Evaluating the WFIP2 Updates to the HRRR Model Using Scanning Doppler Lidar Measurements in the Complex Terrain of the Columbia River Basin

Yelena Pichugina, Robert Banta, W. Brewer, L. Bianco, Caroline Draxl, J. Kenyon, Julie Lundquist, J. Olson, D. Turner, S. Wharton, J. Wilczak, S. Baidar, L. Berg, H. J. S. Fernando, B. McCarty, R. Rai, Billy Roberts, J. Sharp, W. Shaw, M. StoelingaR. Worsnop

Research output: Contribution to journalArticlepeer-review

10 Scopus Citations

Abstract

The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. The effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.

Original languageAmerican English
Article number043301
Number of pages27
JournalJournal of Renewable and Sustainable Energy
Volume12
Issue number4
DOIs
StatePublished - 1 May 2020

Bibliographical note

Publisher Copyright:
© 2020 Author(s).

NREL Publication Number

  • NREL/JA-5000-76747

Keywords

  • complex terrain
  • HRRR model
  • lidar measurements
  • WFIP2
  • WRF

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