Specification of hydrometeor phase in clouds is critical for determining their radiative properties and the evolution of their structure. Cloud phase identification from remote sensors is particularly challenging, especially in temperatures ranging from 0 to -30 °C, where both liquid and ice are sustainable. In this arena, the synergistic relationship of radar and lidar is often exploited, with lidar targeting the liquid, and radar, the ice. Depolarization measurements can assist in resolving phase, although these are not widely available. A new technique that emulates the backscatter and depolarization measurements of high spectral resolution lidar (HSRL) through processing of Doppler cloud radar spectra is described here. It is commonly assumed that radar returns from liquid cloud droplets in the presence of ice are generally too weak to be useful. Our technique demonstrates, to the contrary, that liquid information can be extracted from subtle spectrum features and distortions. We apply it to a month-long dataset collected during the Mixed-Phase Arctic Cloud Experiment (MPACE) conducted at Barrow, Alaska in 2004. Our simulated lidar retrievals based on the colocated MMCR exhibit great morphological consistency with observations from the operational MPACE HSRL and reveal new structure in multilayer clouds that was undetected by the lidar due to extinction. The ability of cloud radars to penetrate liquid layers makes this technique not suffer from the extinction limitations of lidars. It is applicable to all profiling radars with sufficient sensitivity to observe thin clouds and demonstrates that Doppler spectra alone can be used to identify liquid, ice, and mixed-phase clouds.