作者:Feng, YB (Feng, Youbin)[ 1 ] ; Liu, Q (Liu, Qiang)[ 1 ] ; Qu, Y (Qu, Ying)[ 1,2 ] ; Liang, SL (Liang, Shunlin)[ 3,4 ]

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

卷: 54  期: 2  页: 850-868

DOI: 10.1109/TGRS.2015.2468054

出版年: FEB 2016

摘要

Ocean water albedo (OWA) plays an important role in the global climate variation. Compared with the achievements in land surface albedo studies, the global distributions of ocean water and sea ice albedo are seldom addressed. This study designed an operational global OWA algorithm based on the three-component reflectance model of the ocean water: sun glint, whitecaps, and water-leaving reflectance. The related achievements in these three areas are reviewed and integrated into the operational algorithm. After the sensitive analysis, the algorithm is compared with previous studies and validated with ground observations at COVE site located 25 km east of Virginia Beach (36.91 degrees N, 75.71 degrees W), and the results indicate that the proposed algorithm is generally consistent with previous parameterization scheme. As an example, the global OWAs in summer and winter 2011 are generated using the remote sensing reflectance data sets via the Moderate Resolution Imaging Spectroradiometer and Modern-Era Retrospective analysis for Research and Applications meteorological reanalysis data set. The generated product includes instantaneous (e.g., local noon) and daily mean OWAs under both clear-sky and white-sky conditions. Upon the examples, the local noon clear-sky OWA shows a significant latitude variation due to the dominance of the solar angle, whereas the white-sky OWA is sensitive to wind speeds and optical constituents. The global distribution of the daily mean OWA exhibits a similar trend to the local noon OWA. However, the daily mean clear-sky OWA is significantly larger than the local noon OWA; this finding should be noted when using OWA products for energy balance research. Additionally, all forms of OWA products exhibit increase in coastal areas with high input of terrestrial matters.

通讯作者地址: Feng, YB; Liu, Q (通讯作者)

Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

通讯作者地址: Qu, Y (通讯作者)

NE Normal Univ, Sch Geog Sci, Changchun 130024, Peoples R China.

通讯作者地址: Liang, SL (通讯作者)

Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China.

通讯作者地址: Liang, SL (通讯作者)

Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.

地址:

[ 1 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] NE Normal Univ, Sch Geog Sci, Changchun 130024, Peoples R China

[ 3 ] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China

[ 4 ] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA