A method of retrieving cloud microphysical properties using combined observations from both cloud radar and lidar is introduced. The description of the lidar-radar model accounts for nonspherical effects of the ice crystals, with a treatment for multiple scattering and Mie effects. This retrieval makes use of an improvement to the traditional optimal estimation retrieval method, whereby a series of corrections are applied to the state vector during the search for an iterative solution. This allows faster convergence to a solution and is less processor intensive. The retrieval method is applied to radar and lidar observations from the CRYSTAL-FACE experiment, and vertical profiles of ice crystal characteristic diameter, number concentration, and ice water content are retrieved for a cirrus cloud layer observed 1 day of that experiment. Empirical relationships between ice water content and radar reflectivity as well as between particle number concentrations and characteristic diameter are also examined. The results indicate that a distinct and robust relationship exists between the latter two parameters, offering insight into the nature of cirrus microphysical processes.