Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions
Accurate wind speed and direction data are vital for coastal engineering, renewable energy, and climate resilience, particularly in regions with sparse observational datasets. This study evaluates the ERA5 reanalysis model’s performance in predicting wind speeds and directions at ten coastal and off...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/1/149 |
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| author | Mohamad Alkhalidi Abdullah Al-Dabbous Shoug Al-Dabbous Dalal Alzaid |
| author_facet | Mohamad Alkhalidi Abdullah Al-Dabbous Shoug Al-Dabbous Dalal Alzaid |
| author_sort | Mohamad Alkhalidi |
| collection | DOAJ |
| description | Accurate wind speed and direction data are vital for coastal engineering, renewable energy, and climate resilience, particularly in regions with sparse observational datasets. This study evaluates the ERA5 reanalysis model’s performance in predicting wind speeds and directions at ten coastal and offshore stations in Kuwait from 2010 to 2017. This analysis reveals that ERA5 effectively captures general wind speed patterns, with offshore stations demonstrating stronger correlations (up to 0.85) and higher Perkins Skill Score (PSS) values (up to 0.94). However, the model consistently underestimates wind variability and extreme wind events, especially at coastal stations, where correlation coefficients dropped to 0.35. Wind direction analysis highlighted ERA5’s ability to replicate dominant northwest wind patterns. However, it reveals notable biases and underrepresented variability during transitional seasons. Taylor diagrams and error metrics further emphasize ERA5’s challenges in capturing localized dynamics influenced by land-sea interactions. Enhancements such as localized calibration using high-resolution datasets, hybrid models incorporating machine learning techniques, and long-term monitoring networks are recommended to improve accuracy. By addressing these limitations, ERA5 can more effectively support engineering applications, including coastal infrastructure design and renewable energy development, while advancing Kuwait’s sustainable development goals. This study provides valuable insights into refining reanalysis model performance in complex coastal environments. |
| format | Article |
| id | doaj-art-ded3cd2173fb4085be4cd64b0b53a377 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-ded3cd2173fb4085be4cd64b0b53a3772025-01-24T13:37:02ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-01-0113114910.3390/jmse13010149Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore RegionsMohamad Alkhalidi0Abdullah Al-Dabbous1Shoug Al-Dabbous2Dalal Alzaid3Civil Engineering Department, Kuwait University, P.O. Box 5969, Kuwait City 13060, KuwaitEnvironmental and Climate Change Program, Environment and Life Sciences Research Center, Kuwait Institute for Scientific Research, P.O. Box 24885, Safat 13109, KuwaitCivil Engineering Department, Kuwait University, P.O. Box 5969, Kuwait City 13060, KuwaitCivil Engineering Department, Kuwait University, P.O. Box 5969, Kuwait City 13060, KuwaitAccurate wind speed and direction data are vital for coastal engineering, renewable energy, and climate resilience, particularly in regions with sparse observational datasets. This study evaluates the ERA5 reanalysis model’s performance in predicting wind speeds and directions at ten coastal and offshore stations in Kuwait from 2010 to 2017. This analysis reveals that ERA5 effectively captures general wind speed patterns, with offshore stations demonstrating stronger correlations (up to 0.85) and higher Perkins Skill Score (PSS) values (up to 0.94). However, the model consistently underestimates wind variability and extreme wind events, especially at coastal stations, where correlation coefficients dropped to 0.35. Wind direction analysis highlighted ERA5’s ability to replicate dominant northwest wind patterns. However, it reveals notable biases and underrepresented variability during transitional seasons. Taylor diagrams and error metrics further emphasize ERA5’s challenges in capturing localized dynamics influenced by land-sea interactions. Enhancements such as localized calibration using high-resolution datasets, hybrid models incorporating machine learning techniques, and long-term monitoring networks are recommended to improve accuracy. By addressing these limitations, ERA5 can more effectively support engineering applications, including coastal infrastructure design and renewable energy development, while advancing Kuwait’s sustainable development goals. This study provides valuable insights into refining reanalysis model performance in complex coastal environments.https://www.mdpi.com/2077-1312/13/1/149wind reanalysisERA5 modelwind speed predictioncoastal and offshore engineering and meteorology |
| spellingShingle | Mohamad Alkhalidi Abdullah Al-Dabbous Shoug Al-Dabbous Dalal Alzaid Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions Journal of Marine Science and Engineering wind reanalysis ERA5 model wind speed prediction coastal and offshore engineering and meteorology |
| title | Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions |
| title_full | Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions |
| title_fullStr | Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions |
| title_full_unstemmed | Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions |
| title_short | Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions |
| title_sort | evaluating the accuracy of the era5 model in predicting wind speeds across coastal and offshore regions |
| topic | wind reanalysis ERA5 model wind speed prediction coastal and offshore engineering and meteorology |
| url | https://www.mdpi.com/2077-1312/13/1/149 |
| work_keys_str_mv | AT mohamadalkhalidi evaluatingtheaccuracyoftheera5modelinpredictingwindspeedsacrosscoastalandoffshoreregions AT abdullahaldabbous evaluatingtheaccuracyoftheera5modelinpredictingwindspeedsacrosscoastalandoffshoreregions AT shougaldabbous evaluatingtheaccuracyoftheera5modelinpredictingwindspeedsacrosscoastalandoffshoreregions AT dalalalzaid evaluatingtheaccuracyoftheera5modelinpredictingwindspeedsacrosscoastalandoffshoreregions |