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Abstract: One of the most frequently applied methods for integrating controls on primary production through satellite data is the light use efficiency (LUE) approach, which links vegetation gross or net primary productivity (GPP or NPP) to remotely sensed estimates of absorbed photosynthetically active radiation (APAR). Eddy covariance towers provide continuous measurements of carbon flux, presenting an opportunity for evaluation of satellite estimates of GPP. Here we investigate relationships between eddy covariance estimated GPP, environmental variables derived from flux towers, Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and GPP across African savanna ecosystems. MODIS GPP was found to underestimate GPP at the majority of sites, particularly at sites in the Sahel. EVI was found to correlate well with estimated GPP on a site-by-site basis. Combining EVI with tower-measured PAR and evaporative fraction (EF, a measure of water sufficiency) improved the direct relationship between GPP and EVI at the majority of the sites. The slope of this relationship was strongly related to site peak leaf area index (LAI). These results are promising for the extension of GPP through the use of remote sensing data to a regional or even continental scale. [Copyright &y& Elsevier]

Summary: The SEtHyS_Savannah model [Saux-Picart et al., submitted for publication. SEtHyS_Savannah: a multiple source land surface model applied to sahelian landscapes. Agricultural and Forest Meteorology] was developed as an extension of the SEtHyS land surface model to simulate the water and energy fluxes over dry savannah landscapes. The vegetation cover is represented by a two layer model and a mulch approach is used for the soil description. The SEtHyS_Savannah model was regionalized over the AMMA-Niger super-site (about 50km by40km), with the help of remote sensing data. The model uses a regular 1km grid and each cell is divided in sub-grid patches in order to represent land cover and soil heterogeneities (tile approach). The vegetation cover parameters were prescribed according to the land cover map and the seasonal evolution of the Leaf Area Index (LAI), both derived from SPOT-HRV (Satellite Pour l’Observation de la Terre – High Resolution Visible) data imagery. The atmospheric forcing was assumed homogeneous over the area and provided by a meteorological station installed at the Fakara experimental site. The surface water and energy budgets were simulated over a one-year period (2005) at a 5-min time step and validated against MSG-SEVIRI (Meteosat Second Generation – Spinning Enhanced Visible and Infra-red Imager) land surface temperature and ENVISAT-ASAR (ENVIronnement SATellite – Advanced Synthetic Aperture Radar) soil humidity products. The results show realistic surface fluxes and good agreement with the MSG-SEVIRI temperature observations. The soil moisture comparison presents significant correlation but large root mean square errors. These discrepancies are the consequence of both the use of a non-spatialized atmospheric forcing and to residual vegetation effects on the radar signal. Despite these uncertainties, the results increase confidence in the model representation of Sahelian soil–vegetation processes and open new perspectives to quantify the effects of vegetation changes on evapotranspiration and runoff over the region. [Copyright &y& Elsevier]

Summary: The analysis of feedback effects between continental surfaces and the atmosphere is a key element in the understanding of African monsoon dynamics. For this reason, the monitoring of surface parameters, in particular soil moisture, is essential. Satellite remote sensing appears to be the most suitable means of obtaining data relevant to such parameters. The present paper presents the results of statistical analysis of soil moisture products based on data recorded by the ERS scatterometer, over the period 1992–2006, from two sites in Niger and Mali in the Sahel climatic region. Soil moisture products were validated over these two sites using ground data measurements and ASAR/ENVISAT estimations. The soil moisture distribution during the monsoon period is described, and the temporal correlation between estimated soil moisture levels is computed. Finally, the dynamics of cells corresponding to precipitation events and high surface moisture values were evaluated in the studied regions, thereby revealing variations during the monsoon period as well as site specific trends. [Copyright &y& Elsevier]

Summary: This paper deals with the issue of using scintillometry in conjunction with a simple aggregation scheme to derive area-averaged sensible and latent heat fluxes over a small watershed in Niamey, Niger (Wankama catchment). Data collected in the context of the African Monsoon Multidisciplinary Analysis (AMMA) program has been used to test the proposed approach. For this purpose, a Large Aperture Scintillometer (LAS) was set up over heterogeneous surface transect of about 3.2km spanning three vegetation types. The comparison between scintillometer-based estimates of area-averaged sensible heat fluxes and those measured by a network of the classical eddy covariance (EC) devices showed good agreement, with a relative error of about 20% (R 2 =0.85, RMSD=22Wm−2, and SEE=21.39Wm−2). This is a good result considering the contrast in terms of the footprint scales associated with the two devices, which is amplified by the heterogeneity of the catchment. The results also showed that using the LAS-derived values of area-average sensible heat flux in conjunction with a simple aggregation rule to estimate area-average available energy led to a reasonable prediction of area-averaged latent heat flux (R 2 =0.75, RMSD=64Wm−2 and SEE=50Wm−2), when compared to those measured using the EC network. This is of interest since the LAS can potentially be used to validate estimates of surface fluxes, based on the meso-scale model, as well as those estimated using coarse-scale remote sensing-based algorithm. [Copyright &y& Elsevier]