Modeling Radar-Rainfall Estimation Uncertainties Using Parametric and Non-Parametric Approaches

There are large uncertainties associated with radar estimates of rainfall. These errors include both deterministic and random effects of several sources. The deterministic component can be described mathematically in terms of a conditional expectation function and is the focus of this study. Two different approaches will be presented and applied: non-parametric (kernel-based) and parametric (copula-based). A large sample (more than six years) of rain gauge measurements from a highly dense network located in south-west England (Brue catchment) is used as an approximation of the true ground rainfall. These data are complemented with rainfall estimates by a C-band weather radar (Wardon Hill) located at about 40 km from the catchment. The authors compare the results obtained using the above two approaches for four temporal scales of hydrologic interest (5- and 15-minute, hourly and three-hourly) by means of several different performance indexes, and discuss weaknesses and strengths of each approach.