10.5
Characterization of marine boundary layer winds from lidar measurements and regional forecast models

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Thursday, 6 February 2014: 9:30 AM
Room C114 (The Georgia World Congress Center )
Yelena Pichugina, CIRES/Univ. of Colorado, Boulder, CO; and R. M. Banta, A. Brewer, J. Olson, J. Carley, J. Wilczak, I. V. Djalalova, L. Bianco, M. Marquis, S. Benjamin, G. DiMego, and J. W. Cline

The rapidly expanding offshore wind-energy industry requires better characterization of wind flow at turbine heights, understanding of meteorological processes controlling boundary layer, and improved forecast of wind resources.

We analyzed Doppler lidar measurements in U.S. coastal North Atlantic water to characterize observed scales of spatial and temporal variability of wind field in the marine boundary layer and characterize key atmospheric phenomena that impact offshore Wind Energy operations and forecasts.

The lidar is a scanning, coherent, pulsed Doppler lidar designed and operated by the Earth System Research Laboratory (ERSL) of the National Oceanic and Atmospheric Administration (NOAA) for atmospheric boundary-layer research. Deployed on board the NOAA Research Vessel Ronald H. Brown, it was operated over the Gulf of Main 24-h a day, during the NEAQS 2004 field campaign providing accurate, motion compensated measurements with high temporal and spatial resolution. The precision of lidar-measured wind profiles was assessed by comparison with profiles measured by other instruments also operated from the ship. A strong correlation between lidar and rawisondes (0.98), lidar and sonic-anemometer measurements at 17m (0.92) demonstrates high accuracy of implemented motion compensation system.

A potentially important tool in providing offshore winds is the numerical weather prediction (NWP) model, but without measurements at turbine blade levels for verification, the accuracy and fidelity of model output is unknown. The precision and high vertical resolution of lidar profile measurements through the turbine rotor layer make it ideal for verifying NWP output for 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) grid), which includes hourly analysis/forecast cycles with its 12 km North American and 4 km Contiguous United States (CONUS) nest domains. Comparison of these numerical weather prediction (NWP) model output to lidar measurements at hub-height (100m) winds, rotor layer of modern offshore wind turbines (50-150 m), and up to 500m for different stability conditions of MBL, ocean depth 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 wind profilers.

The results demonstrate the importance of observational data to validate, calibrate and improve NWP models and decrease uncertainty of wind resource assessment in one of the US offshore areas projected for wind plant development.