Weather radar has been widely used in hydrologic forecasting and decision making; nevertheless, there is increasing attention on its uncertainties that propagates through hydrologic models. is chapter proposes a fully formulated uncertainty model that can statistically quantify the characteristics of the radar rainfall errors and their spatial and temporal structure, which is a novel method of its kind in the radar data uncertainty eld. e uncertainty model is established based on the distribution of gauge rainfall conditioned on radar rainfall (GR|RR). Its spatial and temporal dependences are simulated based on the copula function. With this proposed uncertainty model, a Multivariate Distributed Ensemble Generator (MDEG) driven by the copula and autoregressive lter is designed. As wind is a typical weather factor that in‚uences radar measurement, this study introduces the wind eld into the uncertainty model and designs the radar rainfall uncertainty model under diƒerent wind conditions. e Brue catchment (135 sq. km) in Southwest England covering 28 radar pixels and 49 rain gauges is chosen as the experimental domain for this study.