ALBERT

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉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 〈span〉 〈span〉\({\le }{-}2.0^{\circ }\hbox {C}\)〈/span〉 〈/span〉 and four sub-divisions Saurashtra and Kutch, Bihar, Gangetic West Bengal, Sub-Himalayan West Bengal (SHWB) and Sikkim showed bias 〈span〉 〈span〉\({\ge }2^{\circ }\hbox {C}\)〈/span〉 〈/span〉. 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 〈span〉 〈span〉\(\ge \)〈/span〉 〈/span〉95% level.〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉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.〈/p〉

Beschreibung: 〈p〉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.〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉The impacts of elevation, terrain slope and vegetation cover on lightning activity are investigated for contrasting environments in the north-east (NE) (21–〈span〉 〈span〉\(29{^{\circ }}\hbox {N}\)〈/span〉 〈/span〉; 86–〈span〉 〈span〉\(94{^{\circ }}\hbox {E}\)〈/span〉 〈/span〉) and the north-west (NW) (28–〈span〉 〈span〉\(36{^{\circ }}\hbox {N}\)〈/span〉 〈/span〉; 70–〈span〉 〈span〉\(78{^{\circ }}\hbox {E}\)〈/span〉 〈/span〉) 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 〈span〉 〈span〉\({〈} 500\ \hbox {m}\)〈/span〉 〈/span〉 (terrain slope 〈span〉 〈span〉\({〈} 2\%\)〈/span〉 〈/span〉) and then sharply falls off at a higher elevation (terrain slope). However, only 49% (47%) of LFRD occurs at an elevation of 〈span〉 〈span〉\({〈} 500\ \hbox {m}\)〈/span〉 〈/span〉 (terrain slope 〈span〉 〈span〉\({〈} 2\%\)〈/span〉 〈/span〉) 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 〈span〉 〈span〉\({\sim } 1000\ \hbox {m}\)〈/span〉 〈/span〉. 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.〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉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).〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉Monitoring of tropical cyclones (TCs) using the Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie (SAPHIR) sounder on-board the Megha-Tropiques satellite is attempted on a qualitative basis. The sounder with a high resolution of 10 km at nadir, combined with its high temporal observation ability, 4–6 times a day, and with six channels at 183.31 ± 11.0 GHz, is used for tracking the cyclones. The study has been performed by applying SAPHIR brightness temperature datasets to the cyclonic regions. In this study, 25 TCs from 2011 to 2018 in the Arabian Sea and the Bay of Bengal over the North Indian Ocean have been observed. A comparison of six channels of SAPHIR shows the clear variations of the eye of the cyclone under various conditions. Furthermore, the positional variations obtained by multiple linear regression models are used to observe the evolution of the cyclone storm from its genesis to dissipation/landfall for all the 25 cyclones. The location accuracy is found to be 0.2–0.3〈span〉 〈span〉\(^{\circ }\)〈/span〉 〈/span〉, as observed from the SAPHIR dataset that agrees reasonably well with the India Meteorological Department dataset and Advanced Microwave Sounding Unit sounder dataset in cyclone tracking. This study attempts at using the unique features of high temporal resolution, good spatial resolution and more channels and is expected to complement other methods of cyclone tracking.〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉Physical characterisation of 〈span〉 〈span〉\(\hbox {PM}_{2.5}\)〈/span〉 〈/span〉, 〈span〉 〈span〉\(\hbox {PM}_{10}\)〈/span〉 〈/span〉 and surface ozone measured during the period from 17 July to 21 August 2012 at four strategic locations in and around the Lumbini Protected Zone, Nepal, is done to assess air quality of the region and understand qualitatively source mechanisms of these pollutants. The measurement locations are Panditarama Lumbini International Vipassana Meditation Centre, Parsahawa, Bhairahawa and Tilaurakot, representing monastic, industrial, urban and control areas, respectively. The overall average concentration of 〈span〉 〈span〉\(\hbox {PM}_{2.5}\)〈/span〉 〈/span〉 at these locations is 〈span〉 〈span〉\({\sim }19\pm 12\)〈/span〉 〈/span〉, 〈span〉 〈span〉\(35\pm 13\)〈/span〉 〈/span〉, 〈span〉 〈span〉\(35\pm 11\)〈/span〉 〈/span〉 and 〈span〉 〈span〉\(25\pm 6~ \upmu \hbox {g/m}^{3}\)〈/span〉 〈/span〉 and of 〈span〉 〈span〉\(\hbox {PM}_{10}\)〈/span〉 〈/span〉 is 〈span〉 〈span〉\({\sim }25\pm 11\)〈/span〉 〈/span〉, 〈span〉 〈span〉\(103\pm 41\)〈/span〉 〈/span〉, 〈span〉 〈span〉\(58\pm 15\)〈/span〉 〈/span〉 and 〈span〉 〈span〉\(32\pm 7~ \upmu \hbox {g/m}^{3}\)〈/span〉 〈/span〉, respectively. 