ecff59c4-aa54-4c43-90a5-dc944b40d6fe Copernicus Marine Service product specification CMEMS servicedesk.cmems@mercator-ocean.eu http://marine.copernicus.eu/ 2025-10-22T08:54:32.155855Z ISO 19139, MyOcean profile 0.2 2 0.01 0.01 false WGS 84 (EPSG:4326) EPSG Iberia Biscay Ireland Significant Wave Height extreme from Reanalysis IBI_OMI_SEASTATE_extreme_var_swh_mean_and_anomaly 2020-06-18 3.4 2025-11-25 a78600a4-a280-47b5-8ddd-0dc8b5e9c9d9 '''DEFINITION''' The Copernicus Marine IBI_OMI_seastate_extreme_var_swh_mean_and_anomaly OMI indicator is based on the computation of the annual 99th percentile of Significant Wave Height (SWH) from model data. Two different CMEMS products are used to compute the indicator: The Iberia-Biscay-Ireland Multi Year Product (IBI_MULTIYEAR_WAV_005_006) and the Analysis product (IBI_ANALYSISFORECAST_WAV_005_005). Two parameters have been considered for this OMI: * Map of the 99th mean percentile: It is obtained from the Multi-Year Product, the annual 99th percentile is computed for each year of the product. The percentiles are temporally averaged in the whole period (1980-2023). * Anomaly of the 99th percentile in 2024: The 99th percentile of the year 2024 is computed from the Analysis product. The anomaly is obtained by subtracting the mean percentile to the percentile in 2024. This indicator is aimed at monitoring the extremes of annual significant wave height and evaluate the spatio-temporal variability. The use of percentiles instead of annual maxima, makes this extremes study less affected by individual data. This approach was first successfully applied to sea level variable (Pérez Gómez et al., 2016) and then extended to other essential variables, such as sea surface temperature and significant wave height (Pérez Gómez et al 2018 and Álvarez-Fanjul et al., 2019). Further details and in-depth scientific evaluation can be found in the CMEMS Ocean State report (Álvarez- Fanjul et al., 2019). '''CONTEXT''' The sea state and its related spatio-temporal variability affect dramatically maritime activities and the physical connectivity between offshore waters and coastal ecosystems, impacting therefore on the biodiversity of marine protected areas (González-Marco et al., 2008; Savina et al., 2003; Hewitt, 2003). Over the last decades, significant attention has been devoted to extreme wave height events since their destructive effects in both the shoreline environment and human infrastructures have prompted a wide range of adaptation strategies to deal with natural hazards in coastal areas (Hansom et al., 2015). Complementarily, there is also an emerging question about the role of anthropogenic global climate change on present and future extreme wave conditions (Young and Ribal, 2019). The Iberia-Biscay-Ireland region, which covers the North-East Atlantic Ocean from Canary Islands to Ireland, is characterized by two different sea state wave climate regions: whereas the northern half, impacted by the North Atlantic subpolar front, is of one of the world’s greatest wave generating regions (Mørk et al., 2010; Folley, 2017), the southern half, located at subtropical latitudes, is by contrast influenced by persistent trade winds and thus by constant and moderate wave regimes. The North Atlantic Oscillation (NAO), which refers to changes in the atmospheric sea level pressure difference between the Azores and Iceland, is a significant driver of wave climate variability in the Northern Hemisphere. The influence of North Atlantic Oscillation on waves along the Atlantic coast of Europe is particularly strong in and has a major impact on northern latitudes wintertime (Gleeson et al., 