fix: update external product types reference

[github-actions]

Update external product types reference from daily fetch. See Python API User Guide / Product types discovery

Changed files

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commit edb85882d38d1a2207624b9a2e1953f2318fe5a7

eodag/resources/ext_product_types.json
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<         "missionStartDate": "1864-01-11T00:00:00Z",
---
>         "missionStartDate": "1841-03-21T00:00:00Z",
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<         "abstract": "Global Ocean- in-situ reprocessed Carbon observations. This product contains observations and gridded files from two up-to-date carbon and biogeochemistry community data products: Surface Ocean Carbon ATlas SOCATv2021 and GLobal Ocean Data Analysis Project GLODAPv2.2021. \nThe SOCATv2022-OBS dataset contains >25 million observations of fugacity of CO2 of the surface global ocean from 1957 to early 2022. The quality control procedures are described in Bakker et al. (2016). These observations form the basis of the gridded products included in SOCATv2020-GRIDDED: monthly, yearly and decadal averages of fCO2 over a 1x1 degree grid over the global ocean, and a 0.25x0.25 degree, monthly average for the coastal ocean.\nGLODAPv2.2022-OBS contains >1 million observations from individual seawater samples of temperature, salinity, oxygen, nutrients, dissolved inorganic carbon, total alkalinity and pH from 1972 to 2020. These data were subjected to an extensive quality control and bias correction described in Olsen et al. (2020). GLODAPv2-GRIDDED contains global climatologies for temperature, salinity, oxygen, nitrate, phosphate, silicate, dissolved inorganic carbon, total alkalinity and pH over a 1x1 degree horizontal grid and 33 standard depths using the observations from the previous iteration of GLODAP, GLODAPv2. \nSOCAT and GLODAP are based on community, largely volunteer efforts, and the data providers will appreciate that those who use the data cite the corresponding articles (see References below) in order to support future sustainability of the data products.\n\n**DOI (product):**   \nhttps://doi.org/10.48670/moi-00035\n\n**References:**\n\n* Bakker et al., 2016. A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT). Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016.\n* Olsen et al., 2020. GLODAPv2.2020 – the second update of GLODAPv2. . doi:10.5194/essd‑2020‑165.\n* Lauvset et al., 2016. A new global interior ocean mapped climatology: t ×  1° GLODAP version 2. Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016.\n",
<         "doi": "10.48670/moi-00035",
---
>         "abstract": "Global Ocean- in-situ reprocessed Carbon observations. This product contains observations and gridded files from two up-to-date carbon and biogeochemistry community data products: Surface Ocean Carbon ATlas SOCATv2023 and GLobal Ocean Data Analysis Project GLODAPv2.2023. \nThe SOCATv2023-OBS dataset contains >25 million observations of fugacity of CO2 of the surface global ocean from 1957 to early 2023. The quality control procedures are described in Bakker et al. (2016). These observations form the basis of the gridded products included in SOCATv2023-GRIDDED: monthly, yearly and decadal averages of fCO2 over a 1x1 degree grid over the global ocean, and a 0.25x0.25 degree, monthly average for the coastal ocean.\nGLODAPv2.2023-OBS contains >1 million observations from individual seawater samples of temperature, salinity, oxygen, nutrients, dissolved inorganic carbon, total alkalinity and pH from 1972 to 2021. These data were subjected to an extensive quality control and bias correction described in Olsen et al. (2020). GLODAPv2-GRIDDED contains global climatologies for temperature, salinity, oxygen, nitrate, phosphate, silicate, dissolved inorganic carbon, total alkalinity and pH over a 1x1 degree horizontal grid and 33 standard depths using the observations from the previous major iteration of GLODAP, GLODAPv2. \nSOCAT and GLODAP are based on community, largely volunteer efforts, and the data providers will appreciate that those who use the data cite the corresponding articles (see References below) in order to support future sustainability of the data products.\"\n\n\n**DOI (product):**   \nhttps://doi.org/10.17882/99089\n\n**References:**\n\n* Bakker et al., 2016. A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT). Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016.\n* Lauvset et al. 2024. The annual update GLODAPv2.2023: the global interior ocean biogeochemical data product. Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-468.\n* Lauvset et al., 2016. A new global interior ocean mapped climatology: t ×  1° GLODAP version 2. Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016.\n",
>         "doi": "10.17882/99089",
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<         "title": "Global Ocean - In Situ reprocessed carbon observations - SOCATv2022 / GLODAPv2.2022"
---
>         "title": "Global Ocean - In Situ reprocessed carbon observations - SOCATv2023 / GLODAPv2.2023"
