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  • Author or Editor: Sietse O. Los x
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Caroline J. Houldcroft, William M. F. Grey, Mike Barnsley, Christopher M. Taylor, Sietse O. Los, and Peter R. J. North


New values are derived for snow-free albedo of five plant functional types (PFTs) and the soil/litter substrate from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board Terra and Aqua. The derived albedo values are used to provide and test an improved specification of surface albedo for the land surface scheme known as the Joint U.K. Land Environment Simulator (JULES) that forms part of the Hadley Centre Global Environmental Model (HadGEM) climate model. The International Geosphere–Biosphere Programme (IGBP) global land cover map is used in combination with the MODIS albedo to estimate the albedo of each cover type in the IGBP classification scheme, from which the albedo values of the JULES PFTs are computed. The albedo of the soil/litter substrate, referred to as the soil background albedo, is derived from partially vegetated regions using a method that separates the vegetation contribution to the albedo signal from that of the soil/litter substrate. The global fields of soil background albedo produced using this method exhibit more realistic spatial variations than the soil albedo map usually employed in conjunction with the JULES model. The revised total shortwave albedo values of the PFTs are up to 8% higher than those in the existing HadGEM scheme. To evaluate the influence of these differences upon surface albedo in the climate model, differences are computed globally between mean monthly land surface albedo, modeled using the existing and revised albedo values, and MODIS data. Incorporating the revised albedo values into the model reduces the global rmse for snow-free July land surface albedo from 0.051 to 0.024, representing a marked improvement on the existing parameterization.

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Armel Thibaut Kaptué Tchuenté, Jean-Louis Roujean, Agnès Bégué, Sietse O. Los, Aaron A. Boone, Jean-François Mahfouf, Dominique Carrer, and Badiane Daouda


Information related to land surface is immensely important to global change science. For example, land surface changes can alter regional climate through its effects on fluxes of water, energy, and carbon. In the past decades, data sources and methodologies for characterizing land surface heterogeneity (e.g., land cover, leaf area index, fractional vegetation cover, bare soil, and vegetation albedos) from remote sensing have evolved rapidly. The double ECOCLIMAP database—constituted of a land cover map and land surface variables and derived from Advanced Very High Resolution Radiometer (AVHRR) observations acquired between April 1992 and March 1993—was developed to support investigations that require information related to spatiotemporal dynamics of land surface. Here is the description of ECOCLIMAP-II: a new characterization of the land surface heterogeneity based on the latest generation of sensors, which represents an update of the ECOCLIMAP-I database over Africa. Owing to the many features of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors (more accurate in spatial resolution and spectral information compared to the AVHRR sensor), a variety of methods have been developed for an extended period of 8 yr (2000–07) to strengthen consistency between land surface variables as required by the meteorological and ecological communities. The relative accuracy (or performance) quality of ECOCLIMAP-II was assessed (i.e., by comparison with other global datasets). Results illustrate a substantial refinement; for instance, the fractional vegetation cover resulting in a root-mean-square error of 34% instead of 64% in comparison with the original version of ECOCLIMAP.

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