Using the NDVI as auxiliary data for rapid quality assessment of rainfall estimates in Africa

Rainfall estimates derived from satellite imagery and global circulation models are frequently used for vegetation monitoring in many areas of Africa because of the shortage of observed rainfall data and the sparse network of meteorological stations. At the same time, this scarce density of rain gauge stations makes the calibration and validation of the modelled data nearly impossible. In this study we propose a methodology for a rapid quality assessment of rainfall estimates that is based on the well-known relationship between rainfall and the Normalized Difference Vegetation Index (NDVI). The results clearly confirm that the NDVI can be used as an indicator of the quality of rainfall estimates at the continental/regional scale and allow a rapid detection of major over- and underestimations of the two rainfall datasets examined for the African continent.