The goal of the GroundWinds program is to develop and demonstrate ultra-violet (UV) lidar technology for a future space-based system that will measure the vertical structure of global winds. The only current source of such data is from operational balloon-borne radiosondes and wind profilers, which are reasonably well represented over the U.S. mainland but absent over the oceans. A satellite system would provide wind measurements distributed all over the globe. Because the air over the Pacific is largely free of aerosols, the NOAA observatory on Mauna Loa at 3-km altitude is an ideal site for testing the optics, hardware, and detectors needed for the satellite system. The Hawaii GroundWinds system is began operations in March 2002 and can operate day or night. The lidar team plans continued operations to provide calibration support for the satellite system when it flies. The purpose of this paper is to discuss the utility of the wind data derived from the Hawaii lidar measurements in nowcasting support for astronomical observatories located at the summit of Mauna Kea (~4000 m). The data from the UV lidar, based at ~3300 m on the slope of Mauna Loa, is used in a custom forecasting project that provides operational support for the world-class group of astronomical observatories on nearby Mauna Kea. The lidar data is used to help prepare wind and turbulence nowcasts and forecasts for the summit of Mauna Kea and as input for an operational mesoscale numerical weather prediction model (MM5). Clear-air turbulence in both the free atmosphere and in the summit boundary layer causes phase distortions to incoming electromagnetic wave fronts, resulting in motion, intensity fluctuations (scintillation), and blurring of images obtained by ground-based telescopes. Astronomical parameters that quantify these effects are generically referred to as seeing. Seeing improves or degrades with changes in the vertical location and strength of turbulence as quantified by profiles of the refractive index structure function Cn2. Cn2 fluctuations usually occur at scales that are too small for routine direct measurement, but they can be parameterized from vertical gradients in wind, temperature, and moisture in our MM5 runs. Seeing at a particular wavelength is then calculated by vertically integrating the Cn2 profile. Since seeing at Mauna Kea varies significantly from one night to the next, or even within one night, as a result of changing synoptic and mesoscale flow patterns, accurate seeing forecasts from MM5 enable telescopes to take best advantage of conditions that are favorable for a particular type of observation. LIDAR wind profiles represent an important data resource for nowcasting, MM5 model input and verification.