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An evaluation of the NOAA global daily gap-filled VIIRS surface albedo.

Authors :
Peng, Jingjing
Yu, Peng
Yu, Yunyue
Jia, Aolin
Wang, Dongdong
Wang, Heshun
Wang, Zhihao
Source :
Remote Sensing of Environment. Dec2023, Vol. 298, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The land surface albedo product of visible infrared imaging radiometer suite (VIIRS) in National Oceanic and Atmospheric Administration (NOAA)'s operational system provides real-time, global daily mean surface albedo, which is a required parameter in the estimation of the daily shortwave net radiation budget. The global gridded VIIRS albedo product is derived from the level-2 granule surface albedo product, which is generated using a Direct Estimation Method. Special gridding and compositing algorithms were developed for aggregating the granular albedo data into the gridded albedo product. This paper describes the design and evaluation of the NOAA VIIRS gridded daily surface albedo product. The cloudy condition, retrieval path, retrieval method, and observing geometry are the criteria in deciding the priority order in the composition processing. The proposed albedo product possesses a complete spatial coverage over global land and ice surface and provides a timely response to surface dynamics. The validation of satellite retrieved daily mean albedo against ground counterparts over a series of well-maintained networks demonstrates the reliability of the composed albedo considering the interference of the seasonal surface heterogeneity conditions around each site. The inter-comparison between the S-NPP and NOAA-20 VIIRS albedo shows good agreement, except for a minor bias related to solar/view angle differences. The cross-comparison between VIIRS albedo and MODIS albedo shows good consistency with some deviations related to the controversy between their upstream snow mask. • Daily global gap-free albedo product from VIIRS operational at NOAA. • Direct estimation of albedo using clear-sky observations. • Comprehensive validation with in-situ observations indicates good product quality. • Major sources of product uncertainty and their mitigation are discussed. • Products from SNPP and NOAA-20 are highly consistent. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
298
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
173097604
Full Text :
https://doi.org/10.1016/j.rse.2023.113822