〈span〉 〈span〉\(\hbox {PM}_{2.5}\)〈/span〉 〈/span〉 never crosses the safe limit of the National Ambient Air Quality Standards of Nepal (NNAAQS) in the monastic and control areas but either crosses the NNAAQS occasionally or remains in its vicinity at the other two locations. The 〈span〉 〈span〉\(\hbox {PM}_{10}\)〈/span〉 〈/span〉 concentration frequently exceeds the safe limit in the industrial area but not in the other remaining areas. The analysis indicates the dominance of the impact of local sources and boundary layer thickness on the atmospheric loadings of the particulate matter. The daily average mixing ratio of surface ozone remains normally low at all the four observational sites although the mixing ratio of ozone at Panditarama Lumbini International Vipassana Meditation Centre is much lower than the NNAAQS but higher than that observed at Tilaurakot.〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉The present study shows spatio-temporal variability in carbon dioxide 〈span〉 〈span〉\((\hbox {CO}_{2})\)〈/span〉 〈/span〉 in the mid-tropospheric region over India (0–32〈span〉 〈span〉\(^{\mathrm{o}}\hbox {N}\)〈/span〉 〈/span〉, 60–100〈span〉 〈span〉\(^{\mathrm{o}}\hbox {E}\)〈/span〉 〈/span〉) during 2003–2011. The 〈span〉 〈span〉\(\hbox {CO}_{2}\)〈/span〉 〈/span〉 data used in the study is retrieved from Atmospheric Infra-Red Sounder (AIRS). Analysis of 9 yrs of data shows that the 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 exhibits a linear increasing trend of 2.01 ppm/year. Besides displaying the linear increasing trend, data show strong seasonal and annual variability. Concentration of 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 is observed to be highest around April–May (summer months), which decreases by 4–5 ppm during the monsoon months. Seasonal decrease in 〈span〉 〈span〉\(\hbox {CO}_{2}\)〈/span〉 〈/span〉 concentration appeared to be influenced by the monsoonal activity. Low OLR (proxy of convection) associated with high rainfall during summer monsoon via increasing vegetation index (NDVI) appears to be the primary cause for the seasonal decrease in 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 through photosynthesis. Correlation coefficient between 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 and NDVI is of the order of –0.90 suggesting vegetation as a seasonal sink of 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉. Decrease in 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 concentration takes place at a delay of 2–3 months of rainfall. However, convection seems to be another component, which causes uplifting of 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 during dry summer (April and May) making high concentration in the mid-troposphere as shown by increase in the planetary boundary layer (PBL) height in this period. Eastward propagating intra-seasonal oscillations with period 30–40 days in OLR anomalies are found to modulate (with a fluctuation of 1–2 ppm) mid-tropospheric 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉. Analysis of seasonal anomalies in 〈span〉 〈span〉\(\hbox {CO}_{{2}}\)〈/span〉 〈/span〉 over four different regions (northern, southern, western and eastern) of India is also being investigated. The regional variability of 〈span〉 〈span〉\(\hbox {CO}_{2}\)〈/span〉 〈/span〉 in northern region show marginal larger values suggesting more anthropogenic activities especially during late winter.〈/p〉

