eodag/resources/ext_product_types.json
1c1
< {"astraea_eod": {"product_types_config": {}, "providers_config": {}}, "cop_marine": {"product_types_config": {"ANTARCTIC_OMI_SI_extent": {"abstract": "**DEFINITION**\n\nEstimates of Antarctic sea ice extent are obtained from the surface of oceans grid cells that have at least 15% sea ice concentration. These values are cumulated in the entire Southern Hemisphere (excluding ice lakes) and from 1993 up to real time aiming to:\ni) obtain the Antarctic sea ice extent as expressed in millions of km squared (106 km2) to monitor both the large-scale variability and mean state and change.\nii) to monitor the change in sea ice extent as expressed in millions of km squared per decade (106 km2/decade), or in sea ice extent loss/gain since the beginning of the time series as expressed in percent per decade (%/decade; reference period being the first date of the key figure b) dot-dashed trend line, Vaughan et al., 2013)). For the Southern Hemisphere, these trends are calculated from the annual mean values.\nThe Antarctic sea ice extent used here is based on the \u201cmulti-product\u201d approach as introduced in the second issue of the Ocean State Report (CMEMS OSR, 2017). Five global products have been used to build the ensemble mean, and its associated ensemble spread.\n\n**CONTEXT**\n\nSea ice is frozen seawater that floats on the ocean surface. This large blanket of millions of square kilometers insulates the relatively warm ocean waters from the cold polar atmosphere. The seasonal cycle of the sea ice, forming and melting with the polar seasons, impacts both human activities and biological habitat. Knowing how and how much the sea ice cover is changing is essential for monitoring the health of the Earth as sea ice is one of the highest sensitive natural environments. Variations in sea ice cover can induce changes in ocean stratification and modify the key rule played by the cold poles in the Earth engine (IPCC, 2019). \nThe sea ice cover is monitored here in terms of sea ice extent quantity. More details and full scientific evaluations can be found in the CMEMS Ocean State Report (Samuelsen et al., 2016; Samuelsen et al., 2018).\n \n**CMEMS KEY FINDINGS**\n\nWith quasi regular highs and lows, the annual Antarctic sea ice extent shows large variability until several monthly record high in 2014 and record lows in 2017 and 2018. Since the year 1993, the Southern Hemisphere annual sea ice extent regularly alternates positive and negative trend. The period 1993-2018 have seen a slight decrease at a rate of -0.01*106km2 per decade. This represents a loss amount of 0.1% per decade of Southern Hemisphere sea ice extent during this period; with however large uncertainties. The last quarter of the year 2016 and years 2017 and 2018 experienced unusual losses of ice. 2019 is not a record year, but the summer of 2019 remains among the lowest since the 1990s. \n\nNote: The key findings will be updated annually in November, in line with OMI evolutions.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00186\n\n**References:**\n\n* IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. (2019). In H. O. P\u00f6rtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegr\u00eda, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Intergovernmental Panel on Climate Change: Geneva, Switzerland. https://www.ipcc.ch/srocc/\n* Samuelsen et al., 2016: Sea Ice In: The Copernicus Marine Environment Monitoring Service Ocean State Report, issue 1, Journal of Operational Oceanography, 9, 2016, http://dx.doi.org/10.1080/1755876X.2016.1273446.\n* Samuelsen et al., 2018: Sea Ice. In: The Copernicus Marine Environment Monitoring Service Ocean State Report, issue 2, Journal of Operational Oceanography, 11:sup1, 2018, DOI: 10.1080/1755876X.2018.1489208.\n* Vaughan, D.G., J.C. Comiso, I. Allison, J. Carrasco, G. Kaser, R. Kwok, P. Mote, T. Murray, F. Paul, J. Ren, E. Rignot, O. Solomina, K. Steffen and T. Zhang, 2013: Observations: Cryosphere. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M.Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 317\u2013382, doi:10.1017/CBO9781107415324.012.\n", "doi": "10.48670/moi-00186", "instrument": null, "keywords": "antarctic-omi-si-extent,coastal-marine-environment,global-ocean,marine-resources,marine-safety,multi-year,numerical-model,oceanographic-geographical-features,sea-ice-extent,target-application#seaiceinformation,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": null, "providers": [{"name": "Mercator Oc\u00e9an International", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Antarctic Sea Ice Extent from Reanalysis"}, "ANTARCTIC_OMI_SI_extent_obs": {"abstract": "**DEFINITION**\n\nSea Ice Extent (SIE) is defined as the area covered by sufficient sea ice, that is the area of ocean having more than 15% Sea Ice Concentration (SIC). SIC is the fractional area of ocean surface that is covered with sea ice. SIC is computed from Passive Microwave satellite observations since 1979. \nSIE is often reported with units of 106 km2 (millions square kilometers). The change in sea ice extent (trend) is expressed in millions of km squared per decade (106 km2/decade). In addition, trends are expressed relative to the 1979-2022 period in % per decade.\nThese trends are calculated (i) from the annual mean values; (ii) from the September values (winter ice loss); (iii) from February values (summer ice loss). The annual mean trend is reported on the key figure, the September (maximum extent) and February (minimum extent) values are reported in the text below.\nSIE includes all sea ice, except for lake and river ice.\nSee also section 1.7 in Samuelsen et al. (2016) for an introduction to this Ocean Monitoring Indicator (OMI).