Lok Sabha Question No. 1902 (UNSTARRED), answered on 2026-02-11
Subject: Accurate Weather Forecasting
Ministry: EARTH SCIENCES
Asked by: Shri Sanatan Pandey

## MINISTRY OF EARTH SCIENCES

## GOVERNMENT OF INDIA LOK SABHA

## UNSTARRED QUESTION NO. 1902 TO BE ANSWERED ON WEDNESDAY, 11 TH  FEBRUARY, 2026

## ACCURATE WEATHER FORECASTING

## †1902. SHRI SANATAN PANDEY:

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) the  details  of  new  techniques  being  used  by  the  Government  for  accurate  weather forecasting  in  view  of  the  rapidly  changing  weather  pattern  and  natural  calamities during the last few years;
- (b) whether any new technology is under consideration to be used in future and if so, the details thereof; and
- (c) the details of types of technologies for which we are dependent on foreign institutions for weather forecasting?

## ANSWER

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

- (a) In view of the occurrences of higher frequencies of natural calamities during the last few years, the Government has strengthened and modernized observational systems, developed  and  operationalized  new  weather  and  climate  models  to  improve  the prediction  of  various  severe  weather  events  at  a  more  granular  scale.  Systematic modernisation activities undertaken through Monsoon Mission and Mission Mausam to increase High Performance Computing (HPC), data integration, and the application of  new  techniques  and  technologies,  such  as  AI/ML-based  systems,  to  the  weather prediction methodology. Some of the major progress achieved till 2025, compared to 2014, is given in Annexure-1.

Under Monsoon Mission and Mission Mausam, two global forecast models, such as GFS 12 km and NCUM 12 km, have been operational in real time since 2018. The Bharat Forecasting System (BharatFS) has been operational since May 2025 at a very high resolution of 6 km to cater to block-levels and, further, to panchayat levels.

To  provide  computational  support  for  such  high-resolution  models  and  to  enable regular  real-time  operation,  the  computing  facilities  have  also  been  substantially increased  in  computational  power  to  integrate  voluminous  data  and  run  mesoscale, regional, and global models at higher resolution. Recently, with the implementation of the HPC Systems "Arunika" and "Arka", the Ministry of Earth Sciences has enhanced its total computing power to 28 Peta FLOPS in 2025, a substantial increase from the previous capacity of 6.8 Peta FLOPS in 2014.

To automate and integrate data and forecasts, IMD has developed an end-to-end GISbased Decision Support System (DSS) that serves as the front end of the early warning systems for the timely detection and monitoring of all-weather hazards. It is supported by specific severe weather modules to provide timely, impact-based early warnings for extreme weather events such as cyclones, heavy rainfall, thunderstorms, lightning, fog, and  heatwaves,  which  have  devastating  impacts  on  human  lives,  livelihoods,  and infrastructure. This system uses all historical data, their extremes, as well as real-time surface and upper-air meteorological observations available to it for the Indian region and neighbourhood. It also includes radar observations available every 10 minutes and Satellite  products  available  every  15  minutes.  It  also  uses  Numerical  Weather Prediction (NWP) products from a suite of models run in MoES. To provide impactbased forecasts and warnings, the DSS integrates exposure and hazard data.

- (b) Yes. To address further gap areas in the weather and climate services and to effectively use new technologies in the future, the Ministry of Earth Sciences has implemented Mission Mausam  Scheme. Mission Mausam  Scheme  is a multi-faceted and transformative initiative to boost India's weather and climate-related science, research, and  services.  In  addition,  the  integration  of  artificial  intelligence  (AI)  and  machine learning (ML) technologies is also improving the precision of predictions by enhancing model accuracy and prediction resolution.
- (c) MoES institutions rely on foreign institutions primarily for core modeling frameworks, advanced  assimilation  techniques,  and  high-end  computing  hardware  related  to numerical weather prediction.