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<         "abstract": "Global Ocean - This delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for ocean surface currents and current vertical profiles. It concerns three delayed time datasets dedicated to near-surface currents measurements coming from two platforms (Lagrangian surface drifters and High Frequency radars) and velocity profiles within the water column coming from the Acoustic Doppler Current Profiler (ADCP, vessel mounted only) platform \n\n**DOI (product):**\nhttps://doi.org/10.17882/86236",
---
>         "abstract": "Global Ocean - This delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for ocean surface and subsurface currents. Current data from 4 different types of instruments are distributed: \n* The NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML) Surface Velocity Program (SVP) Drifter’s reprocessing from 1990. It provides the drifter's position, velocity and includes temperature measurements. In addition, a wind slippage correction is provided from 1993. \n* The near-surface zonal and meridional total velocities, and near-surface radial velocities, measured by High Frequency (HF) radars that are part of the European HF radar Network. These data are delivered together with standard deviation of near-surface zonal and meridional raw velocities, Geometrical Dilution of Precision (GDOP), quality flags and metadata. \n* The zonal and meridional velocities, at parking depth (mostly around 1000m) and at the surface, calculated along the trajectories of the floats which are part of the Argo Program. \n* The velocity profiles within the water column coming from Acoustic Doppler Current Profiler (vessel mounted ADCP, Moored ADCP, saildrones) platforms\n\n**DOI (product):**\nhttps://doi.org/10.17882/86236",
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<         "title": "Global Ocean-Delayed Mode in-situ Observations of surface (drifters and HFR) and sub-surface (vessel-mounted ADCPs) water velocity"
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>         "title": "Global Ocean-Delayed Mode in-situ Observations of surface and sub-surface ocean currents"
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<         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_BALTIC_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset baltic_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea level (SLEV) is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one meter by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves.   \n  \n\n**CMEMS KEY FINDINGS**\n\nUp to 51 stations fulfill the completeness index criteria in this region, a significant improvement with respect to 2019 (only 28 stations), due to new data providers and reprocessed timeseries availability in the new product INSITU_GLO_PHY_SSH_DISCRETE_MY_013_053. The spatial variation of the mean 99th percentiles follow the tidal range pattern, reaching its highest values in the northern end of the Gulf of Bothnia (e.g.: 0.81 m above mean sea level in Kemi) and the inner part of the Gulf of Finland (e.g.: 0.82 m above mean sea level in St. Petersburg). Smaller tides and therefore  99th percentiles are found along the southeastern coast of Sweden, between Stockholm and Gotland Island (e.g.: 0.42 m above mean sea level in Visby). Annual percentiles standard deviation ranges  between 3-5 cm in the South (e.g.: 4 cm in Slipshavn) to 10-13 cm in the Gulf of Finland  (e.g.: 13 cm in St. Petersburg).  Positive anomalies of 2020 99th percentile are observed for most of the basin (up to 11 cm in St. Petersburg),  except at the southern Danish stations, which show negative anomalies reaching -6 cm in Hesnaes and Rodby. This result contrasts with the  remarkably negative anomaly observed in 2019.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00203\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
---
>         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_BALTIC_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset baltic_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\nSea level (SLEV) is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one meter by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves.   \nThe Baltic Sea is affected by vertical land motion due to the Glacial Isostatic Adjustment (Ludwigsen et al., 2020) and consequently relative sea level trends (as measured by tide gauges) have been shown to be strongly negative, especially in the northern part of the basin. On the other hand, Baltic Sea absolute sea level trends (from altimetry-based observations) show statistically significant positive trends (Passaro et al., 2021).  \n\n** KEY FINDINGS**\nUp to 44 stations fulfill the completeness index criteria in this region, a few less than in 2020 (51). The spatial variation of the mean 99th percentiles follow the tidal range pattern, reaching its highest values in the northern end of the Gulf of Bothnia (e.g.: 0.81 m above mean sea level in Kemi) and the inner part of the Gulf of Finland (e.g.: 0.72 m above mean sea level in Hamina, Finland). Smaller tides and therefore 99th percentiles are found along the southeastern coast of Sweden, between Stockholm and Gotland Island (e.g.: 0.43 m above mean sea level in Landsort). Annual percentiles standard deviation ranges between 3-5 cm in the South (e.g.: 3 cm in Korsor, Denmark) to 10-13 cm in the Gulf of Finland (e.g.: 12 cm in Hamina).  Negative anomalies of 2021 99th percentile are observed for most of the basin, reaching maximum values in the Gulf of Bothnia (up to -17 cm in Oulu). Smaller negative anomalies are observed in the southern part (Danish coast), where the only station showing a positive anomaly is Gedser (4 cm).  This result is similar to the one observed in 2019 and contrasts with the remarkably positive anomalies in 2020 for all the stations. \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00203\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
