NASA Geostationary REsearch and Applications Team

GREAT logo

NASA’s Research and Analysis Program’s Weather and Atmospheric Dynamics Focus Area supports research and applications with the constellation of next-generation of geostationary sensors. The NASA Geostationary REsearch and Applications Team (GREAT) was established to foster collaboration on geostationary sensor-related research and applications across the NASA centers and investigators funded though NASA ROSES. The goal is to create a cohesive framework for processing, archiving, and disseminating geostationary satellite imagery to facilitate scientific research and applications. Three projects at NASA centers are the cornerstone of NASA GREAT: GeoNEX at Ames Research Center, the Satellite ClOud and Radiation Property retrieval System (SatCORPS) at Langley Research Center, and the Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center. In addition, projects are competitively selected through the NASA ROSES Earth Science Research from Operational Geostationary Satellite Systems (ESROGSS) solicitation.

Geo-NEX

GeoNEX is a collaborative effort for generating Earth monitoring products from the new generation of geostationary satellite sensors.

SatCORPS

SatCORPS is a collection of acquisition, processing, prediction and display tools focused on the use of satellite data to improve knowledge of atmospheric thermodynamics and clouds to better characterize their impacts on weather and climate.

SPoRT

SPoRT is a NASA project to transition unique observations and research capabilities to the operational weather community to improve short-term forecasts on a regional scale.

ESROGSS

ESROGSS provides an opportunity to the Earth science research community to perform scientific research on the new generation of operational geostationary satellites.

Technical Contact: Dr. Emily Berndt (emily.b.berndt@nasa.gov)
Responsible Official: Dr. Andrew Molthan (andrew.molthan@nasa.gov)
Page Curator: Roger Allen (roger.e.allen@nasa.gov)
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