Wed, Oct 29, 2025

CSIR Fourth Paradigm Institute

(Formerly CSIR Centre for Mathematical Modelling and Computer Simulation)

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

by Priyanshi Singhai, Arindam Chakraborty, Kavirajan Rajendran & Sajani Surendran 

Abstract:
Interannual variability of the Indian summer monsoon rainfall (ISMR) is explained through the total column water vapor in the atmosphere, primarily controlled by the incoming zonal moisture flux over the Arabian Sea (Fw) and outgoing flux over the Bay of Bengal (Fe). In this study, we discern the underlying mechanisms driving Fw and Fe leading to ISMR droughts in the observations and seasonal hindcasts by the Climate Forecast System version 2 (CFSv2) model. In observations, a reduction in Fw is essential for droughts to occur. In addition, an increase in Fe results in a severe drought. On the contrary, droughts in CFSv2 primarily occur due to an enhancement in Fe, seldom accompanied by a decrease in Fw. This hypersensitivity of the CFSv2 ISMR to Fe is further explained using Matsuno–Gill response to moist convection. During El Nino droughts, precipitation decreases over the equatorial western Pacific and eastern Indian Oceans. The resulting anomalous diabatic cooling increases local surface pressure (SP), intensifying meridional SP gradient, and thus, Fe. The reduction in Fw , however,  is associated with a cooling of the central north Pacific Ocean in tandem with El Nino. During non-El Nino droughts, frequent occurrences of cold sea surface temperature over the western north Pacific Ocean are noticed. This cooling decreases SP over east Asia, resulting in an increase in Fe. To summarize, droughts in CFSv2 are controlled by the pan-Pacific climate, significantly increasing Fe but weakly decreasing Fw. But in observations, a strong decrease in Fw and a moderate increase in Fe together lead to droughts.

 

Link:

by P. Ipsita, V. Rakesh, Randhir Singh and G.N. Mohapatra

Abstract

This study focuses to analyse the impact of land use changes on short range weather forecasts over Indian region. Weather Research and Forecasting (WRF) model simulation experiments are conducted by using land use data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Indian Space Research Organization (ISRO) satellites for pre-monsoon and monsoon season. MODIS 2001 land use is used in control (CNT) experiment and updated land use with recent urban class from MODIS (EXP1) and ISRO (EXP2) for the year 2019 is used to generate model lower boundary conditions in other two experiments. Quantitative error measures and skill score computed for rainfall forecast showed that model skill is better with the use of realistic recent land use data from MODIS and ISRO during pre-monsoon and monsoon period. Extreme Dependency Index score computed also revealed that model skill in predicting extreme rare rainfall events is improved with recent landuse data. Model simulated surface meteorological variables and profiles at lower levels also found to be improved with the inclusion of realistic land use class from MODIS and ISRO. Between the two experiments, the one which used ISRO based land use showed larger improvement particularly during the monsoon season.

Source: https://doi.org/10.1016/j.uclim.2023.101558

by Raghavendra Prasad K, Kantha Rao Bhimala, G. K. Patra, Himesh S & Sheshakumar Goroshi 

The present study analyzed the actual evapotranspiration (ETa) and its components [transpiration (Et), bare soil evaporation (Eb), interception loss (Ei), and open water evaporation (Eo)] data to study the long-term (1980–2018) trends over different meteorological sub-divisions in India. Quantitatively, all India average (µ) annual ETa is 573 mm (standard deviation (σ) = 29 mm), where Et (µ = 456 mm; σ = 30 mm) plays a major role compared to other evaporation processes like Eb (µ = 56 mm; σ = 9 mm), Ei (µ = 34 mm; σ = 3 mm), and Eo (µ = 27 mm). The Mann–Kendall (MK) test reveals an increasing trend (1.33 mm/yr) in annual ETa due to the rising trend in Et (1.91 mm/yr) and Ei (0.16 mm/yr). The sub-division-wise analysis shows the increasing trend in ETa observed over irrigated regions located in the south, north-west, and foothills of the Himalayas during pre-monsoon (March–May) and monsoon season (June–September). The correlation analysis observed a complex relationship between ETa and climatic factors (rainfall (RF), soil moisture (SM), surface temperature (T), relative humidity (RH), surface net solar radiation (SSR), and wind speed (WS)) during monsoon season such that the water-limited areas have a positive correlation with SM, RH and RF, and negative correlation with WS, T, and SSR, whereas, in energy-limited areas (east India), the ETa showed a positive correlation with SSR and T and negative correlation with RF. The main climatic drivers for the increasing trend of ETa are SM and rainfall over dry regions and SSR and T over densely vegetated regions in India.

 Source: https://link.springer.com/article/10.1007/s00704-023-04436-x 

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  6. Extreme rainfall event analysis over the state of Himachal Pradesh in India
  7. Relationship of height and intensity of low-level jet stream with Indian summer monsoon rainfall
  8. Exacerbation of Indian Summer Monsoon Breaks by the Indirect Effect of Regional Dust Aerosols
  9. Assessing the impact of modified LULC on extreme hydrological event over a complex terrain: A case study for kodagu 2018 flood event
  10. Association of winter vegetation activity across the indo-gangetic plain with the subsequent Indian summer monsoon rainfall

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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