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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-345
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-345
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 21 Oct 2019

Submitted as: research article | 21 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Cloud Detection over Snow and Ice with Oxygen A- and B-band Observations from the Earth Polychromatic Imaging Camera (EPIC)

Yaping Zhou1,2, Yuekui Yang1, Meng Gao1,3, and Peng-Wang Zhai4 Yaping Zhou et al.
  • 1NASA Goddard Space Flight Center, Greenbelt, MD
  • 2JCET/Universityof Maryland Baltimore County, Baltimore, MD
  • 3SSAI/NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Greenbelt, MD, USA
  • 4JCET/Department of Physics, University of Maryland Baltimore County,Baltimore, MD, 21250, USA

Abstract. Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; cloud mask algorithms often heavily rely on shortwave IR channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow/ice even more challenging. This study investigates the methodology of applying EPIC’s two oxygen absorption band pair ratios in A-band (764 nm, 780 nm) and B-band (688 nm, 680 nm) for cloud detection over the snow and ice surfaces. An elevation and zenith angle-dependent threshold scheme has been developed based on radiative transfer model simulations. The new scheme achieves significant improvement over the existing algorithm that imposes fixed thresholds for the A-band and B-band ratios. The positive detection rate nearly doubled from around 36 % to 70 % while the false detection rate dropped from 50 % to 15 % in January 2016 and 2017. The improvement during the summer months is less significant due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 2.5 km because the sensitivity is low in oxygen band ratios for these cases.

Yaping Zhou et al.
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Yaping Zhou et al.
Data sets

DSCOVR EPIC Level 2 Cloud Products Y. Yang, K. Meyer, G. Wind, A. Marshak, S. Platnick, Q. Min, and A. B. Davis https://doi.org/10.5067/EPIC/DSCOVR/L2_Cloud_01

DSCOVR_EPIC_L1B_2 K. Blank https://doi.org/10.5067/EPIC/DSCOVR/L1B.002

Yaping Zhou et al.
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Short summary
Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces;The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC’s two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.
Satellite cloud detection over snow and ice has been difficult for passive remote sensing...
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