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<         "title": "Baltic Sea Level extreme from Observations Reprocessing"
---
>         "title": "Baltic Sea sea level extreme variability mean and anomaly (observations)"
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<         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_IBI_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset omi_var_extreme_sl_ibi_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea level  is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one metre by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves.\n\n**CMEMS KEY FINDINGS**\n\nThe completeness index criteria is fulfilled by 52 stations, a significant increase with respect to those available in 2019 (17). Most of these new stations belong to UK, Ireland and France, and their reprocessed timeseries are now provided in product  INSITU_GLO_PHY_SSH_DISCRETE_MY_013_053. The mean 99th percentiles reflect the great tide spatial variability around the UK and the north of France. Minimum values are obseved in the Irish coast (e.g.: 0.66 m above mean sea level in Arklow Harbour), South of England (e.g.: 0.70 m above mean sea level in Bournemouth), and the Canary Islands (e.g.: 0.96 m above mean sea level in Hierro). Maximum values are observed in the Bristol and English Channels (e.g.: 6.25 m and 5.16 m above mean sea level in Newport and St. Helier, respectively). The standard deviation reflects the south-north increase of storminess, ranging between 2 cm in the Canary Islands to 12 cm in Newport. Positive anomalies of 2020 99th percentile are observed for most of the stations, increasing northwards from 1-2 cm in the Canary Islands to 16 cm in Workington (Irish Sea). A negative anomaly of -3 cm is observed in Bonanza (Gulf of Cadiz, Guadalquivir river mouth). \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00253\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
---
>         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_IBI_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset ibi_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\nSea level (SLEV) is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one metre by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves.\nThe Iberian Biscay Ireland region shows positive sea level trend modulated by decadal-to-multidecadal variations driven by ocean dynamics and superposed to the long-term trend (Chafik et al., 2019).\n\n** KEY FINDINGS**\nThe completeness index criteria is fulfilled by 55 stations in 2021, three more than those  available in 2020 (52), recently added to the multi-year product  INSITU_GLO_PHY_SSH_DISCRETE_MY_013_053. The mean 99th percentiles reflect the great tide spatial variability around the UK and the north of France. Minimum values are observed in the Irish coast (e.g.: 0.66 m above mean sea level in Arklow Harbour), South of England (e.g.: 0.70 m above mean sea level in Bournemouth), and the Canary Islands (e.g.: 0.96 m above mean sea level in Hierro). Maximum values are observed in the Bristol and English Channels (e.g.: 6.26 m and 5.17 m above mean sea level in Newport and St. Helier, respectively). The standard deviation reflects the south-north increase of storminess, ranging between 2 cm in the Canary Islands to 12 cm in Newport (Bristol Channel). Negative or close to zero anomalies of 2021 99th percentile are observed this year for most of the stations in the region, reaching up to -17.8 cm  in Newport, or -15 cm in St.Helier (Jersey Island, Channel Islands).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00253\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
5193c5193
<         "title": "Iberia Biscay Ireland Sea Level extreme from Observations Reprocessing"
---
>         "title": "Iberia Biscay Ireland sea level extreme variability mean and anomaly (observations)"
5196c5196
<         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_MEDSEA_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset medsea_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea level  is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one metre by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves.\n\n**CMEMS KEY FINDINGS**\n\nThe completeness index criteria is fulfilled in this region by 11 stations, 3 more than in 2019, all of them in the Western Mediterranean. The mean 99th percentiles reflect the spatial variability of the tide, a microtidal regime, along the Spanish and French Mediterranean coasts, ranging from 0.23 m above mean sea level in Ibiza (Balearic Islands) to 0.39 m above mean sea level in Málaga, near the Strait of Gibraltar. The standard deviation ranges between 2 cm in Málaga and Motril (South of Spain) to 8 cm in Marseille. Most of the stations present clear negative anomalies of 2020 99th percentiles, increasing northwards in magnitude, up to -12 cm in Marseille.  Small positive anomalies (around 2 cm) are observed however in Valencia and Ibiza (Spain).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00265\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
