Bharat Forecast System Latest News
Recently, the union Minister of State (Independent Charge) for Science and Technology, Earth Sciences informed the Rajya Sabha about the Bharat Forecast System.
About Bharat Forecast System
- It is an indigenously built advanced weather forecasting system.
- It is based on the newly implemented Triangular Cubic Octahedral (TCo) dynamical grid that enables the model to operate at 6 km horizontal resolution, surpassing its predecessor (GFS T1534 ~ 12km) and typical global operational models having horizontal resolution of 9–14 km.
- Supercomputing facilities Arka (IITM-Pune) and Arunika (NCMRWF-Noida), enabled the model to be used for real-time weather prediction.
- The BharatFS was developed with the objective of generating forecasts at the cluster of panchayats level and improving the prediction of extremes.
-  In research mode, it has demonstrated significant improvement in the rainfall forecast over the core monsoon region and 30% better accuracy for the extreme rainfall forecast compared to the previous operational model.  Â
- With the increase in horizontal resolution, the BharatFS is capable of generating distinct forecasts every 6 km.
- It has demonstrated significant improvement in the skill of predicting the core monsoon region rainfall, with a 30% improvement in the accuracy for the forecasting of extreme rainfall events.
- The BharatFS was developed by a team of scientists from Indian institutions like IITM-Pune, with support from the NCMRWF-Noida and the India Meteorological Department (IMD).
- The development and launch of BharatFS has enabled India to upgrade its meteorological services and support neighboring countries, reinforcing regional leadership and self-reliance.
- Significance: This allows the capturing of local weather features, thus enabling the forecasts to cater to a cluster of panchayats/villages.
- Localized forecasts help farmers with crop planning, irrigation, and harvesting. Additionally, water authorities can better manage reservoirs during monsoons, reducing flood risk and improving yield resilience.
Source: PIB
Last updated on August, 2026
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