Legal Notices

ERA5/ERA5 Land

Contains modified Copernicus Climate Change Service information.

Access to all Copernicus Information and Data is regulated under Regulation (EU) No 1159/2013 of the European Parliament and of the Council of 12 July 2013 on the European Earth monitoring program, under the ECMWF Agreement and under the European Commission's Terms and Conditions. Access to all Copernicus information is regulated under Regulation (EU) No 1159/2013 and under the ECMWF Agreement.

Access to Copernicus Products is given for any purpose in so far as it is lawful, whereas use may include, but is not limited to: reproduction; distribution; communication to the public; adaptation, modification and combination with other data and information; or any combination of the foregoing.

Consult Copernicus Licence to Use

CMIP6

CMIP6 model data is licensed under a Creative Commons International License (https://creativecommons.org/licenses/). The exact license may vary depending on the modelling center:

The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

Consult CMIP6 Terms of Use for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.

CSIRO

CSIRO waves data is licensed under a Creative Commons International License CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/).

Consult https://data.csiro.au/collection/csiro:53176

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References

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[ii] Arias, P.A. & al. (2021). Technical Summary. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. available online

[iii] Hausfather, Z. & al. (2022). Climate simulations: recognize the "hot model" problem. Nature, 605, 26–29. available online

[iv] Shiogama, H. & al. (2021). Selecting CMIP6-based future climate scenarios for impact and adaptation studies. SOLA. available online

[v] Zelinka, M. D. & al. (2020). Causes of higher climate sensitivity in CMIP6 models. Geophys. Res. Lett., 47. available online

[vi] Knutti, R. & al. (2013). Climate model genealogy: Generation CMIP5 and how we got there. Geophysical Research Letters, 40(6), 1194-1199. available online

[vii] Brunner, L. & al. (2020). Reduced global warming from CMIP6 projections when weighting models by performance and independence. Earth Syst. Dynam., 11, 995–1012, 2020. available online

[viii] Maraun, D. (2016). Bias correcting climate change simulations - a critical review. Current Climate Change Reports, 2(4), 211-220. available online

[ix] Michelangeli, P. A. & al. (2009). Probabilistic downscaling approaches: Application to wind cumulative distribution functions. Geophys. Res. Lett. 36.11. available online

[x] Vrac, M. (2016). Bias correction of precipitation through Singularity Stochastic Removal: Because occurrences matter. Journal of Geophysical Research: Atmospheres, 121(10), 5091-6129. available online

[xi] ISO. (2016). Petroleum and natural gas industries — Specific requirements for offshore structures — Part 1: Metocean design and operating considerations (ISO 19901-1:2015), p.15.

[xii] Coles, S. (2001). An Introduction to Statistical Modelling of Extreme Values. Springer Series in Statistics.

[xiii] IPCC. (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. available online

[xiv] Raynal-Villasenor, J. & al. (2014). Estimation procedures for the GEV distribution for the minima. Journal of Hydrology, 519, 512-522.

[xv] Kysely, J. (2002). Probability Estimates of Extreme Temperature Events: Stochastic Modelling Approach vs. Extreme Value Distributions. Studia Geophysica et Geodaetica, 46, 93–112. available online

[xvi] Kurbatova, M., & al. (2018). Comparison of seven wind gust parameterizations over the European part of Russia. Advances in Science and Research. available online

[xvii] ISO. (2016): Op. Cit. p.20.

[xviii] ISO. (2016): Op. Cit. p.46.

[xix] American Petroleum Institute. (2014). Recommended practice for planning, designing and constructing fixed offshore platforms. Formula 5.3.

[xx] Fox-Kemper, B. & al. (2021). Ocean, Cryosphere and Sea Level Change. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. available online

[xxi] IPCC. (2019). IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. p. 327.

[xxii] Fox-Kemper, B. & al. (2021). Op. cit. p. 1308.

[xxiii] ISO. (2016): Op. Cit. p.7.

[xxiv] Martin, P. (2023): How to describe the wave height and wave period parameters? available online

[xxv] WMO. (2020): Guide to wave analysis and forecasting (2018 edition). p. 19. available online

[xxvi] WMO. (2020): Op. Cit. p. 19.

[xxvii] WMO. (2020): Op. Cit. p. 19.

[xxviii] ISO. (2016): Op. Cit. p.5.

[xxix] Fox-Kemper, B. & al. (2021): Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. p. 1310. available online

[xxx] Lobeto, H. & al. (2021): Future behavior of wind wave extremes due to climate change. Sci Rep 11, 7869. available online

[xxxi] Ewans, K. & al. (2023): Uncertainties in estimating the effect of climate change on 100-year return value for significant wave height. Ocean Engineering 272. available online

[xxxii] Morim, J. & al. (2023): Understanding uncertainties in contemporary and future extreme wave events for broad-scale impact and adaptation planning. Science Advances 9.2. available online

[xxxiii] Meucci, A. et al. (2023): 140 years of global ocean wind-wave climate derived from CMIP6 ACCESS-CM2 and EC-Earth3 GCMs: Global trends, regional changes, and future projections. Journal of Climate 36.6: 1605-1631. available online

[xxxiv] WMO. (2020): Op. Cit. p. 14.

[xxxv] Goda, Y. Revisiting Wilson's formulas for simplified wind-wave prediction. J. Waterw. Port Coast. Ocean Eng. 2003, 129, 93–95.