An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations

Sun, Kang; Yousefi, Mahdi; Chan Miller, Christopher; Chance, Kelly; González Abad, Gonzalo; Gordon, Iouli E.; Liu, Xiong; O'Sullivan, Ewan; Sioris, Christopher E.; Wofsy, Steven C.

doi:https://doi.org/10.5194/amt-15-3721-2022

Articles | Volume 15, issue 12

https://doi.org/10.5194/amt-15-3721-2022

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

https://doi.org/10.5194/amt-15-3721-2022

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

Articles | Volume 15, issue 12

Research article

|

23 Jun 2022

Research article |

| 23 Jun 2022

An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations

Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy

Data sets

Level 2 data for SCIAMACHY airglow retrieval in 2010 Kang Sun https://doi.org/10.7910/DVN/T1WRWQ

Model code and software

Kang-Sun-CfA/Methane: airglowOE.py for the AMT paper (1.1) Kang Sun https://doi.org/10.5281/zenodo.6658123

Short summary

This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO₂ in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.