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8.14.14 Chen

CLOUD MASK ALGORITHM FOR SNOW/ICE COVERED SURFACES AND THE VALIDATION USING CALIOP OBSERVATIONS OVER GREENLAND

Nan Chen, NIA Visitor and Stevens Institute of Technology
August 14, 2014, 1:00 pm, NIA, Rm 137
Host: Yongxiang Hu (NASA Langley)

Abstract:
Cloud detection is a critically important first step required to derive many satellite data products. A novel cloud detection algorithm designed for the cryosphere mission of GCOM-C1/SGLI is presented. This reflectance-based cloud detection scheme mainly utilizes only two SWIR channels with dynamic thresholds that depend on sun-satellite viewing geometry
to perform accurate cloud detection over snow/ice surfaces in high-latitude as well as high elevation regions. Profiles of atmospheric absorbing and scattering molecules as well as surface elevation are considered in the determination of the thresholds for the resulting Snow/ice Cloud Mask (SCM) algorithm. Image-based tests and statistical results have been used to validate the performance of the SCM over the Greenland plateau. Statistics using collocated CALIOP and MODIS Aqua observations over Greenland in 2007 show that over snow/ice surfaces the performance of the SCM is generally better than that of the MODIS Cloud Mask.

Bio:
Nan Chen was born in Wuhan, China in 1983. He received the B.S. degree in Wuhan University, China, in 2005, and the M.S. in Nanjing University, China in 2008. Now he is pursuing his Ph.D at the Light and Life Lab (LLLab) of Stevens Institute of Technology and expecting to graduate in a few months.

His main interest in research is atmospheric radiation and the scattering and absorption by snow/ice, clouds and aerosols. He attended the GCOM-C/SGLI project of Japan Aerospace eXploration Agency (JAXA) since 2010, designed the cloud mask as well as the snow albedo retrieval algorithm for snow and ice covered areas

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