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IMD to use CubeSats, IoT data for improved weather forecasts
SOURCE: NEWSBYTESAPP.COM
JAN 11, 2025
Jan 11, 2025
The India Meteorological Department (IMD) plans to improve the accuracy of its weather forecasts by leveraging data from CubeSats, crowdsourcing, and Internet of Things (IoT) devices.
The data will complement the information already being collected from conventional weather satellites.
Last year, IMD had launched a dedicated meteorological satellite and introduced a new high power computing system (HPCS), to provide more accurate forecasts.
Forecasting upgrade
Madhavan Rajeevan, former Secretary of the Ministry of Earth Sciences, revealed that IMD is moving toward an ensemble prediction system with a horizontal resolution of 6km.
This is a major improvement from the existing 12km resolution.
He also emphasized that using advanced technologies like crowdsourcing, CubeSats, IoT devices and unmanned platforms into observation networks, will significantly improve data quality and forecast efficiency.
Research expansion
Separately, the IMD is also setting up research testbeds in Bhopal and Mumbai to further understand monsoon dynamics and cloud physics.
As of now, the department relies on weather observations from over 6,000 surface observatories.
These are complemented by data from weather balloons, satellites, and a network of radars that contribute information into prediction models.
Scientific progress
Under the Ministry of Earth Sciences (MoES), significant scientific and technological advancements have been made across various domains of Earth system sciences.
These include the atmosphere, hydrosphere, lithosphere, cryosphere, biosphere, and their intricate interactions.
The advances in computational resources have enabled the use of advanced deterministic chemical transport models for more accurate air quality forecasts.
Collaboration
Scientists at IMD and Pune's Indian Institute of Tropical Meteorology (IITM) have jointly developed an advanced Air Quality Early Warning System (AQEWS).
Rajesh Verma, Chairman of the Commission for Air Quality Management, revealed the development.
The system marks a major advancement in predicting air quality levels, replacing earlier empirical and statistical methods that had limitations in representing physical and chemical processes of pollutants.
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