Bias adjustment and advection interpolation of long-term high resolution radar rainfall series

It is generally acknowledged that in order to apply radar rainfall data for hydrological proposes adjustment against ground observations are crucial. Traditionally, radar reflectivity is transformed into rainfall rates applying a fixed reflectivity – rainfall rate relationship even though this is known to depend on the changing drop size distribution of the specific rain. This creates a transient bias between the radar rainfall and the ground observations due to seasonal changes of the drop size distribution as well as other atmospheric effects and effects related to the radar observational technology. In this study different bias adjustment techniques is investigated, developing a complete 10-year dataset (2002–2012) of high spatio-temporal resolution radar rainfall based on a radar observations from a single C-band radar from Denmark. Results show that hourly adjustment mean field bias adjustment outperform daily mean field bias adjustment with regards to estimation of rainfall totals and peak rain rates. Furthermore, it is demonstrated that radar rainfall estimates can be improved significantly by implementation of a novel advection interpolation technique.