Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles
Year: 2026
Type: article
Abstract: . The latest generation of geostationary satellites provide Earth observations similar to widely used polar orbiting sensors but at intervals as frequently as every 5–10 minutes, making them ideal for studying diurnal dynamics of land-atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations dataset (GeCGO) for terrestrial ecosystems studies, and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 x 10 km area surrounding 1586 network sites across Americas. GeCGO make it easy to compare the time series of geostationary data with the diurnal ground observations including carbon/water fluxes and aerosol optical depth, and is extensible to other regions. We also developed GeoNEXTools to facilitate analyses that require both GeoNEX data and other NASA satellite data. The objectives of this paper are to introduce GeCGO and GeoNEXTools, and demonstrate their applications. First, we describe the details of GeCGO and GeoNEXTools. Second, we explain how GeCGO can be integrated with other satellite data. Finally, we showcase comparisons between GeCGO and observations from three ground-based networks.
Source: Earth system science data
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,509
Awards: G1286236842, G1337544421, G1380325028, G1632040200, G223002938, G3083819904, G3686510447, G419881185, G42916606, G4331555774, G4501827968, G498139845, Hyper-Temporal Terrestrial Ecosystem Observation with Third Generation Geostationary Satellites, G638836682, G6652958823, G7787287669, G969889393
OpenAlex ID: W7124250374
