Optimal areal rainfall estimation using raingauges and satellite data

The main aim of this paper is to present a new method of areal rainfall est imation using satellite and ground-based data. This method involves optimal merging of the estimates provided by satellite information and estimates o btained from raingauges. In the merging procedure, each estimate is weighte d according to its uncertainty given by its estimation variance. The uncert ainty attributed to the raingauge estimates is obtained using block kriging , while for the satellite uncertainties, a novel regression approach is dev eloped. A standard error is also attached to the new merged estimates. In o rder to test the algorithm, a case study has been undertaken using the EPSA T dense raingauge network in Niger. The complete EPSAT raingauge network (9 4 gauges distributed over a 1x1 degrees square) has been used to obtain a d etailed picture of the rainfall pattern which is then used as a reference f or comparing the estimation schemes. The schemes compared are: (1) estimate s based on satellite data only; (2) kriged estimates from a randomly select ed subset of four gauges; (3) kriging with external drift using both satell ite data and the subset of gauges; and (4) the new merging algorithm. The m erging process gives more reliable results both for the mean areal rainfall and its spatial distribution. (C) 1999 Elsevier Science B.V. All rights re served.