Executive Summary:
The Ministry of Earth Sciences introduced the indigenously developed Bharat Forecast System (BharatFS) on July 30, 2025. BharatFS aims to enhance India's weather prediction capabilities, contribute to reducing crop losses, improve disaster preparedness, and align with the Atmanirbhar Bharat and Make in India initiatives. It leverages high-resolution modeling and supercomputing facilities for improved forecasts.
Key Points / Main Content:
Features and Objectives of Bharat Forecast System (BharatFS):
* BharatFS utilizes a Triangular Cubic Octahedral (TCo) dynamical grid with a 6 km horizontal resolution, improving upon the previous 12km resolution.
* The system is powered by supercomputing facilities Arka IITMPune and Arunika NCMRWFNoida, reducing runtime and enabling real-time weather prediction.
* The objective is to generate forecasts at the cluster of panchayats level and improve the prediction of extreme weather events.
* BharatFS has demonstrated improved rainfall forecasts over the core monsoon region and better accuracy for extreme rainfall forecasts in research mode.
Contribution to Crop Loss Reduction and Disaster Preparedness:
* The increased resolution of BharatFS allows for distinct forecasts every 6 km, capturing local weather features relevant to clusters of panchayats/villages.
* Localized forecasts support farmers in crop planning, irrigation, and harvesting.
* Improved water management during monsoons helps reduce flood risk and increase yield resilience.
* Enhanced prediction of extreme rainfall events contributes to faster and more targeted disaster response.
Significance of Indigenous Development:
* BharatFS represents India's own high-resolution weather prediction model, designed considering the complexities of the Indian geography.
* The system was developed by Indian scientists from institutions like IITMPune, NCMRWFNoida, and IMD.
* The modeling system is powered by indigenous Ministry of Earth Sciences (MoES) supercomputing facilities.
* BharatFS aligns with "Make in India" by showcasing India's capability to build world-class systems locally.
* It enables India to export meteorological services and support neighboring countries, reinforcing regional leadership and self-reliance, aligning with "Atmanirbhar Bharat."
Impact Analysis:
Farmers:
* Impact: Farmers benefit from localized weather forecasts that aid in crop planning, irrigation, and harvesting decisions, ultimately reducing crop losses.
* Action Required: Utilize the granular weather information provided by BharatFS to make informed decisions about agricultural practices.
Water Authorities:
* Impact: Improved weather prediction allows for better reservoir management during monsoons, mitigating flood risks and enhancing water resource management.
* Action Required: Integrate BharatFS forecasts into water management strategies to optimize reservoir operations and minimize flood potential.
Disaster Response Teams:
* Impact: Enhanced prediction of extreme weather events enables faster and more targeted disaster response, improving overall disaster preparedness.
* Action Required: Incorporate BharatFS predictions into disaster response planning and protocols to ensure effective and timely intervention during extreme weather events.
Indian Scientific Community:
* Impact: Showcases Indian capabilities in developing world-class weather prediction systems, fostering innovation and self-reliance in climate and weather sciences.
* Action Required: Continue to develop and refine BharatFS, leveraging supercomputing facilities and expertise to further improve weather prediction accuracy and capabilities.
Neighboring Countries:
* Impact: Potential to receive meteorological services and support from India, reinforcing regional leadership and cooperation in weather forecasting and disaster preparedness.
* Action Required: Engage with India to explore opportunities for collaboration and knowledge sharing in weather forecasting and disaster management.
Key Entities Referenced
Bharat Forecast System: A newly launched weather prediction system developed indigenously by India.
Atmanirbhar Bharat: A Government of India initiative promoting self-reliance.
Make in India: A Government of India initiative to encourage domestic manufacturing.
IITMPune: Indian Institute of Tropical Meteorology, Pune, an institution involved in the development of the Bharat Forecast System.
NCMRWFNoida: National Centre for Medium Range Weather Forecasting, Noida, an institution supporting the Bharat Forecast System.
IMD: India Meteorological Department, an institution supporting the Bharat Forecast System.
Arka IITMPune: Supercomputing facility at IITM Pune, used for real-time weather prediction.
Arunika NCMRWFNoida: Supercomputing facility at NCMRWF Noida, used for real-time weather prediction.
GOVERNMENT OF INDIA
MINISTRY OF EARTH SCIENCES
LOK SABHA
UNSTARRED QUESTION NO. 1840
TO BE ANSWERED ON WEDNESDAY, 30TH JULY, 2025
BHARAT FORECAST SYSTEM
1840. SMT. KAMALJEET SEHRAWAT:
Will the Minister of EARTH SCIENCES be pleased to state:
(a) the key features and objectives of the newly launched Bharat Forecast System and the
manner in which it will enhance Country's weather prediction capabilities;
(b) the manner in which the Bharat Forecast System contribute to reducing crop losses and
improving disaster preparedness, particularly in the context of climate change; and
(c) the significance of the Bharat Forecast System being developed indigenously and the
manner in which it aligns with the goals of Atmanirbhar Bharat and Make in India
initiatives?
ANSWER
THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR
MINISTRY OF SCIENCE AND TECHNOLOGY
AND EARTH SCIENCES
(DR. JITENDRA SINGH)
(a) The Bharat Forecast System (BharatFS) 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. The recently acquired
supercomputing facilities, Arka (IITM-Pune) and Arunika (NCMRWF-Noida), enabled
the model to be used for real-time weather prediction by reducing the runtime from
~12 hours to just 3–6 hours. These key features have enhanced India's weather prediction
capabilities by making India the only country running a global weather prediction model
at such a high resolution 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. On 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.
(b) With the increase in horizontal resolution, the BharatFS is capable of generating distinct
forecasts every 6 km. 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.
Climate change is increasing the frequency and severity of extreme events, and BharatFS
has demonstrated significant improvement in the skill of predicting the core monsoon
region rainfall, with 30% improvement in the accuracy for the forecasting of extreme
rainfall events. All these improvements are crucial for faster and targeted disaster
response, increasing the disaster preparedness of our country.(c) The BharatFS being developed indigenously is highly significant, not only for advancing
India's scientific capabilities but also for furthering national strategic and economic goals.
BharatFS represents India's own high-resolution weather prediction model, designed by
Indian scientists considering the complexities of forecasting due to Indian geography—
the Himalayas and Western Ghats.
Developed by a team of scientists from Indian institutions like IITM-Pune, with support
from the NCMRWF-Noida and the IMD. The modeling system is powered by indigenous
MoES supercomputing facilities (Arka and Arunika). These achievements are aligned
with "Make in India" – Showcasing India's capability to build world-class systems
locally. The development and launch of BharatFS enables India to export meteorological
services and support neighboring countries, reinforcing regional leadership and self-
reliance. Empowering India to own and lead in climate and weather sciences
demonstrates "Atmanirbhar Bharat". All these align strongly with the visions of
Atmanirbhar Bharat (Self-Reliant India) and Make in India.
********