Lok Sabha Question No. 3094 (UNSTARRED), answered on 2026-03-11
Subject: Implementation of Mission Mausam
Ministry: EARTH SCIENCES
Asked by: Shri Chavda Vinod Lakhamshi, Shri Alok Sharma, Shri Praveen Patel

## GOVERNMENT OF INDIA MINISTRY OF EARTH SCIENCES LOK SABHA

UNSTARRED QUESTION NO. 3094

TO BE ANSWERED ON WEDNESDAY, 11 TH  MARCH, 2026

## IMPLEMENTATION OF MISSION MAUSAM

## †3094. SHRI CHAVDA VINOD LAKHAMSHI SHRI ALOK SHARMA: SHRI PRAVEEN PATEL:

Will the Minister of EARTH SCIENCES be pleased to state:

- (a) the details of the implementation and progress of Mission Mausam, launched under IMD Vision, 2047 for enhancement of High-Performance Computing (HPC) up to 21 petaflops for  high-resolution  weather  forecasting, Artificial  Intelligence  (AI)/Machine  Learning (ML) integration and seamless services;
- (b) the  quantitative  assessment  of  improvement  made  in  the  accuracy  of  forecasts  for cyclone,  monsoon,  heatwave  and  the  resultant  economic  impact  of  these  improved predictions; and
- (c) whether the Government has conducted an assessment of the public benefits derived from these advancements and proposes to extend the mission to a second phase and if so, the details thereof?

## ANSWER

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

- (a) Under  Mission  Mausam,  the  High-Performance  Computing  (HPC)  systems  of  the Ministry of Earth Sciences were inaugurated on 26 September 2024 by the Hon'ble Prime Minister at the Indian Institute of Tropical Meteorology, Pune and the National Centre for  Medium  Range  Weather  Forecasting,  Noida.  The  systems,  named  'ARKA' (computing capacity of 11.77 petaflops) and 'ARUNIKA' (8.24 petaflops), along with a dedicated 1.9 petaflops AI/ML system, have increased the Ministry's total computing capacity to 21.91 petaflops.  This enhanced  computational  infrastructure enables development of advanced high-resolution weather and climate models and the application of Artificial Intelligence and Machine Learning (AI and ML) for forecasting.
- (b) IMD has achieved a significant leap in tropical cyclone forecasting accuracy during the 2021-2025 period compared to 2016-2020. Track forecast errors have been reduced by 5-10% for lead times up to 48 hours and by 20-25% for longer lead times. Intensity forecasting has also shown substantial improvement, with a 33-35% enhancement for lead times up to 72 hours, while errors at the 96-hour lead time have decreased by 10%. The most pronounced improvement has been observed in landfall prediction, which is critical for timely coastal evacuations. Landfall point errors decreased by 35-45% for 24 to 48 hours and by about 20% for other lead periods. The average 24- hour landfall point error reduced from 31.9 km during 2016-20 to 19.0 km during 2021-25, while the 48hour landfall error declined from 61.5 km to 34.4 km. Heatwave forecasts are now issued

4-5 days in advance, enabling effective implementation of heat action plans by State and district  authorities.  These  improvements  have  resulted  in  significant  socio-economic benefits, including timely evacuation during cyclones, better agricultural planning during the monsoon, and improved disaster preparedness, thereby reducing loss of life, property, and economic disruptions across multiple sectors.

- (c) Yes.  The  Ministry  of  Earth  Sciences  (MoES)  periodically  evaluates  the  benefits  of improvements in weather and climate services through impact assessments, verification of  forecast  skill  scores,  and  feedback  from  user  sectors  such  as  agriculture,  disaster management, aviation, fisheries, and energy. These assessments indicate that improved forecasting capabilities-implemented by institutions such as the India Meteorological Department,  Indian  Institute  of  Tropical  Meteorology,  and  the  National  Centre  for Medium  Range  Weather  Forecasting-have  resulted  in  significant  public  benefits, including  better  early  warnings  for  cyclones,  heatwaves,  heavy  rainfall,  and  other extreme weather events. The improvements have enabled timely evacuations, enhanced disaster preparedness, better agricultural decision-making, and reduced loss of life and property.

Further,  Mission  Mausam  has  been  designed  as  a  multi-phase  programme.  The Government proposes to continue and expand the initiative in subsequent phases based on  the  outcomes  of  the  first  phase.  Several  initiatives  under  the  mission  expected  to improve  our  understanding  of  the  complex  weather  processes.  The  proposed  second phase  will  focus  on  further  strengthening  the  national  weather  observation  network, enhancing high-resolution weather and climate modelling capabilities using advanced High-Performance Computing, integrating Artificial Intelligence and Machine Learning in forecasting systems.

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