Projection of lightning over South/South East Asia using CMIP5 models

Physical phenomena observed before strong earthquakes have been reported for centuries. Precursor signals, which include radon anomalies, electrical signals, water level changes and ground lights near the epicenter, can all be used for earthquake prediction. Anomalous negative signals observed by ground-based atmospheric electric field instruments under fair weather conditions constitute a novel earthquake prediction approach. In theory, the abnormal radiation of heat before an earthquake produces fair weather around the epicenter. To determine the near-epicenter weather conditions prior to an earthquake, 81 global earthquake events with magnitudes of 6 or above from 2008 to 2021 were collected. According to Harrison's fair weather criteria, in 81.48% of all statistical cases, the weather was fair 6 h before the earthquake; in 62.96% of all cases, the weather was fair 24 h before the event. Moreover, most of these cases without fair weather several hours before the earthquake were near the sea. Among the 37 inland earthquakes, 86.49% were preceded by 6 h of fair weather, and 70.27% were preceded by fair weather for 24 h. We conclude that the weather near the epicenter might be fair for several hours before a strong earthquake, especially for inland events.

     

Axi-symmetric Analysis of Geosynthetic-reinforced Granular Fill-soft Soil System with Group of Stone Columns

The paper presents a mechanical model to predict the behavior of geosynthetic-reinforced granular fill resting over soft soil improved with group of stone columns subjected to circular or axi-symmetric loading. The saturated soft soil has been idealized by spring-dashpot system. Pasternak shear layer and rough elastic membrane represent the granular fill and geosynthetic reinforcement layer, respectively. The stone columns are idealized by stiffer springs. The nonlinear behavior of granular fill and soft soil is considered. Consolidation of the soft soil due to inclusion of stone columns has also been included in the model. The results obtained by using the present model when compared with the reported results obtained from laboratory model tests shows very good agreement. The effectiveness of geosynthetic reinforcement to reduce the maximum and differential settlement and transfer the stress from soft soil to stone columns is highlighted. It is observed that the reduction of settlement and stress transfer process are greatly influenced by stiffness and spacing of the stone columns. It has been further observed that for both geosynthetic-reinforced and unreinforced cases, the maximum settlement does not change if the ratio between spacing and diameter of stone columns is greater than 4.     

Use of objective analysis to estimate winter temperature and precipitation at different stations over western Himalaya

Temperature and fresh snow are essential inputs in an avalanche forecasting model. Without these parameters, prediction of avalanche occurrence for a region would be very difficult. In the complex terrain of Himalaya, nonavailability of snow and meteorological data of the remote locations during snow storms in the winter is a common occurrence. In view of this persistent problem present study estimates maximum temperature, minimum temperature, ambient temperature and precipitation intensity on different regions of Indian western Himalaya by using similar parameters of the neighbouring regions. The location at which parameters are required and its neighbouring locations should all fall in the same snow climatic zone. Initial step to estimate the parameters at a location, is to shift the parameters of neighbouring regions at a reference height corresponding to the altitude of the location at which parameters are to be estimated. The parameters at this reference height are then spatially interpolated by using Barnes objective analysis. The parameters estimated on different locations are compared with the observed one and the Root Mean Square Errors (RMSE) of the observed and estimated values of the parameters are discussed for the winters of 2007–2008.     

An overview of chemical properties of marine-influenced Oligocene coal from the northeastern part of the Assam-Arakan basin, India

The Oligocene coals from the northeastern part of the Assam-Arakan basin show a gradual decrease in the content of moisture, volatile matter and oxygen with corresponding increase in carbon content and calorific value from the Foreland Shelf to the deeper part of the geosyncline, reflecting the coalification trends in this basin. It has been suggested that the oxygen was replaced by organic sulphur, thereby lowering the oxygen content in the coals. The coals are perhydrous in nature with a high sulphur content. The high volatile content, perhydrous nature and high sulphur content in the Oligocene coals, as well as the presence of streaky facies and a very fine clastics unit, indicate that they were probably deposited in a marine-influenced deltaic and lagoonal environment.The plots of carbon versus hydrogen on Seyler's coal band follow a trend which differs from that of Seyler's band of Carboniferous bright coals. The coalification of the Oligocene coals represents the lignitic stage, in the case of the Foreland Shelf, and near subbituminous stage in the deeper geosynclinal part of the basin. A more intense, and probably sudden, dynamic process was involved in bringing about higher coalification in Oligocene coal of the geosynclinal facies than in Foreland Shelf area. This is possibly due to intense mountain-building forces acting from the southeastern direction of the basin.     

On the interaction of mesoscale eddies and a tropical cyclone in the Bay of Bengal

Natural Hazards - Oceanic eddies span over a wide range of sizes and affect the thermodynamic properties of water column. By modifying the thermal structure of the upper ocean, these eddies...     

Area Change and Thickness Variation over Pensilungpa Glacier (J&;K) using Remote Sensing

Accurate representations of the Earth’s surface in the form of digital elevation models (DEMs) are essential for a variety of applications in glaciological and remote-sensing research. In the present study area change and thickness variation over Pensilungpa glacier was attempted using remote sensing approach. It can be remarked that a net loss of 9.23 sq. km. which is 38% of the glacier area mapped in 1962 indicate a drastic change over the glacier area during 1962–2007. Estimation of glacier thickness change on Pensilungpa glacier based on ASTER DEM (2003) and Survey of India (SOI) contour based DEM (1962) indicated increase in the glacier elevation in the accumulation zone mainly by 30 to 90 m and similar reduction by 30 to 90 m in the ablation zone.     

Importance Profiles for Water Vapor

Motivated by the scientific desire to align observations with quantities of physical interest, we survey how scalar importance functions depend on vertically resolved water vapor. Definitions of importance begin from familiar examples of water mass I ^m and TOA clear-sky outgoing longwave flux I ^OLR, in order to establish notation and illustrate graphically how the sensitivity profile or “kernel” depends on whether specific humidity S, relative humidity R, or ln(R) are used as measures of vapor. Then, new results on the sensitivity of convective activity I ^con to vapor (with implied knock-on effects such as weather prediction skill) are presented. In radiative-convective equilibrium, organized (line-like) convection is much more sensitive to moisture than scattered isotropic convection, but it exists in a drier mean state. The lesson for natural convection may be that organized convection is less susceptible to dryness and can survive and propagate into regions unfavorable for disorganized convection. This counterintuitive interpretive conclusion, with respect to the narrow numerical result behind it, highlights the importance of clarity about what is held constant at what values in sensitivity or susceptibility kernels. Finally, the sensitivities of observable radiance signals I ^sig for passive remote sensing are considered. While the accuracy of R in the lower free troposphere is crucial for the physical importance scalars, this layer is unfortunately the most difficult to isolate with passive remote sensing: In high emissivity channels, water vapor signals come from too high in the atmosphere (for satellites) or too low (for surface radiometers), while low emissivity channels have poor altitude discrimination and (in the case of satellites) are contaminated by surface emissions. For these reasons, active ranging (LiDAR) is the preferred observing strategy.