---
>         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_WAVE_MEDSEA_swh_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable significant wave height (swh) measured by in situ buoys. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The percentiles are temporally averaged, and the spatial evolution is displayed, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nProjections on Climate Change foresee a future with a greater frequency of extreme sea states (Stott, 2016; Mitchell, 2006). The damages caused by severe wave storms can be considerable not only in infrastructure and buildings but also in the natural habitat, crops and ecosystems affected by erosion and flooding aggravated by the extreme wave heights. In addition, wave storms strongly hamper the maritime activities, especially in harbours. These extreme phenomena drive complex hydrodynamic processes, whose understanding is paramount for proper infrastructure management, design and maintenance (Goda, 2010). In recent years, there have been several studies searching possible trends in wave conditions focusing on both mean and extreme values of significant wave height using a multi-source approach with model reanalysis information with high variability in the time coverage, satellite altimeter records covering the last 30 years and in situ buoy measured data since the 1980s decade but with sparse information and gaps in the time series (e.g. Dodet et al., 2020; Timmermans et al., 2020; Young & Ribal, 2019). These studies highlight a remarkable interannual, seasonal and spatial variability of wave conditions and suggest that the possible observed trends are not clearly associated with anthropogenic forcing (Hochet et al. 2021, 2023).\nFor the Mediterranean Sea an interesting publication (De Leo et al., 2024) analyses recent studies in this basin showing the variability in the different results and the difficulties to reach a consensus, especially in the mean wave conditions. The only significant conclusion is the positive trend in extreme values for the western Mediterranean Sea and in particular in the Gulf of Lion and in the Tyrrhenian Sea.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00265\n\n**References:**\n\n* De Leo F, Briganti R & Besio G. 2024. Trends in ocean waves climate within the Mediterranean Sea: a review. Clim Dyn 62, 1555–1566. https://doi.org/10.1007/s00382-023-06984-4\n* Dodet G, Piolle J-F, Quilfen Y, Abdalla S, Accensi M, Ardhuin F, et al. 2020. The sea state CCI dataset v1: Towards a sea state climate data record based on satellite observations. https://dx.doi.org/10.5194/essd-2019-253\n* Hochet A, Dodet G, Sévellec F, Bouin M-N, Patra A, & Ardhuin F. 2023. Time of emergence for altimetry-based significant wave height changes in the North Atlantic. Geophysical Research Letters, 50, e2022GL102348. https://doi.org/10.1029/2022GL102348\n* Hochet A, Dodet G, Ardhuin F, Hemer M, Young I. 2021. Sea State Decadal Variability in the North Atlantic: A Review. Climate 2021, 9, 173. https://doi.org/10.3390/cli9120173\n* Goda Y. 2010. Random seas and design of maritime structures. World scientific. https://doi.org/10.1142/7425.\n* Mitchell JF, Lowe J, Wood RA, & Vellinga M. 2006. Extreme events due to human-induced climate change. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 364(1845), 2117-2133.\n* 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\n* 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/10.1080/1755876\n* Stott P. 2016. How climate change affects extreme weather events. Science, 352(6293), 1517-1518.\n* Timmermans BW, Gommenginger CP, Dodet G, Bidlot JR. 2020. Global wave height trends and variability from new multimission satellite altimeter products, reanalyses, and wave buoys, Geophys. Res. Lett., № 47. https://doi.org/10.1029/2019GL086880\n* Young IR & Ribal A. 2019. Multiplatform evaluation of global trends in wind speed and wave height. Science, 364, 548–552. https://doi.org/10.1126/science.aav9527\n",
5221c5221
<         "title": "Mediterranean Sea Mean Sea Level extreme from Observations Reprocessing"
---
>         "title": "Mediterranean Sea sea level extreme variability mean and anomaly (observations)"
5224c5224
