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Mission Mausam: India's weather-readiness push

A multi-phase Earth Sciences mission to make the country weather-ready and climate-smart by 2031.

What happened

In a written reply in the Lok Sabha on 11 March 2026, the Minister of State (Independent Charge) for Earth Sciences set out the status and design of Mission Mausam, the government's flagship programme to upgrade weather, climate and ocean services.
The reply restated the mission's stated aim — to make the country "Weather Ready and Climate Smart" — and listed its working components: better observation networks, sharper numerical weather-prediction (NWP) models, larger high-performance computing (HPC), and AI/ML-driven forecasting.
It named the implementing institutions under the Ministry of Earth Sciences (MoES): the India Meteorological Department (IMD), the Indian Institute of Tropical Meteorology (IITM), Pune, and the National Centre for Medium Range Weather Forecasting (NCMRWF), Noida, with INCOIS handling ocean services.
The mission is being implemented in phases till 2031, integrating observational data, modelling systems and computing across MoES institutions.
The reply also flagged a new field facility — the Atmospheric Research Testbed–Central India (ART-CI) at Silkheda, Sehore district, Madhya Pradesh — set up in the monsoon core zone to close long-standing data gaps on monsoon convection and rainfall variability.
Because it was a Parliament reply, it is a consolidated official statement of where the mission stands rather than a fresh launch announcement.

Background & context

Mission Mausam is best understood as the umbrella weather-services programme of the Ministry of Earth Sciences. It was approved by the Union Cabinet and rolled out from late 2024, and it consolidates the ministry's atmospheric-science work that earlier ran under the scheme cluster known as ACROSS ("Atmosphere & Climate Research–Modelling Observing Systems & Services"). Where ACROSS was a bundle of continuing sub-schemes covering IMD, IITM and NCMRWF, Mission Mausam reframes the same institutional machinery around a single goal — making forecasts more accurate, longer in lead time, and more usable at the last mile — and adds a large injection of computing and AI capability.

It is a Central Sector Scheme, meaning it is funded and run entirely by the Union government through MoES institutions, not cost-shared with the States the way a Centrally Sponsored Scheme would be. This matters for a "consider the statements" question: weather and earth-system science is a Union subject delivered through central scientific bodies, so the money and the delivery both sit with the Centre. The mission's institutional spine is the same set of bodies that already deliver India's day-to-day weather: IMD (the national met agency, founded 1875), IITM Pune (the tropical-meteorology research institute), and NCMRWF Noida (the medium-range NWP centre), with INCOIS Hyderabad supplying ocean-state and tsunami services.

The mission also sits inside a wider Earth-system family of MoES programmes that aspirants pair it with — the Deep Ocean Mission (ocean exploration, the Samudrayaan crewed-submersible Matsya-6000), the O-SMART scheme for ocean services, and the PACER programme for polar and cryosphere research. Mission Mausam is the atmospheric and climate-services pillar of that ecosystem; it is not an ocean-exploration or polar programme, even though INCOIS ocean data feeds into it.

For Prelims

Name & nature: Mission Mausam — a Central Sector Scheme of the Ministry of Earth Sciences (MoES).
Aim: make India "Weather Ready and Climate Smart" by improving the accuracy, lead time and reliability of weather forecasts and early warnings for extreme events.
Timeline: rolled out from late 2024; implemented in phases till 2031.
Predecessor: subsumes the earlier ACROSS scheme cluster of MoES.
Implementing bodies: IMD, IITM (Pune) and NCMRWF (Noida); INCOIS (Hyderabad) for ocean services; other MoES institutes also execute parts of it.
Four working components: (1) expansion and upgradation of observation systems; (2) augmentation of HPC capacity; (3) advanced modelling, including AI and ML; (4) improved impact-based forecasting and last-mile dissemination.
Computing backbone: HPC systems ARKA (11.77 petaflops) and ARUNIKA (8.24 petaflops), plus a dedicated 1.9-petaflop AI/ML system, taking MoES total computing to 21.91 petaflops; these were inaugurated on 26 September 2024 at IITM Pune and NCMRWF Noida.
Observation network: a growing grid of Automatic Weather Stations (AWS), Automatic Rain Gauges (ARG) and Doppler Weather Radars (DWRs); about 48 DWRs operate nationwide and AI weather models such as Pangu, GraphCast and FourCastNet are being used.
New facility: the Atmospheric Research Testbed–Central India (ART-CI) at Silkheda, Sehore district, Madhya Pradesh, in the monsoon core zone, to study monsoon convection, cloud microphysics, land–atmosphere interaction and boundary-layer processes.
Dissemination apps: MoES/IMD reach the public through apps including MAUSAM, MEGHDOOT and DAMINI, plus SMS, TV, radio and social media; sector advisories go to farmers, fishers and disaster authorities.
Nodal minister: the reply was tabled by the Minister of State (Independent Charge) for Earth Sciences.

