Uncertainty analysis of radar rainfall estimates over two different climates in Iran

Accuracy of rainfall quantification is one of the most important concerns in meteorological and hydrological modelling. Satellites and weather radars can provide meteorological information with higher temporal and spatial resolution than ground stations. Rain gauges measure rain rate directly; however, weather radars estimate rain rate by converting radar reflectivity aloft to rain rate at ground level. This conversion with a power law relation between radar reflectivity and rain rate could be altered from place to place or in various precipitation types. This variety may be the source of errors and uncertainty of radar rainfall estimates. One way to assess the uncertainty of radar rainfall is simulation of rainfall fields. In this article, after calibrating two radars located in the south-western and northern parts of Iran, uncertainty of rainfall estimates of these radars has been analysed using the Gaussian Copula model. Reliability of this model was examined for 10% of the rainfall events that were not included in the simulation process. Obtained results of the current research indicate that recalibration of radars can considerably reduce bias and root mean error. In addition, the Copula-based model can generate rainfall fields with similarly spatial structures to those of observed rainfall data.