Atmospheric correction of DSCOVR EPIC: version 2 MAIAC algorithm
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Published version
Date
2021
Authors
Lyapustin, Alexei
Wang, Yujie
Go, Sujung
Choi, Myungje
Korkin, Sergey
Huang, D.
Knyazikhin, Yuri
Blank, Karin
Marshak, Alexander
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Published version
OA Version
Citation
A. Lyapustin, Y. Wang, S. Go, M. Choi, S. Korkin, D. Huang, Y. Knyazikhin, K. Blank, A. Marshak. "Atmospheric Correction of DSCOVR EPIC: Version 2 MAIAC Algorithm." Frontiers in Remote Sensing, Volume 2, https://doi.org/10.3389/frsen.2021.748362
Abstract
The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) provides multispectral images of the sunlit disk of Earth since 2015 from the L1 orbit, approximately 1.5 million km from Earth toward the Sun. The NASA’s Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been adapted for DSCOVR/EPIC data providing operational processing since 2018. Here, we describe the latest version 2 (v2) MAIAC EPIC algorithm over land that features improved aerosol retrieval with updated regional aerosol models and new atmospheric correction scheme based on the ancillary bidirectional reflectance distribution function (BRDF) model of the Earth from MAIAC MODIS. The global validation of MAIAC EPIC aerosol optical depth (AOD) with AERONET measurements shows a significant improvement over v1 and the mean bias error MBE = 0.046, RMSE = 0.159, and R = 0.77. Over 66.7% of EPIC AOD retrievals agree with the AERONET AOD to within ± (0.1 + 0.1AOD). We also analyze the role of surface anisotropy, particularly important for the backscattering view geometry of EPIC, on the result of atmospheric correction. The retrieved BRDF-based bidirectional reflectance factors (BRF) are found higher than the Lambertian reflectance by 8–15% at 443 nm and 1–2% at 780 nm for EPIC observations near the local noon. Due to higher uncertainties, the atmospheric correction at UV wavelengths of 340, 388 nm is currently performed using a Lambertian approximation.
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Copyright Copyright © 2021 Lyapustin, Wang, Go, Choi, Korkin, Huang, Knyazikhin, Blank and Marshak. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.