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Abstract. Environmental science is increasingly reliant on remotely sensedobservations of the Earth's surface and atmosphere. Observations frompolar-orbiting satellites have long supported investigations on land coverchange, ecosystem productivity, hydrology, climate, the impacts ofdisturbance, and more and are critical for extrapolating (upscaling)ground-based measurements to larger areas. However, the limited temporalfrequency at which polar-orbiting satellites observe the Earth limits ourunderstanding of rapidly evolving ecosystem processes, especially in areaswith frequent cloud cover. Geostationary satellites have observed theEarth's surface and atmosphere at high temporal frequency for decades, andtheir imagers now have spectral resolutions in the visible and near-infrared regions that are comparable to commonly used polar-orbiting sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), or Landsat. These advances extend applications of geostationary Earth observations from weather monitoring to multiple disciplines in ecology and environmental science. We review a number of existing applications that use data from geostationary platforms and present upcoming opportunities for observing key ecosystem properties using high-frequency observations from the Advanced Baseline Imagers (ABI) on the Geostationary Operational Environmental Satellites (GOES), which routinely observe the Western Hemisphere every 5–15 min. Many of the existing applications in environmental science from ABI are focused on estimating land surface temperature, solar radiation, evapotranspiration, and biomass burning emissions along with detecting rapid drought development and wildfire. Ongoing work in estimating vegetation properties and phenology from other geostationary platforms demonstrates the potential to expand ABI observations to estimate vegetation greenness, moisture, and productivity at a high temporal frequency across the Western Hemisphere. Finally, we present emerging opportunities to address the relatively coarseresolution of ABI observations through multisensor fusion to resolvelandscape heterogeneity and to leverage observations from ABI to study thecarbon cycle and ecosystem function at unprecedented temporal frequency.
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