A set of observing system simulation experiments (OSSEs) has been conducted to assess the impact on regional model prediction skill from the assimilation of wind observations from a space-based Doppler-lidar wind profiling system. The regional OSSE was run over the Continental United States and coordinated with a companion global lidar OSSE conducted by NCEP. Utilizing simulated observations from a regional nature run and boundary conditions from matched global experiments, regional assimilation experiments were completed with the Rapid-Update Cycle (RUC) model.

Calibration of the OSSE system, accomplished by comparing simulated and real-data impacts for the denial of aircraft observations, indicates realistic error characteristics for the simulated data experiments. Ideal lidar data impact experiments (no error added to the lidar observations, no attenuation of the lidar beam by clouds) show a significant forecast improvement from the addition of lidar observations to the conventional observation mix (rawinsonde, profiler, surface, aircraft, and radar VAD). This improvement occurs through both the direct assimilation of lidar observations on the regional domain and the use of improved lateral boundary conditions from a global model that has itself benefited from the assimilation of lidar observations. A detailed evaluation of the forecast impact will be presented along with preliminary results from more realistic lidar data experiments.