14 Nov 2025
| 14 Nov 2025
Evaluation of ERA5, COSMO-REA6 and CERRA in simulating wind speed along the French coastline for wind energy applications
Anindita Patra
CORRESPONDING AUTHOR
France Energies Marines, Plouzané, France
Electricité de France, Recherche & Développement, Palaiseau, France
Boutheina Oueslati
Electricité de France, Recherche & Développement, Palaiseau, France
Tessa Chevallier
France Energies Marines, Plouzané, France
Paul Renaud
France Energies Marines, Plouzané, France
Youen Kervella
France Energies Marines, Plouzané, France
Laurent Dubus
Réseau de Transport d'Électricité, Paris, France
World Energy & Meteorology Council, Norwich, UK
Related authors
Youen Kervella, Tessa Chevallier, Boutheina Oueslati, Nicolas Raillard, Marissa Yates, Matéo Pimoult, Coline Poppeschi, Anindita Patra, Neil Luxcey, Florent Guinot, and Laurent Dubus
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-266, https://doi.org/10.5194/wes-2025-266, 2025
Preprint under review for WES
Short summary
Short summary
France aims for major offshore wind growth. We examined future climate impacts on wind, waves, and water levels. Results suggest that mean winds and waves may weaken, but extreme waves and sea levels will increase. These trends are nevertheless accompanied by strong model uncertainties. These findings are necessary for designing durable offshore wind farms in France and ensuring reliable energy production for decades to come.
Paul Renaud, Léo Vinour, Fabien Leckler, Shogo Uchiyama, and Jean-François Filipot
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-273, https://doi.org/10.5194/wes-2025-273, 2025
Preprint under review for WES
Short summary
Short summary
This study introduces a parametric model to estimate tropical cyclone winds at offshore sites. It uses satellite-calibrated surface winds that are extrapolated to hub height. Its performance is evaluated using measurements from five cyclones and by comparing the results with high-fidelity models. The model consistently reproduces wind speed time series. Limits remain, especially the lack of large-scale terrain effects such as those in Taiwan.
Youen Kervella, Tessa Chevallier, Boutheina Oueslati, Nicolas Raillard, Marissa Yates, Matéo Pimoult, Coline Poppeschi, Anindita Patra, Neil Luxcey, Florent Guinot, and Laurent Dubus
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-266, https://doi.org/10.5194/wes-2025-266, 2025
Preprint under review for WES
Short summary
Short summary
France aims for major offshore wind growth. We examined future climate impacts on wind, waves, and water levels. Results suggest that mean winds and waves may weaken, but extreme waves and sea levels will increase. These trends are nevertheless accompanied by strong model uncertainties. These findings are necessary for designing durable offshore wind farms in France and ensuring reliable energy production for decades to come.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
Nat. Hazards Earth Syst. Sci., 25, 843–856, https://doi.org/10.5194/nhess-25-843-2025, https://doi.org/10.5194/nhess-25-843-2025, 2025
Short summary
Short summary
Our aim is to characterize the observed evolution of compound winter low-wind and cold events impacting the French electricity system. The frequency of compound events exhibits a decrease over the 1950–2022 period, which is likely due to a decrease in cold days. Large-scale atmospheric circulation is an important driver of compound event occurrence and has likely contributed to the decrease in cold days, while we cannot draw conclusions on its influence on the decrease in compound events.
Cited articles
Bentamy, A. and Croize-Fillon, D.: Spatial and temporal characteristics of wind and wind power off the coasts of Brittany, Renewable Energy, 66, 670–679, https://doi.org/10.1016/j.renene.2014.01.012, 2014.
Bloomfield, H. C., Brayshaw, D. J., Shaffrey, L. C., Coker, P. J., and Thornton, H. E.: Quantifying the increasing sensitivity of power systems to climate variability, Environmental Research Letters, 11, 124025, https://doi.org/10.1088/1748-9326/11/12/124025, 2016.
