The Wind Forecast Improvement Project 2 (WFIP2) included the deployment of more than one hundred instruments. NOAA’s 13- km Rapid Refresh (RAP) and 3-km High Resolution Rapid Refresh (HRRR), developed at the NOAA Earth System Research Laboratory (ESRL) Global Systems Division (GSD) and run operationally at the National Weather Service (NWS) National Center for Environmental Prediction (NCEP), are the models being improved in WFIP2. NOAA operational models are based on the Weather Research and Forecasting (WRF) model. Multiple verification efforts are underway. Verification is being performed by ESRL Chemical Sciences Division (CSD), Physical Sciences Division (PSD), Global Monitoring Division (GMD), and GSD, as well as DOE laboratories, the National Renewable Energy Laboratory (NREL) and Lawrence Livermore National Laboratory (LLNL), and the University of Colorado. Verification efforts include: Comparisons of model output to observations of wind speed and direction from high-resolution scanning Doppler lidars and turbine nacelle-mounted anemometers, for daily, monthly, seasonal, and annual periods; Boundary-layer (mixed-layer) depth analysis using high-resolution scanning Doppler lidars and wind profiling radars; Assessment of temporal, vertical and spatial wind flow variability from scanning Doppler lidars deployed to three sites along the prevalent wind directions; Comparison of model output to observations of wind speed, vector wind, temperature and turbulence from 915-MHz wind profiling radars/RASS, microwave radiometers, sodars, and surface met stations; Comparison of model skill at predicting ramp events against observations from sodars and lidars; Comparison of model downwelling and upwelling longwave and shortwave radiation; direct, diffuse, and global irradiance from pyranometers, pyrogeometers, and pyrheliometers; An experimental 750-m nest of the HRRR in the Pacific Northwest; Regime-specific verification, using the observations from the instruments above, including use of both the WRF and NOAA operational models; Analysis of uncertainty estimates and their changes with meteorological conditions, terrain, time of day, and forecast lead time, which will then be used within a decision support tool.
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