Long-Term Study of the Starspot Activity on the Eclipsing Short-Period RS Canum Venaticorum Star UV Piscium

We present optical photometry of the short period eclipsing RS CVn system, UV Piscium for the years 1966–1984. After removing the spot effects from the light curves of Vivekananda Rao and Sarma (1981), we analyzed the cleaned data to obtain system parameters. For each light curve, we model the distortion waves in order to study the behaviour of star spots in this system. This revised version was published online in July 2006 with corrections to the Cover Date.     

Performance evaluation of COSMO numerical weather prediction model in prediction of OCKHI: one of the rarest very severe cyclonic storms over the Arabian Sea—a case study

Natural Hazards - In the first week of December 2017, a very severe cyclonic storm, namely “OCKHI”, made its landfall over the western coastline of the Indian peninsula. In a...     

Characterizing and navigating small bodies with imaging data

Abstract— Recent advances in the characterization of small body surfaces with stereophotoclinometry are discussed. The principal data output is an ensemble of landmark maps (L‐maps), high‐resolution topography/albedo maps of varying resolution that tile the surface of the body. Because they can have a resolution comparable to the best images, and can be located on a global reference frame to high accuracy, L‐maps provide a significant improvement in discriminatory power for studies of small bodies, ranging from regolith processes to interior structure. These techniques are now being used to map larger bodies such as the Moon and Mercury. L‐maps are combined to produce a standard global topography model (GTM) with about 1.57 million vectors and having a wide variety of applications. They can also be combined to produce high‐resolution topography maps that describe local areas with much greater detail than the GTM. When combined with nominal predictions from other data sources and available data from other instruments such as LIDAR or RADAR, solutions for the spacecraft position and camera pointing are the most accurate available. Examples are drawn from studies of Phobos, Eros, and Itokawa, including surface characterization, gravity analysis, spacecraft navigation, and incorporation of LIDAR or RADAR data. This work has important implications for potential future missions such as Deep Interior and the level of navigation and science that can be achieved.     

On the structure of sea-breeze fronts observed near the coastline of Thumba,India

An investigation has been made of the structure of sea-breeze fronts observed at Thumba mostly during the months of December to April using data from a Doppler SODAR and in situ measurements of wind components, humidity and temperature. The study shows that the vertical wind structure observed in the SODAR height range provides a distinct signature of the passage of a front and that the intensity of the front is decided by the intensity and direction of the prevailing winds as well as the amount of rotation of the wind vector during the onset of the sea-breeze. Spectral analyses of vertical winds during the passage of the front reveal a dominant periodicity of about 6 min for strong sea-breeze fronts.     

Estimating surface sensible heat flux using sodar and surface temperature measurements in the evolving convective boundary layer

A simple method is described for estimating the sensible heat flux by using a Doppler sodar system and a thermal probe. This method, which can be applied to a convective boundary layer in morning hours, is based on knowing the zero heat flux level from the reflectivity and the vertical wind speed.     

Accretion flow dynamics during 1999 outburst of XTE J1859+226—modeling of broadband spectra and constraining the source mass

We examine the dynamical behavior of accretion flow around XTE J1859+226 during the 1999 outburst by analyzing the entire outburst data (～166 days) from RXTE Satellite. Towards this, we study the hysteresis behavior in the hardness intensity diagram (HID) based on the broadband (3–150 keV) spectral modeling, spectral signature of jet ejection and the evolution of Quasi-periodic Oscillation (QPO) frequencies using the two-component advective flow model around a black hole. We compute the flow parameters, namely Keplerian accretion rate (\({\dot{m}}_{d}\)), sub-Keplerian accretion rate (\({\dot{m}}_{h}\)), shock location (\(r_{s}\)) and black hole mass (\(M_{\mathit{bh}}\)) from the spectral modeling and study their evolution along the q-diagram. Subsequently, the kinetic jet power is computed as \(L^{\mathrm{obs}}_{\mathrm{jet}} \sim3\mbox{--}6 \times10^{37}~\mbox{erg}\,\mbox{s}^{-1}\) during one of the observed radio flares which indicates that jet power corresponds to 8–16% mass outflow rate from the disc. This estimate of mass outflow rate is in close agreement with the change in total accretion rate (～14%) required for spectral modeling before and during the flare. Finally, we provide a mass estimate of the source XTE J1859+226 based on the spectral modeling that lies in the range of 5.2–7.9 \(M_{\odot}\) with 90% confidence.     

Predictive modelling of the spatial pattern of past and future forest cover changes in India

This study was carried out to simulate the forest cover changes in India using Land Change Modeler. Classified multi-temporal long-term forest cover data was used to generate the forest covers of 1880 and 2025. The spatial data were overlaid with variables such as the proximity to roads, settlements, water bodies, elevation and slope to determine the relationship between forest cover change and explanatory variables. The predicted forest cover in 1880 indicates an area of 10,42,008 km², which represents 31.7% of the geographical area of India. About 40% of the forest cover in India was lost during the time interval of 1880–2013. Ownership of majority of forest lands by non-governmental agencies and large scale shifting cultivation are responsible for higher deforestation rates in the Northeastern states. The six states of the Northeast (Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura) and one union territory (Andaman & Nicobar Islands) had shown an annual gross rate of deforestation of >0.3 from 2005 to 2013 and has been considered in the present study for the prediction of future forest cover in 2025. The modelling results predicted widespread deforestation in Northeast India and in Andaman & Nicobar Islands and hence is likely to affect the remaining forests significantly before 2025. The multi-layer perceptron neural network has predicted the forest cover for the period of 1880 and 2025 with a Kappa statistic of >0.70. The model predicted a further decrease of 2305 km² of forest area in the Northeast and Andaman & Nicobar Islands by 2025. The majority of the protected areas are successful in the protection of the forest cover in the Northeast due to management practices, with the exception of Manas, Sonai-Rupai, Nameri and Marat Longri. The predicted forest cover scenario for the year 2025 would provide useful inputs for effective resource management and help in biodiversity conservation and for mitigating climate change.