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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 Puja Sahu, P. K. Mohanty & Krushna Chandra Gouda

Climate change has direct effect on rice crop production, resulting in an impact on food security in tropical countries like India. The coastal state of Odisha, situated in the country's eastern region, also suffered from crop production/yield due to the regional climate change. In this research work, the multi-source long term data analysis is being carried out to quantify the climate-crop relation in the state of Odisha. The analysis of rainfall, temperature, Kharif crop (rice) yield and production for the past three decades in Odisha at district scale is carried out. The study based on the cluster analysis of different physiographical regions i.e. coastal plain (CP), river catchment (RC) and mountainous zone (MZ). The region wise climatology, interannual variability, and trend analysis of both rainfall and temperature and the rain/temperature days are computed using the data over 30 (1993–2022) years. The variability of annual and monsoon rainfall is comparatively higher in the CP and RC than in MZ. The monsoon rainfall trend seems to be decreasing in the CP region, increasing in the MZ and no trend over RC. The analysis infers a negligible (0.01 °C/year) temperature trend in the state. The correlation result suggested that the Kharif rice crop yield & production well correlated with the summer monsoon rainfall over RC and MZ at 90% confidence levels. The rice production in the state shows increasing trend in RC as compared to other two regions. The results suggest a good correlation between the rainfall and rice crop production observed in RC and MZ regions. Similarly, temperature also correlates better with the Kharif crop production and yield in CP as compared to other regions. The district scale analysis also indicated that strong correlation (95%) of rice crop yield with temperature is observed in 10 districts and the relation of crop production and rainfall is strong in 12 districts. The impact of large-scale process like ENSO on the district scale Kharif yield/production also assessed. The analysis signifies the global, local, and direct impact of climate patterns on rice production at district and regional scales. This study opens a scope for the potential use of the integrated approach to address the impact of climate change on a state's agriculture and food sector.

 
Source: https://doi.org/10.1007/s00704-025-05839-8 

by K. Shimna, R. K. Archana, C. Vineeth, Gang Lu, T. K. Pant and M. S. M. Vijayan

During the recovery phase of the Gannon Superstorm on 11 May 2024, the thermosphere-ionosphere system experienced dramatic changes marked by an unusual redistribution of plasma density. The peak electron density (Nmax) from Global-scale Observations of the Limb and Disk (GOLD), ground-based Vertical Total Electron Content (VTEC), and topside VTEC from Swarm C satellite revealed an enhanced electron density at the equator and a complete disappearance of the Equatorial Ionization Anomaly (EIA) crests. This absence of EIA crests was linked to a strong daytime Counter Electrojet (CEJ) caused by disturbance dynamo effects observed in ground magnetic data. The unusually strong CEJ suppressed the ExB vertical drift, thereby eliminating the fountain effect. Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) simulations further indicated the presence of equatorward converging meridional winds from both hemispheres. This converging wind hindered the diffusion of plasma from the dip equatorial rΣO/N2 ratio along the equator was observed during the recovery phase, further contributing to this phenomenon. The present study, therefore, for the first time, demonstrates the combined effects of storm-induced changes in equatorial electrodynamics, meridional winds, and significant compositional changes during the recovery phase of a superstorm, and their influence on plasma distributions. The corroborative evidence from model simulations further strengthened these observational findings.

Source: https://doi.org/10.1029/2025SW004428 

by Smrutishree Lenka, K. C. Gouda, MOHAN T. S., Rani Devi and V. S. Prasad

This study examines the mechanisms involved in the onset and progression of the monsoon over the Indian subcontinent by analyzing key dynamical and thermodynamical processes. Additionally, it investigates the characteristics of monsoon onset during various ENSO phases. To achieve this, we utilized long-term observations and ERA5 reanalysis data to conduct a comprehensive study on the onset and related characteristics. 

Results indicate that, a robust connection between the thermal gradient in both zonal and meridional directions and the corresponding vertical wind shear both across the active monsoon shear domain (MSD) and Kerala domain (KD). It is found that, this relationship varies across different time scales i.e., annual, seasonal (ISM-length), and onset pentad (p0), underscoring that the intensity of monsoon convection hinges on the thermal gradient and wind shear. The analysis concludes that presence of weak vertical wind shear, creates a stable state and the presence of a significant thermal gradient, characterized by minimal variations in wind speed and direction at different altitudes, are critical factors that facilitate the monsoon onset. Further, El Niño tends to increase wind shear over the Indian subcontinent and leads to a delayed monsoon onset. Elevated geopotential height during an El Niño year indicates the existence of a high-pressure region, which is an unfavorable condition for the onset of the monsoon. Analysis of temperature tendency equation exhibit a robust diabatic heating which is linked to a Gill-like Rossby wave response, initiating thermodynamic interactions with midlatitude westerly jet. Furthermore, this study also gives an indication of the influence of central pacific (CP) warming events and its influence on monsoon onset characteristics, which needs further exploration.

Source: https://doi.org/10.54302/mausam.v76i4.7064 

More Articles ...

  1. 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
  2. Impact of assimilating GNSS ground-based and Space-based observations on Extreme rainfall prediction over Karnataka, India
  3. Multi-Instrument Observations of Unseasonal Post-Sunset Equatorial Plasma Bubbles During Two Moderate Geomagnetic Storms in May and June 2024 Over East/Southeast Asia
  4. Identification of malaria vulnerable zones in North East Region of India: Spatiotemporal assessment through geographical information system and self-organizing maps
  5. WRF Model Forecast Evaluation of Extreme Rainfall Events over Karnataka during the Indian Summer Monsoon
  6. Regional assessment of rainfall indices for drought conditions during the monsoon season in Odisha
  7. Influence of large-scale climate modes (ENSO, IOD and PJ) on marine heatwave characteristics in the Indian ocean region
  8. Impact of assimilation of microwave imager radiance data on simulation of tropical cyclones over Bay of Bengal using National Centre for Medium Range Weather Forecasting Unified Model modelling system
  9. Quantifying CMIP6 models’ performance in simulating marine heatwaves over the Indian Ocean region: A comprehensive analysis of key MHW properties and future projections
  10. Climate variability and warming in Coastal Odisha: assessing interannual temperature trends and impacts

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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