<         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_NORTHWESTSHELF_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset northwestshelf_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea level  is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one metre by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves.\n\n**CMEMS KEY FINDINGS**\n\nThe completeness index criteria is fulfilled in this region by 23 stations, a significant increase with respect to those used in 2019 (only 6). Most of these new stations belong to UK and Denmark, and their reprocessed timeseries are now provided in product  INSITU_GLO_PHY_SSH_DISCRETE_MY_013_053. The mean 99th percentiles present a large spatial variability related to the tidal pattern, ranging from the 3.08 m and 3.38 m above mean sea level in Immingan (East England) and Calais (France, English Channel) respectively,  to 0.59 m above mean sea level in Aarhus (Denmark). The standard deviation ranges between 3 and 8 cm. There is a clear positive anomaly of 99th percentiles in 2020 for most of the stations, reaching 11 cm in Kungsvik (Sweden) and Ullapool (Scotland). Null or very small negative anomalies are only observed at two stations in the southeastern coast of England.  \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00272\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
---
>         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SL_NORTHWESTSHELF_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset northwestshelf_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea level (SLEV) is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one metre by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves. \nThe North West Shelf area presents positive sea level trends with higher trend estimates in the German Bight and around Denmark, and lower trends around the southern part of Great Britain (Dettmering et al., 2021).\n\n**KEY FINDINGS**\n\nThe completeness index criteria is fulfilled in this region by 26 stations, three more than in 2020 (23). The mean 99th percentiles present a large spatial variability related to the tidal pattern, ranging from the 3.08 m above mean sea level in Immingan (East England)  to 0.58 m above mean sea level in Ringhals (Sweden). The standard deviation ranges between 3 cm in the western part of the region (Sheerness, Lerwick or Dunkerke) and 8 cm in the eastern part and the Kattegat (e.g. Hornbaek, Denmark). All the stations show negative or close to zero anomalies in 2021, reaching larger negative values along the Swedish coast (up to -13 cm in Ringhals) and the North of Scotland (-10 cm in Ullapool).  This negative anomaly is significantly smaller in the Southern part of the region (e.g. close to zero in Dover).   \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00272\n\n**References:**\n\n* Abram, N., Gattuso, J.-P., Prakash, A., Cheng, L., Chidichimo, M. P., Crate, S., Enomoto, H., Garschagen, M., Gruber, N., Harper, S., Holland, E., Kudela, R. M., Rice, J., Steffen, K., & von Schuckmann, K. (2019). Framing and Context of the Report. In H. O. Pörtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (pp. 73–129). in press. https://www.ipcc.ch/srocc/\n* Legeais J-F, W. Llowel, A. Melet and B. Meyssignac: Evidence of the TOPEX-A Altimeter Instrumental Anomaly and Acceleration of the Global Mean Sea Level, in Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 2020, accepted.\n* 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\n* 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.\n* WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present. 2018. Earth Syst. Sci. Data, 10, 1551-1590, https://doi.org/10.5194/essd-10-1551-2018.\n* Vousdoukas MI, Mentaschi L, Hinkel J, et al. 2020. Economic motivation for raising coastal flood defenses in Europe. Nat Commun 11, 2119 (2020). https://doi.org/10.1038/s41467-020-15665-3.\n",
5249c5249
<         "title": "North West Shelf Mean Sea Level extreme from Observations Reprocessing"
---
>         "title": "North West Shelf sea level extreme variability mean and anomaly (observations)"
5252c5252
<         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SST_BALTIC_sst_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea surface temperature measured by in situ buoys at depths between 0 and 5 meters. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The percentiles are temporally averaged, and the spatial evolution is displayed, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea surface temperature (SST) is one of the essential ocean variables affected by climate change (mean SST trends, SST spatial and interannual variability, and extreme events). In Europe, several studies show warming trends in mean SST for the last years.  An exception seems to be the North Atlantic, where, in contrast, anomalous cold conditions have been observed since 2014 (Mulet et al., 2018; Dubois et al. 2018). Extremes may have a stronger direct influence in population dynamics and biodiversity. According to Alexander et al. 2018 the observed warming trend will continue during the 21st Century and this can result in exceptionally large warm extremes. Monitoring the evolution of sea surface temperature extremes is, therefore, crucial.\nThe Baltic Sea has showed in the last two decades a warming trend across the whole basin. This trend is significantly higher when considering only the summer season, which would affect the high extremes (e.g. Høyer and Karagali, 2016).\n\n**CMEMS KEY FINDINGS**\n\nThe mean 99th percentiles showed in the area go from 18.7ºC in Slipshavn to 21.2ºC around the Zealand Region, and the standard deviation ranges between 1ºC and 2ºC.