Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 13, issue 10
Articles | Volume 13, issue 10
https://doi.org/10.5194/amt-13-5259-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-5259-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 10
Research article
 | 
06 Oct 2020
Research article |  | 06 Oct 2020

Cloud-top pressure retrieval with DSCOVR EPIC oxygen A- and B-band observations

Bangsheng Yin, Qilong Min, Emily Morgan, Yuekui Yang, Alexander Marshak, and Anthony B. Davis

Data sets

DSCOVR EPIC Level 1B Version 2 NASA LARC ASDC DAAC (Langley Research Center's Atmospheric Science Data Center Distributed Active Archive Centers): https://doi.org/10.5067/EPIC/DSCOVR/L1B.002

Earth Observations from DSCOVR EPIC Instrument A. Marshak, J. Herman, S. Adam, S. Carn, A. Cede, I. Geogdzhayev, D. Huang, L. K. Huang, Y. Knyazikhin, M. Kowalewski, and N. Krotkov https://doi.org/10.1175/BAMS-D-17-0223.1

DSCOVR EPIC Cloud Products NASA LARC ASDC DAAC (Langley Research Center's Atmospheric Science Data Center Distributed Active Archive Centers) https://doi.org/10.5067/EPIC/DSCOVR/L2_Cloud_01

Surface reflectivity climatologies from UV to NIR determined from Earth observations by GOME-2 and SCIAMACHY L. G. Tilstra, P. Wang, and P. Stammes https://doi.org/10.1002/2016JD025940

Data product: LIDAR Level2 Version 4.20 5-km Cloud Layer NASA LARC https://subset.larc.nasa.gov/calipso/index.php

Fully automated analysis of space-based lidar data: An overview of the CALIPSO retrieval algorithms and data products Mark A. Vaughan, Stuart A. Young, David M. Winker, Kathleen A. Powell, Ali H. Omar, Zhaoyan Liu, Yongxiang Hu, and Chris A. Hostetler https://doi.org/10.1117/12.572024

GOME-2 surface LER Tropospheric Emission Monitoring Internet Service (TEMIS) http://temis.nl/surface/gome2_ler/databases/

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Short summary
Cloud-top pressure (CTP) is an important cloud property for climate and weather studies. Based on differential oxygen absorption, both oxygen A-band and B-band pairs can be used to retrieve CTP. However, it is currently very challenging to perform a CTP retrieval accurately due to the complicated in-cloud penetration effect. To address this issue, we propose an analytic transfer inverse model for DSCOVR EPIC observations to retrieve CTP considering in-cloud photon penetration.
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