What it is NOT: Mission Mausam is not a Centrally Sponsored Scheme — it is a Central Sector Scheme run wholly by MoES, with no State cost-share. It is not a brand-new institution: it works through existing bodies (IMD, IITM, NCMRWF, INCOIS), not a new authority. It is not the Deep Ocean Mission, O-SMART or the PACER polar programme — those are sibling MoES programmes, and INCOIS ocean data only feeds into Mausam. ARKA and ARUNIKA are MoES weather supercomputers, not the same as India's earlier weather HPCs Pratyush and Mihir, which they supersede in capacity.

For UPSC: Mission Mausam = MoES Central Sector Scheme (from late-2024, subsumes ACROSS, runs in phases to 2031) to make India "Weather Ready and Climate Smart"; backed by the ARKA (11.77 PF) and ARUNIKA (8.24 PF) supercomputers (21.91 PF total) and delivered via IMD, IITM, NCMRWF and INCOIS.

Why it matters

India is one of the most disaster-exposed large economies in the world: cyclones on both coasts, monsoon floods, droughts, heatwaves, thunderstorms and lightning each year impose heavy costs on lives, agriculture and infrastructure. The single most effective way to cut those losses is not always more concrete — it is more warning time. A heatwave alert issued four to five days ahead lets districts trigger heat-action plans; a sharper cyclone landfall forecast lets coastal districts evacuate the right villages rather than the whole coast. Mission Mausam is the programme that funds the observation, computing and modelling needed to buy that lead time.

The reply pointed to measurable gains attributed to this build-up. For tropical cyclones, MoES reports cut track-forecast errors and, most importantly, landfall errors — the average 24-hour landfall-point error fell from about 31.9 km in 2016–20 to roughly 19.0 km in 2021–25, with the 48-hour error dropping from about 61.5 km to 34.4 km. Better landfall accuracy directly shrinks the area that must be evacuated and the cost of a false alarm. The agriculture and fisheries pay-offs are equally concrete: monsoon and rainfall outlooks shape crop planning and irrigation scheduling, while ocean-state advisories and Potential Fishing Zone (PFZ) maps from INCOIS keep fishers safe and direct them to fish aggregation, improving both safety and catch efficiency.

There is also a strategic-technology dimension. By standing up petaflop-scale HPC and adopting AI weather models (Pangu, GraphCast, FourCastNet), India is keeping pace with a global shift from purely physics-based NWP toward AI-accelerated forecasting that is faster and cheaper to run. Mission Mausam is thus both a disaster-risk-reduction programme and a domestic capability-building programme in scientific computing and AI.

For Mains

Anchor

A question on India's disaster early-warning architecture or on the application of AI and supercomputing in governance can be built directly around Mission Mausam — its four components, its institutional spine (IMD/IITM/NCMRWF/INCOIS) and its 2031 phase plan.

Data

Use the hard numbers: 21.91 petaflops of MoES computing (ARKA 11.77 + ARUNIKA 8.24 + 1.9 AI/ML); cyclone 24-hour landfall error down from ~31.9 km (2016–20) to ~19.0 km (2021–25); heatwave alerts now 4–5 days ahead.

Example

As a worked example of "S&T in everyday life and indigenisation," cite the move from physics-only NWP to AI models (GraphCast, FourCastNet, Pangu) and the indigenous supercomputers that succeeded Pratyush and Mihir.

Problematise

The reply itself concedes the gaps Mausam exists to close — data gaps over the monsoon core zone (hence ART-CI at Silkheda) and weak last-mile dissemination in remote regions — useful for showing why forecasting accuracy is necessary but not sufficient without reach.

Way forward

Frame impact-based, district-level, last-mile warnings (via MAUSAM/MEGHDOOT/DAMINI apps and sector advisories) as the template for converting forecast skill into actual lives and crops saved.

Position

The government's stated stance: weather-readiness is a science-and-computing problem, to be solved by upgrading observation, HPC and modelling under a single mission running in phases to 2031.

Deploys into: disaster management and early-warning systems (GS3.15); application of S&T, AI and supercomputing in everyday life and governance (GS3.13); and, by extension, monsoon/agriculture planning and the science institutions of the Ministry of Earth Sciences.

Ministry of Earth Sciences · 2026-03-11 · PRID 2238025 · PIB source ↗