Quantification of atmospheric carbon dioxide from the Geostationary Operational Environmental Satellite (GOES East)
Researchers have developed a physics-guided neural network capable of quantifying atmospheric carbon dioxide ($XCO_2$) using data from the Geostationary Operational Environmental Satellite (GOES-East). This model leverages the satellite's high temporal and spatial resolution, along with meteorological and surface reflectance data, to estimate $XCO_2$. While not as precise as dedicated instruments, the GOES-East derived data offers a unique view of $CO_2$ variability over large geographic areas with frequent updates, showing potential for observing urban enhancements and agricultural drawdowns. AI
IMPACT This AI-driven approach could enhance climate monitoring by providing more frequent and spatially comprehensive carbon dioxide data.