2017; Martínez-Asensio et al. 2016; Wolf et al., 2002; Bauer, 2001; Kushnir et al., 1997; Bouws et al., 1996; Bacon and Carter, 1991). Swings in the North Atlantic Oscillation index produce changes in the storms track and subsequently in the wind speed and direction over the Atlantic that alter the wave regime. When North Atlantic Oscillation index is in its positive phase, storms usually track northeast of Europe and enhanced westerly winds induce higher than average waves in the northernmost Atlantic Ocean. Conversely, in the negative North Atlantic Oscillation phase, the track of the storms is more zonal and south than usual, with trade winds (mid latitude westerlies) being slower and producing higher than average waves in southern latitudes (Marshall et al., 2001; Wolf et al., 2002; Wolf and Woolf, 2006). Additionally, a variety of previous studies have uniquevocally determined the relationship between the sea state variability in the IBI region and other atmospheric climate modes such as the East Atlantic pattern, the Arctic Oscillation, the East Atlantic Western Russian pattern and the Scandinavian pattern (Izaguirre et al., 2011, Martínez-Asensio et al., 2016). In this context, long‐term statistical analysis of reanalyzed model data is mandatory not only to disentangle other driving agents of wave climate but also to attempt inferring any potential trend in the number and/or intensity of extreme wave events in coastal areas with subsequent socio-economic and environmental consequences. '''CMEMS KEY FINDINGS''' The climatic mean of 99th percentile (1980-2023) reveals a north-south gradient of Significant Wave Height with the highest values in northern latitudes (above 8m) and lowest values (2-3 m) detected southeastward of Canary Islands, in the seas between Canary Islands and the African Continental Shelf. This north-south pattern is the result of the two climatic conditions prevailing in the region and previously described. The 99th percentile anomalies in 2024 show that during this period, virtually the entire IBI region was affected by positive anomalies in maximum SWH, which exceeded the standard deviation of the historical record in the waters west of the Iberian Peninsula, the Spanish coast of the Bay of Biscay, and the African coast south of Cape Ghir. Anomalies reaching twice the standard deviation of the time series were also observed in coastal regions of the English Channel. '''DOI (product):''' https://doi.org/10.48670/moi-00249 E.U. Copernicus Marine Service Information IBI-NOW-MADRID-ES P0M0D0H/P0M0D0H N/A https://documentation.marine.copernicus.eu/IMG/IBI_OMI_SEASTATE_extreme_var_swh_mean_and_anomaly.png Oceanographic geographical features GEMET - INSPIRE themes, version 1.0 2009-09-22 numerical-model Discipline 2023-03-16 geonetwork.thesaurus.local.discipline.myocean.discipline Climate and Forecast Standard Names 2017-04-04 geonetwork.thesaurus.external.parameter.myocean.ocean-variables multi-year Temporal scale 2024-07-26 geonetwork.thesaurus.local.temporal-scale.myocean.temporal-scale marine-safety weather-climate-and-seasonal-forecasting coastal-marine-environment marine-resources Area of benefit 2025-07-29 geonetwork.thesaurus.local.area-of-benefit.myocean.area-of-benefit iberian-biscay-irish-seas Reference Geographical Areas 2024-07-26 geonetwork.thesaurus.local.reference-geographical-area.myocean.reference-geographical-area N/A Processing level 2024-07-26 geonetwork.thesaurus.local.processing-level.myocean.processing-level Not Applicable Model assimilation 2016-02-03 geonetwork.thesaurus.external.theme.myocean.model-assimilation See Copernicus Marine Environment Monitoring Service