Bollmeyer, C., Keller, J. D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs, P., Hense, A., Keune, J., Kneifel, S., Pscheidt, I., Redl, S., and Steinke, S.: Towards a high-resolution regional re-analysis for the European CORDEX domain, Quarterly Journal of the Royal Meteorological Society, 141, 1–15, https://doi.org/10.1002/qj.2486, 2015.
Cañadillas, B., Wang, S., Ahlert, Y., Djath, B., Barekzai, M., Foreman, R., and Lampert, A.: Coastal horizontal wind speed gradients in the North Sea based on observations and ERA5 reanalysis data, Meteorologische Zeitschrift, 32, 207–228, https://doi.org/10.1127/metz/2022/1166, 2023.
Cannon, D. J., Brayshaw, D. J., Methven, J., Coker, P. J., and Lenaghan, D.: Using reanalysis data to quantify extreme wind power generation statistics: A 33-year case study in Great Britain, Renewable Energy, 75, 767–778, https://doi.org/10.1016/j.renene.2014.10.024, 2015.
Carvalho, D., Rocha, A., Gómez-Gesteira, M., and Santos, C. S.: WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal, Applied Energy, 117, 116–126, https://doi.org/10.1016/j.apenergy.2013.12.001, 2014a.
Carvalho, D., Rocha, A., Gómez-Gesteira, M., and Santos, C. S.: Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula, Applied Energy, 134, 57–64, https://doi.org/10.1016/j.apenergy.2014.08.018, 2014b.
Clarke, E., Doddy, S., Griffin, F., McDermott, J., Monteiro Correia, C., and Sweeney, C.: Which reanalysis dataset should we use for renewable energy analysis in Ireland?, Atmosphere, 12, 624, https://doi.org/10.3390/atmos12050624, 2021.
Dawkins, L. C.: Weather and climate related sensitivities and risks in a highly renewable UK energy system: a literature review, Crown Copyright, Met Office, Exeter (UK), London, UK, 2019.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Quarterly Journal of the Royal Meteorological Society, 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Drobinski, P., Coulais, C., and Jourdier, B.: Surface wind-speed statistics modelling: Alternatives to the Weibull distribution and performance evaluation, Boundary-Layer Meteorology, 157, 97–123, https://doi.org/10.1007/s10546-015-0035-7, 2015.
Fan, W., Liu, Y., Chappell, A., Dong, L., Xu, R., Ekström, M., and Fu, T. M.: Evaluation of global reanalysis land surface wind speed trends to support wind energy development using in situ observations, Journal of Applied Meteorology and Climatology, 60, 33–50, https://doi.org/10.1175/JAMC-D-20-0037.1, 2021.
Fragano, C. and Colle, B.: Validation of offshore winds in the ERA5 reanalysis and NREL NOW-23 WRF analysis using two floating LiDARs in the New York Bight, Weather and Forecasting, 40, 1307–1323, https://doi.org/10.1175/WAF-D-24-0155.1, 2025
Gandoin, R. and Garza, J.: Underestimation of strong wind speeds offshore in ERA5: evidence, discussion and correction, Wind Energ. Sci., 9, 1727–1745, https://doi.org/10.5194/wes-9-1727-2024, 2024.
Gualtieri, G.: Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review, Renewable and Sustainable Energy Reviews, 167, 112741, https://doi.org/10.1016/j.rser.2022.112741, 2022.
Heppelmann, T., Steiner, A., and Vogt, S.: Application of numerical weather prediction in wind power forecasting: Assessment of the diurnal cycle, Meteorologische Zeitschrift, 26, 319–331, https://doi.org/10.1127/metz/2017/0820, 2017.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Holtslag, A. A. M., Svensson, G., Baas, P., Basu, S., Beare, B., Beljaars, A. C. M., Bosveld, F. C., Cuxart, J., Lindvall, J., Steeneveld, G. J., Tjernström, M., and Van de Wiel, B. J. H.: Stable atmospheric boundary layers and diurnal cycles: Challenges for weather and climate models, Bulletin of the American Meteorological Society, 94, 1691–1706, https://doi.org/10.1175/BAMS-D-11-00187.1, 2013.
