Policy Update
Prashail Tripathi
BACKGROUND
IMD’s “Upgradation of Forecast System” scheme is an ongoing scheme that largely consists of ongoing programs that are integrated in order to provide efficient meteorological and climate-related services throughout the country in multiple sectors. This initiative is part of MoES’s umbrella scheme “Atmosphere & Climate Research-Modelling Observing Systems & Services (ACROSS)”. It receives funding under the ACROSS scheme. It was sanctioned as part of the broader ACROSS (Atmosphere & Climate Research–Modelling Observing Systems & Services) initiative by the Cabinet on November 25, 2021, covering the five-year period 2021–2026. The scheme “Upgradation of Forecast System” drives to ameliorate the precision of weather forecasts to meet international standards, which will benefit many sectors such as military operations, agribusinesses, tourism, mountaineering, aviation, roadways and communications, energy production, water management, environmental studies, sports and adventure, government authorities, non-governmental organisations, and the general public.
The scheme aims to upgrade and maintain communication systems for efficient data and product transmission, establish advanced operational forecast and delivery systems, and conduct targeted campaigns to enhance cyclone, thunderstorm, and fog forecasting through aircraft reconnaissance and additional observations. It also includes implementing the Integrated Himalayan Meteorological Programme for the Western and Central Himalayas, along with capacity building, volunteering, and maintaining specialized observation systems across India.
The main participating institution in this scheme is the Indian Meteorological Department, New Delhi.
https://in.linkedin.com/company/ministry-of-earth-science
FUNCTIONING
It intends to considerably enhance weather forecast accuracy to meet worldwide standards in industries such as agriculture, aviation, defence, tourism, road transport, water management, power, sports and adventure, and general public welfare. The budget allocations, up till the year 2020, in INR Crores, as published by the Ministry of Earth Sciences, are as follows:
| YEAR | ALLOCATION |
| 2017-18 | 99.33 |
| 2018-19 | 102.44 |
| 2019-2020 | 104.63 |
| TOTAL | 310.40 |
Source: https://www.moes.gov.in/programmes/upgradation-forecast-system?language_content_entity=en
The scheme basically operates with the help of some core components and the functioning is done in the following manner:
1. Expanding and modernising the observation network. As part of the program, this is a top focus for India’s weather forecasting skills. One of the scheme’s main goals is to increase the overall number of Doppler Weather Radars (DWRs) from the current number of 40 to approximately crossing the three mark figure in the upcoming years, thus substantially improving the country’s weather monitoring networks. A fleet of Automatic Weather Stations (AWS), rain indicators, wind profilers, weather balloons, ocean buoys, and ship-based observations will be added to the network in addition to the DWRs. The Indian Meteorological Department (IMD), Indian Institute of Tropical Meteorology (IITM), and Indian National Centre for Ocean Information Services (INCOIS) are the institutions at the helm of implementation and management of this observation network.
2. The events occurring during a cyclone plays out as an excellent example of how the upgraded Forecast System works. When a cyclone is formed, or when it reaches anywhere near the coast of the Indian subcontinent, the expanded network of radars and satellites would detect it immediately, while the high-resolution Bharat Forecasting System (BFS) would immediately forecast its path and expected landfall. The advanced High-Performance Computers would then run repeated simulations to negate the errors, while simultaneously, the AI would help in identifying the more vulnerable points. Lastly, in addition to using broadcasting and mobile applications like Mausam and Damini, the India Meteorological Department (IMD) will also use state disaster teams and local panchayats to help issue early warnings. This joint strategy reduces mortality and protects property by giving people vital time to prepare.
3. The optimization of High-Performance Computing (HPC) is important, as the advanced weather models require powerful supercomputers to process huge amounts of data and complex calculations on a daily basis. To help with this, HPC’s capability under the scheme has been expanded with systems such as Pratyush and Mihir at IMD and NCMRWF, and Arka at IITM, as well as increased data storage, faster servers, and dependable backups. Improved HPC infrastructure enables finer model grids, better group runs, and quicker results, resulting in more accurate and timely predictions.
4. Since these intricate computer models serve as the foundation for contemporary weather forecasting systems by projecting how the atmosphere will evolve over time, Numerical Weather Prediction (NWP) systems are becoming more and more significant in the overall strategy.