Beschreibung: 〈h3〉Abstract〈/h3〉 〈p〉Flood-plain wetlands are the seasonal water bodies formed along a river. These wetlands become active during the monsoon season, which frequently grow in size with seasonal floods and eventually dry up during the non-monsoon season. The flow interaction between flood-plain wetlands and the river sometimes vary over a very short period in response to rapid rise in the river water level due to high precipitation in its upstream catchment. Understanding the complex flow interactions between the river and its associated flood-plain wetlands with field-based measurements of wetland hydrologic characteristics is always a challenging task. To overcome these challenges, an attempt has been made to utilise Topex/Poseidon satellite altimetry-derived water levels into a hydrodynamic model (HEC-RAS) to study river and wetland flow interactions in the lower reach of the Kosi river in India. The satellite altimetry-derived water levels and Landsat satellite images on the Kosi wetlands are used to develop volume-elevation relation. HEC-RAS is setup over the study area and calibrated for different values of manning’s roughness coefficient (〈em〉n〈/em〉) for the river bank and the main channel of the river for the period of 1993–1996. Unsteady flow simulations are carried out for different monsoon seasons to simulate daily river flow interaction (inflow/outflow) between river and wetlands. Statistical analysis is performed between the altimetry-derived and the model-simulated water levels. It is found that simulated water levels are in good agreement (〈span〉 〈span〉\(R^{2}=0.87\)〈/span〉 〈/span〉, root mean square error of 0.84 m and Nash–Sutcliffe efficiency coefficient of 0.85) with altimetry-derived water levels. The analysis of simulations indicates that interactions between the wetland and the river are bidirectional with most of the flow coming out from the river during the month of August and leaving out from the wetlands during the month of September. The wetlands respond in three different ways, i.e., (i) gaining stage, (ii) wetland and river in equilibrium and (iii) loosing stage, which is reflected on water levels of the river and wetland. This study demonstrates complex interaction processes happening between the Kosi river and its surrounding wetlands.〈/p〉

Beschreibung: 〈p〉The prime objective of this study is to find the suitable petrophysical parameters which depict the maximum change in seismic amplitude due to fluid substitution. Therefore, in the present study the petrophysical parameters are analysed to detect the most sensitive parameters due to fluid substitution. The analysis is performed in three steps: In the first step, the Gassmann fluid substitution is performed and a considerable change in velocity, density, impedance, lambda–mu–rho parameters and Shuey’s parameters is examined. The study shows that the most sensitive parameters are 〈em〉A〈/em〉 (intercept), which shows the maximum drop of 22% with respect to CO〈sub〉2〈/sub〉 injection, and 〈em〉B〈/em〉 (gradient), which shows the maximum increase of 10% with CO〈sub〉2〈/sub〉 injection in the formation. Thereafter, in the second step, the seismic forward modelling is performed to examine the changes in seismic amplitude by the fluid substitution in the formation. The analysis depicts that the seismic amplitude increases steadily with increasing CO〈sub〉2〈/sub〉 saturation. The amplitude increases by 4% at 20% CO〈sub〉2〈/sub〉 injection, by 8% at 50% CO〈sub〉2〈/sub〉 injection and the seismic amplitude increases by 12% at 100% CO〈sub〉2〈/sub〉 injection in the target zone. Finally, in the third step, the numerical modelling is performed to assess the ability of seismic methods to detect the CO〈sub〉2〈/sub〉 plume accurately by injecting CO〈sub〉2〈/sub〉 plume of cylindrical shape. The analysis shows that the CO〈sub〉2〈/sub〉 plume can be detected more prominently by analysing the impedance volume rather than the seismic amplitude section. This study is helpful in deciding which parameters should be monitored carefully in fluid replacement modelling projects.〈/p〉