Tue, Jul 08, 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 C. Neethu & K. V. Ramesh 

Heat waves are increasing in frequency and exhibit high spatial variability in their distribution over India. There are limited studies focused on thermal indices over India due to the nonavailability of high-resolution (HR) climate data. Here we develop dynamically downscaled HR (4 × 4 km) daily climate information for the months of April to June during 2001–2016 using a regional climate model called Weather Research and Forecasting (WRF) Model, which are validated with station observations. The thermal comfort, heat stress, and its spatiotemporal variability and change over India are quantified in terms of indices like excessive heat factor (EHF), the heat index (HI), humidex, apparent temperature (AT), and wet bulb globe temperature (WBGT). The results show that there is an increasing trend in annual heat waves coverage (22,240 km2/year), annual frequency (0.07 days/year), and average intensity (0.04 °C/year) during 2001–2016. The spatial distribution of indices exhibits high spatial and temporal variability. The days with the severe threshold of indices are significantly increasing over north India at the rate of EHF (15.9%), HI (14.9%), humidex (15.9%), AT (13.4%), and WBGT (13.8%). The heat waves’ most vulnerable hotspots are on the parts of Rajasthan, Uttar Pradesh, Madhya Pradesh, and the coastal regions of Andhra Pradesh and Odisha. During heat waves, prolonged exposure under the sun will lead to adverse health impacts, and it is mostly observed over severe heat wave zone. These findings stress the need for developing suitable mitigation strategies for a sustainable ecosystem with minimum impact.

Source: https://link.springer.com/article/10.1007/s00704-022-03987-9 

by Adithya Samanth, V Rakesh, Smrati Purwar, S M Gavaskar, B Jagadeesha Pai & G N Mohapatra 

Karnataka, a state in south India with nearly 80% of the cultivated land under rainfed farming, is very much dependent on rainfall for agricultural productivity. The spatio-temporal variability in observed rainfall over Karnataka is investigated using various data analytical techniques such as parametric and non-parametric methods, rotated empirical orthogonal function (REOF), clustering and spectral analysis. The observed data used for studying rainfall variability is the daily taluk-wise telemetric rain gauge data for a period of 1960–2016. A similar pattern in trend is observed in annual and south-west monsoon (SWM) rainfall over Karnataka such that taluks in the western and northern parts showed a decreasing trend, whereas the south interior part showed an increasing trend. A significant increasing trend in rainfall was found during pre-monsoon seasons whereas the northeast monsoon (NEM) rainfall showed a decreasing trend. The REOF analysis also indicated an upward (downward) trend in SWM and annual over the northern (southern) Karnataka and a weakening trend in the NEM rainfall. Using the hierarchical clustering method, six homogeneous rainfall clusters were identified over Karnataka based on distribution and variability of rainfall. The spectral analysis over different clusters showed significant oscillations in the annual and SWM rainfall in the 1970s and recent decades except the Western Ghat region where oscillations were much weaker during recent decades. The pre-monsoon and NEM rainfall also showed strong variability with a periodicity of 2–4 years in recent decades. The findings of this study can have implications while designing water resource management strategies across various sectors in Karnataka.

Source: https://link.springer.com/article/10.1007/s12040-022-01810-7

 

by Rameshan Kallummal

The spatio-temporal characteristics of the observed warming of the Indian Ocean (IO) surface temperature and its statistical link to the IO Warm Pool (IOWP) are still unclear. This study discriminates the basin-wide monotonic warming mode of the IO surface from the internally and remotely forced variability. The trend pattern reported in this study reveals a radically different warming signal. It shows that the monotonic warming in the observed sea surface temperature (SST) has the spatial pattern of summer-mean SST and the Warm Pool as its most conspicuous feature. The highest warming (0.17∘C per decade) is in IOWP and not in the other IO regions identified in the previous studies. By 2070, IOWP will cover about 80% of tropical IO at the current latitudinal expansion rates. The mean states of equatorial SST, wind, and surface pressure are shifting towards an endless summer. Irrespective of the season, SST near Indonesia would remain above 31∘C by 2080 and beyond (i.e., more than 2.2∘C rise since 1950). This would substantially increase local rainfall intensity and frequency. Thus, IO is poised to play a more significant role in climate change. We also argue that the basin-wide warming is due to anthropogenic forces’ rectification by coupled processes in ocean-atmosphere mixed layers.

Source: https://doi.org/10.1007/s00382-022-06181-9

 

More Articles ...

  1. Assessment of Aerosol Optical Depth over Indian Subcontinent during COVID-19 lockdown (March–May 2020)
  2. Effect of large-scale oceanic and atmospheric processes on the Indian summer monsoon
  3. Water vapour characteristics and radiative effects at high-altitude Himalayan sites
  4. Evaluation of long-term variability of ionospheric total electron content from IRI-2016 model over the Indian sub-continent with a latitudinal chain of dual-frequency geodetic GPS observations during 2002 to 2019
  5. Imaging subsurface geological complexity (2D/3D) beneath the Greater Srinagar region of the Kashmir basin, Northwest Himalaya
  6. Detecting aliasing and artifact free co-seismic and tsunamigenic ionospheric perturbations using GPS
  7. Temperature-duration-frequency analysis over Delhi and Bengaluru city in India
  8. Application of neo-deterministic seismic hazard assessment to India
  9. Sinking Slab Stress and Seismo-Tectonics of the Indo-Burmese Arc: A Reappraisal
  10. On the Semidiurnal Variation in Surface Rainfall Rate over the Tropics in a Global Cloud-Resolving Model Simulation and Satellite Observations

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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 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.

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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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