DOAJ Open Access 2018

Surface albedo from the geostationary Communication, Ocean and Meteorological Satellite (COMS)/Meteorological Imager (MI) observation system

Chang Suk Lee Kyung-Soo Han Jong-Min Yeom Kyeong-sang Lee Minji Seo +7 lainnya

Abstrak

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.

Penulis (12)

C

Chang Suk Lee

K

Kyung-Soo Han

J

Jong-Min Yeom

K

Kyeong-sang Lee

M

Minji Seo

J

Jinkyu Hong

J

Je-Woo Hong

K

Keunmin Lee

J

Jinho Shin

I

In-Chul Shin

J

Junghwa Chun

J

Jean-Louis Roujean

Format Sitasi

Lee, C.S., Han, K., Yeom, J., Lee, K., Seo, M., Hong, J. et al. (2018). Surface albedo from the geostationary Communication, Ocean and Meteorological Satellite (COMS)/Meteorological Imager (MI) observation system. https://doi.org/10.1080/15481603.2017.1360578

Akses Cepat

Informasi Jurnal
Tahun Terbit
2018
Sumber Database
DOAJ
DOI
10.1080/15481603.2017.1360578
Akses
Open Access ✓