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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Dec 2018

Research article | 21 Dec 2018

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

Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: Hourly results from EPIC/DSCOVR satellite in deep space

Xiaoguang Xu1,2, Jun Wang1, Yi Wang1, Jing Zeng1, Omar Torres3, Jeffrey S. Reid4, Steven D. Miller5, J. Vanderlei Martins2, and Lorraine A. Remer2 Xiaoguang Xu et al.
  • 1Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Informatics Initiative, The University of Iowa, Iowa City, Iowa, 52241, USA
  • 2Joint Center for Earth Systems Technology and Department of Physics, University of Maryland Baltimore County, Baltimore, Maryland, 21250, USA
  • 3Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, 20770, USA
  • 4Marine Meteorology Division, Naval Research Laboratory, Monterey, California, 93943, USA
  • 5Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado, 80523, USA

Abstract. We present an algorithm for retrieving aerosol layer height (ALH) and aerosol optical depth (AOD) for smoke over vegetated land and water surfaces from measurements of the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR). The algorithm uses earth-reflected radiances in six EPIC bands in visible and near-infrared and incorporates flexible spectral fittings that account for specifics of land and water surface reflectivity. The fitting procedure first determines AOD using EPIC atmospheric window bands (443 nm, 551 nm, 680 nm, and 780 nm), then uses oxygen (O2) A and B bands (688 nm and 764 nm) to derive the ALH that represents an optical centroid altitude. ALH retrieval over vegetated surface primarily takes advantage of the measurements in the O2 B band. We applied the algorithm to EPIC observations of several biomass burning events over United State and Canada in August 2017. We found the algorithm can well capture AOD and ALH multiple times daily over water and vegetated land surface. Validations are performed against aerosol extinction profile detected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and AOD observed at nine Aerosol Robotic Network (AERONET) sites, showing, in average, an error of 0.58 km and a bias of −0.13 km in retrieved ALH and an error of 0.05 and a bias of 0.03 in retrieved AOD. Additionally, we show that the aerosol height information retrieved by the present algorithm can potentially benefit the retrieval of aerosol properties from the EPIC’s ultraviolet (UV) bands.

Xiaoguang Xu et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Xiaoguang Xu et al.
Xiaoguang Xu et al.
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Publications Copernicus
Short summary
Detecting aerosol layer height from space has been challenging. Tradition method relies on active sensors such as lidar that provides detailed vertical structure of aerosol profile, but is costly and has limited spatial coverage (it needs more than one year to have a global coverage). Here we developed a PASSIVE remote sensing technique that uses backscattered sunlight to retrieve smoke aerosol layer height over both water and vegetated surfaces from a sensor that is 1.5 M kms from the Earth.
Detecting aerosol layer height from space has been challenging. Tradition method relies on...