Reviews and syntheses: Ongoing and emerging opportunities to improve environmental science using observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites

Abstract

Abstract. Environmental science is increasingly reliant on remotely-sensed observations of the Earth's surface and atmosphere. Observations from polar-orbiting satellites have long supported investigations on land cover change, ecosystem productivity, hydrology, climate, the impacts of disturbance, and more, and are critical for extrapolating (upscaling) ground-based measurements to larger areas. However, the limited temporal frequency at which polar-orbiting satellites observe the Earth limits our understanding of rapidly evolving ecosystem processes, especially in areas with frequent cloud cover. Geostationary satellites have observed the Earth's surface and atmosphere at high temporal frequency for decades, and their 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 minutes. 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 for expanding ABI observations to estimate vegetation greenness, moisture, and productivity at high temporal frequency across the Western Hemisphere. Finally, we present emerging opportunities to address the relatively coarse resolution of ABI observations through multi-sensor fusion to resolve landscape heterogeneity and to leverage observations from ABI to study the carbon cycle and ecosystem function at unprecedented temporal frequency.

Reply on RC1

“…Correcting for atmospheric attenuation of radiation to derive surface reflectance from TOA reflectance is a crucial prerequisite to studying surface processes for any satellite platform. Current efforts to estimate surface reflectance from ABI, Advanced Himawari Imager (AHI), and the Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) include generating lookup tables from the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model (He et al, 2019;Tian et al, 2010;Vermote et al, 1997;Yeom et al, 2018Yeom et al, , 2020. Optimal estimation methods that estimate surface BRF from SEVIRI have been extended to estimate surface broadband albedo and surface reflectance from ABI and the AHI on Himawari-8 (Govaerts et al, 2010;He et al, 2019He et al, , 2012Wagner et al, 2010).…”

“…In Australia, compared to NDVI, EVI shows less SZA induced diurnal variation and is less impacted by the midday hot spot effect during times of the year (spring and autumn equinox) when the SZA and AHI VZA are aligned (Tran et al, 2020). NDVI measurements can be normalized to a reference sun-target-sensor geometry by estimating bidirectional reflectance distribution functions (BRDF) to address the impacts of varying sun-sensor geometry (Fensholt et al, 2006;Seong et al, 2020;Tian et al, 2010;Yeom et al, 2018;. Given the SZA sensitivity of NDVI measurements, Wheeler and Dietze (2019)…”

“…The ABI features three longwave infrared bands with spatial resolutions of about 2 km for measuring land surface temperature (LST)the skin temperature of the uppermost layer of the land surfaceincluding correction for atmospheric moisture (Yu et al, 2012). Determination of a physical surface temperature rather than an effective surface temperature is critical for many applications and, as previously discussed, requires knowledge of the surface emissivity (Yu et al, 2009(Yu et al, , 2012.…”

“…The ABI features three longwave infrared bands with spatial resolutions of about 2 km for measuring land surface temperature (LST)the skin temperature of the uppermost layer of the land surfaceincluding correction for atmospheric moisture (Yu et al, 2012). Determination of a physical surface temperature rather than an effective surface temperature is critical for many applications and, as previously discussed, requires knowledge of the surface emissivity (Yu et al, 2009(Yu et al, , 2012. Data sources for land surface emissivity in LST retrievals from geostationary satellites can include spectral libraries given a specific type of environmental surface (Peres and DaCamara, 2005), the MODIS operational land surface emissivity product (MOD11) or the Combined ASTER and MODIS Emissivity over Land (CAMEL) product (Pinker et al, 2019).…”

“…The hourly ABI LST product uses the difference between the brightness temperatures of ABI bands 14 (11.2 μm) and 15 (12.3 μm) in a split-window algorithm with an added term to correct for path length at high view zenith angles (Yu et al, 2009(Yu et al, , 2012. These bands were chosen because they are placed in regions of maximum surface emission with low https://doi.org/10.5194/bg-2020-454 Preprint.…”