Turbulence associated with wake vortices generated by arriving and departing aircraft pose a potential safety risk to other nearby aircraft, and as such this potential risk may apply to aircraft operating on Closely Spaced Parallel Runways (CSPRs). To take wake vortex behavior into account, current aircraft departing/landing standards require a safe distance behind the wake generating aircraft at which operations can be conducted. The Federal Aviation Administration (FAA) and National Aeronautics and Space Administration (NASA) have initiated an improved wake avoidance solution, referred to as Wake Turbulence Mitigation for Departures (WTMD). The process is designed to safely increase runway capacity via actively monitoring wind conditions that impact wake behavior (Hallock, et al., 1998; Lang et al., 2005). An important component of WTMD is a Wind Forecast Algorithm (WFA) being developed by MIT Lincoln Laboratory (Cole & Winkler, 2004). The WFA predicts runway crosswinds from the surface up to a height of approximately ~300 m (1000 ft) once per minute and thus forecasts when winds favorable for WTMD will persist long enough for safe procedures for a particular runway (Lang et al., 2007). The algorithm uses 1–4 hr wind forecasts from the Rapid Update Cycle (RUC) model operated by the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction (NOAA/NCEP) for upper atmospheric wind profiles. Detailed description of the RUC model can be found elsewhere (Benjamin et al., 1994; 2004a; 2004b). Briefly, the RUC model inputs are assimilations of high frequency observations from a suite of meteorological sensors, including Automated Surface Observing System (ASOS), rawinsonde profiles, satellite, airborne sensors from commercial aircraft, etc. The vertical layers of the atmosphere are resolved approximately isentropically. The model is run hourly, producing hourly forecasts out to 24 hours. The coverage of the RUC grid includes the continental United States, southern Canada, northern Mexico, and adjacent coastal waters. Here we evaluate the performance of RUC in predicting crosswinds with reliability sufficient to support WTMD. For RUC validation, in situ wind profile data were obtained from a Light Imaging Detection and Ranging (LIDAR) deployed at St. Louis Lambert International Airport (STL). The focus of this study is to provide a general quantitative characterization of the difference between RUC predictions and LIDAR measurements of the runway crosswinds. Particular attention was given to cases with inaccurate RUC crosswind forecasts, and cases when significant horizontal and vertical shears occur during situations of convective weather or proximity to large scale weather features, e.g., air mass fronts. (In practice, WTMD procedures and existing weather sources in the Control Tower will manage, to an acceptable level of risk, the hazard exposure associated with the extreme wind shift examples presented here.) Also included was examination of performance degradation with longer RUC forecast horizons and coarser horizontal resolutions, which may be relevant with regard to actual operational forecast data availability, or future applications of the operational concept to include arrival operations. A detailed report for this study is also available (Huang et al., 2007).