Performance of satellite-based and GPCC 7.0 rainfall products in an extremely data-scarce country in the Nile Basin

摘要: Abstract The rain gage networks in the African countries are notorious for their poor density and low frequency of observations. Rainfall products based on satellite estimates and/or ground observations have proven to be a viable alternative recent evolving campaigns overcome this deficiency. newly-borne country within Nile Basin, South Sudan, has extremely few operating stations. Herein, evaluation six long-term (1983 onward) rainfall products, i.e. Global Precipitation Climatology Centre full data reanalysis version 7.0 (GPCC 7.0) five Satellite-Rainfall Products (SRPs), is undertaken. Data from only currently stations (five) with reasonably up-to-date records used conduct point-to-pixel (from 1983 2010). results error linear fit metrics rank GPCC as best performing product monthly, maximum annual scales, followed by Climate Hazards group Infrared Stations 2.0 (CHIRPS v2.0). As regards variability rainfall, outperforms whereas Estimation Remotely Sensed Information Using Artificial Neural Networks–Climate Record (PERSIANN-CDR) CHIRPS v2.0 second-best performance. Multi-Source Weighted-Ensemble (MSWEP 2.0) show better agreement monthly that station rainfall. Africa (ARC2) performs capturing 7.0. In relation median complex performance evident across following remarks: relatively good MSWEP scale PERSIANN-CDR; mostly (relatively) operational rainfall; (CHIRSPS v2.0) (partly) suitable an estimator median. All present SRPs unequivocally under-estimate peaks. Enhancing estimation observation network key improving understanding modeling hydrological processes phenomena occurring basin general floodplains particular.