ}$C) aqueous solution, which was acidic in nature and high in sulphur, probably derived from the host Deccan trap basaltic magma itself.

The present study examines the effect of Diwali festival (17–21 October 2017; 19th October was the Diwali day) on aerosol characteristics over Patiala, northwestern part of India. Diwali being one of the major festivals of India that falls between mid-October and mid-November is celebrated with full enthusiasm by burning crackers, fireworks, etc. During this period, the study site also is engulfed with high aerosol loading because of extensive paddy residue burning emission. During Diwali event, a particulate matter (PM$_{10}$) concentration varies from 132 to 155 ${\mu}$g m$^{-3}$, while a mass concentration of black carbon aerosols varies from 6 to 9 ${\mu}$g m$^{-3}$ with the maximum concentration on post-Diwali day. Aerosol optical depth (AOD$_{500}$) was maximum (0.852) on post-Diwali day indicating the additional loading of submicron particles due to burning of crackers and fireworks. The magnitude of single scattering albedo (SSA$_{500}$) decreases to a minimum value around 0.864 showing abundance of absorbing aerosols on Diwali affected days (19th and 20th October). A sudden jump of +12.9 W m$^{-2}$ in atmospheric radiative forcing resulting in a heating rate of up to 1.4 K day$^{-1}$ on next day of Diwali shows the warming state of the lower and middle atmosphere.

Trends in tropical cyclone (TC) genesis and landfall over the Bay of Bengal (BOB) were analysed to identify global warming and climate change impacts. The historical TC data for the period 1901–2015 available through the cyclone eAtlas from India Meteorological Department were used. The analysis was confined to the 3-month period from October to December when the maximum number of TCs occurs over the BOB. Analysis was conducted for the two 50-yr periods of 1901–1950 and 1961–2010 and the four 30-yr periods of 1921–1950, 1961–1990, 1971–2000 and 1981–2010 to ascertain the differences and tendencies in the genesis and landfall points during the current global warming era since the 1960s and the previous years. The results indicate an increase of TC genesis over the south-east and central BOB and decrease over the south central region. Furthermore, an increased vulnerability of the Bangladesh coastline to TC landfall was detected. In addition, TC systems had decreased in number but increased in intensity. These results confirm the general reports of TC trends over the BOB as of other ocean basins in the post-industrialisation global warming era.

Groundwater flow modelling provides the water flow dynamics for the estimation and prediction of groundwater movement and its condition in the aquifer. The modelling helps for the management of the groundwater resources under various hydrological and anthropogenic stresses. In this paper, a modelling exercise was performed using the analytic element method (AEM) and finite difference method (FDM) for the part of Ganga river basin which includes the Varanasi district. Further compression was performed to understand the limitations and benefits of both AEM and FDM based on ease of model development, data requirement and their performances. The groundwater model was developed for the transient state condition based on data for the year 2004–2017. The results show that for most of the observed wells, the difference between the observed head and the simulated head is found in the 90% confidence level. It is found that the AEM does not require a fixed boundary condition which makes the development of the conceptual model less complicated. In the FDM, pumping wells are approximately located and averaged over the cell which becomes a cause of the inaccurate location of the wells. It is found that model development in the AEM is less complicated compared to the FDM. It can be concluded that in some cases AEM-based modelling is more accurate as compared to FDM-based flow modelling. This study can be very helpful for groundwater professionals in deciding the best suitable method for their study area and to avoid the complexity of the model.

Drifting buoys (DBs) are widely deployed to observe near-surface ocean currents and sea surface temperature. The National Institute of Ocean Technology (NIOT), Chennai, India, had indigenised the DB with the Indian satellite (INSAT) in 2012. This paper describes the results of various studies conducted by NIOT using the indigenised DBs and also describes unique features attempted in indigenised DBs to measure the near-surface ocean current with 24 position acquisitions per day to capture small-scale surface eddies and the use of real-time geostationary satellite communication every hour. Additionally, the surface currents observed with indigenous DB are compared with DBs available in the market, Marlin-Yug (coefficient of determination $R^{2}$ > 0.88) and forecast using the ocean surface current analyses real-time (coefficient of determination $R^{2}$ > 0.90). Our results show that the DBs in the Bay of Bengal are carried with the East India Coastal Current in the March–May periods and the in-situ observations by the DB provide accurate surface current observations than satellite-based data. Furthermore, the new observations near the world’s largest tidal mangrove and delta system, the Sundarbans and Bengal Delta, will help in further enhancing our understanding of the spatiotemporal variability in the region in terms of coastal currents and its influence on marine environments.