\n\n**CONTEXT**\n\nSea ice is frozen seawater that floats at the ocean surface. This large blanket of millions of square kilometers insulates the relatively warm ocean waters from the cold polar atmosphere. The seasonal cycle of sea ice, forming and melting with the polar seasons, impacts both human activities and biological habitat. Knowing how and by how much the sea-ice cover is changing is essential for monitoring the health of the Earth (Meredith et al. 2019). \n\n**CMEMS KEY FINDINGS**\n\nSince 1979, there has been an overall slight increase of sea ice extent in the Southern Hemisphere but a sharp decrease was observed after 2016. Over the period 1979-2022, the annual rate amounts to +0.02 +/- 0.05 106 km2 per decade (+0.18% per decade). Winter (September) sea ice extent trend amounts to +0.06 +/- 0.05106 km2 per decade (+0.32% per decade). Summer (February) sea ice extent trend amounts to -0.01+/- 0.05 106 km2 per decade (-0.38% per decade). These trend estimates are hardly significant, which is in agreement with the IPCC SROCC, which has assessed that \u2018Antarctic sea ice extent overall has had no statistically significant trend (1979\u20132018) due to contrasting regional signals and large interannual variability (high confidence).\u2019 (IPCC, 2019). Both June and July 2022 had the lowest average sea ice extent values for these months since 1979. \n\n**Figure caption**\n\na) The seasonal cycle of Southern Hemisphere sea ice extent expressed in millions of km2 averaged over the period 1979-2022 (red), shown together with the seasonal cycle in the year 2022 (green), and b) time series of yearly average Southern Hemisphere sea ice extent expressed in millions of km2. Time series are based on satellite observations (SMMR, SSM/I, SSMIS) by EUMETSAT OSI SAF Sea Ice Index (v2.2) with R&D input from ESA CCI. Details on the product are given in the corresponding PUM for this OMI. The change of sea ice extent over the period 1979-2022 is expressed as a trend in millions of square kilometers per decade and is plotted with a dashed line on panel b).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00187\n\n**References:**\n\n* Meredith, M., M. Sommerkorn, S. Cassotta, C. Derksen, A. Ekaykin, A. Hollowed, G. Kofinas, A. Mackintosh, J. Melbourne-Thomas, M.M.C. Muelbert, G. Ottersen, H. Pritchard, and E.A.G. Schuur, 2019: Polar Regions. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [H.-O. Po\u0308rtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegri\u0301a, M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. In press.\n* IPCC, 2019: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [H.-O. Po\u0308rtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegri\u0301a, M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. In press.\n* Samuelsen, A., L.-A. Breivik, R.P. Raj, G. Garric, L. Axell, E. Olason (2016): Sea Ice. In: The Copernicus Marine Service Ocean State Report, issue 1, Journal of Operational Oceanography, 9:sup2, s235-s320, DOI: 10.1080/1755876X.2016.1273446\n", "doi": "10.48670/moi-00187", "instrument": null, "keywords": "antarctic-omi-si-extent-obs,coastal-marine-environment,global-ocean,marine-resources,marine-safety,multi-year,oceanographic-geographical-features,satellite-observation,sea-ice-extent,target-application#seaiceinformation,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1978-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": null, "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Antarctic Monthly Sea Ice Extent from Observations Reprocessing"}, "ARCTIC_ANALYSISFORECAST_BGC_002_004": {"abstract": "The operational TOPAZ5-ECOSMO Arctic Ocean system uses the ECOSMO biological model coupled online to the TOPAZ5 physical model planned for a future update of the ARCTIC_ANALYSIS_FORECAST_PHYS_002_001_a physical forecast. It is run daily to provide 10 days of forecast of 3D biogeochemical variables ocean. The coupling is done by the FABM framework.\n\nCoupling to a biological ocean model provides a description of the evolution of basic biogeochemical variables. The output consists of daily mean fields interpolated onto a standard grid and 40 fixed levels in NetCDF4 CF format. Variables include 3D fields of nutrients (nitrate, phosphate, silicate), phytoplankton and zooplankton biomass, oxygen, chlorophyll, primary productivity, carbon cycle variables (pH, dissolved inorganic carbon and surface partial CO2 pressure in seawater, carbon export) and light attenuation coefficient. Surface Chlorophyll-a from satellite ocean colour is assimilated every week and projected downwards using the Uitz et al. (2006) method. A new 10-day forecast is produced daily using the previous day's forecast and the most up-to-date prognostic forcing fields.\nOutput products have 6.25 km resolution at the North Pole (equivalent to 1/8 deg) on a stereographic projection. See the Product User Manual for the exact projection parameters.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00003\n\n**References:**\n\n* Daewel, U. and Schrum, C. (2013). Simulating long-term dynamics of the coupled North Sea and Baltic Sea ecosystem with ECOSMO II: Model description and validation. Journal of Marine Systems. 119-120. 30-49. 10.1016/j.jmarsys.2013.03.008.\n* Samuelsen, A., Hansen, C., and Wehde, H.: Tuning and assessment of the HYCOM-NORWECOM V2.1 biogeochemical modeling system for the North Atlantic and Arctic oceans, Geosci. Model Dev., 8, 2187\u20132202, https://doi.org/10.5194/gmd-8-2187-2015, 2015.\n* Uitz,J.,H.Claustre,A.Morel,andS.B.Hooker(2006),Vertical distribution of phytoplankton communities in open ocean: An assessment based on surface chlorophyll, J.Geophys. Res.,111,C08005, doi:10.1029/2005JC003207.