RADALIA: A new tool for dealiasing Doppler cloud radar observations

Abstract. Doppler cloud radars provide valuable insights into cloud dynamics and microphysical processes. However, their measurements are often affected by velocity aliasing when hydrometeor motions exceed the radar Nyquist velocity. Aliasing affects Doppler velocity spectra (DVS) and the derived spectral moments, introducing uncertainties in cloud classification and microphysical retrievals. Despite its importance, a dedicated dealiasing algorithm for cloud radar observations is not yet available. We present RADALIA (RAdar De-ALIsing Algorithm), a new open-source tool designed to detect and correct aliasing in Doppler cloud radar spectra. RADALIA includes two complementary approaches: an interpolation-based method (IntB) that can operate with either single-frequency (i.e., standalone) or dual-frequency observations, and an iterative method based on vertical continuity (IterBU) that operated on single-frequency observations. The algorithms were assessed using dual-frequency cloud radar observations at two ACTRIS CCRES stations: AGORA in Granada (Spain) and JOYCE in Jülich (Germany), representing contrasting atmospheric conditions and levels of dealiasing complexity. The dual-frequency configuration was used as a reference, since it provides the most robust performance in complex situations involving strong attenuation and multiple hydrometeor populations. Under straightforward spectral conditions, all standalone approaches successfully dealiased the DVS, achieving 98.6 %–99.6 % agreement with the dual-frequency reference. In the most challenging spectral scenario, standalone approaches achieved success rates above 70 %. RADALIA addresses a longstanding gap in cloud radar processing and serves as the basis for the dealiasing algorithm being implemented within the Cloudnet processing chain. It has the potential to improve cloud radar products and their application to microphysical retrievals, model evaluation, and satellite validation. Future work will focus on broader validation and extension to additional cloud radar systems and scanning observations.