Abstract
Abstract. During the second Wind Forecast Improvement Project (WFIP2; October 2015–March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR – 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST – 750 m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80 m wind speeds (wind turbine hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and three profiling lidars for comparison. Improvements due to the experimental physics (EXP vs. CNT runs) and those due to finer horizontal grid spacing (HRRRNEST vs. HRRR) and the combination of the two are compared, using standard bulk statistics such as mean absolute error (MAE) and mean bias error (bias). On average, the HRRR 80 m wind speed MAE is reduced by 3 %–4 % due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5 % on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80 m wind speed MAE, up to 7 %–8 %. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena. Causes of model weaknesses are identified. Finally, bias correction methods are applied to the 80 m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors.
Highlights
The second Wind Forecast Improvement Project (WFIP2) took place in Oregon and Washington states from October 2015 through March 2018
WFIP2 model development and improvement included a number of model components: the boundary-layer and surface-layer schemes, the representation of drag associated with sub-grid-scale topography and wind farms, and the cloud–radiation interaction
While the reader is referred to Olson et al (2019a, b) for complete details on the improved model configurations, we provide a list with brief summaries of the set of model physical parameterizations and relevant numerical methods targeted for development in WFIP2
Summary
The second Wind Forecast Improvement Project (WFIP2) took place in Oregon and Washington states from October 2015 through March 2018. Since the primary goal of WFIP2 is to advance the state of the art of wind energy forecasting in areas with complex terrain in general, and in the BPA region in particular, in this paper we use hub-height wind speed observations from sodars and profiling lidars to assess the impacts of the experimental parameterizations and finer horizontal grid spacing on the performance of the models These instruments were chosen because they accurately measure wind speed and direction from 20 m up to a few hundred meters above ground level, which is the layer of the atmosphere most relevant for wind energy production.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
