Parameterization of snow-free land surface albedo as a function of vegetation phenology based on MODIS data and applied in climate modelling

The aim of this study was to develop an advanced parameterization of the snow-free land surface albedo for climate modelling describing the temporal variation of surface albedo as a function of vegetation phenology on a monthly time scale. To estimate the effect of vegetation phenology on snow-free land surface albedo, remotely sensed data products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra platform measured during 2001 to 2004 are used. The snow-free surface albedo variability is determined by the optical contrast between the vegetation canopy and the underlying soil surface. The MODIS products of the white-sky albedo for total shortwave broad bands and the fraction of absorbed photosynthetically active radiation (FPAR) are analysed to separate the vegetation canopy albedo from the underlying soil albedo. Global maps of pure soil albedo and pure vegetation albedo are derived on a 0.5° regular latitude/longitude grid, re-sampling the high-resolution information from remote sensing-measured pixel level to the model grid scale and filling up gaps from the satellite data. These global maps show that in the northern and mid-latitudes soils are mostly darker than vegetation, whereas in the lower latitudes, especially in semi-deserts, soil albedo is mostly higher than vegetation albedo. The separated soil and vegetation albedo can be applied to compute the annual surface albedo cycle from monthly varying leaf area index. This parameterization is especially designed for the land surface scheme of the regional climate model REMO and the global climate model ECHAM5, but can easily be integrated into the land surface schemes of other regional and global climate models.