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https://doi.org/10.5194/amt-2018-137
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
25 May 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Screening for Snow/Snowmelt in SNPP VIIRS Aerosol Optical Depth Algorithm
Jingfeng Huang1,2,a, Istvan Laszlo2,3, Lorraine A. Remer4, Hongqing Liu2,5, Hai Zhang2,5, Pubu Ciren2,5, and Shobha Kondragunta2 1Earth Resources Technology Inc., Laurel, MD, USA
2National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, College Park, MD, USA
3Department of Atmospheric and Oceanic Science, University of Maryland, College Park, Maryland, USA
4Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, USA
5I. M. Systems Group, Inc., College Park, MD, USA
apreviously at: Earth System Science Interdisciplinary Center (ESSIC)/Cooperative Institute for Climate and Satellites (CICS)-Maryland, University of Maryland, College Park, MD, USA
Abstract. The Visible/Infrared Imaging/Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft provides validated daily global aerosol optical thickness (AOT) retrievals; however, a close examination of the VIIRS aerosol product identified residual snow and snowmelt contamination, resulting generally in an overestimation of AOT. The contamination was particularly evident over northern hemisphere high latitude regions during the spring thaw. To improve the product performance, we introduced a new empirical snow and snowmelt screening scheme that combines a Normalized Difference Snow Index (NDSI) and Brightness Temperature (BT) based snow test, a snow adjacency test and a spatial homogeneity test (aka. spatial filter). Testing of retrievals for May 18, 2014 indicated that compared to the previous, visible reflectance anomaly (VRA) based snow test, the new NDSI and BT based snow test screened out an additional 3.44 % of VIIRS AOT retrievals, most of which were over high latitudes experiencing snowmelt. The new snow adjacency test and the homogeneity test degraded another 5.57 % and 0.26 %, respectively, otherwise Good quality AOT retrievals. For the VIIRS vs. AERONET matchups over northern hemisphere high latitude regions during three years of spring (2013–2015), the new scheme also effectively screened out a significant number of the matchups that had anomalous high positive biases attributable to snow and snowmelt contamination. The new snow and snowmelt screening scheme was transferred to the Interface Data Processing Segment (IDPS) VIIRS aerosol algorithm on Jun 22, 2015. Subsequently no significant snow and snowmelt contamination was found during spring 2016. The scheme is also implemented in the new Enterprise VIIRS aerosol algorithm in the National Oceanic and Atmospheric Administration (NOAA) Enterprise Processing System (EPS) that became operational in 2017.
Citation: Huang, J., Laszlo, I., Remer, L. A., Liu, H., Zhang, H., Ciren, P., and Kondragunta, S.: Screening for Snow/Snowmelt in SNPP VIIRS Aerosol Optical Depth Algorithm, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-137, in review, 2018.
Jingfeng Huang et al.
Jingfeng Huang et al.
Jingfeng Huang et al.

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Short summary
A new snow/snowmelt screening approach, combining normalized difference snow index (NDSI) and brightness temperature (BT) based snow test, snow adjacency test and spatial filter, is proposed to significantly reduce the snow/snowmelt contamination in the NOAA’s operational Visible/Infrared Imaging/Radiometer Suite (VIIRS) aerosol optical thickness (AOT) product, particularly over northern hemisphere high latitude regions during spring thaw.
A new snow/snowmelt screening approach, combining normalized difference snow index (NDSI) and...
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