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Analysis of Global Land Surface Shortwave Broadband Albedo From Multiple Data Sources

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5 Author(s)
Xiaotong Zhang ; Sch. of Resource & Environ. Sci., Wuhan Univ., Wuhan, China ; Shunlin Liang ; Kaicun Wang ; Lin Li
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Land surface shortwave albedo plays a central role in global and regional climate modeling. In this study, we analyzed the land surface shortwave broadband albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2008. The statistical results are obtained using MODIS Collection 5 land surface albedo (MCD43C3), land cover (MOD12C1) datasets, and Global Energy and Water-cycle Experiment (GEWEX) surface radiation data. The results include all nine-year shortwave Black-Sky albedo (BSA) and White-Sky albedo (WSA) variability for global, Northern Hemisphere (NH), Southern Hemisphere (SH), and 15 International Geosphere-Biosphere Program (IGBP) ecosystem surface types; each has a discernible signature. We also compared spatial and temporal variations of MODIS albedos with other datasets: International Satellite Cloud Climatology Project (ISCCP), 21 Global Circulation Models (GCMs)-which were used in the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC-AR4)-and GEWEX albedos. The comparison results show that most GCM-simulated albedos are lower than the remotely sensed MODIS data. The MODIS-based global average land surface albedo is 0.24, and has its peak value in the winter and lowest in summer. Comparison of global albedo anomalies from MODIS shows a small decrease of ~ 0.01 during these years in the Northern Hemisphere (NH), and increases of ~ 0.01 in the Southern Hemisphere (SH). Moreover, the map of the nine-year global MODIS albedo, and normalized difference vegetation index (NDVI) variation trends, are correlated in this paper. We also summarize global and zonal albedos for different IGBP land surface classes, and present the global and zonal albedos under both snow-covered and snow-free conditions.

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Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  (Volume:3 ,  Issue: 3 )