The Visible Infrared Imager Radiometer Suite (VIIRS) Cloud Mask (VCM) determines, on a pixel-by-pixel basis, whether or not a given location contains cloud. The VCM serves as an intermediate product (IP) between the production of VIIRS sensor data records and 22 downstream Environmental Data Records that each depends upon the VCM output. As such, the validation of the VCM IP is critical to the success of the Suomi National Polar-orbiting Partnership (S-NPP) product suite. The methods used to validate the VCM and the current results are presented in this paper. Detailed analyses of golden granules along with tools providing deep insights into granule performance, and specific cloud detection tests reveal the details behind a given granule's performance. Matchup results with CALIPSO, in turn, indicate the large-scale performance of the VCM and whether or not it is meeting its specifications. Comparisons with other cloud masks indicate comparable performance for the determination of clear pixels. As of September 2013 the VCM is either meeting or within 2% of all of its documented requirements.
A geometry-based approach is presented to identify cloud shadows using an automated cloud classification algorithm developed for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. These new procedures exploit both the cloud confidence and cloud phase intermediate products generated by the Visible/Infrared Imager/Radiometer Suite (VIIRS) cloud mask (VCM) algorithm. The procedures have been tested and found to accurately detect cloud shadows in global datasets collected by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are applied over both land and ocean background conditions. These new procedures represent a marked departure from those used in the heritage MODIS cloud mask algorithm, which utilizes spectral signatures in an attempt to identify cloud shadows. However, they more closely follow those developed to identify cloud shadows in the MODIS Surface Reflectance (MOD09) data product. Significant differences were necessary in the implementation of the MOD09 procedures to meet NPOESS latency requirements in the VCM algorithm. In this paper, the geometry-based approach used to predict cloud shadows is presented, differences are highlighted between the heritage MOD09 algorithm and new VIIRS cloud shadow algorithm, and results are shown for both these algorithms plus cloud shadows generated by the spectral-based approach. The comparisons show that the geometry-based procedures produce cloud shadows far superior to those predicted with the spectral procedures. In addition, the new VCM procedures predict cloud shadows that agree well with those found in the MOD09 product while significantly reducing the execution time as required to meet the operational time constraints of the NPOESS system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.