Thermal effect on the pulses of the rotating Sun

In this paper, a theoretical investigation is undertaken of the group travel-time for the Sun's pulses to travel from the source of the pulse to the solar surface. For mathematical simplicity, we consider a simple ionized model of the Sun that includes the thermal effect and rotation with uniform angular velocity. The expression for the group travel time gives two terms: the term arising from the linear theory which varies inversely to (2-)^1/2 and the term introduced by the thermal effect which is inversely proportional to (2-)^7/2. The thermal effect variation has been shown and an estimation of the temperature of the medium has been made. Furthermore, the velocity distribution and the amplitude of the magnetic field of the wave, arising from the damping of ionized particles, have been calculated.     

A multiwavelength view of a classical T Tauri star CV Cha

Using long-term optical, ultraviolet(UV) and X-ray data, we present a study of a classical T Tauri star CV Cha. The V-band light curve obtained from the All Sky Automated Survey(ASAS) shows short as well as long-term variability. The short-term variability could be due to rotational modulation of CV Cha. We derive the rotational period of 3.714 ± 0.001 d for CV Cha. UV light curves obtained from Swift also show the variations. X-ray light curves from XMM-Newton and Swift do not show any significant short as well as long-term variability. However, the light curve from Chandra appears to be variable, which could be due to the emergence of flaring activities. X-ray spectra from all observations are explained well by the single temperature plasma of 0.95 keV with X-ray luminosity of 1030.4erg s-1in the 0.5–7.5 keV energy band. It appears that variability in optical and UV bands could be due to the presence of both hot and cool spots on the surface, while X-ray emission is dominated by magnetic processes.     

On the Differential Rotation of Stars

We discussmethods for analyzing the observational manifestations of differential rotation (DR). Based on the literary sources and our estimates (for 4 cool dwarfs), a list containing 75 stars was compiled. Using an example of analysis of the ‘ΔΩ–T_eff’, ‘ΔΩ–rotation period’ and ‘ΔΩ–Rossby number’ diagrams we compared the determined parameters of DR stars with the results of theoretical studies. Particular attention is paid to the problems of measurements of DR parameters in low-mass dwarf stars, including the completely convective ones.We analyzed the measured parameters of solar-type DR stars. The objects having anti-solar DR (α < 0), and possiblemethods allowing to determine the sign of α are considered.We distinguish the areas of research that in the future may expand our understanding of DR manifestations: a study of DR in the inner regions of stars and an analysis of manifestations of the rotational brightness modulation caused by the spottedness of components in eclipsing-variable systems (subsynchronized systems).     

Numerical simulation of physical and dynamical characteristics associated with the severe thunderstorm on April 5, 2015 at Kushtia and Jhenaidah

The paper deals with the study of the physical and dynamical characteristics of a severe thunderstorm, which had occurred on April 5, 2015, at about 2100 UTC in the southwestern Bangladesh with location around 23.3–23.7N and 89.0–89.4E within the upazilas (sub-districts) of Kumarkhali and Shailkupa under the districts of Kushtia and Jhenaidah, respectively. The thunderstorm was associated with numerous hails of large size. More than 5000 birds which used to live in the bird sanctuary at Shailkupa and 22,011 birds in Chhaglapara Bird Sanctuary of Kumarkhali died as they were hit by the hails. Large hails also damaged crops, houses and forests over the thunderstorm hit areas. The evolution of the thunderstorm is studied by the WRF model, which is initialized using the National Centers for Environmental Prediction Final reanalysis data of 0000 UTC of April 5, 2015. The simulated results provide a basis to study the physical and dynamical characteristics of the thunderstorm, which are generally not identified by the meteorological observations which are too sparse. The model has captured a micro-low over Kumarkhali and its neighborhood, which favored the occurrence of the severe thunderstorm. The model simulated rainfall is about 26 mm near the place of occurrence, which matches well with the area where the reflectivity of hydrometeor is maximum. The convective available potential energy is found to be 1600 J kg^?1 at 1730 UTC near the place of occurrence of the thunderstorm; this indicates high atmospheric instability over the thunderstorm location for the formation of the thunderstorm. The vertical velocity, convergence, cloud water mixing ratio and the ice water mixing ratio and their vertical extensions are found to be satisfactory and responsible for the occurrence of large hails associated with the thunderstorm.     

Mapping of rock types using a joint approach by combining the multivariate statistics,self-organizing map and Bayesian neural networks: an example from IODP 323 site

Modeling and classification of the subsurface lithology is very important to understand the evolution of the earth system. However, precise classification and mapping of lithology using a single framework are difficult due to the complexity and the nonlinearity of the problem driven by limited core sample information. Here, we implement a joint approach by combining the unsupervised and the supervised methods in a single framework for better classification and mapping of rock types. In the unsupervised method, we use the principal component analysis (PCA), K-means cluster analysis (K-means), dendrogram analysis, Fuzzy C-means (FCM) cluster analysis and self-organizing map (SOM). In the supervised method, we use the Bayesian neural networks (BNN) optimized by the Hybrid Monte Carlo (HMC) (BNN-HMC) and the scaled conjugate gradient (SCG) (BNN-SCG) techniques. We use P-wave velocity, density, neutron porosity, resistivity and gamma ray logs of the well U1343E of the Integrated Ocean Drilling Program (IODP) Expedition 323 in the Bering Sea slope region. While the SOM algorithm allows us to visualize the clustering results in spatial domain, the combined classification schemes (supervised and unsupervised) uncover the different patterns of lithology such of as clayey-silt, diatom-silt and silty-clay from an un-cored section of the drilled hole. In addition, the BNN approach is capable of estimating uncertainty in the predictive modeling of three types of rocks over the entire lithology section at site U1343. Alternate succession of clayey-silt, diatom-silt and silty-clay may be representative of crustal inhomogeneity in general and thus could be a basis for detail study related to the productivity of methane gas in the oceans worldwide. Moreover, at the 530 m depth down below seafloor (DSF), the transition from Pliocene to Pleistocene could be linked to lithological alternation between the clayey-silt and the diatom-silt. The present results could provide the basis for the detailed study to get deeper insight into the Bering Sea’ sediment deposition and sequence.     

Identification of flood seasonality and drivers across Canada

Floods are the most frequently occurring natural hazard in Canada. An in-depth understanding of flood seasonality and its drivers at a national scale is essential. Here, a circular, statistics-based approach is implemented to understand the seasonality of annual-maximum floods (streamflow) and to identify their responsible drivers across Canada. Nearly 80% and 70% of flood events were found to occur during spring and summer in eastern and western watersheds across Canada, respectively. Flooding in the eastern and western watersheds was primarily driven by snowmelt and extreme precipitation, respectively. This observation suggests that increases in temperature have led to early spring snowmelt-induced floods throughout eastern Canada. Our results indicate that precipitation (snowmelt) variability can exert large controls on the magnitude of flood peaks in western (eastern) watersheds in Canada. Further, the nonstationarity of flood peaks is modelled to account for impact of the dynamic behaviour of the identified flood drivers on extreme-flood magnitude by using a cluster of 74 generalized additive models for location scale and shape models, which can capture both the linear and nonlinear characteristics of flood-peak changes and can model its dependence on external covariates. Using nonstationary frequency analysis, we find that increasing precipitation and snowmelt magnitudes directly resulted in a significant increase in 50-year streamflow. Our results highlight an east–west asymmetry in flood seasonality, indicating the existence of a climate signal in flood observations. The understating of flood seasonality and flood responses under the dynamic characteristics of precipitation and snowmelt extremes may facilitate the predictability of such events, which can aid in predicting and managing their impacts.     

Large-scale dynamics have greater role than thermodynamics in driving precipitation extremes over India

Climate Dynamics - The changing characteristics of precipitation extremes under global warming have recently received tremendous attention, yet the mechanisms are still insufficiently understood....