Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain)
This study evaluates the performance of statistical models applied to the output of numerical models for short-term (1−24 h) hourly wind forecasts at three locations in the Basque Country. The target variables are horizontal wind components and the maximum wind gust at 3 h intervals. Stati...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-12-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/11/1/45 |
| _version_ | 1818164188433874944 |
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| author | Sheila Carreno-Madinabeitia Gabriel Ibarra-Berastegi Jon Sáenz Eduardo Zorita Alain Ulazia |
| author_facet | Sheila Carreno-Madinabeitia Gabriel Ibarra-Berastegi Jon Sáenz Eduardo Zorita Alain Ulazia |
| author_sort | Sheila Carreno-Madinabeitia |
| collection | DOAJ |
| description | This study evaluates the performance of statistical models applied to the output of numerical models for short-term (1−24 h) hourly wind forecasts at three locations in the Basque Country. The target variables are horizontal wind components and the maximum wind gust at 3 h intervals. Statistical approaches such as persistence, analogues, linear regression, and random forest (RF) are used. The verification statistics used are coefficient of determination (R<sup>2</sup>) and root mean square error (RMSE). Statistical models use three inputs: (1) Local wind observations; (2) extended EOFs (empirical orthogonal functions) derived from past local observations and ERA-Interim variables in a previous 24-h period covering a domain around the area of study; and (3) wind forecasts provided by ERA-Interim. Results indicate that, for horizons less than 1−4 h, persistence is the best model. For longer predictions, RF provides the best forecasts. For horizontal components at 4−24 h horizons, RF slightly outperformed ERA-Interim wind forecasts. For gust, RF performs better than ERA-Interim for all the horizons. Persistence is the most influential factor for 2−5 h. Beyond this horizon, predictors from the ERA-Interim wind forecasts led the contribution. Hybrid numerical−statistical methods can be used to improve short-term wind forecasts. |
| first_indexed | 2024-12-11T17:01:29Z |
| format | Article |
| id | doaj.art-0f25130eacf44fbcacfde4580b7bc86f |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-12-11T17:01:29Z |
| publishDate | 2019-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-0f25130eacf44fbcacfde4580b7bc86f2022-12-22T00:57:49ZengMDPI AGAtmosphere2073-44332019-12-011114510.3390/atmos11010045atmos11010045Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain)Sheila Carreno-Madinabeitia0Gabriel Ibarra-Berastegi1Jon Sáenz2Eduardo Zorita3Alain Ulazia4TECNALIA, Parque Tecnológico de Álava, Albert Einstein 28, E-01510 Vitoria-Gasteiz (Araba/Álava), SpainNE and Fluid Mechanics Department, Faculty of Engineering, University of the Basque Country, E-48013 Bilbao, SpainApplied Physics II Department, Faculty of Science and Technology, University of the Basque Country, E-48940 Leioa, SpainInstitute of Coastal Research, Helmholtz-Zentrum-Geesthacht, 21502 Geesthacht, GermanyNE and Fluid Mechanics Department, Faculty of Engineering, University of the Basque Country, E-20600 Eibar, SpainThis study evaluates the performance of statistical models applied to the output of numerical models for short-term (1−24 h) hourly wind forecasts at three locations in the Basque Country. The target variables are horizontal wind components and the maximum wind gust at 3 h intervals. Statistical approaches such as persistence, analogues, linear regression, and random forest (RF) are used. The verification statistics used are coefficient of determination (R<sup>2</sup>) and root mean square error (RMSE). Statistical models use three inputs: (1) Local wind observations; (2) extended EOFs (empirical orthogonal functions) derived from past local observations and ERA-Interim variables in a previous 24-h period covering a domain around the area of study; and (3) wind forecasts provided by ERA-Interim. Results indicate that, for horizons less than 1−4 h, persistence is the best model. For longer predictions, RF provides the best forecasts. For horizontal components at 4−24 h horizons, RF slightly outperformed ERA-Interim wind forecasts. For gust, RF performs better than ERA-Interim for all the horizons. Persistence is the most influential factor for 2−5 h. Beyond this horizon, predictors from the ERA-Interim wind forecasts led the contribution. Hybrid numerical−statistical methods can be used to improve short-term wind forecasts.https://www.mdpi.com/2073-4433/11/1/45short-term forecastwindstatistical forecastrandom forestera-interimpersistence |
| spellingShingle | Sheila Carreno-Madinabeitia Gabriel Ibarra-Berastegi Jon Sáenz Eduardo Zorita Alain Ulazia Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain) Atmosphere short-term forecast wind statistical forecast random forest era-interim persistence |
| title | Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain) |
| title_full | Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain) |
| title_fullStr | Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain) |
| title_full_unstemmed | Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain) |
| title_short | Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain) |
| title_sort | sensitivity studies for a hybrid numerical statistical short term wind and gust forecast at three locations in the basque country spain |
| topic | short-term forecast wind statistical forecast random forest era-interim persistence |
| url | https://www.mdpi.com/2073-4433/11/1/45 |
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