  Three-dimensional wind retrievals from ground-based Doppler radars have
played an important role in meteorological research and nowcasting over the
past four decades. However, in recent years, the proliferation of open-source
software and increased demands from applications such as convective
parameterizations in numerical weather prediction models has led to a renewed
interest in these analyses. In this study, we analyze how a major, yet
often-overlooked, error source effects the quality of retrieved 3D wind fields.
Namely, we investigate the effects of spatial interpolation, and show how the
common practice of pre-gridding radial velocity data can degrade the accuracy
of the results. Alternatively, we show that assimilating radar data directly at
their observation locations improves the retrieval of important dynamic
features such as the rear flank downdraft and mesocyclone within a simulated
supercell, while also reducing errors in vertical vorticity, horizontal
divergence, and all three velocity components.
