Lok Sabha Question No. 2911 (UNSTARRED), answered on 2025-12-17
Subject: Weather Forecasting Technology and Infrastructure
Ministry: EARTH SCIENCES
Asked by: Shri Balwant Baswant Wankhade, Shri Amrinder Singh Raja Warring, Dr. Dharamvira Gandhi

## GOVERNMENT OF INDIA

## MINISTRY OF EARTH SCIENCES LOK SABHA UNSTARRED QUESTION NO. 2911

## TO BE ANSWERED ON WEDNESDAY, 17 TH  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  postprocessing, 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  PanguWeather,  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 statelevel 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.

|   S. No. | State/Union Territory   | DWRLocations                           |
|----------|-------------------------|----------------------------------------|
|        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)                        |