Thu, Feb 12, 2026

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 Sumana Sarkar & P. Lakshmikanthan 

Quantifying the variability of hydro-meteorological variables and various land-surface processes in response to the diverse sources of uncertainties arising from the structure of hydrological models, model parameters, calibration procedures, and schemes related to the various physical process representations is a significant scientific endeavour with important implications in hydrology. Sensitivity analysis is the only plausible way to provide valuable insights into how different parameters influence model outputs and helps evaluate the rationality of each model parameter. Hence, the present study employs sensitivity analysis for comprehensive evaluation of the impact of an enhanced hydrological parameterized and newly developed WRF-Hydro model towards the simulation of hydro-meteorological variables, in terms of model parameter uncertainty and structural variability. The study is carried out in the vicinity of the Krishna River basin in India with a sub grid-scale of 200 m. We evaluate the model's fidelity to accurately simulate streamflow and key hydrometeorological variables, including Evapotranspiration, soil moisture, and land heat and moisture fluxes, through a series of sensitivity experiments. These experiments quantify the impact of uncertainties related to land surface model parameterization, thresholds of model parameters, and structural configurations of the WRF-Hydro framework. The characteristics of the simulations thus generated have been validated against in-situ gauge data and remote sensing-based multi-platform observations, revealing a significant improvement in the simulation accuracy, with correlation coefficients exceeding 0.9 and 0.7 for soil moisture and soil temperature, respectively. Our findings show marked enhancement in the model’s predictive accuracy. By identifying the configurations with superior performance, this study provides practical insight for selecting optimal model parameterizations, thereby contributing to improving the hydro-meteorological forecasting frameworks and supporting better water management practices in regions with limited data availability.

 
Source: https://doi.org/10.1007/s00024-025-03909-6 
 

by Smrutishree Lenka, Krushna Chandra Gouda, Rani Devi & T. S. Mohan 

This study evaluates future changes in Indian summer monsoon (ISM) rainfall, seasonal duration, and impact of pre-monsoon temperature rise using the simulations from twelve CMIP6 climate models under multiple Shared Socioeconomic Pathways (SSPs). Analysis indicates that historical simulations (1951–2014) from the models, assessed against India Meteorological Department (IMD) gridded observational data led to the selection of five models that closely capture observed monsoon rainfall patterns within one standard deviation. Analysis indicates that, over central Indian region extreme rise in temperature > 5.4 °C accompanied by a 3.2% increase in monsoon rainfall in the far-future (2075–2100) scenario. Further, the ISM length at each grid point computed using a novel algorithm from the historical analysis reveals that Northwestern India experiences a comparatively shorter monsoon season. Projections under more intense emission scenarios like SSP-370 and SSP-585, exhibits the ISM-length .decrease by nearly 7–8 days over the next 76 years. At the same time, future projections in indicate a substantial rise in ISM rainfall under high-emission scenarios, suggesting an intensification of the monsoon despite a shortened duration. This paradox is closely linked to increasing pre-monsoon temperatures, which enhance atmospheric moisture-holding capacity and lead to more compound extreme events. The study quantifies the sensitivity of monsoon rainfall to pre-monsoon warming, highlighting spatial variability in rainfall response per 1 °C temperature increase and found that that pre-monsoon temperatures continue to be on the higher side in both SSP5-8.5 and the far-feature scenarios. These findings indicate a growing risk of hydro-meteorological extremes such as heatwaves and urban flooding, especially under high-emission futures like SSP3-7.0 and SSP5-8.5. The projected combination of shorter rainy seasons and more intense rainfall events underscores the urgent need for targeted adaptation and resilience planning across sectors and regions in India.

Source: https://doi.org/10.1007/s00382-025-07923-1 

 

by Swagata Mukhopadhyay, Shantikumar S. Ningombam, Akihiro Uchiyama, Sonam Jorphel, Chiranjeevi G. Vivek, T.S. Shrungeshwara, Sreedevi P., Tsuneo Matsunaga, Som K. Sharma, Pawan Gupta, Dorje Angchuk, Sridevi Jade

Sun-sky radiometer (model POM-01) is commonly used for studying aerosol optical and physical properties at selected aerosol-specific channels. Although the instrument is equipped with a precipitable water vapor (PWV) channel at 940 nm, the inbuilt software does not provide a tool for estimation of PWV. Hence, the current study adopted a new methodology to estimate PWV from three high-altitude ( 3400 m MSL) sites, Hanle, Merak, and Leh, located in Ladakh, India. The retrieval algorithm focuses on the precise estimation of the calibration constant () and coefficients and using modified Langley plots in two different methods. The estimated average value of is 0.59 ± 0.09 which is very close to those commonly used in global studies. Further, the estimated and values from both methods are found to be similar, which may be due to the advantages of the dry and high-altitude environment, where the annual total column water vapor is typically less than 6 mm. The estimated PWV using observations at selected full clear and stable atmospheric conditions compares well with satellite, AERONET, GPS, reanalysis and empirical model data with correlation coefficient varying from 0.91 to 0.97. Further, the estimated propagated root mean square error (rmse) varies from 0.37 mm to 2.58 mm. These results indicated that sun-sky radiometer derived PWV showed good consistency with the derived PWV from independent data sources at the three sites.
 
Source: https://doi.org/10.1016/j.atmosenv.2026.121789

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  4. Seismo-ionospheric anomalies associated with the 2025 Mw 7.7 Myanmar earthquake: a case study
  5. Quantifying weather-rice crop production relationships across different physiographical zones in Odisha, India
  6. Impact of the Gannon Superstorm on the Equatorial Ionization Anomaly Dynamics During Its Recovery Phase on 11 May 2024
  7. Assessing the dynamics and thermodynamics of Monsoon onset: The impact of ENSO
  8. 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
  9. Impact of assimilating GNSS ground-based and Space-based observations on Extreme rainfall prediction over Karnataka, India
  10. Multi-Instrument Observations of Unseasonal Post-Sunset Equatorial Plasma Bubbles During Two Moderate Geomagnetic Storms in May and June 2024 Over East/Southeast Asia

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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SPARK is intended to provide a unique opportunity to bright and motivated students of reputed Universities to carry out their major project/thesis work and advance their research knowledge in mathematical modelling and simulation of complex systems. The programme is intended to increase the interaction between scientists and faculty members of academic institutes along with their students towards a long term research collaboration. Click here to apply for SPARK.

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