J2.2 Lidar Characterization of Boundary-Layer Winds and Validation of NWP Forecast Model Performance during the Second Wind Forecast Improvement Project in Complex Terrain of the Columbia River Basin

Wednesday, 25 January 2017: 8:45 AM
606 (Washington State Convention Center )
Yelena Pichugina, CIRES/Univ. of Colorado, Boulder, CO; and A. W. Brewer, R. M. Banta, A. Choukulkar, T. A. Bonin, J. B. Olson, J. Kenyon, C. T. Clack, M. Marquis, L. Bianco, J. Sharp, W. M. Angevine, S. Baidar, S. P. Sandberg, A. Weickmann, and B. J. McCarty

During the Second Wind Forecast Improvement Project (WFIP2), conducted in the complex terrain of the Columbia River Basin in September 2015-March 2017, spatial and temporal variability of winds in the lowest 1 km above ground level were observed with two ground-based scanning Doppler lidar systems. Continuous measurements from September 2015 and high vertical resolution of data obtained allow for the analysis of monthly and seasonal distributions and variability of boundary layer winds and evaluation of the accuracy of power estimates based on hub-height and rotor-equivalent winds.

Simultaneous measurements from two identical scanning lidars on sites separated by ~40 km allow accurate wind profile data to be obtained upstream and downstream of the local wind farms to analyze the combined effects of the spatial separation of the two lidars, sites topography and overall impacts of wind farms on wind flow. Comparison of rotor-layer winds between the two sites for various wind directions will be presented for different months, seasons, and for the entire period of the experiment. Likewise, turbulence statistics between the two sites will be compared to analyze how complex terrain modifies the turbulent structure of the planetary boundary layer.  These results, combined with the records of meteorological phenomena, are being used to better understand wind flow in complex terrain and to capture cases of unusual wind flow behavior for further detailed analysis.  

In addition, results of the statistical metrics between lidar-observed winds in the turbine rotor layer and those predicted by NWP models will be presented for the diurnal cycle of selected cases as well as for monthly and seasonal averages. Such analysis provides insight into model performance and the influence of captured atmospheric features on model accuracy and will help to improve model physics and forecast of wind flow over complex terrain.

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