This article describes the algorithmic principles used to generate LAI, fAPAR and fCover estimates from VEGETATION observations. These biophysical variables are produced globally at 10 days temporal sampling interval under lat-lon projection at 1/112°spatial resolution. After a brief description of the VEGETATION sensors, radiometric calibration process, based on vicarious desertic targets is first presented. The cloud screening algorithm was then fine tuned using a global network of cloudiness observations. Atmospheric correction is then achieved using the SMAC code with inputs coming from meteorological values of pressure, ozone and water vapour. Aerosol optical thickness is derived from MODIS climatology assuming continental aerosol type. The Roujean BRDF model is then adjusted for red, near infrared and short wave infrared bands used to the remaining cloud free observations collected over a time window of ± 15 days. Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated and prior information is used to get more robust estimates of the three BRDF kernel coefficients. Nadir viewing top of canopy reflectance in the three bands is input to the biophysical algorithm to compute the products at 10 days sampling interval. This algorithm is based on training neural networks over SAIL + PROPSPECT radiative transfer model simulations for each biophysical variable. Details on the way the training data base was generated and the neural network designed and calibrated are presented. Finally, theoretical performances are discussed. Validation over ground measurement data sets and inter-comparison with other similar biophysical products are presented and discussed in a companion paper. The CYCLOPES products and associated detailed documentation are available at

The paper discusses an application of the TOPEX/Poseidon (T/P) altimetry data to estimate the discharge of one of the largest Arctic rivers-the Ob' river. We first discuss the methodology to select and retrieve the altimeter water levels during the various phases of the hydrological regime. Then we establish the relationships between the satellite-derived water levels and the in situ river discharge measurements at the Salekhard gauging station near the Ob' estuary. The comparison of in situ and satellite-derived estimations of the Ob' discharge at Salekhard shows that the T/P data can successfully be used for hydrological studies of this river. We address the problems affecting the accuracy of the discharge estimations from altimeter measurements, identify potential solutions and suggest how satellite altimetry data may benefit hydrological studies of Arctic rivers. (A.V. Kouraev).

[1] The variability of the Sahelian albedo is investigated through the combined analysis of 5 years of in situ radiation data from the African Monsoon Multidisciplinary Analysis northernmost sites and remotely sensed albedo from 7 years of Moderate Resolution Imaging Spectroradiometer data. Both data sets are found to be in good agreement in terms of correlation and bias. The drivers of albedo variability are identified by means of in situ measurements of biological and physical properties of the land surface collected over a network of 29 long-term survey sites. Short-term variability is dominated by changes in the spectral composition of incident radiation, which reflects aerosol optical depth and integrated water content, and changes in soil moisture, which have a short-lived effect (1 d). Bush fires cause a marked decrease of albedo of the order of 10 d, whereas a dry season storm event is suspected to have increased albedo through litter and soil surface abrasion. Seasonal plant growth causes the largest changes in rainy season albedo, and displays a large interannual variability: Because of the 2004 drought, albedo increases steadily from late 2003 to early 2005 at latitude 15°N. Grazing pressure is found to impact albedo mostly in the dry season. Dry season albedo is controlled by the amount of litter and standing dead phytomass hiding the bright soils. Thus rainfall anomalies have a direct effect on albedo through plant growth but also a lagged effect caused by above normal amounts of dry phytomass that can persist until the arrival of the next monsoon. EOF analysis and Hovmüller diagrams show these effects to be present on a large scale.

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