TY - JOUR
T1 - New land surface albedo parameterization based on MODIS data
T2 - Remote Sensing and Modeling of Ecosystems for Sustainability
AU - Liang, Xin Zhong
AU - Xu, Min
AU - Gao, Wei
AU - Kunkel, Kenneth
AU - Slusser, James
AU - Dai, Yongjiu
AU - Min, Qilong
PY - 2004
Y1 - 2004
N2 - A new parameterization of snow-free land surface albedo is developed using the MODerate resolution Imaging Spectroradiometer (MODIS) products of broadband black-sky and white-sky reflectance and vegetation information as well as the North American and Global Land Data Assimilation System (LDAS) outputs of soil moisture during 2000-2003. It represents the predictable albedo dependences on solar zenith angle, surface soil moisture, fractional vegetation cover, and leaf plus stem area index, while including a statistic correction for static effects specific of local surface characteristics. All parameters are estimated by solving optimization problems of a physically-based conceptual model for the minimization of the bulk variances between simulations and observations. A preliminary result showed that, for composites of all temporal and spatial samples of a same land cover category over North America, correlation coefficients between the new parameterization with the MODIS data range from 0.6 to 0.9, while relative errors vary within 5-20%. This is a substantial improvement over the existing state-of-the-art Common Land Model (CLM) albedo scheme, which has correlation coefficients from -0.5 to 0.5 and relative errors of 20-100%.
AB - A new parameterization of snow-free land surface albedo is developed using the MODerate resolution Imaging Spectroradiometer (MODIS) products of broadband black-sky and white-sky reflectance and vegetation information as well as the North American and Global Land Data Assimilation System (LDAS) outputs of soil moisture during 2000-2003. It represents the predictable albedo dependences on solar zenith angle, surface soil moisture, fractional vegetation cover, and leaf plus stem area index, while including a statistic correction for static effects specific of local surface characteristics. All parameters are estimated by solving optimization problems of a physically-based conceptual model for the minimization of the bulk variances between simulations and observations. A preliminary result showed that, for composites of all temporal and spatial samples of a same land cover category over North America, correlation coefficients between the new parameterization with the MODIS data range from 0.6 to 0.9, while relative errors vary within 5-20%. This is a substantial improvement over the existing state-of-the-art Common Land Model (CLM) albedo scheme, which has correlation coefficients from -0.5 to 0.5 and relative errors of 20-100%.
UR - http://www.scopus.com/inward/record.url?scp=15844366955&partnerID=8YFLogxK
U2 - 10.1117/12.563449
DO - 10.1117/12.563449
M3 - Conference article
AN - SCOPUS:15844366955
SN - 0277-786X
VL - 5544
SP - 55
EP - 60
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
M1 - 41
Y2 - 2 August 2004 through 4 August 2004
ER -