Wed, Apr 02, 2025

CSIR Fourth Paradigm Institute

(Formerly CSIR Centre for Mathematical Modelling and Computer Simulation)

A constituent laboratory of Council of Scientific & Industrial Research (CSIR).

Ministry of Science and Technology, Government of India.

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Modelling for science, for a better future - some recent outcomes

by Sampad Kumar Panda, Siva Sai Kumar Rajana, Chiranjeevi G. Vivek, Jyothi Ravi Kiran Kumar Dabbakuti, Wangshimenla Jamir and Punyawi Jamjareegulgarn

In this study, we explored the occurrence of near-sunrise equatorial plasma bubbles (EPBs) and inhibition of dusk-time EPBs during the geomagnetic storm (SYM-Hmin= −139 nT) of 19–20 April 2024 using multi-instrument observations over the Indian and Southeast Asian longitude sectors. The initial phase of this storm commenced around 0530 UT on 19 April 2024 and did not manifest any visible alterations in the ionospheric electric fields during the main phase of the storm, which corresponded to a period between post-sunset to midnight over the study region. However, during the recovery phase of the storm, the IMF Bz suddenly flipped northward and was associated with an overshielding of the penetrating electric fields, which triggered the formation of near-sunrise EPBs. Interestingly, the persistence of EPBs was also noticed for more than three hours after the sunrise terminator. Initially, sunrise EPBs were developed in the Southeast Asian region and later drifted toward the Indian longitude region, along with the sunrise terminator. Moreover, this study suggested that the occurrence of EPBs was suppressed due to the altered storm time electric fields at the dip equatorial region across the 70–90°E longitude sector in the recovery period. This study highlighted that even moderate geomagnetic storms can generate near-sunrise EPBs in a broader longitude sector due to penetrating electric fields in overshielding conditions, which can significantly affect trans-ionospheric signals.

Source: https://doi.org/10.3390/rs17061100

 

by Dhananjay A. Sant, Gunjankumar K. Makwana, Prabhin Sukumaran, Imtiyaz A. Parvez, Govindan Rangarajan and K. Krishnan

We propose a rapid and cost-effective Horizontal-to-Vertical Spectral Ratio (HVSR) method that uses microtremors (ambient noise) for mapping intercalated sedimentary sequences with lateral heterogeneity for a depth of about 100 m in Lower reaches of Narmada Valley, western India. The elastic parameters for various units/layers at a given site (1D) were derived theoretically based on HVSR inversion, built on the concepts of Diffuse Field Assumption and retrieval of the imaginary part of Green's function. This approach enables efficient forward calculation, delves into the relationship between the HVSR curve and elastic parameters, and accelerates the inversion process. A site-specific priori knowledge gathered during the field visits is further integrated. We successfully derive overall shear wave velocity and density models inferring three sedimentary Units and associated Subunits. The key highlight of this study is successfully distinguishing low-velocity sedimentary Units/Subunits within a sedimentary sequence.

Source: https://doi.org/10.1016/j.soildyn.2025.109235

 

by Sridevi Jade & T. S. Shrungeshwara 

The 2500 km Himalayan arc spanning Kashmir, Ladakh, in the west to Eastern syntaxis in the east is a tectonically complex and seismically active northern subduction boundary of the Indian plate. Three decades of GPS data give well-constrained surface convergence rates ranging from 10 to 26 mm/yr in the various segments of the Himalayas (Kashmir, Ladakh, Himachal, Garhwal, Kumaun, Nepal, Sikkim, Bhutan, Arunachal and Eastern syntaxis). Arc parallel rates of 3–10 mm/yr is the manifestation of locked curvature of the central Himalayan arc and the E–W extension rate of Tibet. Inverse modelling of surface convergence rates is used to estimate oblique slip rate of 13–20 mm/yr along Main Himalayan Thrust (MHT) at a depth of 15–20 km and locking width of 100–150 km from the frontal Himalayas suggesting that each segment of the Himalaya is unique in nature. Geodetic strain rates derived from the GPS-derived surface convergence rates suggest that the Himalayan region is predominantly under compression with high strain rate coinciding with the northern boundary of sub surface basal decollement (MHT) along which Indian plate subducts below Tibet. Seismic strain rates for each segment of the Himalaya are computed using the instrumental and historical earthquake catalogue. Seismic potential of each segment of the Himalaya is estimated by a combined analysis of geodetic and seismic strain rates and the corresponding moment rates. Further, strain budget and accumulated slip since the last devastating earthquake was used to estimate the recurrence interval and probable magnitude of impending earthquake in the Himalayan segments.

Source: https://doi.org/10.1007/978-981-97-7658-0_3 

More Articles ...

  1. Relative Impact of Assimilation of Multi-Source Observations using 3D-Var on Simulation of Extreme Rainfall Events over Karnataka, India
  2. The curious case of a strong relationship between ENSO and Indian summer monsoon in CFSv2 model
  3. Outer-arc active tectonic deformation off the Nias – Nicobar Trench: Insights from lithospheric stress and seismic slip models
  4. A comprehensive study of atmospheric dynamics associated with cloudburst events in 2022 over Indian Himalayan Region
  5. Morphology of Equatorial F-region Irregularities over the Indian Longitude sector using GPS-derived ROTI Observations
  6. Assessment of long-term spatio-temporal variability of hot extremes and associated physical mechanism over India
  7. Homogeneity Adjustment of Surface Temperature Data and Study of the Climate Variability Over Coastal Odisha by a Climate Departure Index
  8. Assessment of Country-Specific GHG Emissions from Road Transport Sector in India
  9. Decoding low-frequency climate variations: A case study on ENSO and ocean surface warming
  10. Intensity duration and frequency of Heat wave in different phases of MJO over India

Vision: 

To synergize the Transdisciplinary Pan-CSIR expertise and build a unified platform that embodies a rich set of big data enabling technologies and services with optimized performance to facilitate data intensive scientific discovery in the country.

Mission:

To Pioneer data driven interdisciplinary research in diverse fields through state-of-the-art data science ecosystem and impactful industrial partnerships for the betterment of Society.

Mandate: 

To develop cutting edge data science products as a horizontal across the CSIR Themes and position as an Institute of Excellence in Bigdata and Artificial Intelligence.

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