An assessment of the value of data from the NOAA Profiler Network (NPN) on weather forecasting is presented. A series of experiments using the Rapid Update Cycle (RUC) model in which various data sources were denied from RUC were conducted to assess the relative importance of the profiler data for short-range wind forecasts. Average verification statistics from a 14-day test period indicate that the profiler data have a positive impact on short-range (3-12 h) forecasts over the RUC domain containing the lower 48 United States, strongest at 3 h over a central U.S. subdomain that includes most of the profiler sites as well downwind of the profiler observations over the eastern U.S. Overall, profiler data reduce wind forecast errors at all levels from 850-150 hPa, especially below 300 hPa where there are relatively few automated aircraft observations. At night when fewer commercial aircraft are flying, profiler data also contribute strongly to more accurate 3-h forecasts, especially at jet levels. For the test period, the profiler data contributed up to 20-30% (at 700 hPa) of the overall reduction of 3-h wind forecast error by all data sources combined. Inclusion of wind profiler data also reduced 3-h errors for height, relative humidity and wind by 3-18%.

Case studies are summarized illustrating the value of the profiler observations for improving weather forecasts. The first case study indicates that inclusion of profiler data in the RUC model runs for the 3 May 1999 Oklahoma tornado outbreak improved model guidance of convective available potential energy (CAPE), 850-300 hPa wind shear, 0-3 km helicity, and precipitation in southwestern Oklahoma prior to the outbreak of the severe weather. In the second case study, inclusion of profiler data led to better RUC precipitation forecasts associated with a severe snow and ice storm that occurred over the central plains of the United States in February 2001. Summaries of National Weather Service (NWS) forecaster use of profiler data in daily operations support the results from these case studies and the statistical forecast model impact study that profiler data contribute significantly to improved forecasts over the central U.S. where these observations currently exist.