\n", "doi": "10.48670/moi-00003", "instrument": null, "keywords": "arctic-analysisforecast-bgc-002-004,arctic-ocean,coastal-marine-environment,forecast,level-4,marine-resources,marine-safety,mass-concentration-of-chlorophyll-a-in-sea-water,mole-concentration-of-dissolved-inorganic-carbon-in-sea-water,mole-concentration-of-dissolved-molecular-oxygen-in-sea-water,mole-concentration-of-nitrate-in-sea-water,mole-concentration-of-phosphate-in-sea-water,mole-concentration-of-phytoplankton-expressed-as-carbon-in-sea-water,mole-concentration-of-silicate-in-sea-water,mole-concentration-of-zooplankton-expressed-as-carbon-in-sea-water,near-real-time,net-primary-production-of-biomass-expressed-as-carbon-per-unit-volume-in-sea-water,numerical-model,oceanographic-geographical-features,satellite-chlorophyll,sea-floor-depth-below-sea-level,sea-water-ph-reported-on-total-scale,sinking-mole-flux-of-particulate-organic-matter-expressed-as-carbon-in-sea-water,surface-partial-pressure-of-carbon-dioxide-in-sea-water,volume-attenuation-coefficient-of-downwelling-radiative-flux-in-sea-water,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "2019-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Biogeochemistry Analysis and Forecast"}, "ARCTIC_ANALYSISFORECAST_PHY_002_001": {"abstract": "The operational TOPAZ5 Arctic Ocean system uses the HYCOM model and a 100-member EnKF assimilation scheme. It is run daily to provide 10 days of forecast (average of 10 members) of the 3D physical ocean, including sea ice with the CICEv5.1 model; data assimilation is performed weekly to provide 7 days of analysis (ensemble average).\n\nOutput products are interpolated on a grid of 6 km resolution at the North Pole on a polar stereographic projection. The geographical projection follows these proj4 library parameters: \n\nproj4 = \"+units=m +proj=stere +lon_0=-45 +lat_0=90 +k=1 +R=6378273 +no_defs\" \n\n**DOI (product):**\nhttps://doi.org/10.48670/moi-00001\n\n**References:**\n\n* Sakov, P., Counillon, F., Bertino, L., Lis\u00e6ter, K. A., Oke, P. R. and Korablev, A.: TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic, Ocean Sci., 8(4), 633\u2013656, doi:10.5194/os-8-633-2012, 2012.\n* Melsom, A., Counillon, F., LaCasce, J. H. and Bertino, L.: Forecasting search areas using ensemble ocean circulation modeling, Ocean Dyn., 62(8), 1245\u20131257, doi:10.1007/s10236-012-0561-5, 2012.\n", "doi": "10.48670/moi-00001", "instrument": null, "keywords": "age-of-first-year-ice,age-of-sea-ice,arctic-analysisforecast-phy-002-001,arctic-ocean,coastal-marine-environment,forecast,fraction-of-first-year-ice,in-situ-ts-profiles,level-4,marine-resources,marine-safety,near-real-time,numerical-model,ocean-barotropic-streamfunction,ocean-mixed-layer-thickness,oceanographic-geographical-features,sea-floor-depth-below-sea-level,sea-ice-albedo,sea-ice-area-fraction,sea-ice-concentration-and/or-thickness,sea-ice-thickness,sea-ice-x-velocity,sea-ice-y-velocity,sea-level,sea-surface-elevation,sea-water-potential-temperature,sea-water-potential-temperature-at-sea-floor,sea-water-salinity,sea-water-x-velocity,sea-water-y-velocity,sst,surface-snow-thickness,target-application#seaiceforecastingapplication,upward-sea-water-velocity,weather-climate-and-seasonal-forecasting,x-sea-water-velocity,y-sea-water-velocity", "license": "proprietary", "missionStartDate": "2021-07-05T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Physics Analysis and Forecast"}, "ARCTIC_ANALYSISFORECAST_PHY_ICE_002_011": {"abstract": "The Arctic Sea Ice Analysis and Forecast system uses the neXtSIM stand-alone sea ice model running the Brittle-Bingham-Maxwell sea ice rheology on an adaptive triangular mesh of 10 km average cell length. The model domain covers the whole Arctic domain, including the Canadian Archipelago, the Baffin and Hudson Bays. neXtSIM is forced with surface atmosphere forcings from the ECMWF (European Centre for Medium-Range Weather Forecasts) and ocean forcings from TOPAZ5, the ARC MFC PHY NRT system (002_001a). neXtSIM runs daily, assimilating manual ice charts, sea ice thickness from CS2SMOS in winter and providing 9-day forecasts. The output variables are the ice concentrations, ice thickness, ice drift velocity, snow depths, sea ice type, sea ice age, ridge volume fraction and albedo, provided at hourly frequency. The adaptive Lagrangian mesh is interpolated for convenience on a 3 km resolution regular grid in a Polar Stereographic projection. The projection is identical to other ARC MFC products.\n\n\n**DOI (product):** \n\nhttps://doi.org/10.48670/moi-00004\n\n**References:**\n\n* Williams, T., Korosov, A., Rampal, P., and \u00d3lason, E.: Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F, The Cryosphere, 15, 3207\u20133227, https://doi.org/10.5194/tc-15-3207-2021, 2021.\n", "doi": "10.48670/moi-00004", "instrument": null, "keywords": "arctic-analysisforecast-phy-ice-002-011,arctic-ocean,coastal-marine-environment,forecast,level-4,marine-resources,marine-safety,near-real-time,numerical-model,oceanographic-geographical-features,sea-ice-age,sea-ice-albedo,sea-ice-area-fraction,sea-ice-classification,sea-ice-concentration-and/or-thickness,sea-ice-thickness,sea-ice-volume-fraction-of-ridged-ice,sea-ice-x-velocity,sea-ice-y-velocity,surface-snow-thickness,target-application#seaiceservices,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "2019-08-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "NERSC (Norway)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Sea Ice Analysis and Forecast"}, "ARCTIC_ANALYSISFORECAST_PHY_TIDE_002_015": {"abstract": "The Arctic Ocean Surface Currents Analysis and Forecast system uses the HYCOM model at 3 km resolution forced with tides at its lateral boundaries, surface winds sea level pressure from the ECMWF (European Centre for Medium-Range Weather Forecasts) and wave terms (Stokes-Coriolis drift, stress and parameterisation of mixing by Langmuir cells) from the Arctic wave forecast. HYCOM runs daily providing 10 days forecast. The output variables are the surface currents and sea surface heights, provided at 15 minutes frequency, which therefore include mesoscale signals (though without data assimilation so far), tides and storm surge