Data commitments and licence at: http://marine.copernicus.eu/web/27-service-commitments-and-licence.php No limitations on public access Álvarez Fanjul E, Pascual Collar A, Pérez Gómez B, De Alfonso M, García Sotillo M, Staneva J, Clementi E, Grandi A, Zacharioudaki A, Korres G, Ravdas M, Renshaw R, Tinker J, Raudsepp U, Lagemaa P, Maljutenko I, Geyer G, Müller M, Çağlar Yumruktepe V. Sea level, sea surface temperature and SWH extreme percentiles: combined analysis from model results and in situ observations, Section 2.7, p:31. In: Schuckmann K, Le Traon P-Y, Smith N, Pascual A, Djavidnia S, Gattuso J-P, Grégoire M, Nolan G, et al. 2019. Copernicus Marine Service Ocean State Report, Issue 3, Journal of Operational Oceanography, 12:sup1, S1-S123, DOI: 10.1080/1755876X.2019.1633075 2019-05-08 Bacon S, Carter D J T. 1991. Wave climate changes in the north Atlantic and North Sea, International Journal of Climatology, 11, 545–558. 2019-05-08 Bauer E. 2001. Interannual changes of the ocean wave variability in the North Atlantic and in the North Sea, Climate Research, 18, 63–69. 2019-05-08 Bouws E, Jannink D, Komen GJ. 1996. The increasing wave height in the North Atlantic Ocean, Bull. Am. Met. Soc., 77, 2275–2277. 2019-05-08 Folley M. 2017. The wave energy resource. In Pecher A, Kofoed JP (ed.), Handbook of Ocean Wave Energy, Ocean Engineering & Oceanography 7, doi:10.1007/978-3-319-39889-1_3. 2019-05-08 Gleeson E, Gallagher S, Clancy C, Dias F. 2017. NAO and extreme ocean states in the Northeast Atlantic Ocean, Adv. Sci. Res., 14, 23–33, doi:10.5194/asr-14-23-2017. 2019-05-08 González-Marco D, Sierra J P, Ybarra O F, Sánchez-Arcilla A. 2008. Implications of long waves in harbor management: The Gijón port case study. Ocean & Coastal Management, 51, 180-201. doi:10.1016/j.ocecoaman.2007.04.001. 2019-05-08 Hanson et al., 2015. Extreme Waves: Causes, Characteristics and Impact on Coastal Environments and Society January 2015 In book: .Coastal and Marine Hazards, Risks, and Disasters Edition: Hazards and Disasters Series, Elsevier Major Reference Works Chapter: Chapter 11: Extreme Waves: Causes, Characteristics and Impact on Coastal Environments and Society. Publisher: Elsevier Editors: Ellis, J and Sherman, D. J. 2019-05-08 Hewit J E, Cummings V J, Elis J I, Funnell G, Norkko A, Talley T S, Thrush S.F. 2003. The role of waves in the colonisation of terrestrial sediments deposited in the marine environment. Journal of Experimental marine Biology and Ecology, 290, 19-47, doi:10.1016/S0022-0981(03)00051-0. 2019-05-08 Izaguirre C, Méndez F J, Menéndez M, Losada I J. 2011. Global extreme wave height variability based on satellite data Cristina. Geoph. Res. Letters, Vol. 38, L10607, doi: 10.1029/2011GL047302. 2019-05-08 Martínez-Asensio A, Tsimplis M N, Marcos M, Feng F, Gomis D, Jordàa G, Josey S A. 2016. Response of the North Atlantic wave climate to atmospheric modes of variability. International Journal of Climatology, 36, 1210–1225, doi: 10.1002/joc.4415. 2019-05-08 Mørk G, Barstow S, Kabush A, Pontes MT. 2010. Assessing the global wave energy potential. Proceedings of OMAE2010 29th International Conference on Ocean, Offshore Mechanics and Arctic Engineering June 6-11, 2010, Shanghai, China. 