This paper describes the direct assimilation of water vapour (WV) clear sky brightness temperatures (CSBTs) from the INSAT-3D imager in the National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model (NCUM) assimilation and forecast system. INSAT-3D imager WV CSBTs show a systematic bias of 2–3 K compared to the data simulated from the model first guess fields in the pre-assimilation study. The bias in the INSAT-3D imager WV CSBTs is removed using a statistical bias correction prior to assimilation. The impact of INSAT-3D imager WV channel CSBTs is investigated through different approaches: (i) single observation experiments and (ii) global assimilation experiments using the hybrid-four-dimensional variational technique. Single observation experiments of channels of the same frequency from different instruments like the INSAT-3D imager and sounder, and the Meteosat visible and infrared imager (MVIRI) onboard Meteosat-7, show the INSAT-3D imager and MVIRI WV channels have a similar impact on the analysis increment. Global assimilation clearly shows the positive impact of the INSAT-3D imager WV CSBTs on the humidity and upper tropospheric wind fields, whereas the impact on the temperature field, particularly over the tropics, is neutral. Validation of model forecasted parameters with the in situ radio sonde observations also showed the positive impact of assimilation on the humidity and wind fields. INSAT-3D imager WV CSBTs have been assimilated operationally in NCUM since August 2018.

The NW–SE trending grabens of Sers–Siliana, located in the Central Tunisian Atlas, show a peculiarity, compared to adjacent grabens, which comes from the existence of an early Miocene sedimentary gap. This paper discusses the structural evolution of these grabens, during the Neogene–Quaternary episode, which have been poorly studied in previous studies. To better understand the chronology of the two grabens, a set of direct and indirect pieces of evidence are given in order. The results show that the collapse is of Aquitanian–Tortonian age which is synchronous with the regional collapse of the Alpine chain foreland grabens. In addition, our field observations show that the E-trending faults affect the incompetent materials (marls) and assured the mechanical junction between these two grabens. The chronology of tectonic events, during the Neogene–Quaternary time, in the Sers–Siliana area coincides with that described at the regional scale for the Tunisian Atlas domain, allowing a better understanding of the role played by the convergence between African and Eurasian plates.

The estimation of accurate reservoir parameters is essential for conventional and non-conventional hydrocarbon prospects. An artificial neural network has been developed to predict the reservoir parameters (porosity and saturation of gas hydrates) in a silty-sand, sandy-silt and pelagic-poor clay reservoir at two neighbour wells using the petrophysical information at another well in the Krishna–Godavari basin. The well log data were acquired during the Expedition-02 of Indian National Gas Hydrates Program (NGHP Exp-02). The estimation of gas hydrate saturation using Archie’s equation may be erroneous, as it is valid for the quantification of conventional hydrocarbons in the clean sand reservoir. Since the study area is clay dominated, it is subjective to adjust Archie’s exponents so that it matches with the saturation, measured from the core data. To overcome this problem of estimating the reservoir parameters in such a scenario, first of all we have derived porosity from the density log data and estimated saturation by employing modified Archie’s equation to the resistivity log data at one well. In order to train the network, the log data at one well are taken as inputs and corresponding porosity and saturation are taken as outputs. The reservoir parameters are then predicted at two neighbour wells using the wireline log data as input in those two wells. The predicted porosity and saturation of gas hydrates are alike to the traditionally estimated porosity and saturation at the neighbour wells. The predicted porosity in the studied region varies between 33 and 76%, whereas the saturation of gas hydrates ranges between 3.39 and 86.92%. This shows that the designed network can be used to estimate the reservoir parameters directly from the well log data in the same reservoirs.

Rapid identification of inrush water sources is vital for the safe operation of a coal mine. Hydrogeochemical (fuzzy comprehensive evaluation method and cluster analysis method) and isotope analyses are applied to identify the inrush water sources of the Mindong No. 1 mine, which is located in north-east Inner Mongolia, China. The clustering analysis and isotope analysis results show that the inrush water sources are from aquifer 1 (A1), aquifer 2 (A2) and Yimin river. However, fuzzy comprehensive evaluation shows that the inrush water sources are from A2, aquifer 3 (A3) and Yimin river. Considering the hydrogeological conditions of the study area, it is concluded that the inrush water sources are A1, A2 and Yimin river, with mixing ratios of 30.8%, 60.6% and 8.6%, respectively. The application of multiple methods makes the conclusion more reliable. Additionally, this study improves the speed and effectiveness of the identification of inrush water sources in coal mines and provides a practical reference for research related to mine water inrush to ensure the safe operation of coal mines.