Lok Sabha Question No. 4214 (UNSTARRED), answered on 2026-03-18
Subject: Real-Time Weather Updates
Ministry: EARTH SCIENCES
Asked by: Shri Raja A

## GOVERNMENT OF INDIA

## MINISTRY OF EARTH SCIENCES LOK SABHA UNSTARRED QUESTION NO. 4214

## TO BE ANSWERED ON WEDNESDAY, 18 TH  MARCH, 2026

## REAL-TIME WEATHER UPDATES

## 4214.   SHRI RAJA A:

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) the  details  of  measures  taken  by  the  Government  to  improve  country's  weather forecasting capabilities;
- (b) whether  the  Government  has  adopted  any  advanced  technologies  like  Artificial Intelligence or machine learning to enhance the accuracy of forecasts;
- (c) the details of measures being taken by the Government to extend real-time weather updates to rural farmers for better crop management; and
- (d) the details of mobile Apps used to provide location-specific forecasts and advisories and to disseminate information through social media platforms in regional languages for the benefit of farmers?

## ANSWER

## THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR MINISTRY OF SCIENCE AND TECHNOLOGY AND EARTH SCIENCES (DR. JITENDRA SINGH)

- (a) To  improve  India's  weather  forecasting  capabilities,  the  Government  has  fully organized an institutional mechanism for strengthening the observational network and adopting new techniques and technology to integrate and assimilate all types of data through  all  computational  and  modelling  supports  for  generating  forecasts  and warnings  at  a  more  granular  scale  of  various  severe  weather  events  affecting  the region.  The  India  Meteorological  Department  (IMD),  in  coordination  with  other centres under the Ministry of Earth Sciences (MoES)-including the Indian Institute of Tropical  Meteorology  (IITM),  Pune,  and  the  National  Centre  for  Medium  Range Weather  Forecasting  (NCMRWF),  Noidahas  undertaken  related  research  and operational activities through time-bound projects such as the Monsoon Mission and the recently launched Mission Mausam.

The main objective of the project is to enhance India's climate and weather observation and monitoring capabilities, which includes the deployment of more radars and other modern monitoring systems in a time-bound manner. Under this project, the Bharat Forecasting  System  (BharatFS)  was  launched,  along  with  ensemble  forecasting systems  and  Impact-Based  Forecasting  (IBF)  approaches,  to  improve  forecast accuracy and lead time for events such as heavy rainfall and heat waves.

Mithuna-FS  is  NCMRWF's  new-generation  global  coupled  forecasting  system  for sharper medium-range weather predictions in India. It integrates atmosphere, ocean, land  surface,  and  sea  ice  with  advanced  physics  and  upgraded  data  assimilation, running  at  12-km  global  resolution.  The  suite  includes  a  4-km  regional  model  for monsoons/cyclones and a 330-m hyper-local urban model for Delhi fog/air quality. Mithuna-FS reduces biases in rainfall, temperature, fog visibility; pairs with AI/ML post-processing for district-level extreme event probabilities (heatwaves, thunderstorms). Developed under Mission Mausam, it boosts severe weather forecast accuracy by 30-40% over the past decade.

IMD  has  developed  indigenous,  technology-driven,  and  citizen-centric  weather forecasting systems that strengthen disaster preparedness and improve public safety across India. IMD's in-house developed Decision Support System (DSS) is a major step  in  the  direction  of  promoting  self-reliance  under  the  "Atmanirbhar  Bharat" initiative. Developed "Mausamgram" (Har Har Mausam, Har Ghar Mausam), a unique citizen-focused  platform  providing  location-specific,  hyperlocal  weather  forecasts down to the village level. "Mausamgram" delivers hourly forecasts for the next 36 hours, three-hourly forecasts for the next five days, and six-hourly forecasts for up to ten days. Users can conveniently access weather information by searching through PIN  code  or  location  name,  or  by  selecting  the  state,  district,  block,  and  gram panchayat.  This  user-friendly  system  ensures  easy  access  to  hyperlocal  forecasts, enabling  citizens  to  obtain  accurate  and  timely  weather  updates  tailored  to  their specific location.

- (b) Yes. IMD, in coordination with various centres of MoES institutes, has developed the following:
-  Utilization of the AI/ML-based Advanced Dvorak Technique (AiDT) to estimate the intensity of cyclones.
-  A novel deep learning model (meteoGAN) has been developed for the Delhi-NCR region  and  successfully  tested  for  rainfall  downscale  using  ground-based  and Climate  Hazards  Group  InfraRed  Precipitation  with  Station  data  (CHIRPS) rainfall analysis at 300 m spatial resolution.
-  A machine learning model based on a decision tree is developed to predict daily rainfall at Delhi during the monsoon season.

