Home India EARTH SCIENCES Parliament Question: Weather Forecasting Technology and Infr...
Date: 2025-12-17 Category: Not Applicable State: Union Government Country: India

Parliament Question: Weather Forecasting Technology and Infrastructure

Issued by EARTH SCIENCES · Not Applicable

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Executive Summary & Key Takeaways

**Executive Summary** This document, written in response to an unstarred question in the Lok Sabha, outlines the weather forecasting technologies and infrastructure used and being developed by the Indian government under Mission Mausam. It details advancements like the Bharat Forecast System (BharatFS) and the Mithuna Forecast System (Mithuna-FS) and the Meghdoot mobile application. The response is dated December 17, 2025. **Key Points / Main Content** * **Weather Forecasting Technologies** * **BharatFS:** An advanced computer simulation model operational at 6 km resolution, used to provide predictions of rainfall events up to 10 days at the panchayat level. * **Mithuna-FS:** A new-generation global coupled model operating at 12-km resolution. * **AI/ML Integration:** A dedicated virtual center established to integrate AI/ML into the weather forecasting chain for bias correction, downscaling, nowcasting, and multi-source data fusion. * **Satellite Monitoring:** 6 Channels in INSAT 3-D provide 30-minute gap cloud pictures at a resolution of up to 1 km. * **Radar Network:** 47 Doppler Weather Radars (DWRs) currently in operation, covering 87% of the country's total area under radar coverage. * **Decision Support System (DSS):** A real-time multi-hazard impact-based early warning system. * **Meghdoot Mobile Application** * Extended nationwide to cover nearly 700 agriculturally important districts. * Provides daily weather forecasts for nearly 7,000 blocks and 747 districts. * Includes multilingual support for 12 languages and pictorial representations. * Integrated with 21 State Government platforms. * Linked with national digital platforms. * **Doppler Weather Radars (DWRs)** * 47 DWRs are currently in operation across India. * In the coming years, DWRs will be installed to cover remaining gap areas, provide redundancy, and replace old radars. **Impact Analysis** **Stakeholder: Farmers** * **Impact:** Access to improved weather forecasts and agromet advisories through the Meghdoot app, enabling better decision-making and response to weather conditions. * **Action Required:** Download and utilize the Meghdoot app and other integrated platforms for weather information. **Stakeholder: General Public** * **Impact:** Access to timely alerts and warnings through various media platforms, including the UMANG app. * **Action Required:** Utilize available platforms to stay informed about weather conditions and warnings. **Stakeholder: Government/IMD** * **Impact:** Improved ability to predict and manage weather patterns, disseminate information, and support sectors like agriculture and disaster risk reduction. * **Action Required:** Continue strengthening observational capabilities, R&D infrastructure, and dissemination networks.