signals. \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00005", "doi": "10.48670/moi-00005", "instrument": null, "keywords": "arctic-analysisforecast-phy-tide-002-015,arctic-ocean,coastal-marine-environment,forecast,level-4,marine-resources,marine-safety,near-real-time,numerical-model,oceanographic-geographical-features,sea-surface-elevation,weather-climate-and-seasonal-forecasting,x-sea-water-velocity,y-sea-water-velocity", "license": "proprietary", "missionStartDate": "1970-01-01T00:00:00.000000Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Tidal Analysis and Forecast"}, "ARCTIC_ANALYSIS_FORECAST_WAV_002_014": {"abstract": "The Arctic Ocean Wave Analysis and Forecast system uses the WAM model at 3 km resolution forced with surface winds and boundary wave spectra from the ECMWF (European Centre for Medium-Range Weather Forecasts) together with currents and ice from the ARC MFC analysis (Sea Ice concentration and thickness). WAM runs twice daily providing one hourly 10 days forecast and one hourly 5 days forecast. From the output variables the most commonly used are significant wave height, peak period and mean direction.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00002", "doi": "10.48670/moi-00002", "instrument": null, "keywords": "arctic-analysis-forecast-wav-002-014,arctic-ocean,coastal-marine-environment,forecast,level-4,marine-resources,marine-safety,near-real-time,numerical-model,oceanographic-geographical-features,sea-floor-depth-below-sea-level,sea-ice-area-fraction,sea-surface-primary-swell-wave-from-direction,sea-surface-primary-swell-wave-mean-period,sea-surface-primary-swell-wave-significant-height,sea-surface-secondary-swell-wave-from-direction,sea-surface-secondary-swell-wave-mean-period,sea-surface-secondary-swell-wave-significant-height,sea-surface-wave-from-direction,sea-surface-wave-from-direction-at-spectral-peak,sea-surface-wave-maximum-crest-height,sea-surface-wave-maximum-height,sea-surface-wave-mean-period-from-variance-spectral-density-inverse-frequency-moment,sea-surface-wave-mean-period-from-variance-spectral-density-second-frequency-moment,sea-surface-wave-period-at-variance-spectral-density-maximum,sea-surface-wave-significant-height,sea-surface-wave-stokes-drift-x-velocity,sea-surface-wave-stokes-drift-y-velocity,sea-surface-wind-wave-from-direction,sea-surface-wind-wave-mean-period,sea-surface-wind-wave-significant-height,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1970-01-01T00:00:00.000000Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Wave Analysis and Forecast"}, "ARCTIC_MULTIYEAR_BGC_002_005": {"abstract": "The TOPAZ-ECOSMO reanalysis system assimilates satellite chlorophyll observations and in situ nutrient profiles. The model uses the Hybrid Coordinate Ocean Model (HYCOM) coupled online to a sea ice model and the ECOSMO biogeochemical model. It uses the Determinstic version of the Ensemble Kalman Smoother to assimilate remotely sensed colour data and nutrient profiles. Data assimilation, including the 80-member ensemble production, is performed every 8-days. Atmospheric forcing fields from the ECMWF ERA-5 dataset are used.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00006\n\n**References:**\n\n* Simon, E., Samuelsen, A., Bertino, L. and Mouysset, S.: Experiences in multiyear combined state-parameter estimation with an ecosystem model of the North Atlantic and Arctic Oceans using the Ensemble Kalman Filter, J. Mar. Syst., 152, 1\u201317, doi:10.1016/j.jmarsys.2015.07.004, 2015.\n", "doi": "10.48670/moi-00006", "instrument": null, "keywords": "arctic-multiyear-bgc-002-005,arctic-ocean,coastal-marine-environment,level-4,marine-resources,marine-safety,mass-concentration-of-chlorophyll-a-in-sea-water,mole-concentration-of-dissolved-molecular-oxygen-in-sea-water,mole-concentration-of-nitrate-in-sea-water,mole-concentration-of-phosphate-in-sea-water,mole-concentration-of-phytoplankton-expressed-as-carbon-in-sea-water,mole-concentration-of-silicate-in-sea-water,mole-concentration-of-zooplankton-expressed-as-carbon-in-sea-water,multi-year,net-primary-production-of-biomass-expressed-as-carbon-per-unit-volume-in-sea-water,numerical-model,nutrients-(o2-n-p),oceanographic-geographical-features,satellite-chlorophyll,sea-floor-depth-below-sea-level,volume-attenuation-coefficient-of-downwelling-radiative-flux-in-sea-water,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "2007-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "NERSC (Norway)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Biogeochemistry Reanalysis"}, "ARCTIC_MULTIYEAR_PHY_002_003": {"abstract": "The current version of the TOPAZ system - TOPAZ4b - is nearly identical to the real-time forecast system run at MET Norway. It uses a recent version of the Hybrid Coordinate Ocean Model (HYCOM) developed at University of Miami (Bleck 2002). HYCOM is coupled to a sea ice model; ice thermodynamics are described in Drange and Simonsen (1996) and the elastic-viscous-plastic rheology in Hunke and Dukowicz (1997). The model's native grid covers the Arctic and North Atlantic Oceans, has fairly homogeneous horizontal spacing (between 11 and 16 km). 50 hybrid layers are used in the vertical (z-isopycnal), more than the TOPAZ4 system (28 layers). TOPAZ4b uses the Deterministic version of the Ensemble Kalman filter (DEnKF; Sakov and Oke 2008) to assimilate remotely sensed as well as temperature and salinity profiles. The output is interpolated onto standard grids and depths. Daily values are provided at all depths. Data assimilation, including the 100-member ensemble production, is performed weekly.