Development of land surface albedo parameterization based on Moderate Resolution Imaging Spectroradiometer (MODIS) data

[1] A new dynamic-statistical 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 and the North American and Global Land Data Assimilation System (LDAS) outputs of soil moisture during 2000–2003. The dynamic component represents the predictable albedo dependences on solar zenith angle, surface soil moisture, fractional vegetation cover, leaf plus stem area index, and greenness, while the statistical part represents the correction for static effects that are specific to local surface characteristics. All parameters of the dynamic and statistical components are determined by solving nonlinear constrained optimization problems of a physically based conceptual model for the minimization of the bulk variances between simulations and observations. They all depend on direct beam or diffuse radiation and visible or near-infrared band. The dynamic parameters are also functions of land cover category, while the statistical factors are specific to geographic location. The new parameterization realistically represents surface albedo variations, including the mean, shape, and distribution, around each dependent parameter. For composites of all temporal and spatial samples of the same land cover category over North America, correlation coefficients between the dynamic component of the new parameterization and the MODIS data range from 0.39 to 0.88, while relative errors vary within 8–42%. The gross (i.e., integrated over all categories) correlations and errors are 0.57–0.71 and 17–26%, changing with direct beam or diffuse radiation and visible or near-infrared band. The static local correction results in a further reduction in relative errors, producing gross values of 11–21%. The new parameterization is a marked improvement over the existing albedo scheme of the state-of-the-art Common Land Model (CLM), which has correlation coefficients from −0.57 to 0.71 and relative errors of 18–140% for individual land cover categories, and gross values of 0.03–0.32 and 37–71%, respectively.

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