Rainfall Estimation in the Sahel: What Is the Ground Truth?

Areal rainfall estimation from ground sensors is essential as a direct input to various hydrometeorological models or as a validation of remote sensing estimates. More critical than the estimation itself is the assessment of the uncertainty associated with it. In tropical regions knowledge on this topic is especially scarce due to a lack of appropriate data. It is proposed here to assess standard estimation errors of the areal rainfall in the Sahel, a tropical region of notoriously unreliable rainfall, and to validate those errors using the data of the EPSAT– Niger experiment. A geostatistical framework is considered to compute theoretical variances of estimation errors for the event-cumulative rainfall, and rain gauge networks of decreasing density are used for the validation. As a result of this procedure, charts giving the standard estimation error as a function of the network density, the area, and the rainfall depth are proposed for the Sahelian region. An extension is proposed for larger timescales (decade, month, and season). The seasonal error is estimated as a product of the error at the event scale by a reduction coefficient, which is a function of the number K of recorded events and the probability distribution function of the point storm rain depth. For a typical network of 10 stations regularly dispatched over a 18 3 18 square, the relative estimation error decreases from 14% for an average storm rain depth of 16 mm to 5% for an average August rainfall of 160 mm. For a density comparable to that of the operational rain gauge network of southern Niger and similar Sahelian regions, the standard errors are, respectively, 26% at the event scale and 10%–15% at the monthly scale, depending on the number of events recorded during the month. The areas considered here are 18 3 18 and smaller, which makes a comparison with results obtained in previous studies for other regions of the world difficult since the reference area most often used in these studies is either 2.58 3 2.58 or 58 3 58. Further work is thus needed to extend the results presented here to larger spatial scales.