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00007", "doi": "10.48670/moi-00007", "instrument": null, "keywords": "arctic-multiyear-phy-002-003,arctic-ocean,coastal-marine-environment,in-situ-ts-profiles,level-4,marine-resources,marine-safety,multi-year,numerical-model,ocean-barotropic-streamfunction,ocean-mixed-layer-thickness,oceanographic-geographical-features,sea-floor-depth-below-sea-level,sea-ice-area-fraction,sea-ice-concentration-and/or-thickness,sea-ice-thickness,sea-ice-x-velocity,sea-ice-y-velocity,sea-level,sea-surface-elevation,sea-water-potential-temperature,sea-water-potential-temperature-at-sea-floor,sea-water-salinity,sst,surface-snow-thickness,weather-climate-and-seasonal-forecasting,x-sea-water-velocity,y-sea-water-velocity", "license": "proprietary", "missionStartDate": "1991-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "NERSC (Norway)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Physics Reanalysis"}, "ARCTIC_MULTIYEAR_WAV_002_013": {"abstract": "The Arctic Ocean Wave Hindcast system uses the WAM model at 3 km resolution forced with surface winds and boundary wave spectra from the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA5 reanalysis together with ice from the ARC MFC reanalysis (Sea Ice concentration and thickness). Additionally, in the North Atlantic area, surface winds are used from a 2.5km atmospheric hindcast system. From the output variables the most commonly used are significant wave height, peak period and mean direction.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00008", "doi": "10.48670/moi-00008", "instrument": null, "keywords": "arctic-multiyear-wav-002-013,arctic-ocean,coastal-marine-environment,level-4,marine-resources,marine-safety,multi-year,numerical-model,oceanographic-geographical-features,sea-floor-depth-below-sea-level,sea-ice-area-fraction,sea-ice-thickness,sea-surface-primary-swell-wave-from-direction,sea-surface-primary-swell-wave-mean-period,sea-surface-primary-swell-wave-significant-height,sea-surface-secondary-swell-wave-from-direction,sea-surface-secondary-swell-wave-mean-period,sea-surface-secondary-swell-wave-significant-height,sea-surface-wave-from-direction,sea-surface-wave-from-direction-at-variance-spectral-density-maximum,sea-surface-wave-mean-period-from-variance-spectral-density-inverse-frequency-moment,sea-surface-wave-mean-period-from-variance-spectral-density-second-frequency-moment,sea-surface-wave-period-at-variance-spectral-density-maximum,sea-surface-wave-significant-height,sea-surface-wave-stokes-drift-x-velocity,sea-surface-wave-stokes-drift-y-velocity,sea-surface-wind-wave-from-direction,sea-surface-wind-wave-mean-period,sea-surface-wind-wave-significant-height,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1970-01-01T00:00:00.000000Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Ocean Wave Hindcast"}, "ARCTIC_OMI_SI_Transport_NordicSeas": {"abstract": "**DEFINITION**\n\nNet sea-ice volume and area transport through the openings Fram Strait between Spitsbergen and Greenland along 79\u00b0N, 20\u00b0W - 10\u00b0E (positive southward); northern Barents Sea between Svalbard and Franz Josef Land archipelagos along 80\u00b0N, 27\u00b0E - 60\u00b0E (positive southward); eastern Barents Sea between the Novaya Zemlya and Franz Josef Land archipelagos along 60\u00b0E, 76\u00b0N - 80\u00b0N (positive westward). For further details, see Lien et al. (2021).\n\n**CONTEXT**\n\nThe Arctic Ocean contains a large amount of freshwater, and the freshwater export from the Arctic to the North Atlantic influence the stratification, and, the Atlantic Meridional Overturning Circulation (e.g., Aagaard et al., 1985). The Fram Strait represents the major gateway for freshwater transport from the Arctic Ocean, both as liquid freshwater and as sea ice (e.g., Vinje et al., 1998). The transport of sea ice through the Fram Strait is therefore important for the mass balance of the perennial sea-ice cover in the Arctic as it represents a large export of about 10% of the total sea ice volume every year (e.g., Rampal et al., 2011). Sea ice export through the Fram Strait has been found to explain a major part of the interannual variations in Arctic perennial sea ice volume changes (Ricker et al., 2018). The sea ice and associated freshwater transport to the Barents Sea has been suggested to be a driving mechanism for the presence of Arctic Water in the northern Barents Sea, and, hence, the presence of the Barents Sea Polar Front dividing the Barents Sea into a boreal and an Arctic part (Lind et al., 2018). In recent decades, the Arctic part of the Barents Sea has been giving way to an increasing boreal part, with large implications for the marine ecosystem and harvestable resources (e.g., Fossheim et al., 2015).\n\n**CMEMS KEY FINDINGS**\n\nThe sea-ice transport through the Fram Strait shows a distinct seasonal cycle in both sea ice area and volume transport, with a maximum in winter. There is a slight positive trend in the volume transport over the last two and a half decades. In the Barents Sea, a strong reduction of nearly 90% in average sea-ice thickness has diminished the sea-ice import from the Polar Basin (Lien et al., 2021). In both areas, the Fram Strait and the Barents Sea, the winds governed by the regional patterns of atmospheric pressure is an important driving force of temporal variations in sea-ice transport (e.g., Aaboe et al., 2021; Lien et al., 2021).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00192\n\n**References:**\n\n* Aaboe S, Lind S, Hendricks S, Down E, Lavergne T, Ricker R. 2021. Sea-ice and ocean conditions surprisingly normal in the Svalbard-Barents Sea region after large sea-ice inflows in 2019. In: Copernicus Marine Environment Monitoring Service Ocean State Report, issue 5, J Oper Oceanogr. 14, sup1, 140-148\n* Aagaard K, Swift JH, Carmack EC. 1985. Thermohaline circulation in the Arctic Mediterranean seas. J Geophys Res. 90(C7), 4833-4846\n* Fossheim M, Primicerio R, Johannesen E, Ingvaldsen RB, Aschan MM, Dolgov AV. 2015. Recent warming leads to a rapid borealization of fish communities in the Arctic. Nature Clim Change. doi:10.1038/nclimate2647\n* Lien VS, Raj RP, Chatterjee S. 2021. Modelled sea-ice volume and area transport from the Arctic Ocean to the Nordic and Barents seas. In: Copernicus Marine Environment Monitoring Service Ocean State Report, issue 5, J Oper Oceanogr. 