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Kumar, V.

Snow Depth Estimation in the Indian Himalaya Using Multi-Channel Passive Microwave Radiometer

Abstract Views :241 | PDF Views:110

Authors

K. K. Singh ¹, A. Kumar ², A. V. Kulkarni ³, P. Datt ¹, S. K. Dewali ¹, V. Kumar ¹, R. Chauhan ¹

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 National Institute of Technology, Kurukshetra 136 119, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Source

Current Science, Vol 108, No 5 (2015), Pagination: 942-953

Abstract

Snow depth is an important parameter for avalanche forecast and hydrological studies. In the Himalaya, manual snow depth data collection is difficult due to remote and rugged terrain and the severe weather conditions. However, microwave-based sensors in various satellites have the capability to estimate snow depth in all weather conditions. In the present study, experiments were performed to establish an algorithm for snow depth estimation using ground-based passive microwave radiometer with 6.9, 18.7 and 37 GHz antenna frequencies at Dhundhi and Patseo, Himachal Pradesh, India. Different layers in the snowpack were identified and layer properties, i.e. thickness, density, moisture content, etc. were measured manually and using a snow fork. Brightness temperature (T_B) of the entire snowpack and of the individual snow layers was measured using passive microwave radiometer. It was observed that T_B of the snow is affected by various snow properties such as depth, density, physical temperature and wetness. A decrease in T_B with increase in snow depth was observed for all types of snow. T_B of the snowpack was observed higher at Dhundhi in comparison to Patseo. Based on the measured radiometer data, snow depth algorithms were developed for the Greater Himalaya and Pir-Panjal ranges. These algorithms were validated with ground measurements for snow depth at different observatory locations and a good agreement between the two was observed (absolute error: 7 to 39 cm; correlation: 0.95).

Keywords

Brightness Temperature, Microwave Radiometer, Snow Depth Algorithm, Snowpack.

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Macropore Flow as a Groundwater Component in Hydrologic Simulation:Modelling, Applications and Results

Abstract Views :202 | PDF Views:79

Authors

M. Ranjit Kumar ¹, T. Meenambal ¹, V. Kumar ²

Affiliations
1 Department of Civil Engineering, GCT, Coimbatore 641 013, IN
2 Department of Agricultural Engineering, AC&RI, Madurai 625 104, IN

Source

Current Science, Vol 112, No 06 (2017), Pagination: 1197-1207

Abstract

Macropore flow carries water from the soil surface to deeper profile or groundwater, bypassing the intermediate soil profile. The phenomenon is ubiquitous and not rare. A theoretical framework of this flow has not been perfected so far, but ignoring this process may lead to incomplete conceptualization of soil-water flow. The macropore flow has been modelled based on observed data on morphometry, macropore size distribution and fractal dimensions of soil voids and stain patterns, and incorporated in the Watershed Processes Simulation (WAPROS) model. The performance of WAPROS model was evaluated to be good (NSE - hourly; daily = 0.8578; 0.9020), when applied to a real watershed. The sensitivity of macropore flow submodel showed that the adjustment factor was linearly related to macropore flow. Simulations were performed for five types of soil, namely sandy loam, sandy clay loam, sandy clay, clay loam and silty clay loam (A, B, C, D and E respectively). The values of macroporosity factors and fractal dimensions generated for the five types of soil have been presented. The model generated data for A, B, C, D and E soil types were: the number of macropores: 379, 3074, 3412, 153 and 0; the macropore flow (mm): 1.5121, 9.3667, 15.1728, 4.4055 and 0; the average pore flow (mm/pore): 0.0040, 0.0030, 0.0044, 0.0287 and 0; and the macropore flow to base flow ratio: 0.0055, 0.0474, 0.1908, 0.2759 and 0. The modelling methodology gives encouraging results. The model can be updated as and when better equations are made available.

Keywords

Groundwater, Hydrologic Simulation, Macropore Flow Model, Sensitivity, Soil Types.

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Detection of Solar Cycle Signal in the Tropospheric Temperature using COSMIC Data

Abstract Views :227 | PDF Views:73

Authors

V. Kumar ¹, S. K. Dhaka ¹, V. Panwar ¹, Narendra Singh ², A. S. Rao ³, Shristy Malik ³, S. Yoden ⁴

Affiliations
1 Radio and Atmospheric Physics Lab, Rajdhani College, University of Delhi, Delhi 110 015, IN
2 Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital 263 002, IN
3 Department of Applied Physics, Delhi Technical University, Delhi 110 042, IN
4 Department of Geophysics, Kyoto University, Kyoto 606850, IN

Source

Current Science, Vol 115, No 12 (2018), Pagination: 2232-2239

Abstract

Influence of the solar cycle on temperature structure is examined using radio occultation measurements by COSMIC/FORMASAT-3 satellite. Observations from January 2007 to December 2015 comprising 3,764,728 occultations, which are uniformly spread over land and sea, have been used to study temperature changes mainly in the troposphere along with the solar cycle over 60°N–60°S geographic latitudes. It was a challenging task to identify the height at which the solar cycle signal could be observed in temperature perturbations as different atmospheric processes contribute towards temperature variability. Using a high spatial resolution dataset from COSMIC we are able to detect solar cycle signal in the zonal mean temperature profiles near surface at 2 km and upward. A consistent rise in the interannual variation of temperature was observed along with the solar cycle. The change in the temperature structure showed a latitudinal variation from southern to northern hemisphere over the period 2007–2015 with a significant positive influence of sunspot numbers in the solar cycle. It can be concluded that the solar cycle induces changes in temperature by as much as 1.5°C. However, solar cycle signal in the stratospheric region could not be identified as the region is dominated by large-scale dynamical motions like quasi-biennial oscillation which suppress the influence of solar signal on temperature perturbations due to its quasi-periodic nature.

