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Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin
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 Orego...
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Published in: | Journal of renewable and sustainable energy 2020-05, Vol.12 (4) |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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. |
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ISSN: | 1941-7012 1941-7012 |
DOI: | 10.1063/5.0009138 |