Thursday, 12 June 2014: 8:45 AM
Queens Ballroom (Queens Hotel)
A potentially important tool in providing characteristics and behavior of the marine Boundary Layer (BL) in response to various atmospheric conditions, stability, seasonality and diurnal cycle is the numerical weather prediction (NWP) model, but without measurements in this layer for verification, the accuracy and fidelity of model output is unidentified. With a rapidly expanding offshore wind-energy industry, it is crucial to have reliable data to understand meteorological processes controlling boundary layer, and improve forecast of wind resources. To evaluate models and obtain information on key atmospheric phenomena that impact offshore Wind Energy operations and forecasts, we analyzed wind speed and direction profiles from motion-compensated, high-resolution ship-borne lidar measurements in U.S. coastal North Atlantic water in July-August 2004. The precision and high vertical resolution of lidar profile measurements through the turbine rotor layer make it ideal for verifying NWP output for BL studies and Wind Energy use. The study presents validation of retrospective runs using the NOAA/ESRL Rapid Refresh (RAP, 13 km horizontal grid) and High Resolution Rapid Refresh (HRRR, 3 km horizontal grid) models, and an experimental version of the NOAA/NWS/NCEP North American Mesoscale forecast system (NAM), which includes hourly analysis/forecast cycles with its 12 km North American and 4 km Contiguous United States nest domains. Comparison of these NWP model output to lidar measurements allowed us to evaluate the model skill and the ability to simulate meteorological boundary layer structure in the coastal marine environment. Lidar data also were used to estimate impact of data assimilation from all available during the experiment coastal wind profilers. The results show strong spatial and temporal variability of the wind field in the marine boundary layer. Winds near the coast show diurnal behavior, and frequent occurrences of low-level jet structure are evident especially during nocturnal periods. Overall, the results demonstrate the importance of observational data to validate NWP models, assess the impact of inland wind profiler data assimilation on the accuracy of hourly updated weather model forecasts, and determine the uncertainty of wind resource assessment in one of the US offshore areas projected for wind plant development.
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