14, sup1, 10-17\n* Lind S, Ingvaldsen RB, Furevik T. 2018. Arctic warming hotspot in the northern Barents Sea linked to declining sea ice import. Nature Clim Change. doi:10.1038/s41558-018-0205-y\n* Rampal P, Weiss J, Dubois C, Campin J-M. 2011. IPCC climate models do not capture Arctic sea ice drift acceleration: Consequences in terms of projected sea ice thinning and decline. J Geophys Res. 116, C00D07. https://doi.org/10.1029/2011JC007110\n* Ricker R, Girard-Ardhuin F, Krumpen T, Lique C. 2018. Satellite-derived sea ice export and its impact on Arctic ice mass balance. Cryosphere. 12, 3017-3032\n* Vinje T, Nordlund N, Kvambekk \u00c5. 1998. Monitoring ice thickness in Fram Strait. J Geophys Res. 103(C5), 10437-10449\n", "doi": "10.48670/moi-00192", "instrument": null, "keywords": "arctic-ocean,arctic-omi-si-transport-nordicseas,coastal-marine-environment,level-4,marine-resources,marine-safety,multi-year,numerical-model,oceanographic-geographical-features,sea-ice-concentration-and/or-thickness,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "NERSC (Norway)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Sea Ice Area/Volume Transport in the Nordic Seas from Reanalysis"}, "ARCTIC_OMI_SI_extent": {"abstract": "**DEFINITION**\n\nEstimates of Arctic sea ice extent are obtained from the surface of oceans grid cells that have at least 15% sea ice concentration. These values are cumulated in the entire Northern Hemisphere (excluding ice lakes) and from 1993 up to the year 2019 aiming to:\ni) obtain the Arctic sea ice extent as expressed in millions of km square (106 km2) to monitor both the large-scale variability and mean state and change.\nii) to monitor the change in sea ice extent as expressed in millions of km squared per decade (106 km2/decade), or in sea ice extent loss since the beginning of the time series as expressed in percent per decade (%/decade; reference period being the first date of the key figure b) dot-dashed trend line, Vaughan et al., 2013). These trends are calculated in three ways, i.e. (i) from the annual mean values; (ii) from the March values (winter ice loss); (iii) from September values (summer ice loss).\nThe Arctic sea ice extent used here is based on the \u201cmulti-product\u201d approach as introduced in the second issue of the Ocean State Report (CMEMS OSR, 2017). Five global products have been used to build the ensemble mean, and its associated ensemble spread.\n\n**CONTEXT**\n\nSea ice is frozen seawater that floats on the ocean surface. This large blanket of millions of square kilometers insulates the relatively warm ocean waters from the cold polar atmosphere. The seasonal cycle of the sea ice, forming and melting with the polar seasons, impacts both human activities and biological habitat. Knowing how and how much the sea ice cover is changing is essential for monitoring the health of the Earth as sea ice is one of the highest sensitive natural environments. Variations in sea ice cover can induce changes in ocean stratification, in global and regional sea level rates and modify the key rule played by the cold poles in the Earth engine (IPCC, 2019). \nThe sea ice cover is monitored here in terms of sea ice extent quantity. More details and full scientific evaluations can be found in the CMEMS Ocean State Report (Samuelsen et al., 2016; Samuelsen et al., 2018).\n\n**CMEMS KEY FINDINGS**\n\nSince the year 1993 the Arctic sea ice extent has decreased significantly at an annual rate of -0.75*106 km2 per decade. This represents an amount of \u20135.8 % per decade of Arctic sea ice extent loss over the period 1993 to 2018. Summer (September) sea ice extent loss amounts to -1.18*106 km2/decade (September values), which corresponds to -14.85% per decade. Winter (March) sea ice extent loss amounts to -0.57*106 km2/decade, which corresponds to -3.42% per decade. These values slightly exceed the estimates given in the AR5 IPCC assessment report (estimate up to the year 2012) as a consequence of continuing Northern Hemisphere sea ice extent loss. Main change in the mean seasonal cycle is characterized by less and less presence of sea ice during summertime with time. The last twelve years have the twelve lowest summer minimums ever measured since 1993, the summer 2012 still being the lowest minimum. 2019 follows the recent trend of the 2010's with a summer and winter well below the 1990-2000's average. \n\nNote: The key findings will be updated annually in November, in line with OMI evolutions.\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00190\n\n**References:**\n\n* IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. (2019). In H. O. P\u00f6rtner, D. C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegr\u00eda, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC Intergovernmental Panel on Climate Change: Geneva, Switzerland. https://www.ipcc.ch/srocc/\n* Samuelsen et al., 2016: Sea Ice In: The Copernicus Marine Environment Monitoring Service Ocean State Report, issue 1, Journal of Operational Oceanography, 9, 2016, http://dx.doi.org/10.1080/1755876X.2016.1273446.\n* Samuelsen et al., 2018: Sea Ice. In: The Copernicus Marine Environment Monitoring Service Ocean State Report, issue 2, Journal of Operational Oceanography, 11:sup1, 2018, DOI: 10.1080/1755876X.2018.1489208.\n* Vaughan, D.G., J.C. Comiso, I. Allison, J. Carrasco, G. Kaser, R. Kwok, P. Mote, T. Murray, F. Paul, J. Ren, E. Rignot, O. Solomina, K. Steffen and T. Zhang, 2013: Observations: Cryosphere. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M.Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 317\u2013382, doi:10.1017/CBO9781107415324.012.