Implications of whole-disc DSCOVR EPIC spectral observations for estimating earth's spectral reflectivity based on low-earth-orbiting and geostationary observations

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Abstract

Earth's reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)'s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)'s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth's reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth's reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth's reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between -0.7% and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between -10% and 23%.

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Song, W., Knyazikhin, Y., Wen, G., Marshak, A., Mõttus, M., Yan, K., … Myneni, R. B. (2018). Implications of whole-disc DSCOVR EPIC spectral observations for estimating earth’s spectral reflectivity based on low-earth-orbiting and geostationary observations. Remote Sensing, 10(10). https://doi.org/10.3390/rs10101594

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