Sriharikota: India's latest satellite, the Megha Tropiques, launched in Sriharikota today, will study the patterns and dynamics of the monsoon. The 1000-kg satellite was one of four hoisted into space today, about 80 kms from Chennai.
The French flavour in the name of the satellite has its roots in the joint venture between India and France which hopes to gain more information on how global warming will impact the monsoon.
For the Indian Space Research Organization (ISRO), this satellite stands the very real chance of turning into a game-changer. "The whole world is looking at this mission... many countries around the world are interested to share the data with us," said Dr G Raju, the Project Director at ISRO for the Megha Tropiques.
Built at a cost of Rs 500 crore, India has contributed the satellite bus and rocket to launch the Megha-Tropiques into space. France has provided most of the hi-tech scientific instruments. India's workhorse rocket - the Polar Satellite Launch Vehicle or PSLV- now handling its 20th launch was used today for the mission.
The PSLV weights 230 tons -as much as 50 adult and very well-fed elephants. Like a bus delivering passengers at different spots, it dropped of four satellites today, of which the Megha-Tropiques was the heaviest.
The three smaller satellites include one built by students of SRM University near Chennai and the three-kg satellite Jugnu built by the Indian Institute of Technology-Kanpur .
The Megha-Tropiques has day, night and all-weather viewing capabilities; it will pass over India almost a dozen times every day, giving scientists an almost real- time assessment of the evolution of clouds.
The satellite will provide scientific data on contribution of the water cycle to the tropical atmosphere with information on condensed water in clouds, water vapour in the atmosphere, precipitation and evaporation.
According to ISRO, Megha-Tropiques with its circular orbit inclined 20 degree to the equator will enable climate research and also aid scientists seeking to refine weather prediction models.