Fri, Dec 12, 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 Imtiyaz A. Parvez and Sanjeev Ekka

The Himalayas rank among the world’s most seismically active regions, as evidenced by major historical earthquakes, including the 1905 Kangra (Mw 7.8), 1934 Bihar–Nepal (Mw 8.2), 1950 Assam (Mw 8.4), 2005 Kashmir (Mw 7.6), and 2015 Gorkha (Mw 7.8) events. These earthquakes underscore the ongoing tectonic activity along the Himalayan arc and have caused substantial human and economic losses. Seismic hazard assessment is a critical tool for mitigating such impacts, informing preparedness efforts, risk reduction strategies, and policy formulation. Significant advancements have been made in recent decades in assessing seismic hazard and risk across the Himalayas. This article reviews key developments in probabilistic and deterministic seismic hazard studies, integrating both historical and instrumental earthquake data. Notably, peak ground accelerations (PGA) in certain Himalayan regions surpass 0.6 g, with areas near the 1897 and 1950 Assam earthquake epicenters recording extreme PGA values of 1.2–1.3 g. These zones also exhibit high ground velocities and permanent displacements, reflecting the severe ground-shaking potential of large Himalayan earthquakes. The article further explores how local geological conditions and source characteristics influence ground motion, emphasizing their role in microzonation studies. Despite progress, critical research gaps remain, particularly the need for high-resolution seismic hazard mapping across the Himalayan arc to enhance risk reduction and resilience-building efforts.

Source: https://doi.org/10.1007/s43538-025-00626-5 

 

by Payoshni Samantray & Krushna Chandra Gouda

Cloudbursts are brief, intense rainfall occurrences that present significant risks to human life, infrastructure, and ecosystems, especially in the Indian Himalayan Region (IHR). Despite their damaging characteristics, predicting these events remains challenging due to their localized nature, the influence of complex terrain, and a lack of high-resolution observational data. Therefore, enhancing the simulation and comprehension of such occurrences is crucial for improved forecasting and disaster readiness. This research introduces a high-resolution computational modeling technique utilizing the Weather Research and Forecasting (WRF) model to replicate cloudburst events in the Indian Himalayan Region (IHR) during the monsoon season of 2022. These extreme weather phenomena, marked by intense and localized rainfall, are hard to forecast because of the region's complex terrain and convective dynamics. In this study six representative cloudburst events from Himachal Pradesh, Uttarakhand, and Jammu & Kashmir were simulated at a resolution of 3 km using six-hourly NCEP-FNL reanalysis data. The analysis concentrated on critical atmospheric mechanisms such as vorticity, convective instability (CAPE, CINE), moisture availability, and orographic lifting. The model outputs were validated against daily rainfall data from the India Meteorological Department (IMD), Global Precipitation Measurement Mission (GPM), and the CPC MORPHing technique (CMORPH). The model demonstrated a strong correlation with IMD data (correlation coefficient of 0.84 and RMSE of 45.07 mm), although performance varied with satellite-based datasets. This study contributes to understanding the simulation of cloudburst events using high-resolution regional modeling and multiple observational validations.

 
Source: https://doi.org/10.1007/s40808-025-02680-w 

by Siva Sai Kumar Rajana, Sambit Prasanajit Naik, Sampad Kumar Panda, Chiranjeevi G. Vivek, Sridevi Jade

Myanmar, located at the convergence of the Indian and Sunda plates, is one of the most seismically active and tectonically complex regions in Southeast Asia. Despite the high seismic hazard, limited ionospheric research has been conducted to understand earthquake-related atmospheric and ionospheric disturbances in this region. The Mw 7.7 Myanmar earthquake that occurred near Mandalay on 28 March 2025 has been considered in this work to examine seismo-ionospheric coupling along the active Sagaing Fault. Using GNSS-derived Total Electron Content (TEC) data, this study identifies both co-seismic and pre-seismic ionospheric anomalies. Multiple Receiver-Satellite (R-S) pairs reveal coherent, temporally correlated perturbations peaking around 0635 UT, indicative of upward-propagating seismic-induced Acoustic Gravity Waves (AGWs). The disturbance amplitudes decreased with distance from the epicenter, with dominant frequencies (3–5 mHz) consistent with seismically induced Traveling Ionospheric Disturbances (TIDs). Horizontal propagation speed of 1.19 km/s confirm the acoustic wave origin of these TEC perturbations. Prominent ionospheric anomalies are detected in the western side of the epicenter, corresponding to the fault rupture zone. These localized, directional perturbations indicate the clear coupling between the strike-slip fault dynamics and ionospheric disturbances. A significant regional TEC reduction detected three days prior to the event under geomagnetically quiet conditions suggests Lithosphere-Atmosphere-Ionosphere (LAI) coupling, likely linked to stress-induced radon emissions or electric field changes. The timing and characteristics of these anomalies reinforce the potential of TEC monitoring as an effective earthquake precursor. The findings not only demonstrate the sensitivity of TEC data to both pre- and post-seismic disturbances but also highlight the potential of TEC-based monitoring as a viable early warning tool, particularly in inter-plate settings where conventional seismic networks may be sparse or underdeveloped. Such ionospheric precursor detection can play a crucial role in enhancing seismic hazard forecasting and preparedness in geologically complex and high-risk regions like Myanmar.
 

More Articles ...

  1. Quantifying weather-rice crop production relationships across different physiographical zones in Odisha, India
  2. Impact of the Gannon Superstorm on the Equatorial Ionization Anomaly Dynamics During Its Recovery Phase on 11 May 2024
  3. Assessing the dynamics and thermodynamics of Monsoon onset: The impact of ENSO
  4. Leaf area index estimation over the Kosi watershed in central Himalaya from remote sensing data using machine/deep learning models and validation against in situ measurements
  5. Impact of assimilating GNSS ground-based and Space-based observations on Extreme rainfall prediction over Karnataka, India
  6. Multi-Instrument Observations of Unseasonal Post-Sunset Equatorial Plasma Bubbles During Two Moderate Geomagnetic Storms in May and June 2024 Over East/Southeast Asia
  7. Identification of malaria vulnerable zones in North East Region of India: Spatiotemporal assessment through geographical information system and self-organizing maps
  8. WRF Model Forecast Evaluation of Extreme Rainfall Events over Karnataka during the Indian Summer Monsoon
  9. Regional assessment of rainfall indices for drought conditions during the monsoon season in Odisha
  10. Influence of large-scale climate modes (ENSO, IOD and PJ) on marine heatwave characteristics in the Indian ocean region

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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.

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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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