Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC

Huang, Xinzhou; Yang, Kai

doi:https://doi.org/10.5194/amt-15-5877-2022

Articles | Volume 15, issue 20

https://doi.org/10.5194/amt-15-5877-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-15-5877-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 20

Research article

|

19 Oct 2022

Research article |

| 19 Oct 2022

Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC

Xinzhou Huang and Kai Yang

Data sets

DSCOVR EPIC Level 2 O3SO2AI NASA/LARC/SD/ASDC https://doi.org/10.5067/EPIC/DSCOVR/L2_O3SO2AI.003

ESA SEOM-IAS - Measurement and ACS database O3 UV region (II) M. Birk and G. Wagner https://doi.org/10.5281/zenodo.4423918

ESA SEOM-IAS - Measurement and ACS database SO2 UV region (Version 1) M. Birk and G. Wagner https://doi.org/10.5281/zenodo.1492582

Short summary

This paper describes the algorithm for O₃ and SO₂ retrievals from DSCOVR EPIC. Algorithm advances, including the improved O₃ profile representation and the regulated direct fitting inversion technique, improve the accuracy of O₃ and SO₂ from the multi-channel measurements of DSCOVR EPIC. A thorough error analysis is provided to quantify O₃ and SO₂ retrieval uncertainties due to various error sources and simplified algorithm physics treatments.