A classic example of this approach is the Bharat Forecasting System. Launched in 2025, it utilizes a high-resolution grid of 6 km in tropical areas and implements ensemble forecasting by executing multiple model variations to better account for uncertainties. This upgrade enables forecasters to predict small-scale weather events such as local thunderstorms, intense rain cells, and monsoon surges more reliably, improving short- and medium-range forecasts.
https://en.wikipedia.org/wiki/Numerical_weather_prediction#/media/File:AtmosphericModelSchematic.png
ACHIEVEMENTS
With the upgradation in the Forecast System, the time availability for the prediction of cyclones, their development and their landfall, has increased from one day in 2008 to seven days in the year 2023, giving the to-be-affected communities ample time to prepare. By 2023, severe weather forecasts had achieved a precision of 80% for heavy rainfall, 86% for thunderstorms, and 88% for heat and cold waves. (MoES Annual Report 2022–23 & 2023–24)
A potential achievement that would soon be realised is that the scheme will increase India’s Doppler Weather Radar network from around 40 to almost 100 units, providing coverage to additional coastal, interior, and mountainous areas, allowing for real-time tracking of rainfall, cyclones, thunderstorms, and local weather concerns.(Ministry of Earth Sciences. (2023). Annual Report 2022–23)
The consolidation of Artificial Intelligence and Machine Learning has enhanced forecasting, short-term rainfall prediction, and impact-based forecasting, improving local risk assessment. Forecasts are now designed to show not just what the weather will be but what it will do, enabling disaster managers and local authorities to plan more targeted and effective responses.
ADOPTION
IMD, IITM, NCMRWF, and INCOIS sub-projects under the ambit of ACROSS are responsible for the improvement of weather models, radars, supercomputing (HPC), satellite data utilisation, and forecast delivery systems. Yearly fund releases for ACROSS and sub-programs under forecast system modernisation are consistently among the highest utilised within MoES. This shows steady implementation.
The program’s adoption has been robust and constant, and its continually substantial utilisation rates show that the implementing agencies have made good use of the money released for updating models, radars, and computer systems. The main components of the plan are on track, as evidenced by significant milestones such as the rollout of more Doppler Weather Radars (growing from about 35 to 40 to an anticipated 100), the May 2025 launch of the Bharat Forecasting System (BFS) with a higher 6 km resolution, and frequent upgrades to supercomputing capacity with systems like Pratyush, Mihir, and Arka. India’s observation network has also been reinforced with the addition of new weather stations, ocean buoys, automated weather systems, and better use of satellite data.
The forecast system improvement has received generally positive feedback from stakeholders. Governments of affected states and the state and national disaster management officials attribute the improved forecast accuracy to a reduction in losses and fatalities during severe storms and periods of high precipitation. For instance, a notable achievement during Cyclone Biparjoy in 2023 was that the number of fatalities was somewhat lower than during a comparable occurrence in the 1990s. A more precise agromet advisory that is disseminated at the block and Panchayat levels have made it possible for farmers to more efficiently schedule their planting and harvesting.
IMAGE 1 IMAGE 2
https://mausam.imd.gov.in/imd_latest/contents/all_india_forcast_bulletin.php
https://mausam.imd.gov.in/imd_latest/contents/all_india_forcast_bulletin.php
EMERGING CHALLENGES
Notwithstanding significant advancements, the MoES’s Upgradation of Forecast System still faces new difficulties, such as last-mile dissemination gaps that occasionally prevent rural and remote communities from receiving timely, clear warnings. Rapid, efficient responses at the district and panchayat levels are hampered by a lack of local ability to evaluate intricate, impact-based forecasts. In challenging regions like the Himalayas and isolated islands, there are still physical coverage gaps, and it is still challenging to reliably integrate massive live information flows from radars, satellites, and ocean systems.
Getting to function smoothly, providing the necessary data on time, has to go hand in hand with maintaining public confidence and community response to warnings, which continues to be an important behavioural challenge. Also, as the climate is changing at such a rapid pace, that it also pushes the boundaries of these forecast models, necessitating ongoing improvements and expert labour.
https://theunitedindian.com/news/blog?Bharat-Forecast-System-India&b=490&c=3
WAY FORWARD
A multi-pronged approach to boost the reach and effectiveness of this scheme, the government should prioritise last mile connectivity by implementing multilingual, community-based alert systems through mediums like radio, schools, colleges, self-help groups and panchayats operating in remote areas which have poor internet connectivity. Regular training and capacity building will help authorities, disaster response teams, and leaders to better comprehend impact-based estimates and make wiser decisions.
