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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 Siva Sai Kumar Rajana, Sampad Kumar Panda, Sridevi Jade, Chiranjeevi G. Vivek

The occurrence characteristics of Equatorial F-region Irregularities (EFIs) along the Indian longitude sector are investigated using GPS-derived ROTI observations from 2010 to 2023, under both quiet and disturbed geomagnetic conditions. The analysis of the results emphasizes a strong dependence of EFIs occurrence on solar cycle variation. Additionally, the EFIs are more intense at the EIA regions under maximum solar activity periods attributed to the high ambient electron density in the F-layer. The occurrence of EFIs is found to be severe and frequently observed in equinox seasons in contrast to solstice seasons. Also, the occurrence of EFIs exhibits equinoctial asymmetry with more intense EFIs in the spring equinox than autumn equinox during the peak and declining periods of the solar cycle. Conversely, severe EFIs are observed during autumn equinox than spring equinox in the ascending phase of the solar cycle. The seasonal occurrence probability of EFIs is highest in the equinox seasons, following the winter solstice, and summer solstice in high solar activity conditions. Investigations of EFIs during two prominent geomagnetic storm events (17 March 2015 and 08 September 2017) during the study period show that the storm-induced Prompt Penetration Electric Fields (PPEFs) modulated the regular intensity of dusk time Pre-Reversal Enhancement (PRE), resulting in poleward expansion of ionospheric irregularities up to mid-latitude regions with spatial time lags. However, storm-induced westward electric fields and oscillating IMF Bz created Counter Electrojet (CEJ) like conditions, suppressing the dusk time ionospheric irregularities over dip equatorial and low-latitude regions on 17 March 2013. This study provides a comprehensive understanding of how ionospheric irregularities manifest under varying conditions, thereby supporting further research on substantiating the spatiotemporal EFIs characteristics and their predictions over the region.

by Rani Devi, K. C. Gouda & Smrutishree Lenka 

By exploring the multifaceted physical mechanisms underlying hot extreme events, the way for informed strategies to mitigate their impacts and enhance the nation's resilience in the wake of a changing climate can be paved. The long-term spatio-temporal variability of hot extremes analysis found an increasing trend (0.001 °C) of DMXT over whole Indian region except the eastern parts (Indo-Gangetic plains). The hot day is noted when DMXT > 40 °C, DMXT > 37 °C, DMXT > 35 °C and also DMXT is above the 90th percentile at each grid point in the plains, hilly, coastal region of India. The temperature tendency equation has been computed to identify the role of various physical processes driving the local extreme temperature changes in India. The analysis showed that the surface adiabatic warming found to be one of the prominent drivers of hot extreme events over India. The impact of El Niño-Southern Oscillation (ENSO) phases on the frequency of hot extreme days at local scale in India are quantified. The linear trend of hot days has been found increasing at a rate of 0.14/year, 0.08/year and 0.06/year in El Niño, La Niña and neutral years respectively. Similarly, the DMXT anomaly found to be 0.4 °C higher in El Niño phase as compared to La Niña phase. The results infers that the chances of hot days occurrence are increased (decreased) by 38% (16% and 8%) in El Niño (La Niña and neutral) period. The advection of hot air by westerlies into the Indian region leads to an increase in temperature. The composite elevated (dropped) geopotential height at 500 hPa showed the presence of high (low) pressure systems which leads to hot days occurrence over western, southern and central (northern, north western) India, where winds are westerlies (easterlies) in El Niño (La Niña) phase of ENSO. This reversal of wind is linked with the movement of warm sea surface temperature from western to eastern Pacific Ocean. Comprehending the dynamics of hot extremes in the India is vital for the development of strategies to mitigate the adverse impacts on various sectors, including agriculture, health, water resources, and infrastructure.

Source: https://doi.org/10.1007/s00477-024-02744-w 

 

by Bishnupada Sethi, Krushna Chandra Gouda, Sarat Chandra Sahu, Manas Kumar Mallick, Amrutanshu Panigrahi & Satish Kumar Samal 

In the recent years, extreme temperature i.e. cold in winter and warm in summer has been observed in the coastal Odisha state in the east part of India. Hydro-meteorological disasters such as floods, droughts, heat waves and cold spells being experienced nowadays are unprecedented in living memory. In this work the climate variability over the coastal Odisha region is quantified considering the temperature parameter. A climate departure index (CDI) of three versions (simple, absolute and least-square) are calculated using monthly, annually and seasonally maximum, minimum as well as mean temperature form seven stations in the costal Odisha for the period 1969 to 2018 for assessing the degree of normal/unusual/extreme of a particular year in compared to the long-term average for the specific coast under consideration. Temperature time series data for the period 1969 to 2018 are homogenized by using the relative comparison between station observations and composite reference series by calculating CDI. Results indicates that CDI values of least-square on all cases are comparatively greater than simple and absolute CDIs. Least-square method is the appropriate method for determining the category of a year or a month or a season in terms of the temperature variation. Analysis based on mean temperature infers that only twenty extreme seasons are observed in monsoon season while three normal are observed during the month of October i.e., in post-monsoon season over the coastal Odisha. The relationship of climatic event including El Nino or La Nina feature of a particular year with respect to CDI is also investigated. The climatic variability is very high on some of the years based on analysis of index values of annual average of the temperatures (maximum, minimum and mean) over a region.

Source: https://doi.org/10.1007/s00024-024-03465-5

 

More Articles ...

  1. Assessment of Country-Specific GHG Emissions from Road Transport Sector in India
  2. Decoding low-frequency climate variations: A case study on ENSO and ocean surface warming
  3. Intensity duration and frequency of Heat wave in different phases of MJO over India
  4. Impact of two severe geomagnetic storms on the ionosphere over Indian longitude sector during March-April 2023
  5. Impact of COVID-19 vaccination: a global perspective
  6. Precipitation Scaling in Extreme Rainfall Events and the Implications for Future Indian Monsoon: Analysis of High-Resolution Global Climate Model Simulations
  7. Modeling and forecasting atmospheric Carbon Dioxide concentrations at Bengaluru city in India
  8. Implications of seismic and GNSS strain rates in Himachal, Kashmir and Ladakh
  9. Projected changes in heat wave characteristics over India
  10. Improved learning by using a modified activation function of a Convolutional Neural Network in multi-spectral image classification

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.

Student Programme for Advancement in Research Knowledge (SPARK)

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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