Jourdier, B.: Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA, and AROME to simulate wind power production over France, Advances in Science and Research, 17, 63–77, https://doi.org/10.5194/asr-17-63-2020, 2020.
Jourdier, B., Diaz, C., and Dubus, L.: Evaluation of CERRA for wind energy applications, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 September 2023, EMS2023-311, https://doi.org/10.5194/ems2023-311, 2023.
MacDonald, M. and Teixeira, J.: Scaling behavior of a turbulent kinetic energy closure scheme for the stably stratified atmosphere: A steady-state analysis, Journal of the Atmospheric Sciences, 77, 3161–3170, https://doi.org/10.1175/JAS-D-19-0332.1, 2020.
Miao, H., Dong, D., Huang, G., Hu, K., and Tian, Q.: Evaluation of northern hemisphere surface wind speed and wind power density in multiple reanalysis datasets, Energy, 200, 117382, https://doi.org/10.1016/j.energy.2020.117382, 2020.
Olsen, B. T., Hahmann, A., Žagar, M., Hristov, Y., Mann, J., Kelly, M., and Badger, J.: Mapping the European wind climate: Validation of the New European Wind Atlas, EMS Annual Meeting, 2019, 9–13 September 2019, Lyngby, Denmark, 2019.
Potisomporn, P., Adcock, T. A., and Vogel, C. R.: Evaluating ERA5 reanalysis predictions of low wind speed events around the UK, Energy Reports, 10, 4781–4790, https://doi.org/10.1016/j.egyr.2023.11.035, 2023.
Pronk, V., Bodini, N., Optis, M., Lundquist, J. K., Moriarty, P., Draxl, C., Purkayastha, A., and Young, E.: Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain?, Wind Energ. Sci., 7, 487–504, https://doi.org/10.5194/wes-7-487-2022, 2022.
Ramon, J., Lledó, L., Torralba, V., Soret, A., and Doblas-Reyes, F.: What global reanalysis best represents near-surface winds?, Quarterly Journal of the Royal Meteorological Society, 145, 3236–3251, https://doi.org/10.1002/qj.3616, 2019.
Ridal, M., Bazile, E., Le Moigne, P., Randriamampianina, R., Schimanke, S., Andrae, U., Berggren, L., Brousseau, P., Dahlgren, P., Edvinsson, L., El-Said, A., Glinton, M., Hagelin, S., Hopsch, S., Isaksson, L., Medeiros, P., Olsson, E., Unden, P., and Wang, Z. Q.: CERRA, the Copernicus European Regional Reanalysis system, Quarterly Journal of the Royal Meteorological Society, 150, 3385–3411, https://doi.org/10.1002/qj.4764, 2024.
Rouholahnejad, F., Meyer, P. J., and Gottschall, J.: Collocating wind data: A case study on the verification of the CERRA dataset, Journal of Physics: Conference Series, 2875, 012016, https://doi.org/10.1088/1742-6596/2875/1/012016, 2024.
RTE: Bilan électrique 2023, RTE, https://assets.rte-france.com/analyse-et-donnees/2024-03/Bilan%20%C3%A9lectrique%202023%20rapport%20complet_29fev24.pdf (last access: 13 November 2025), 2023.
RTE: Futurs énergétiques 2050, Principaux résultats, RTE, https://assets.rte-france.com/prod/public/2021-10/Futurs-Energetiques-2050-principaux-resultats_0.pdf (last access: 13 November 2025), 2021.
