NASA has selected a team of researchers, including US-based Southwest Research Institute, to develop the Cyclone Global Navigation Satellite System (CYGNSS), which will assist in enhancing prediction of hurricanes and extreme-weather.
The $151.7m NASA satellite project will be led by the University of Michigan.
The CYGNSS constellation consists of eight nanosatellite observatories, which will be launched together aboard a single rocket into low-Earth orbit in 2017.
Following the launch, the observatories will obtain global positioning system (GPS) signals both directly from GPS satellites, which identify CYGNSS observatory positions and replicated signals from the Earth's surface, which determine wind speeds.
CYGNSS will examine the bond between ocean surface assets, moist atmospheric thermodynamics, radiation and convective dynamics, as well as determine tropical cyclone formation, which would help advance forecasting and tracking methods.
CYGNSS principal investigator, University of Michigan atmospheric, oceanic and space sciences professor Chris Ruf said that the system would allow the team to probe the inner core of hurricanes in greater detail to understand their rapid intensification.
"This will allow us to observe and understand the complete lifecycle of storms and understand the thermodynamics and radiation that drive their evolution," Ruf said. "Our goal is a fundamental improvement in hurricane forecasting."
Other team members include Surrey Satellite Technology and NASA Ames Research Center, which will provide the delay Doppler mapping instrument and the deployment module.
NASA Science Mission Directorate associate administrator John Grunsfeld said that the CYGNSS mission was both a scientific and a programmatic advance for NASA's Earth science and applications programme.
"CYGNSS will provide vital science data on tropical cyclones, and the CYGNSS team will advance our ability to obtain high-quality Earth science data through smaller, more affordable space systems," Grunsfeld said.
The mission is mainly aimed at measuring the ocean surface wind speed in majority precipitating conditions and in the tropical cyclone core, which will further be useful for hurricane forecasting community.