Also, timely completion of the remaining observation gaps would improve real-time coverage, especially by accelerating Doppler Weather Radar installations in hard-to-reach regions such as the North-East, the Himalayas, and islands. To help with this, India must continue to invest steadily in High-performance Computers (HPC), collaborate on areas of research and development to keep up the same pace as the extreme weather calamities, and ensure that numerical models like the Bharat Forecasting System (BFS) are updated on a regular basis.
REFERENCES
1. Ministry of Earth Sciences. (n.d.). Upgradation of forecast system. Ministry of Earth Sciences, Government of India. https://www.moes.gov.in/programmes/upgradation-forecast-system?language_content_entity=en
2. India Science, Technology & Innovation Portal. (n.d.). Upgradation of forecast system: Research and development. Office of the Principal Scientific Adviser to the Government of India.
https://www.indiascienceandtechnology.gov.in/programme-schemes/research-and-development/upgradation-forecast-system?
3. India Meteorological Department. (2021, October 19). Recent advances in early warning services of India Meteorological Department [Blog post]. WordPress. https://imdweather1875.wordpress.com/2021/10/19/recent-advances-in-early-warning-services-of-india-meteorological-department/
4. Business Standard. (2017, January 16). Ministry of Earth Sciences commissions higher resolution weather prediction model. Business Standard India. https://www.business-standard.com/article/news-cm/ministry-of-earth-sciences-commissions-higher-resolution-weather-prediction-model-117011600961_1.html
5. Business Standard. (2025, May 26). Centre launches Bharat Forecast System for high-resolution weather. Business Standard India. https://www.business-standard.com/india-news/centre-launches-bharat-forecast-system-for-high-resolution-weather-125052601103_1.html?utm_source=chatgpt.com
6. Hybrid Minds. (n.d.). India’s Bharat Forecast System: Supercomputer-powered weather model explained. Hybrid Minds. https://hybridminds.in/indias-bharat-forecast-system-supercomputer-powered-weather-model-explained/
7. India Meteorological Department. (n.d.). Mausam. India Meteorological Department. https://mausam.imd.gov.in/
8. Press Information Bureau. (n.d.). Ministry of Earth Sciences commissions higher resolution weather prediction model [Press release]. Press Information Bureau, Government of India. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2141315
9. ThePrint. (n.d.). IMD makes leap with made-in-India Bharat Forecast System, promises more accurate predictions. ThePrint. https://theprint.in/science/imd-makes-leap-with-made-in-india-bharat-forecast-system-promises-more-accurate-predictions/2637673/
10. Ministry of Earth Sciences. (2022–2024). Annual report 2022–23 & 2023–24: Sections on IMD’s forecasting services and achievements. Ministry of Earth Sciences, Government of India.
11. Ministry of Earth Sciences. (n.d.). Official responses to Parliamentary Questions (PQ) in the Rajya Sabha and Lok Sabha. Ministry of Earth Sciences, Government of India. Retrieved from https://www.moes.gov.in/
12. Ministry of Earth Sciences. (n.d.). Annual reports. Ministry of Earth Sciences, Government of India. https://moes.gov.in/annual-reports
13. Rajya Sabha Secretariat. (2022, July 21). Parliamentary Question No. 497 [PDF]. Rajya Sabha Debates. https://rsdebate.nic.in/bitstream/123456789/732678/1/PQ_257_21072022_U497_p199_p201.pdf
ABOUT THE CONTRIBUTOR
Prashail Tripathi has completed his post graduation (M.A) in National Security Studies from the Central University of Jammu. He has been affiliated with IMPRI as a Policy Research Intern since June 2025. His core interests include understanding current geopolitical scenarios, civil-military relations of India’s neighbouring countries, energy security and International Relations.
ACKNOWLEDGEMENT
The author extends sincere gratitude to Ms. Aasthaba Jadeja for her invaluable guidance and mentorship throughout the research process.
Disclaimer:
All views expressed in the article belong solely to the author and not necessarily to the organization.
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