PARLIAMENT QUESTION: FORECAST SYSTEM
1. At a Glance
- BharatFS is India's indigenously developed high-resolution Numerical Weather Prediction (NWP) model operating at ~6 km horizontal resolution, the world's highest for an operational global model. [S1][S3]
- Developed by IITM-Pune under Ministry of Earth Sciences (MoES), supported by NCMRWF-Noida and IMD. [S1][S2]
- Significant for UPSC: intersects GS-III (S&T, Disaster Management), agriculture, and India's push for indigenous scientific capability ("Atmanirbhar Bharat" in weather modelling). [S3]
2. Why in the News
- Subject of a Parliament Question (Lok Sabha) answered by MoES on 29 January 2026 on accuracy of weather predictions. [S1]
- Operationally launched on 26 May 2025 at Vigyan Bhawan, New Delhi, by Union Minister of Earth Sciences Dr. Jitendra Singh. [S3]
3. Background & Evolution
- Predecessor: Global Forecast System GFS T1534 running at ~12 km resolution. [S1]
- Built on the newly implemented Triangular Cubic Octahedral (TCo) dynamical grid — improved orography representation, filtering, and conservation properties. [S1]
- Enabled by acquisition of two supercomputers — Arka (IITM-Pune) and Arunika (NCMRWF-Noida) — which cut model runtime from ~12 hours to 3–6 hours. [S1]
- Project spearheaded by a team including four women scientists. [S3]
4. Core Static Facts
- Parent ministry: Ministry of Earth Sciences (MoES). [S1]
- Developer: Indian Institute of Tropical Meteorology (IITM), Pune. [S1][S3]
- Supporting bodies: NCMRWF (Noida), India Meteorological Department (IMD). [S1]
- Grid: Triangular Cubic Octahedral (TCo). [S1]
- Resolution: ~6 km (vs. 9–14 km for typical global operational models; 12 km for predecessor GFS T1534). [S1]
- Forecast horizon: 10-day forecast of rainfall, temperature, low-pressure genesis. [S1]
- Supercomputers: Arka + Arunika. [S1]
- Data inputs: Integrates real-time data from 40 Doppler Weather Radars. [S3]
5. Multi-Dimensional Analysis
Scientific / Technological - TCo grid offers better mass/energy conservation than standard Gaussian grids — important for tropical convection. [S1] - Resolution leap from 12 km → 6 km enables block-level forecasts (existing administrative blocks span ~12 km+). [S1] - Runtime reduction (12 h → 3–6 h) is what makes the high-res model operationally viable. [S1]
Administrative / Disaster Management - Improves early warning for farmers, fishermen, and disaster-prone communities — feeding into IMD's dissemination chain. [S1] - Higher skill for extreme rainfall events (~30% improvement claimed) is critical for monsoon-flood preparedness. [S3]
Economic - Better block-level rainfall forecasts directly support agro-advisories (Krishi Vigyan Kendras) and fisheries advisories (potential fishing zone). [S1] - Inputs to insurance (PMFBY) and commodity planning.
Strategic / Indigenous Capability - One of the world's first indigenously developed high-resolution global NWP models — reduces dependence on ECMWF/NCEP outputs. [S3]
6. Recent Developments
- 26 May 2025: Operational launch at Vigyan Bhawan by Dr. Jitendra Singh. [S3]
- 29 Jan 2026: MoES reply to Parliament Question detailing BharatFS performance and accuracy claims. [S1]
7. Prelims Hooks
- BharatFS operates at ~6 km horizontal resolution. [S1]
- Uses the Triangular Cubic Octahedral (TCo) dynamical grid. [S1]
- Developed by IITM-Pune under Ministry of Earth Sciences (not MoEFCC, not DST). [S1]
- Predecessor model: GFS T1534 at ~12 km. [S1]
- Supercomputers used: Arka (IITM-Pune) and Arunika (NCMRWF-Noida). [S1]
- Provides a 10-day forecast of rainfall, temperature and low-pressure genesis. [S1]
- Launched on 26 May 2025 at Vigyan Bhawan, New Delhi. [S3]
- Integrates real-time data from 40 Doppler Weather Radars. [S3]
- Model runtime reduced from ~12 hours to 3–6 hours. [S1]
- Project team prominently includes four women scientists. [S3]
- Supporting agencies include NCMRWF (Noida) and IMD. [S1]
- Targets forecasts at the district and block level. [S1]
8. Mains Relevance
- GS-III: Science & Technology — indigenisation of weather modelling; Disaster Management — early warning for cyclones/floods; Agriculture — agro-advisories.
- GS-I: Indian Geography — monsoon dynamics.
- Possible question stems:
- "Discuss how the Bharat Forecast System represents a paradigm shift in India's weather prediction capability and its implications for disaster preparedness."
- "High-resolution numerical weather prediction is as much a computational achievement as a meteorological one. Examine in the context of BharatFS."
- "Evaluate the role of indigenous supercomputing (Arka, Arunika) in advancing India's earth system services."
9. Related Topics to Study Next
- Mission Mausam — MoES umbrella programme; BharatFS is a key deliverable.
- NCMRWF & IMD — institutional architecture of weather services.
- National Supercomputing Mission — Param series; backbone for NWP.
- Doppler Weather Radar network — observational input to BharatFS.
- Cyclone early warning — IMD colour-coded alerts; application of high-res NWP.
- PMFBY (crop insurance) — downstream user of block-level rainfall forecasts.
- AI in weather forecasting — parallel MoES initiative (separate PIB note PRID 2158416).
- Monsoon Mission — earlier MoES initiative that seeded indigenous modelling.
10. Common Errors / Trap Areas
- Confusing developer (IITM-Pune) with IMD — IMD is the disseminator; IITM is the modeller.
- Mixing up Arka (IITM) and Arunika (NCMRWF) supercomputers.
- Treating BharatFS as a satellite mission — it is a numerical model, not a satellite.
- Citing ministry as MoEFCC or DST — correct parent is Ministry of Earth Sciences.
- Quoting resolution as 12 km — that is the predecessor GFS T1534; BharatFS is 6 km.
11. Sources
- [S1] PARLIAMENT QUESTION: FORECAST SYSTEM — https://www.pib.gov.in/PressReleasePage.aspx?PRID=2220205 — (tier: 1)
- [S2] PARLIAMENT QUESTION: BHARAT FORECAST SYSTEM — https://www.pib.gov.in/PressReleasePage.aspx?PRID=2153585 — (tier: 1)
- [S3] Union Earth Sciences Minister Unveils Indigenously Developed High-Resolution 'Bharat Forecast System' by IITM — https://www.pib.gov.in/PressReleasePage.aspx?PRID=2131392 — (tier: 1)