\n", "doi": "10.48670/moi-00190", "instrument": null, "keywords": "arctic-ocean,arctic-omi-si-extent,coastal-marine-environment,marine-resources,marine-safety,multi-year,numerical-model,oceanographic-geographical-features,sea-ice-extent,target-application#seaiceinformation,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": null, "providers": [{"name": "Mercator Oc\u00e9an International", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Sea Ice Extent from Reanalysis"}, "ARCTIC_OMI_SI_extent_obs": {"abstract": "**DEFINITION**\n\nSea Ice Extent (SIE) is defined as the area covered by sufficient sea ice, that is the area of ocean having more than 15% Sea Ice Concentration (SIC). SIC is the fractional area of ocean that is covered with sea ice. It is computed from Passive Microwave satellite observations since 1979. \nSIE is often reported with units of 106 km2 (millions square kilometers). The change in sea ice extent (trend) is expressed in millions of km squared per decade (106 km2/decade). In addition, trends are expressed relative to the 1979-2022 period in % per decade.\nThese trends are calculated (i) from the annual mean values; (ii) from the March values (winter ice loss); (iii) from September values (summer ice loss). The annual mean trend is reported on the key figure, the March and September values are reported in the text below.\nSIE includes all sea ice, but not lake or river ice.\nSee also section 1.7 in Samuelsen et al. (2016) for an introduction to this Ocean Monitoring Indicator (OMI).\n\n**CONTEXT**\n\nSea ice is frozen seawater that floats at the ocean surface. This large blanket of millions of square kilometers insulates the relatively warm ocean waters from the cold polar atmosphere. The seasonal cycle of sea ice, forming and melting with the polar seasons, impacts both human activities and biological habitat. Knowing how and by how much the sea ice cover is changing is essential for monitoring the health of the Earth. Sea ice has a significant impact on ecosystems and Arctic communities, as well as economic activities such as fisheries, tourism, and transport (Meredith et al. 2019).\n\n**CMEMS KEY FINDINGS**\n\nSince 1979, the Northern Hemisphere sea ice extent has decreased at an annual rate of -0.51 +/- 0.03106 km2 per decade (-4.41% per decade). Loss of sea ice extent during summer exceeds the loss observed during winter periods: Summer (September) sea ice extent loss amounts to -0.81 +/- 0.06 106 km2 per decade (-12.73% per decade). Winter (March) sea ice extent loss amounts to -0.39 +/- 0.03 106 km2 per decade (-2.55% per decade). These values are in agreement with those assessed in the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) (Meredith et al. 2019, with estimates up until year 2018). September 2022 had the 11th lowest mean September sea ice extent. Sea ice extent in September 2012 is to date the record minimum Northern Hemisphere sea ice extent value since the beginning of the satellite record, followed by September values in 2020.\n\n**Figure caption**\n\na) The seasonal cycle of Northern Hemisphere sea ice extent expressed in millions of km2 averaged over the period 1979-2022 (red), shown together with the seasonal cycle in the year 2022 (green), and b) time series of yearly average Northern Hemisphere sea ice extent expressed in millions of km2. Time series are based on satellite observations (SMMR, SSM/I, SSMIS) by EUMETSAT OSI SAF Sea Ice Index (v2.2) with R&D input from ESA CCI. Details on the product are given in the corresponding PUM for this OMI. The change of sea ice extent over the period 1979-2022 is expressed as a trend in millions of square kilometers per decade and is plotted with a dashed line in panel b).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00191\n\n**References:**\n\n* Samuelsen, A., L.-A. Breivik, R.P. Raj, G. Garric, L. Axell, E. Olason (2016): Sea Ice. In: The Copernicus Marine Service Ocean State Report, issue 1, Journal of Operational Oceanography, 9:sup2, s235-s320, DOI: 10.1080/1755876X.2016.1273446\n* Meredith, M., M. Sommerkorn, S. Cassotta, C. Derksen, A. Ekaykin, A. Hollowed, G. Kofinas, A. Mackintosh, J. Melbourne-Thomas, M.M.C. Muelbert, G. Ottersen, H. Pritchard, and E.A.G. Schuur, 2019: Polar Regions. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [H.-O. Po\u0308rtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegri\u0301a, M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. In press.\n", "doi": "10.48670/moi-00191", "instrument": null, "keywords": "arctic-ocean,arctic-omi-si-extent-obs,coastal-marine-environment,marine-resources,marine-safety,multi-year,oceanographic-geographical-features,satellite-observation,sea-ice-extent,target-application#seaiceinformation,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1978-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": null, "providers": [{"name": "MET Norway", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Monthly Mean Sea Ice Extent from Observations Reprocessing"}, "ARCTIC_OMI_TEMPSAL_FWC": {"abstract": "**DEFINITION**\n\nEstimates of Arctic liquid Freshwater Content (FWC in meters) are obtained from integrated differences of the measured salinity and a reference salinity (set to 34.8) from the surface to the bottom per unit area in the Arctic region with a water depth greater than 500m as function of salinity (S), the vertical cell thickness of the dataset (dz) and the salinity reference (Sref). Waters saltier than the 34.8 reference are not included in the estimation. The regional FWC values from 1993 up to real time are then averaged aiming to:\n* obtain the mean FWC as expressed in cubic km (km3) \n* monitor the large-scale variability and change of liquid freshwater stored in the Arctic Ocean (i.e. the change of FWC in time).