Equilibrium structure of differentially rotating polytropic models of the stars

In this paper we propose a method for computing the equilibrium structure of differentially rotating polytropic models of the stars. A general law of differential rotation of the type ²=b ₀+b ₁ s ²+b ₂ s ⁴, which can account for a reasonably large variety of possible differential rotations in the stars has been used. The distortional effects have been incorporated in the structure equations up to second order of smallness in distortion parametersb ₀,b ₁, andb ₂ using Kippenhahn and Thomas' averaging approach in conjunction with Kopal's results on Roche equipotentials in manner similar to the one earlier used by Mohan and Saxena for computing the equilibrium structure of polytropes having solid body rotation. Numerical results have been obtained for various types of differentially rotating polytropic models of stars of polytropic indices 1.5, 3, and 4. Certain differentially rotating models of the Sun which are possible with such a type of law of differential rotation, have also been computed.     

Hydromagnetic cylindrical shock in self-gravitating gas

Chisnell-Chester-Whitham method has been used to study the propagation of diverging hydromagnetic cylindrical shock through an infinitely electrically conducting self-gravitating gas having an initial density distribution ₀= r^-w where is the density at the axis of symmetry andw is a constant, simultaneously for the two cases, viz.: (i) when the shock is weak and (ii) when it is strong. The magnetic field is taken to be axial and initially of constant strength. Analytical relations for shock velocity and shock strength have been obtained. the expressions for the pressure, the density and the particle velocity immediately behind the shock have also been derived.     

Effect of cavitation on spherical blast waves

For spherical blast waves propagating through a self-gravitating gas with an energy inputE =E ₀ t , whereE is the energy released up to timet,E ₀ is a functional constant, and is a constant, kinetic, internal heat, and gravitational potential energies have been computed. Taking the parameterA ², which characterises the gravitational field, equal to 2, variations of the percentages of these energies for =0, 1/2, 4/3, and 3 with shock strength have been presented. For =3, the effect of cavitation on the percentages of kinetic energy and internal heat energies has been explored.     

An agile very low frequency radio spectrum explorer

The very low frequency(VLF) regime below 30 MHz in the electromagnetic spectrum has presently been drawing global attention in radio astronomical research due to its potentially significant science outcomes exploring many unknown extragalactic sources,transients,and so on.However,the nontransparency of the Earth's ionosphere,ionospheric distortion and artificial radio frequency interference(RFI) have made it difficult to detect the VLF celestial radio emission with ground-based instruments.A straightforward solution to overcome these problems is a space-based VLF radio telescope,just like the VLF radio instruments onboard the Chang'E-4 spacecraft.But building such a space telescope would be inevitably costly and technically challenging.The alternative approach would be then a ground-based VLF radio telescope.Particularly,in the period of post 2020 when the solar and terrestrial ionospheric activities are expected to be in a 'calm' state,it will provide us a good chance to perform VLF ground-based radio observations.Anticipating such an opportunity,we built an agile VLF radio spectrum explorer co-located with the currently operational Mingantu Spectra Radio Heliograph(MUSER).The instrument includes four antennas operating in the VLF frequency range 1-70 MHz.Along with them,we employ an eight-channel analog and digital receivers to amplify,digitize and process the radio signals received by the antennas.We present in the paper this VLF radio spectrum explorer and the instrument will be useful for celestial studies of VLF radio emissions.     

Characterizing atmospheric surface layer turbulence using chaotic return map analysis

Nonlinear time series analysis methods are used to investigate the dynamics of mechanical and convective turbulences in the atmospheric surface layer flow. Using dynamical invariant analysis (e.g. correlation dimension, Lyapunov exponent and mutual information) along with recurrence quantification analysis (e.g. recurrent rate, determinism, average diagonal length of recurrence plot, etc.) of the vertical wind component data, it is confirmed that a convective turbulence is a lower order manifold in its phase space exhibiting higher degree of organization than a mechanical turbulence. Applying a quasi-one-dimensional chaotic return map technique, the topological differences between the mechanical and convective turbulences are explored. These quasi-one-dimensional return maps are produced using the local maxima of the first principal component of the reconstructed turbulence data. A comparison of the probability distribution of the local maxima of a forced Lorenz model with the turbulence data indicates the possible existence of a stable fixed point for both type of turbulences. Furthermore, dynamically the mechanical turbulence is found to resemble an unforced Lorenz model whereas the convective turbulence resembles a forced Lorenz model.     

