Land surface albedo is a key variable for characterising the energy balance in the coupled soil-vegetation-atmosphere system. The albedo quantifies the part of the energy that is absorbed and transformed into heat and latent fluxes. Owing to strong feedback effects the knowledge of albedo is important for determining weather conditions at the atmospheric boundary layer. Climate sensitivity studies with Global Circulation Models have confirmed the unsteady nature of the energy balance with respect to small changes in surface albedo. Other domains of applications are in hydro-meteorology, agro-meteorology and environment-related studies.
The characteristics and file format of this demonstration Data Record are the same as its correspondent NRT product. Thus documented by the common Algorithm Theoretical Basis Document (ATBD), Product User Manual document (PUM) and Product Output Format document (POF) documents. The validation results for this Data Record are available in the (VR) document.
Please see Product Peer-Review publications in References.
The use of LSA SAF products in publications is kindly requested to be duly acknowledged:
ALBEDO was provided by the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF; Trigo et al., 2011)
Trigo, I. F., C. C. DaCamara, P. Viterbo, J.-L. Roujean, F. Olesen, C. Barroso, F. Camacho-de Coca, D. Carrer, S. C. Freitas, J. García-Haro, B. Geiger, F. Gellens-Meulenberghs, N. Ghilain, J. Meliá, L. Pessanha, N. Siljamo, and A. Arboleda, 2011: The Satellite Application Facility on Land Surface Analysis. Int. J. Remote Sens., 32, 2725-2744, doi: 10.1080/01431161003743199
The MSG mission (in operations since 2004) already provides a relatively long time series of VIS and IR observations over the full Earth Disk centred at 0º. The full archive of MSG/SEVIRI data was reprocessed to provide the user comunity a consistent, homogeneous and continuous Data Record of the Daily Surface Albedo (MDAL) for the period 2004-2015.
This Data Record was obtained with the best version of its equivalent NRT product (MDAL) which can also complement the time series from 2016 onwards.