Core  Modeling  Frameworks:  Through  MoES,  NCMRWF  (National  Centre  For Medium Range Weather Forecasting) is a core partner in the "Momentum" partnership with  the  UK,  Australia,  New  Zealand,  and  Singapore.  The  aim  of  the  Momentum Partnership is to provide a framework for all partners to effectively use and contribute to the development of a world-leading seamless modelling framework for NWP. The NCMRWF-NWP system is based on the Momentum Partnership's advanced Unified Model system. This modelling system used an advanced dynamical core (END Game) and representation of physical processes. The data assimilation system is Hybrid 4DVar. The ensemble prediction system used the En-4DEnVar system.  4D-Var/Hybrid Data Assimilation: UKMO-sourced variational codes customized for NCUM, handling radar/satellite observations critical for monsoon/cyclone initialization.

Hardware  and  Software:  Supercomputing  Components:  NVIDIA/AMD  GPUs  in Arunika supercomputer, plus CUDA libraries for AI/ML acceleration (GraphCast/Pangu downscaling).

## Annexure-1

| Parameter/ System                        | December 2014                                                                                                                                                          | December 2025                                                                                                                                                                                                                                                                                                                                                                |
|------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Automatic Weather Station network        | 12                                                                                                                                                                     | 1008                                                                                                                                                                                                                                                                                                                                                                         |
| Doppler Weather Radar                    | 15                                                                                                                                                                     | 47                                                                                                                                                                                                                                                                                                                                                                           |
| Rain Gauge Stations                      | 3500                                                                                                                                                                   | 6700                                                                                                                                                                                                                                                                                                                                                                         |
| Runway Visual Range Systems              | 20                                                                                                                                                                     | 186 (49 Drishti + 137 FSM RVR)                                                                                                                                                                                                                                                                                                                                               |
| Current weather indicating systems atRWY | 29 Airports out of 99 Airports                                                                                                                                         | All airports are equipped with RWY instruments, including all new airports (137 Digital Current Weather Indicating System at 93 Airport out of 107 Airports)                                                                                                                                                                                                                 |
| Pressure measuring                       | Mercury Barometers                                                                                                                                                     | Digital Barometers                                                                                                                                                                                                                                                                                                                                                           |
| No of stations for City forecasts        | 300 cities                                                                                                                                                             | 1601 cities                                                                                                                                                                                                                                                                                                                                                                  |
| Nowcast stations                         | 141                                                                                                                                                                    | 1211                                                                                                                                                                                                                                                                                                                                                                         |
| High Performance Computing (HPC)         | 1.1 Peta flops Processing speed                                                                                                                                        | 28 Peta flops Processing speed                                                                                                                                                                                                                                                                                                                                               |
| Upper air observations                   | 43 RS/RW Stations 62 Pilot Balloon stations                                                                                                                            | 56 RS/RW Stations. 62 Pilot Balloon stations                                                                                                                                                                                                                                                                                                                                 |
| High Wind Speed Recorders                | 19                                                                                                                                                                     | 36 (Goa station decommissioned)                                                                                                                                                                                                                                                                                                                                              |
| Early Warnings for Tropical Cyclones     | No extended range outlook was issued. No pre-genesis forecast of track & intensity was issued. Early Warnings for Tropical Cyclones were issued 3 days in advance from | Since April, 2018, extended range outlook are being issued for cyclogenesis over entire North Indian Ocean for next two weeks every Thursday. Since April, 2022, pre-genesis forecast of track & intensity are being issued from low pressure stage itself. Early Warnings for Tropical Cyclones were issued 5 days in advance from deep depression stage since April, 2018. |

|                                    | deep depression stage. 24 Hours forecast error was 125 km during 2006-13. 72 Hours forecast error was 268 km during 2006-13.   | 24 Hours forecast error was reduced to 16.2 km during 2020-24. 72 Hours forecast error was reduced to 69.5 km during 2020-24. In particular, accuracy of cyclone track, intensity and landfall point forecasts increased by 35-40%, 15-30% and 45-65% up to 48 hrs in advance. All these improvements have led to significant improvement in forecast accuracy of severe weather events and also significant reduction in death toll e.g., due to cyclones, around 7000 people lost their lives in 1999 Odisha Super Cyclone while it has been reduced to less than 100 over entire region from impact of tropical cyclones during recent years. Accurate forecast of 1 cyclone saves around 1100 crore rupees in terms of expenditure towards payment of ex-gratia to kins of dead, cost towards evacuation and savings to various sectors e.g., Power, Marine, Aviation, Railways etc. sector.   |
|------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Agro- Meteorological Advisories    | Agro- Meteorological Advisories were reaching to about 70 lakh farmers.                                                        | Agro-Meteorological Advisories are now reaching to about 276.7 lakh farmers.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
| District Agro- Met Units Agro AWSs | There was no District Agro- Met Unit (DAMU). 125 Agro- Automatic Weather Stations (Agro- AWS) were established.                | 199 District Agro-Met Units (DAMUs)were established and are functioning. A total number of 200 Agro-Automatic Weather Stations (Agro-AWS) are functioning and installed at KVKs under DAMUproject. Earlier installed 125 Agro AWS during 2009-2012 is under upgradation under 330 Agro AWS Project 2025- 2026. All 130 AMFUsis under upgraded with Agro AWSwith four depth soil sensors and sunshine duration and global radiation measurement under 330 Agro AWS Project 2025-2026                                                                                                                                                                                                                                                                                                                                                                                                                |

| Coverage of Agro- Meteorological Advisories                       | Resolution persisted up to district level.                                                                                      | District level Agro advisory services are Provided to all districts of India.                                                                                                                                                                                                                                                                            |
|-------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Medium Range Forecast Global Forecasting System                   | 25 km resolution with 2 Models (GFS, NCUM)                                                                                      | 6 km Bharat Forecasting System: Government has launched indigenously built BFS, a state of art numerical weather prediction model, since 27 May 2025. It promises finer and accurate rain forecasts down to the panchayat/cluster of panchayats level . 2 other models: 12 km resolution with 2 Models (GFS, NCUM)                                       |
| Heat wave forecast accuracy at meteorological sub-division levels | 68 %for 24 hr lead period 50 %for 48 hr lead period 27 %for 72 hr lead period                                                   | 100 %for 24 hr lead period 95% for 48 hr lead period 90 %for 72 hr lead period                                                                                                                                                                                                                                                                           |
| Heavy Rainfall forecast accuracy                                  | Probability of Detection (POD) for south west monsoon heavy rainfall warning is 50 - for day 1 48 - for day 2 and 37 - for day3 | Probability of Detection (POD) for south west monsoon heavy rainfall warning is 85 - for day 1 73 - for day 2 and 67 - for day3                                                                                                                                                                                                                          |
| Thunderstorm and lightning warning                                | 3 days in advance up to Meteorological Sub-divisions level only.                                                                | Thunderstorm and lightning warnings are issued twice a day 5 days in advance upto District level. The Probability of detection for 24 hourly thunderstorm forecast is 0.89 in 2025 as compared to 0.31 in the year 2016. Similarly, the Probability of detection for 3 hourly thunderstorm nowcast is 0.93 in 2025 as compared to 0.61 in the year 2014. |
| Quantitative Precipitation Forecast (QPF)                         | It had a 2-day validity with a 3-day outlook in 2014.                                                                           | By 2024, the validity period has increased to 7- days and accuracy has improved by over 10- 15% since 2016                                                                                                                                                                                                                                               |

| Establishment of Meso-network of Automatic Rain Gauges (ARG) and Doppler Weather Radars(DWRs) over Mumbai Metropolitan Region   | 2 ARG established by MoES   | 57 ARGs were installed by MoES 60 ARGs were installed by BMC C-Band Doppler Weather Radar at Veravali made operational in January 2022. 4 X-band Doppler Weather Radars were installed under the project of IITM, Pune. Dissemination of real-time rainfall information through mobile apps (Mumbai Weather Live) and web based data portal (Monsoon Online ) http://mumbairain.tropmet.res.in/   |
|---------------------------------------------------------------------------------------------------------------------------------|-----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Data assimilation in NWPmodels                                                                                                  | 50 GB per day               | 500 GB per day                                                                                                                                                                                                                                                                                                                                                                                    |

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