Wavelet-based combination approach for modeling sub-divisional rainfall in India

Agriculture in India is highly sensitive to climatic variations particularly to rainfall and temperature; therefore, any change in rainfall and temperature will influence crop yields. An understanding of the spatial and temporal distribution and changing patterns in climatic variables is important for planning and management of natural resources. Time series analysis of climate data can be a very valuable tool to investigate its variability pattern and, maybe, even to predict short- and long-term changes in the series. In this study, the sub-divisional rainfall data of India during the period 1871 to 2016 has been investigated. One of the widely used powerful nonparametric techniques namely wavelet analysis was used to decompose and de-noise the series into time–frequency component in order to study the local as well as global variation over different scales and time epochs. On the decomposed series, autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models were applied and by means of inverse wavelet transform, the prediction of rainfall for different sub-divisions was obtained. To this end, empirical comparison was carried out toward forecast performance of the approaches namely Wavelet-ANN, Wavelet-ARIMA, and ARIMA. It is reported that Wavelet-ANN and Wavelet-ARIMA approach outperforms the usual ARIMA model for forecasting of rainfall for the data under consideration.     

Investigation of the ozone and trace gases contribution to the total optical depth in the polluted urban environment of Athens

This study focuses on the determination of optical depths caused by ozone and trace gases absorption in the Chappuis band, 500–700 nm, and the contribution to the Total Minus Rayleigh Optical Depth (TMROD). The optical depths were derived using the transmission functions implemented in the SMARTS parametric model, while the Total Optical Depths (TODs) were derived by solar extinction measurements obtained in Athens during May 1995. From the data analysis it is obvious that both the ozone and trace gases contribute significantly to TMROD in the Chappuis band. More specifically, the trace gases contributions are higher for air with high pollution levels, while ozone's contribution can be significant under clear-sky conditions. Therefore, the correction in TMROD due to ozone and trace gases optical depths is necessary for an accurate determination of the Aerosol Optical Depth (AOD) in the Chappuis band. The optical depth of ozone is generally removed during the process of the AOD retrievals, since the significance of its absorption in the Chappuis band is well understood. Nevertheless, the optical depth of the trace gases (mainly NO₂) is not always taken into account in the AOD retrievals, though its contribution can be significant in urban polluted atmospheres. In this respect, the present study attempts to quantify the ozone and trace gases contributions in an urban environment and to provide some new functions that help estimate the contribution of ozone to the TMROD in the Chappuis band.     

GPS-derived precipitable water vapour and its comparison with MODIS data for Almora, Central Himalaya, India

The present study is an attempt to analyse the precipitable water vapour (PWV) derived from Global Positioning System (GPS) and observed meteorological data over Almora, Central Himalayan Region. The PWV values derived using GPS study is compared with the corresponding moderate resolution imaging spectro-radiometer (MODIS) data. The statistical analysis reveals a positive correlation between both methods. Moderate resolution imaging spectroradiometer near-infrared (MODIS NIR) clear column water vapour product shows a higher correlation (R ² = 90–93 %) with GPS-derived precipitable water vapour on annual scale as compared to the seasonal scale (R ² = 62–87 %). MODIS is found to be overestimating in NIR clear column where the magnitude of bias and RMSE show systematic changes from season to season. Monsoon is an important phenomenon in the Indian weather context and holds significant importance in Central Himalayan ecosystem. The monthly and seasonal variation in precipitable water vapour is related with monsoon onset in the region. Diurnal variations in precipitable water vapour are studied with other meteorological data over Almora during dry and wet season. The precipitable water vapour had minimum value in the morning, increases in the afternoon to evening and again decreases to the midnight in both the dry and wet seasons. These results suggest that diurnal variation of water vapour is caused by the transport of water vapour by thermally induced local circulation.     

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR.