AUTHOR=Lyapustin Alexei , Choi Myungje , Wang Yujie , Korkin Sergey , Hyer Edward , Marshak Alexander 

TITLE=Simultaneous retrieval of aerosol optical depth, spectral absorption and layer height from DSCOVR EPIC using MAIAC algorithm

JOURNAL=Frontiers in Remote Sensing

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1677438

DOI=10.3389/frsen.2025.1677438

ISSN=2673-6187

ABSTRACT=A novel MAIAC algorithm is described for joint retrievals of the aerosol optical depth, spectral absorption and layer height (ALH) from DSCOVR EPIC observations in the UV-Vis-NIR spectral range including atmospheric oxygen A- and B-bands. While the oxygen bands have been used to estimate ALH in several existing algorithms, MAIAC for the first time employs a synergy between the UV and O2 A,B-bands to enhance sensitivity to the height of aerosol layer and retrieves it simultaneously with other major aerosol properties. The ALH retrieval capability is illustrated using several examples for smoke and dust aerosols over different parts of the globe. A global AERONET validation of aerosol properties based on the full EPIC data record (mid-2015–2025) shows an accuracy of AOD with correlation coefficient R ∼ 0.71-0.73, RMSE ∼ 0.4, and expected error EE ∼ 20%. While accuracy of AOD is moderate due to the backscattering view geometry of EPIC, achieved agreement of spectral single scattering albedo (SSA) at 443 and 680 nm with AERONET inversion data is very good: the expected error ± 0.03 agrees with AERONET uncertainty, the RMSE is within 0.02–0.03, and bias is within ±0.01. The ALH product was validated globally for the overlapping EPIC- CALIOP CALIPSO period using the CALIPSO total backscatter weighted height. The ALH validation shows a robust performance with global RMSE ∼ 1.1 km and 60%–77% of retrievals within EE = ±1 km. The retrieved ALH is lower than CALIOP ALHC by 0.45–0.75 km over land and is unbiased over the ocean. This new capability and suite of aerosol products, designed to support both the Earth system modeling and the air quality applications, are part of the version 3 MAIAC EPIC algorithm. The v3 algorithm has recently completed reprocessing of the EPIC record covering the period of 2015–2025.