NCMRWF  has  developed  the  multi-scale  Mithuna-FS  model  suite  for  sharper medium-range  forecasts,  nowcasting,  and  district-level  extreme  event  probabilities (rainfall, heatwaves, fog). This system integrates global AI/ML models like PanguWeather,  GraphCast,  and  FourCastNet  on  the  Arunika  Supercomputer  for  rapid downscaling to urban scales using GANs and CNNs.

- (c)-(d)  Government has taken various measures to extend real-time weather updates to rural farmers for better crop management. A weather-based crop advisory service is a step towards  providing  real-time  information  about  weather  updates,  crop  health,  and appropriate measures to the farmers, enabling them to make informed decisions about various crop management practices leading to higher yields and increased income.

In  order  to  cater  to  the  needs  of  the  farming  community,  the India  Meteorological Department  (IMD)  runs  a  scheme,  viz.  Gramin  Krishi  Mausam  Sewa  (GKMS)  to render  weather  forecast-based  operational  Agrometeorological  Advisory  Services (AAS) in collaboration  with  the  Indian  Council  of  Agricultural  Research  (ICAR), State  Agriculture  Universities  (SAUs),  Indian  Institute  of  Technology  (IIT),  etc. Under GKMS, 130 Agromet Field Units (AMFUs) covering 127 agroclimatic zones, located at various SAUs, IITs, ICAR institutes, etc., are operational across the country. IMD  provides  medium-range  weather  forecasts  for  rainfall,  temperature,  relative humidity, cloud cover, wind speed and direction at district and block levels for the next five days, along with subsequent week rainfall and temperature outlook at the meteorological sub-division level. Based on observed and forecasted weather, AMFUs prepare Agromet Advisories twice in a week (every Tuesday and Friday) in English as well as in Regional languages for their respective districts and communicate to the farmers to make appropriate decisions on day-to-day agricultural operations such as selection  of  type  of  crops  and  varieties,  appropriate  time  for  sowing,  harvesting, fertilizer  application,  choosing  windows  for  various  intercultural  operations  e.g., weeding,  hoeing,  etc.,  appropriate  time  and  method  of  irrigation,  including  waterefficient methods, etc. as per the need of specific agro-climatic regions. Under the GKMS scheme, all agriculturally important districts are covered across the country for providing weather updates, agromet advisories, and early warnings directly to the farmers.

Along with the AAS bulletins, daily weather forecast and nowcast information are also issued by Regional Meteorological Centers (RMCs) and Meteorological Centers (MCs)  of  IMD.  Impact-based  forecast (IBFs) and appropriate advisories for agriculture are also being prepared by AMFUs based on the severe weather warnings for  different  districts  of  various  States  and  UTs  across  the  country  issued  by  the National Weather Forecasting Centre (NWFC), New Delhi, and RMCs and MCs of IMD.

To provide real-time weather updates and early warnings directly to farmers' mobile phones, including the farmers of climate-vulnerable districts, weather forecasts and Agromet Advisories are disseminated through a real-time mechanism or multichannel dissemination system, including  print and electronic media,  Doordarshan, internet, and SMS under Public-Private Partnership (PPP) initiatives. Under the PPP mode, about 5.56 million farmers are getting benefitted with weather forecasts, alerts, and agromet  advisories.  SMS-based  alerts  and  warnings  along  with  suitable  remedial measures  are being sent  during  extreme  weather events like cyclones,  deep depressions, etc., through the Kisan Portal. Technological advancements have further enhanced  accessibility,  enabling  farmers  to  receive  location-specific  forecasts  and advisories through mobile apps such as 'Meghdoot' and 'Mausam', and Social media platforms like WhatsApp, Facebook, etc. Additionally, IMD has integrated its services with  IT  platforms  of  21  State  Governments,  and  about  15.6  million  farmers  are accessing  the  information  in  English  and  regional  languages  from  these  State Government IT platforms.

IMD,  in  collaboration  with  the  Ministry  of  Panchayati  Raj  (MoPR),  has  recently launched Panchayat-level weather forecasts covering nearly all Gram Panchayats in India. These forecasts are accessible through digital platforms such as e-Gramswaraj (https://egramswaraj.gov.in),  Meri  Panchayat  app,  e-Manchitra  of  MoPR,  and Mausamgram of IMD, MoES (https://mausamgram.imd.gov.in). IMD developed an AI/ML-based tool called meteoGAN to give area-specific rainfall information with 300-meter spatial resolution.

IMD is using an AI/ML tool called 'Bhashini'  to disseminate the weather-related information  to  all  farmers  in  their  regional  languages.  The  Government  has  taken various measures to extend real-time weather updates to rural farmers for better crop management. A weather-based crop advisory service is a step towards providing realtime information about weather updates, crop health, and appropriate measures to the farmers, enabling them to make informed decisions about various crop management practices leading to higher yields and increased income.

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