2019-05-08 Pérez-Gómez B, Álvarez-Fanjul E, She J, Pérez-González I, Manzano F. 2016. Extreme sea level events, Section 4.4, p:300. In: Von Schuckmann K, Le Traon PY, Alvarez-Fanjul E, Axell L, Balmaseda M, Breivik LA, Brewin RJW, Bricaud C, Drevillon M, Drillet Y, Dubois C , Embury O, Etienne H, García-Sotillo M, Garric G, Gasparin F, Gutknecht E, Guinehut S, Hernandez F, Juza M, Karlson B, Korres G, Legeais JF, Levier B, Lien VS, Morrow R, Notarstefano G, Parent L, Pascual A, Pérez-Gómez B, Perruche C, Pinardi N, Pisano A, Poulain PM , Pujol IM, Raj RP, Raudsepp U, Roquet H, Samuelsen A, Sathyendranath S, She J, Simoncelli S, Solidoro C, Tinker J, Tintoré J, Viktorsson L, Ablain M, Almroth-Rosell E, Bonaduce A, Clementi E, Cossarini G, Dagneaux Q, Desportes C, Dye S, Fratianni C, Good S, Greiner E, Gourrion J, Hamon M, Holt J, Hyder P, Kennedy J, Manzano-Muñoz F, Melet A, Meyssignac B, Mulet S, Nardelli BB, O’Dea E, Olason E, Paulmier A, Pérez-González I, Reid R, Racault MF, Raitsos DE, Ramos A, Sykes P, Szekely T, Verbrugge N. 2016. The Copernicus Marine Environment Monitoring Service Ocean State Report, Journal of Operational Oceanography. 9 (sup2): 235-320. http://dx.doi.org/10.1080/1755876X.2016.1273446 2019-05-08 Pérez Gómez B., De Alfonso M., Zacharioudaki A., Pérez González I., Álvarez Fanjul E., Müller M., Marcos M., Manzano F., Korres G., Ravdas M., Tamm S. 2018. Sea level, SST and waves: extremes variability. In: Copernicus Marine Service Ocean State Report, Issue 2, Journal of Operational Oceanography, 11:sup1, Chap. 3.1, s79–s88, DOI: https://doi.org/10.1080/1755876X.2018.1489208 2019-05-08 Savina H, Lefevre J-M, Josse P, Dandin P. 2003. Definition of warning criteria. Proceedings of MAXWAVE Final Meeting, October 8-11, Geneva, Switzerland. 2019-05-08 Woolf D K, Challenor P G, Cotton P D. 2002. Variability and predictability of the North Atlantic wave climate, J. Geophys. Res., 107(C10), 3145, doi:10.1029/2001JC001124. 2019-05-08 001acb8a-2e6e-467f-a5fe-fb23bf387527 09350d76-a79c-4146-8f43-0c54a031f322 226ba3e3-74ef-4ce1-804a-0d635fc277ef Wolf J, Woolf D K. 2006. Waves and climate change in the north-east Atlantic. Geophysical Research Letters, Vol. 33, L06604, doi: 10.1029/2005GL025113. 2019-05-08 Young I R, Ribal A. 2019. Multiplatform evaluation of global trends in wind speed and wave height. Science, 364, 548-552, doi: 10.1126/science.aav9527. 2019-05-08 Kushnir Y, Cardone VJ, Greenwood JG, Cane MA. 1997. The recent increase in North Atlantic wave heights. Journal of Climate 10:2107–2113. 2019-05-08 Marshall, J., Kushnir, Y., Battisti, D., Chang, P., Czaja, A., Dickson, R., ... & Visbeck, M. (2001). North Atlantic climate variability: phenomena, impacts and mechanisms. International Journal of Climatology: A Journal of the Royal Meteorological Society, 21(15), 1863-1898. 2019-05-08 eng oceans bounding box -19.00 5.00 26.00 56.00 1980-01-01 2024-12-31 0 0 display priority: 53800 observation vertical level number: 1 temporal resolution: annual mean false Grid NetCDF-4 https://stac.marine.copernicus.eu/metadata/IBI_OMI_SEASTATE_extreme_var_swh_mean_and_anomaly/ibi_omi_seastate_extreme_var_swh_mean_and_anomaly_202311/dataset.stac.json WWW:STAC ibi_omi_seastate_extreme_var_swh_mean_and_anomaly For accessing native data and Analysis-ready Cloud-optimized data services, consult this STAC metadata endpoint https://wmts.marine.copernicus.eu/teroWmts/IBI_OMI_SEASTATE_extreme_var_swh_mean_and_anomaly/ibi_omi_seastate_extreme_var_swh_mean_and_anomaly_202311?service=WTMS&request=GetCapabilities OGC:WMTS ibi_omi_seastate_extreme_var_swh_mean_and_anomaly COMMISSION REGULATION (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 See the referenced specification The myOcean products depends on other products for production or validation. The detailed list of dependencies is given in ISO19115's aggregationInfo (ISO19139 Xpath = "gmd:MD_Metadata/gmd:identificationInfo/gmd:aggregationInfo[./gmd:MD_AggregateInformation/gmd:initiativeType/gmd:DS_InitiativeTypeCode/@codeListValue='upstream-validation' or 'upstream-production']")