Key Entities Referenced

India Meteorological Department (IMD): The primary agency responsible for weather forecasting and related services. Mission Mausam: A government initiative focused on improving weather forecasting capabilities and infrastructure. Doppler Weather Radars (DWRs): Radar systems crucial for monitoring and predicting weather phenomena. Meghdoot: A mobile application that provides weather-based agromet advisories to farmers. Ministry of Earth Sciences: The ministry responsible for the policy and the India Meteorological Department (IMD).
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GOVERNMENT OF INDIA MINISTRY OF EARTH SCIENCES LOK SABHA UNSTARRED QUESTION NO. 2911 TO BE ANSWERED ON WEDNESDAY, 17TH DECEMBER, 2025 WEATHER FORECASTING TECHNOLOGY AND INFRASTRUCTURE 2911. SHRI AMRINDER SINGH RAJA WARRING: SHRI BALWANT BASWANT WANKHADE: DR. DHARAMVIRA GANDHI: Will the Minister of EARTH SCIENCES be pleased to state: (a) the details of the weather forecasting technologies currently being used by the Government and its affiliated agencies such as the India Meteorological Department (IMD) including numerical weather prediction models, radar networks, satellites and AI based systems; (b) the details of new technologies and models being developed or implemented by the Government to predict and manage increasingly unpredictable weather patterns caused by climate change; (c) the number of farmers registered to the Meghdoot mobile application since 2021 and the steps taken to expand coverage, year-wise; (d) the current status of the network of Doppler Weather Radars (DWRs) under Mission Mausam including the number and locations installed and operational so far; and (e) the details of the expansion plan including the exact number of additional DWRs planned, the timeline for their installation and the States/locations earmarked for the new installations? ANSWER THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR MINISTRY OF SCIENCE AND TECHNOLOGY AND EARTH SCIENCES (DR. JITENDRA SINGH) (a) Under the Mission Mausam, the Bharat Forecast System (BharatFS), an advanced computer simulation model, has already been developed, and it has been operational at a very high spatial resolution of 6 km. It has also the capability to provide predictions of rainfall events up to 10 days, covering the short and medium-range forecasts. Due to its higher resolution and improved dynamics, it is being used to generate weather forecasts at the level of a panchayat or cluster of panchayats. To further support the operations of high-resolution model simulations in real-time, the computing facilities (Arunika and Arka) have been substantially increased to integrate voluminous data and run meso-scale, regional, and global models. Further, a major achievement is the introduction of the Mithuna Forecast System (Mithuna-FS). This new-generation global coupled model integrates the atmosphere, ocean, land surface, and sea ice components with state-of-the-art physics and an upgraded data assimilation framework. Currently, this forecasting system operates at 12-km resolution, marking a significant advancement in India's medium-range localized weather forecasting capability.The multi-scale Mithuna-FS suite reduces biases in rainfall, temperature, and fog visibility. Coupled with intelligence and machine learning (AI/ML)-based post- processing, these models provide sharper medium-range forecasts, better nowcasting capability, and more reliable district-scale probabilities for extreme rainfall, heatwaves, fog, air quality, and thunderstorms. The Ministry has established a dedicated virtual centre involving the India Meteorological Department, National Centre for Medium Range Weather Forecasting (NCMRWF), and other institutes to integrate AI/ML systematically into the weather forecasting chain under the Mission Mausam. This virtual centre coordinates the development of AI/ML tools for bias correction, statistical post-processing, downscaling, nowcasting, and multi-source data fusion from radars, satellites, and AWS networks. NCMRWF also experimentally runs global operational AI models such as Pangu- Weather, FourCastNet, and GraphCast on the Arunika Supercomputer at ~25 km resolution and fine-tunes them for India. These data‑driven components run alongside the dynamical NWP systems on the Ministry's HPC resources, enabling the rapid generation of tailored hyperlocal products for sectors such as agriculture, urban management, and disaster risk reduction. Satellite and radar-based monitoring has increased manifold. Currently, 6 Channels in INSAT 3-D are providing 30-minute gap cloud pictures and water vapour, wind-related products at a very high resolution of up to 1 km. Currently, 47 DWRs are in operation across India, and the details are given in Annexure-1. (b) The Ministry is continuously working to strengthen observational capabilities and R&D infrastructure to achieve greater accuracy in weather forecasting. The IMD has adopted new techniques and technologies over time to detect, monitor, and provide timely early warnings for disruptive weather patterns caused by climate change. The IMD has expanded its infrastructure for observations, data exchange, monitoring & analysis, forecasting, and warning services in the country. The major new initiative undertaken by the Government is the implementation of the Mission Mausam. A couple of Doppler Weather Radars (DWRs) have already been installed under the mission. Currently, 47 radars are in operation across India, with 87% of the country's total area under radar coverage. As discussed in (a), the Bharat Forecast System (BharatFS), an advanced weather forecasting model, is also used to generate short and medium-range