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- Title
Wind Ramp Events Validation in NWP Forecast Models during the Second Wind Forecast Improvement Project (WFIP2) Using the Ramp Tool and Metric (RT&M).
- Authors
DJALALOVA, IRINA V.; BIANCO, LAURA; AKISH, ELENA; WILCZAK, JAMES M.; OLSON, JOSEPH B.; KENYON, JAYMES S.; BERG, LARRY K.; CHOUKULKAR, ADITYA; COULTER, RICHARD; FERNANDO, HARINDA J. S.; GRIMIT, ERIC; KRISHNAMURTHY, RAGHAVENDRA; LUNDQUIST, JULIE K.; MURADYAN, PAYTSAR; TURNER, DAVID D.; WHARTON, SONIA
- Abstract
The second Wind Forecast Improvement Project (WFIP2) is a multiagency field campaign held in the Columbia Gorge area (October 2015-March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011-August 2012). TheRT&Mwas designed to explicitly measure the skill ofNWPmodels at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and three lidars, and to forecasts from the High-Resolution Rapid Refresh (HRRR), 3-km, and from the High-Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.
- Subjects
GREAT Plains; NUMERICAL weather forecasting; WIND power industry; RELIEF models; ELECTRICITY pricing; WIND power; WIND forecasting
- Publication
Weather & Forecasting, 2020, Vol 35, Issue 6, p2407
- ISSN
0882-8156
- Publication type
Article
- DOI
10.1175/WAF-D-20-0072.1