Extended Abstract

used in this paper were obtained from the “FY-2E” weather satellite provided by the NationalSatellite Meteorological Center (NSMC) which horizontal resolution of 0.1 by 0.1 degree. Thestation rainfall observation we used in this study is obtained from the National MeteorologicalInformation Center (NMIC) as shown in the Fig1.a.Fig.1.Illustration of automatic weatherstations locationFig.1.b Distribution of hydrological observationstationsThe evaluation precipitation data we used is the observed precipitation in the hydrological stations.The location of the hydrological stations was given in Fig2.b, which is obtained from the sharing datasystem between the China Meteorological Administration (CMA) and the Bureau of Hydrology, theMinistry of Water Resources of P.R.China (Bureau of Hydrology, MWR).2.2 “Fusing” technique description (combine satellite result with rain gaugedata)The satellite precipitation estimation product we used is based on the “split window channeltechnique” by NSMC. As well known, there are many kinds of typical algorithms of satelliteprecipitation estimation in the world , for example ,Barrett Method, Arkin Method, Life HistoryMethod, Stout Method, Griffith Method, Scofield Method, etc (Arnold Gruber,2000). But what weconcerned technique is how to combine or “fusing” the satellite precipitation estimation product andthe rain gauges data together. In this paper, we use a intellective objective analysis scheme which isbrought forward by LU mai-meng (2004) to accomplish the fusing, which method is not onlyconsidered distance between the grid and rain gauges, but also consider the orientation of the raingauges.The R represents precipitation , superscibe O to refers to observation,a refers to analysis and srefers to satellite estimate,the suffix i is for the ith grid-point and k is thekthraingaugelocation .thepkis weights and n is the tatal number of raingauges.The Wθ j is a distancefactor ,Wr is a function of distance ,the Π is the orientation factor ,in which2-93-