Impact of model improvements on 80-m wind speeds during the second Wind Forecast Improvement Project (WFIP2)

Abstract. During the second Wind Forecast Improvement Project (WFIP2; Oct 2015–Mar 2017, Columbia River Gorge and Basin area) several improvements to the parameterizations applied 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 (hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and 3 profiling lidars for verification. Improvements due to the experimental physics (EXP vs CNT runs) versus 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, also looking for the causes of model weaknesses. 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.