\nResults for this year show a slight positive anomaly in the central Baltic Sea below +0.5ºC, a moderate positive anomaly in Bomholm and Arkona Basins, reaching +2.8ºC in Slipshavn, and a negative anomaly in the Southwest of Zealand Region (Bay of Mecklenburg, Kiel Basin and South of Great Belt) between -1.5ºC and -2.5ºC. \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00204\n\n**References:**\n\n* Alexander MA, Scott JD, Friedland KD, Mills KE, Nye JA, Pershing AJ, Thomas AC. 2018. Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans. Elem Sci Anth, 6(1), p.9. DOI: http://doi.org/10.1525/elementa.191.\n* Dubois C, von Schuckmann K, Josey S, Ceschin A. 2018. Changes in the North Atlantic. In: Copernicus Marine Service Ocean State Report, Issue 2, Journal of Operational Oceanography, vol 11, sup1, s66–s70. DOI: 10.1080/1755876X.2018.1489208\n* Høyer, JL, Karagali, I. 2016. Sea surface temperature climate data record for the North Sea and Baltic Sea. Journal of Climate, 29(7), 2529-2541. https://doi.org/10.1175/JCLI-D-15-0663.1\n* 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\n* 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.\n",
---
>         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SST_BALTIC_sst_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea surface temperature measured by in situ buoys at depths between 0 and 5 meters. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The percentiles are temporally averaged, and the spatial evolution is displayed, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018). \n\n**CONTEXT**\nSea surface temperature (SST) is one of the essential ocean variables affected by climate change (mean SST trends, SST spatial and interannual variability, and extreme events). In Europe, several studies show warming trends in mean SST for the last years (von Schuckmann, 2016; IPCC, 2021, 2022). An exception seems to be the North Atlantic, where, in contrast, anomalous cold conditions have been observed since 2014 (Mulet et al., 2018; Dubois et al. 2018; IPCC 2021, 2022). Extremes may have a stronger direct influence in population dynamics and biodiversity. According to Alexander et al. 2018 the observed warming trend will continue during the 21st Century and this can result in exceptionally large warm extremes. Monitoring the evolution of sea surface temperature extremes is, therefore, crucial.\nThe Baltic Sea has showed in the last two decades a warming trend across the whole basin with more frequent and severe heat waves (IPCC, 2022). This trend is significantly higher when considering only the summer season, which would affect the high extremes (e.g. Høyer and Karagali, 2016).\n\n** KEY FINDINGS**\n\nThe mean 99th percentiles showed in the area go from 18.9ºC in Slipshavn to 21.0ºC around the Zealand Region, and the standard deviation ranges between 1ºC and 5ºC reached in the Estonian Coast.\nResults for this year show a general positive anomaly. This anomaly is noticeable in Rohukula and Virtsu tide gauges (Estonia) with +5ºC and +4.8ºC, but inside the standard deviation in both locations. The positive anomaly is remarkable in the South Baltic, in the area of Denmark Islands with an anomaly of +3.0ºC in Slipshavn and 1.2ºC of standard deviation and +2.2ºC of anomaly and 1.1ºC of standard deviation in Fynshavn and also in Greifswalder Island (+2.5ºC of anomaly; 1.7ºC of standard deviation). In the rest of the Baltic the anomaly, even when positive, is under the margin of the standard deviation. \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00204\n\n**References:**\n\n* Alexander MA, Scott JD, Friedland KD, Mills KE, Nye JA, Pershing AJ, Thomas AC. 2018. Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans. Elem Sci Anth, 6(1), p.9. DOI: http://doi.org/10.1525/elementa.191.\n* Dubois C, von Schuckmann K, Josey S, Ceschin A. 2018. Changes in the North Atlantic. In: Copernicus Marine Service Ocean State Report, Issue 2, Journal of Operational Oceanography, vol 11, sup1, s66–s70. DOI: 10.1080/1755876X.2018.1489208\n* Høyer, JL, Karagali, I. 2016. Sea surface temperature climate data record for the North Sea and Baltic Sea. Journal of Climate, 29(7), 2529-2541. https://doi.org/10.1175/JCLI-D-15-0663.1\n* 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\n* 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.\n* von Schuckmann K, Le Traon PY, Alvarez-Fanjul E, Axell L, Balmaseda M, Breivik LA, … Verbrugge N. 2016. The Copernicus Marine Environment Monitoring Service Ocean State Report. Journal of Operational Oceanography, 9(sup2), s235–s320. https://doi.org/10.1080/1755876X.2016.1273446\n",
5277c5277
<         "title": "Baltic Sea Surface Temperature extreme from Observations Reprocessing"
---
>         "title": "Baltic Sea sea surface temperature extreme variability mean and anomaly (observations)"
5280c5280
<         "abstract": "**DEFINITION**\n\nThe OMI_EXTREME_SST_IBI_sst_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea surface temperature measured by in situ buoys at depths between 0 and 5 meters. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The percentiles are temporally averaged, and the spatial evolution is displayed, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018).\n\n**CONTEXT**\n\nSea surface temperature (SST) is one of the essential ocean variables affected by climate change (mean SST trends, SST spatial and interannua