Salameh, T., Drobinski, P., Vrac, M., and Naveau, P.: Statistical downscaling of near-surface wind over complex terrain in southern France, Meteorology and Atmospheric Physics, 103, 253–265, https://doi.org/10.1007/s00703-008-0330-7, 2009.
Sandu, I., Beljaars, A., Bechtold, P., Mauritsen, T., and Balsamo, G.: Why is it so difficult to represent stably stratified conditions in numerical weather prediction (NWP) models?, Journal of Advances in Modeling Earth Systems, 5, 117–133, https://doi.org/10.1002/jame.20013, 2013.
Schimanke, S., Ridal, M., Le Moigne, P., Berggren, L., Undén, P., Randriamampianina, R., Andrea, U., Bazile, E., Bertelsen, A., Brousseau, P., Dahlgren, P., Edvinsson, L., El Said, A., Glinton, M., Hopsch, S., Isaksson, L., Mladek, R., Olsson, E., Verrelle, A., and Wang, Z.: CERRA sub-daily regional reanalysis data for Europe on height levels from 1984 to present, CDS [data set], https://doi.org/10.24381/cds.38b394e6, 2021a.
Schimanke, S., Ridal, M., Le Moigne, P., Berggren, L., Undén, P., Randriamampianina, R., Andrea, U., Bazile, E., Bertelsen, A., Brousseau, P., Dahlgren, P., Edvinsson, L., El Said, A., Glinton, M., Hopsch, S., Isaksson, L., Mladek, R., Olsson, E., Verrelle, A., and Wang, Z.: CERRA sub-daily regional reanalysis data for Europe on single levels from 1984 to present, CDS [data set], https://doi.org/10.24381/cds.622a565a, 2021b.
Shen, C., Zha, J., Wu, J., Zhao, D., Azorin-Molina, C., Fan, W., and Yu, Y.: Does CRA-40 outperform other reanalysis products in evaluating near-surface wind speed changes over China?, Atmos Res., 266, 105948, https://doi.org/10.1016/j.atmosres.2021.105948, 2022.
Sheridan, L. M., Krishnamurthy, R., García Medina, G., Gaudet, B. J., Gustafson Jr., W. I., Mahon, A. M., Shaw, W. J., Newsom, R. K., Pekour, M., and Yang, Z.: Offshore reanalysis wind speed assessment across the wind turbine rotor layer off the United States Pacific coast, Wind Energ. Sci., 7, 2059–2084, https://doi.org/10.5194/wes-7-2059-2022, 2022.
Spangehl, T., Borsche, M., Niermann, D., Kaspar, F., Schimanke, S., Brienen, S., Möller, T., and Brast, M.: Intercomparing the quality of recent reanalyses for offshore wind farm planning in Germany's exclusive economic zone of the North Sea, Adv. Sci. Res., 20, 109–128, https://doi.org/10.5194/asr-20-109-2023, 2023.
Wilczak, J., Akish, E., Capotondi, A., and Compo, G.: Evaluation and bias correction of the ERA5 reanalysis over the United States for wind and solar energy applications, Energies, 17, 1667, https://doi.org/10.3390/en17071667, 2024.
Xu, Y., Yu, H., Wang, S., Chai, Y., and Zhang, C.: Comparison of temperature, relative humidity and surface pressure from CERRA, UERRA and ERA5 reanalysis over Europe, Advances in Space Research, 75, 5363–5373, https://doi.org/10.1016/j.asr.2025.01.038, 2025.
Short summary
In this study, the quality of 10 and 100 m wind speeds from three different reanalyses (global and regional) are evaluated along the different coasts of France. The evaluation show that Copernicus Regional Reanalysis for Europe (CERRA) has a high skill for surface wind speed on the three French seafronts, as well as for offshore wind speed at 100 m. Thus, CERRA appears to be the optimal reanalysis to use as a reference for offshore wind studies over the French maritime zone.
In this study, the quality of 10 and 100 m wind speeds from three different reanalyses (global...
