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GOVERNMENT OF INDIA
MINISTRY OF EARTH SCIENCES
RAJYA SABHA
UNSTARRED QUESTION NO. 3086
ANSWERED ON 19/03/2026
MONITORING AND PREDICTION OF CLIMATE CHANGE
3086. SHRI BABUBHAI JESANGBHAI DESAI:
SHRI SANJAY KUMAR JHA:
Will the Minister of EARTH SCIENCES be pleased to state:
(a) whether Government has adopted advanced and state-of-the-art techniques, including
high-resolution climate models, satellite-based observation systems and Artificial
Intelligence-enabled forecasting tools, for more accurate monitoring and prediction of
climate change and if so, the details thereof;
(b) whether there has been significant improvement in real-time data collection,
integration and scientific analysis through strengthened national and regional climate
data centres and the details of capacity-building initiatives undertaken in this regard;
and
(c) whether these proactive measures have enhanced evidence-based environmental
policymaking, strengthened disaster preparedness and early warning systems, and
contributed to climate resilience and sustainable development across the country?
ANSWER
THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR
MINISTRY OF SCIENCE AND TECHNOLOGY
AND EARTH SCIENCES
(DR. JITENDRA SINGH)
(a) Yes. The Ministry of Earth Sciences (MoES) has a very good weather observation
network consisting of Manual observatories, Automatic Weather Stations (AWSs),
upper-air observatories, and Remote sensing tools such as Doppler Weather Radars
(DWRs) and Satellites to observe and monitor climate change and extreme weather
events across the country. The details are given below:-
o A state-of-the-art climate model with improved representation of Earth system
processes is being developed at the Indian Institute of Tropical Meteorology
(IITM, Pune) to improve the prediction of climate change. As part of model
development, increased horizontal resolution, Indian Land-use land-cover data
from the National Remote Sensing Centre, and glacier components are integrated
into the Earth System Model. In addition, an improved cloud microphysics
scheme and hybrid (Physics-informed Neural Network) parameterizations (use of
AI/ML) for improving the physics and reducing the model biases are also being
implemented at IITM.
o AI/ML is used for detection and attribution of climate change and downscaling
climate projections, identifying climate fingerprints in heatwaves, heavy rain,
cyclones, and estimating anthropogenic contributions.o Mission Mausam is also launched by the Government of India, under the Ministry
of Earth Sciences, to strengthen the country’s climate preparedness. Under
Mission Mausam, initiatives have been taking place to increase the observational
network for monitoring climate change. Climate reference stations are being
established across India for continuous monitoring of climate parameters.
o For the forecasting of extreme weather events, two global models forecast
systems, such as GFS 12 km and NCUM 12 km, have been operational since
2018. In addition, the New Bharat Forecasting System (BharatFS) was made
operational in May 2025 with a very high resolution of 6 km to cater to generate
forecast as very high resolution.
o 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.
o Recently, with “Arunika” and “Arka” systems, 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, which was in 2014. For
automation and integration of data and forecasts.
o IMD has also developed an end-to-end GIS-based Decision Support System
(DSS), which has been working as the front end of the early warning systems for
the timely detection and monitoring of all-weather hazards.
o 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 every 15 minutes. It also uses Numerical Weather
Prediction (NWP) products from a suite of models run in MoES. For providing
impact-based forecasts and warnings, the DSS integrates exposure data with
hazard data in the system.
(b) Yes. IMD continues to expand and upgrade its observational systems, such as Doppler
Weather Radars (DWRs), Automatic Weather Stations, Automatic Rain Gauges, and
upper-air systems. Numerical weather prediction systems have been improved with
higher-resolution models, better data assimilation, and the use of the Multi-Model
Ensemble (MME) approach.
The current DWR network of 48 DWRs covers about 92% of the country's total area.
Further 6726 rain gauge stations, 1008 AWS, 186 runway visual range systems, 56
RS/RW stations, and 36 High wind speed recorders have been installed and are
operational. To date 104 lightning location networks are also available across the
India. Impact-Based Forecasting services and early warning dissemination have been
strengthened through mobile applications, web portals, SMS alerts, and closer
coordination with disaster management authorities.The India Meteorological Department has developed advanced techniques for
generating high-resolution gridded datasets of rainfall and temperature over India.
These datasets are produced by integrating observations from a large network of
meteorological stations and applying rigorous quality control and spatial interpolation
techniques. These datasets are made available to research institutions, government
agencies, and other stakeholders to support evidence-based planning, policy
formulation, and scientific research.
These initiatives contribute to strengthening environmental policy and disaster
management by enhancing early warning systems and supporting evidence-based
decision-making and planning. In addition, the development of Earth System models
through the incorporation of new Earth System components and AI/ML-based hybrid
parameterization supports more reliable regional climate projections.
The India Meteorological Department has taken significant steps to enhance training,
strengthen international cooperation, and expand awareness activities for improved
climate and weather services. IMD actively collaborates with global and regional
agencies—including WMO, WHO, UKMO, RIMES, UNESCAP, and all South Asian
countries—to advance climate services in India and contribute to the regional climate
services framework. IMD experts participate in several high-level international
committees such as the WMO Task Team on the National Framework for Climate
Services (TT-NFCS), the Climate Services Working Group of the South Asian
Hydromet Forum (SAHF), and CLIVAR scientific panels, ensuring India's strong
presence in global climate service development and international cooperation.
Capacity building is further strengthened through numerous international training
programmes conducted by IMD’s Meteorological Training Institute (MTI), which
regularly hosts participants from developing and neighbouring countries. These
combined efforts are substantially contributing to more robust climate services,
improved early warning capabilities, and better-informed decision-making across
sectors in India.
(c) Yes, the initiatives of the India Meteorological Department, including improved
forecasting systems and impact-based advisories, provide reliable scientific data and
real-time information to governments and stakeholders. Tools such as the Bharat
Forecast System, which offers high-resolution forecasts at around 6 km spatial scale,
allow authorities to understand localized weather patterns and climate risks more
accurately. These advancements have enhanced evidence-based environmental
policymaking by enabling policymakers to integrate climate data into planning for
sectors such as agriculture, water management, urban infrastructure, and public health.
Accurate forecasts and climate outlooks support informed decisions related to crop
planning, heat-action plans, flood management, and climate adaptation strategies.
Furthermore, IMD’s impact-based forecasts, heavy rainfall warnings, flash-flood
guidance, and urban flood advisories have strengthened disaster preparedness and
early warning systems. State Governments and disaster management agencies can now
take timely preventive measures, such as evacuations, resource mobilization, and
infrastructure protection, which help reduce loss of life and property during extreme
weather events.Overall, these proactive measures have played an important role in building climate
resilience and promoting sustainable development across rural and urban areas by
improving risk awareness, enabling adaptive planning, and strengthening institutional
response mechanisms to climate-related hazards.
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