forecasts. IMD consistently issues timely alerts and forecasts to the public and concerned stakeholders. Various steps have been taken to ensure effective dissemination of warnings to vulnerable populations. IMD's weather information, including alerts and warnings to the public, is provided through various media platforms like mass media, Internet (e-mail), Public Website (mausam.imd.gov.in), mobile applications (Mausam/Meghdoot/DAMINI/RAIN ALARM). IMD has launched seven of its services (Current Weather, Nowcast, City Forecast, Rainfall Information, Tourism Forecast, Warnings, and Cyclone) with the 'UMANG' Mobile App for use by the public.IMD currently is equipped with a Decision Support System (DSS) based real-time multi-hazard impact based early warning system (EWS), which integrates all types of real-time and historical data, numerical weather prediction products, etc., to effectively monitor, detect and provide timely forecasts and impact-based warnings with suggested actions up to districts and city/station levels against all types of extreme weather events such as heavy rainfall events, droughts etc. As a result of these new initiatives, the overall skill of forecasting these severe weather events has been improved by 30-40% over the last 10 years. (c) Year-wise statistics and steps taken to expand the Meghdoot coverage are given in Annexure-1. (d)-(e) Currently, 47 DWRs are in operation across India, and the details are given in Annexure-2. In the coming years, DWRs will be installed as per the requirement to cover the remaining gap areas in the country, provide redundancy, and replacement of old radars in the DWR network under Mission Mausam of MoES.Annexure-1 Year Meghdoot registered users Since the launch to 2021 2,36,188 2022 2,81,561 2023 3,18,560 2024 3,78,540 2025 (Till Date – 28 Nov 2025) 4,16,056 Nationwide Expansion of the Application: The India Meteorological Department (IMD), under the Ministry, has undertaken systematic efforts to expand the Meghdoot mobile application, which provides weather-based agromet advisories to farmers. Initially launched for around 150 districts, the application has now been extended across the country and presently covers nearly 700 agriculturally important districts for the dissemination of agromet advisories under Gramin Krishi Mausam Sewa (GKMS). Enhanced Spatial Reach at Block Level: To further improve the geographical reach of the services, the application has been upgraded to provide daily weather forecasts for nearly 7,000 blocks and 747 districts of the country. Additionally, real-time weather warnings and nowcasts have been incorporated to assist farmers in responding promptly to adverse or rapidly changing weather conditions. The application includes multilingual support for 12 languages, pictorial representations of advisories, and simplified formats to enhance usability among farmers. Promotion Through Farmer Awareness Activities: The Meghdoot application has been widely promoted through farmer awareness programmes (FAP) conducted by AMFUs across various states. Multiple communication channels, including SMS, agromet advisories, social media platforms, and local outreach initiatives, have been utilised to inform farmers about the downloads, demos, availability, and benefits of the app. Linkage with State Government Platforms: To further extend outreach, Meghdoot advisories have been integrated with 21 State Government platforms, including state- level mobile applications and agricultural information portals/websites. This linkage has helped widen access to advisories among farmers using state-specific digital services. Integration with National Digital Platforms: In addition, the weather-based agromet advisories disseminated through Meghdoot are linked with major national platforms such as UMANG, Mausam, Krishi Decision Support System (DSS), VISTAAR, WINDS of the Ministry of Agriculture, and other digital systems. These integrations ensure uniform dissemination of advisories across multiple access points.Annexure-2 S. No. State/Union Territory DWR Locations 1. Andhra Pradesh Machilipatnam (S-Band) 2. Andhra Pradesh Visakhapatnam (S-Band) 3. Andhra Pradesh Sriharikota, ISRO (S-Band) 4. Assam Mohanbari (S-Band) 5. Bihar Patna (S-Band) 6. Chhattisgarh Raipur 7. Goa Goa (S-Band) 8. Gujarat Bhuj (S-Band) 9. Himachal Pradesh Jot (X-Band) 10. Himachal Pradesh Murari Devi (X-Band) 11. Himachal Pradesh Kufri (X-Band) 12. Kerala Kochi (S-Band) 13. Kerala VSSC, ISRO Thiruvananthapuram (C-Band) 14. Madhya Pradesh Bhopal (S-Band) 15. Maharashtra Mumbai (S-Band) 16. Maharashtra Nagpur (S-Band) 17. Maharashtra IITM Solapur (C-Band) 18. Maharashtra Veravali (C-Band) 19. Maharashtra Mumbai, Juhu (X-band) 20. Maharashtra Mumbai, Panvel (X-band) 21. Maharashtra Mumbai, Kalyan, Dombivli (X-band) 22. Maharashtra Mumbai, Vasai, Virar (X-band) 23. Maharashtra Mahabaleshwar (X-band) 24. Meghalaya Cherrapunji, ISRO (S-Band) 25. Odisha Gopalpur (S-Band) 26. Odisha Paradip (S-Band) 27. Punjab Patiala (S-Band) 28. Rajasthan Jaipur (C-Band) 29. Tamil Nadu Chennai (S-Band) 30. Tamil Nadu Karaikal (S-Band) 31. Tamil Nadu NIOT Chennai (X-Band) 32. Telangana Hyderabad (S-Band) 33. Tripura Agartala (S-Band) 34. Uttarakhand Lansdowne (X-Band) 35. Uttarakhand Mukteshwar (X-Band) 36. Uttarakhand Surkanda Devi (X-Band) 37. Uttar Pradesh Lucknow (S-Band) 38. West Bengal Kolkata (S-Band) 39. Jammu & Kashmir Banihal Top (X-Band) 40. Jammu & Kashmir Jammu (X-Band) 41. Jammu & Kashmir Srinagar (X-Band) 42. Delhi Aya nagar (X-Band) 43. Delhi Palam (S-Band) 44. Delhi HQ Mausam Bhawan (C-Band) 45. Ladakh Leh (X-Band) 46. Karnataka Mangaluru (C-Band) 47. Chhattisgarh Raipur (C-Band) *****

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