Abstract
The surface albedo is an essential climate variable that is considered in many applications used for predicting climate and understanding the mechanisms of climate change. In this study, surface albedo was estimated using a bidirectional reflectance distribution function model based on Communication, Ocean and Meteorological Satellite/Meteorological Imager data. Geostationary orbiting satellite data are suitable for a level 2 product like albedo, which requires a synthetic process to estimate. The authors modified established methods to consider the geometry of the solar-surface-sensor of COMS/MI. Of note, the viewing zenith angle term was removed from the kernel integration used for estimating spectral albedo. Finally, the spectral (narrow) albedo was converted into the broadband albedo with shortwave length (approximately 0.3–2.5 μm). This study determined conversion coefficients using only one spectral albedo of visible channel. The estimated albedo had a relatively high correlation with Satellite Pour l’Observation de la Terre/Vegetation and low unweighted error values specific for land types or times. The validation results show that estimated albedo has a root mean square error of 0.0134 at Jeju flux site that indicates accuracy similar to that of other satellite-based products.
Original language | English |
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Pages (from-to) | 38-62 |
Number of pages | 25 |
Journal | GIScience and Remote Sensing |
Volume | 55 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2018 Jan 2 |
Bibliographical note
Funding Information:This study was supported by the National Meteorological Satellite Center [Project No. 153-31003137-301-210-13] of Korea Meteorological Administration (KMA) and ?Development of Scene Analysis & Surface Algorithms? project, funded by ETRI, which is a subproject of ?Development of Geostationary Meteorological Satellite Ground Segment [NMSC-2016-01]? program funded by NMSC (National Meteorological Satellite Center) of KMA (Korea Meteorological Administration). This study was supported by the National Meteorological Satellite Center [Project No. 153-31003137-301-210-13] of Korea Meteorological Administration (KMA) and ?Development of Scene Analysis & Surface Algorithms? project, funded by ETRI, which is a subproject of ?Development of Geostationary Meteorological Satellite Ground Segment [NMSC-2017-01]? program funded by NMSC (National Meteorological Satellite Center) of KMA (Korea Meteorological Administration).We thank the National Institute of Forest Science (NIFS) for providing Flux data.
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)