Radar data with high spatial and temporal resolution are commonly used to track and predict rainfall patterns that serve as an input for urban drainage models. However these data are continuously subjected to high errors for high resolution input (1km 2 and 5min) required for the urban application. Different approaches have been implemented by different studies in order to gain better radar estimates by integration information from station data. Conditional merging is one of these methods that

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... ses past information (15min window) to merge the station intensities with the spatial variability of the radar data (Berndt et al., 2012; Fuchs et al., 2017) .