Keywords

Radio Occultation, Solar Cycle, Sunspot Number, Tropospheric Temperature.

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Commissioning of the MACE gamma-ray telescope at Hanle, Ladakh, India

Abstract Views :192 | PDF Views:73

Authors

K. K. Yadav ¹, N. Chouhan ², R. Thubstan ², S. Norlha ², J. Hariharan ², C. Borwankar ², P. Chandra ², V. K. Dhar ¹, N. Mankuzhyil ², S. Godambe ², M. Sharma ², K. Venugopal ², K. K. Singh ¹, N. Bhatt ², S. Bhattacharyya ¹, K. Chanchalani ², M. P. Das ², B. Ghosal ², S. Godiyal ², M. Khurana ², S. V. Kotwal ², M. K. Koul ², N. Kumar ², C. P. Kushwaha ², K. Nand ², A. Pathania ², S. Sahayanathan ¹, D. Sarkar ², A. Tolamati ², R. Koul ³, R. C. Rannot ⁴, A. K. Tickoo ⁵, V. R. Chitnis ⁶, A. Behere ⁷, S. Padmini ⁷, A. Manna ⁷, S. Joy ⁷, P. M. Nair ⁷, K. P. Jha ⁷, S. Moitra ⁷, S. Neema ⁷, S. Srivastava ⁷, M. Punna ⁷, S. Mohanan ⁷, S. S. Sikder ⁷, A. Jain ⁷, S. Banerjee ⁷, Krati ⁷, J. Deshpande ⁷, V. Sanadhya ⁸, G. Andrew ⁸, M. B. Patil ⁸, V. K. Goyal ⁸, N. Gupta ⁸, H. Balakrishna ⁸, A. Agrawal ⁸, S. P. Srivastava ⁹, K. N. Karn ⁹, P. I. Hadgali ⁹, S. Bhatt ⁹, V. K. Mishra ⁹, P. K. Biswas ⁹, R. K Gupta ⁹, A. Kumar ⁹, S. G. Thul ⁹, R. Kalmady ¹⁰, D. D. Sonvane ¹⁰, V. Kumar ¹⁰, U. K. Gaur ¹⁰, J. Chattopadhyay ¹¹, S. K. Gupta ¹¹, A. R. Kiran ¹¹, Y. Parulekar ¹¹, M. K. Agrawal ¹¹, R. M. Parmar ¹¹, G. R. Reddy ¹², Y. S. Mayya ¹³, C. K. Pithawa ¹⁴

Affiliations
1 Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India; Homi Bhabha National Institute, Mumbai 400 085, India, IN
2 Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
3 Formerly at Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
4 Raja Ramanna Fellow at Astrophysical Sciences Division, Mumbai 400 085, India, IN
5 Deceased, IN
6 Department of High Energy Physics, Tata Institute of Fundamental Research, Mumbai 400 005, India, IN
7 Electronics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
8 Control and Instrumentation Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
9 Center for Design and Manufacture, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
10 Computer Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
11 Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
12 Formerly at Reactor Safety Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
13 Formerly at Reactor Control Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN
14 Formerly at Electronics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India, IN

Source

Current Science, Vol 123, No 12 (2022), Pagination: 1428-1435

Abstract

The MACE telescope has recently been commissioned at Hanle, Ladakh, India. It had its first light in April 2021 with a successful detection of very high energy gamma-ray photons from the standard candle Crab Nebula. Equipped with a large light collector of 21 m diameter and situated at an altitude of ~4.3 km amsl, the MACE telescope is expected to explore the mysteries of the non-thermal Universe in the energy range above 20 GeV with very high sensitivity. It can also play an important role in carrying out multi-messenger astronomy in India.

Keywords

Gamma-ray astronomy, high energy radiative processes, non-thermal Universe, telescope.

Full Text

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Study of Sea Surface Salinity Due to River Fluxes Using the CMIP6 Models for the Bay of Bengal Region

Abstract Views :92 | PDF Views:59

Authors

V. Kumar ¹, A. P. Joshi ¹, H. V. Warrior ¹

Affiliations
1 Department of Ocean Engineering and Naval Architecture, Indian Institute of Technology, Kharagpur 721 302, India., IN

Source

Current Science, Vol 124, No 11 (2023), Pagination: 1290-1299

Abstract

The large influx of freshwater and mixing of different water masses make simulating salinity challenging for the Bay of Bengal (BoB) region. This study analyses the variability of the simulated sea surface salinity (SSS) using models present in the Coupled Modal Intercomparison Project Phase 6 (CMIP6). We collected data for 37 models from CMIP6 and validated them against the Argo (2005–14) and Aquarius (2011–14) data. Based on the skill scores, we narrowed down our search to one CMIP6 model, viz. CIESM. This model was used to study the freshwater spread (FWS) in BoB during different seasons. We found that the correlation between pH and FWS was appreciable. The CIESM model was then used to project the future trends for 10 years for the tier-1 scenario. The trend analysis of future projections revealed a positive trend in SSP1-2.6, with a decreasing trend in SSP2-4.5 and SSP5-8.5.

Keywords

Climate Models, Freshwater Spread, River Fluxes, Skill Score, Trend Analysis.

Full Text

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