Quantification of atmospheric carbon dioxide from the Geostationary Operational Environmental Satellite (GOES East)

The need for characterizing global variability of atmospheric carbon dioxide (CO2) is quickly increasing, with a growing urgency for tracking greenhouse gasses with sufficient resolution, precision and accuracy so as to support independent verification of CO2 fluxes at local to global scales. The current generation of space-based sensors, however, can only provide sparse observations in space and/or in time, by design. While upcoming missions may address some of these challenges, most are still years away from launch. This challenge has fueled interest in the potential use of data from existing missions originally developed for other applications for inferring global greenhouse gas variability. The Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite (GOES-East), operational since 2017, provides full coverage of much of the western hemisphere at 10-minute intervals from geostationary orbit at 16 wavelengths at an approximately 2km2 spatial resolution. Here, we leverage this high temporal resolution by developing a single-pixel, fully connected neural network to estimate dry-air column CO2 mole fractions (XCO2). The model employs a time series of GOES-East's 16 spectral bands, ECMWF ERA5 lower tropospheric meteorology, MODIS surface reflectance, solar angles, and day of year. Training used collocated GOES-East and OCO-2/OCO-3 observations. The model is able to capture realistic XCO2 variability when compared against held-out years of OCO-2 observations and against observations from the TCCON network. We also present case studies illustrating the use of the model to observe XCO2 enhancements over urban areas, drawdown over agricultural regions, and enhanced ability to observe regions with persistent cloud cover thanks to GOES-East’s full spatial coverage and high observational frequency. Overall, although GOES-East derived XCO2 precision cannot rival that of dedicated instruments, its unprecedented combination of contiguous geographic coverage, 10-minute temporal frequency, and multi-year record offers the potential to observe aspects of atmospheric CO2 variability currently unseen from space.