\n\n**CONTEXT**\n\nThe Arctic region is warming twice as fast as the global mean and its climate is undergoing unprecedented and drastic changes, affecting all the components of the Arctic system. Many of these changes affect the hydrological cycle. Monitoring the storage of freshwater in the Arctic region is essential for understanding the contemporary Earth system state and variability. Variations in Arctic freshwater can induce changes in ocean stratification. Exported southward downstream, these waters have potential future implications for global circulation and heat transport. \n\n**CMEMS KEY FINDINGS**\n\nSince 1993, the Arctic Ocean freshwater has experienced a significant increase of 423 \u00b1 39 km3/year. The year 2016 witnessed the highest freshwater content in the Artic since the last 24 years. Second half of 2016 and first half of 2017 show a substantial decrease of the FW storage. \n\nNote: The key findings will be updated annually in November, in line with OMI evolutions.\n\n**DOI (product):**\nhttps://doi.org/10.48670/moi-00193\n\n**References:**\n\n* G. Garric, O. Hernandez, C. Bricaud, A. Storto, K. A. Peterson, H. Zuo, 2018: Arctic Ocean freshwater content. In: Copernicus Marine Service Ocean State Report, Issue 2, Journal of Operational Oceanography, 11:sup1, s70\u2013s72, DOI: 10.1080/1755876X.2018.1489208\n", "doi": "10.48670/moi-00193", "instrument": null, "keywords": "arctic-ocean,arctic-omi-tempsal-fwc,coastal-marine-environment,marine-resources,marine-safety,multi-year,numerical-model,oceanographic-geographical-features,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": null, "providers": [{"name": "Mercator Oc\u00e9an International", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Arctic Freshwater Content from Reanalysis"}, "BALTICSEA_ANALYSISFORECAST_BGC_003_007": {"abstract": "This Baltic Sea biogeochemical model product provides forecasts for the biogeochemical conditions in the Baltic Sea. The Baltic forecast is updated daily providing a new six days forecast. Three different datasets are provided. One with daily means and one with monthly means values for these parameters: nitrate, phosphate, chl-a, ammonium, dissolved oxygen, ph, phytoplankton, zooplankton, silicate, dissolved inorganic carbon, and partial pressure of co2 at the surface. Instantaenous values for the Secchi Depth and light attenuation valid for noon (12Z) are included in the daily mean files/dataset. Additionally a third dataset with daily accumulated values of the netto primary production is available. The product is produced by the biogeochemical model ERGOM (Neumann, 2000) one way coupled to a Baltic Sea set up of the NEMO ocean model, which provides the CMEMS Baltic physical ocean forecast product (BALTICSEA_ANALYSISFORECAST_PHY_003_006). This biogeochemical product is provided at the models native grid with a resolution of 1 nautical mile in the horizontal, and up to 56 vertical depth levels. The product covers the Baltic Sea including the transition area towards the North Sea (i.e. the Danish Belts, the Kattegat and Skagerrak).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00009", "doi": "10.48670/moi-00009", "instrument": null, "keywords": "baltic-sea,balticsea-analysisforecast-bgc-003-007,cell-thickness,coastal-marine-environment,forecast,level-4,marine-resources,marine-safety,mass-concentration-of-chlorophyll-a-in-sea-water,model-level-number-at-sea-floor,mole-concentration-of-ammonium-in-sea-water,mole-concentration-of-dissolved-inorganic-carbon-in-sea-water,mole-concentration-of-dissolved-molecular-oxygen-in-sea-water,mole-concentration-of-nitrate-in-sea-water,mole-concentration-of-phosphate-in-sea-water,mole-concentration-of-phytoplankton-expressed-as-carbon-in-sea-water,mole-concentration-of-silicate-in-sea-water,mole-concentration-of-zooplankton-expressed-as-carbon-in-sea-water,near-real-time,net-primary-production-of-biomass-expressed-as-carbon-per-unit-volume-in-sea-water,none,numerical-model,oceanographic-geographical-features,sea-binary-mask,sea-floor-depth-below-geoid,sea-water-ph-reported-on-total-scale,secchi-depth-of-sea-water,surface-partial-pressure-of-carbon-dioxide-in-sea-water,volume-attenuation-coefficient-of-downwelling-radiative-flux-in-sea-water,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "2020-10-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "SMHI (Sweden)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Baltic Sea Biogeochemistry Analysis and Forecast"}, "BALTICSEA_ANALYSISFORECAST_PHY_003_006": {"abstract": "This Baltic Sea physical model product provides forecasts for the physical conditions in the Baltic Sea. The Baltic forecast is updated twice daily providing a new six days forecast. Several datasets are provided: One with hourly instantaneous values, one with daily mean values and one with monthly mean values, all containing these parameters: sea level variations, ice concentration and thickness at the surface, and temperature, salinity and horizontal and vertical velocities for the 3D field. Additionally a dataset with 15 minutes (instantaneous) surface values are provided for the sea level variation and the surface horizontal currents. The product is produced by a Baltic Sea set up of the NEMOv4.0 ocean model. This product is provided at the models native grid with a resolution of 1 nautical mile in the horizontal, and up to 56 vertical depth levels. The area covers the Baltic Sea including the transition area towards the North Sea (i.e. the Danish Belts, the Kattegat and Skagerrak). The ocean model is forced with Stokes drift data from the Baltic Wave forecast product (BALTICSEA_ANALYSISFORECAST_WAV_003_010). Satellite SST, ice concentrations and in-situ T and S profiles are assimilated into the model's analysis field. \n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00010", "doi": "10.48670/moi-00010", "instrument": null, "keywords": "baltic-sea,balticsea-analysisforecast-phy-003-006,coastal-marine-environment,eastward-sea-water-velocity,eastward-sea-water-velocity-assuming-no-tide,forecast,level-4,marine-resources,marine-safety,near-real-time,northward-sea-water-velocity,northward-sea-water-velocity-assuming-no-tide,numerical-model,ocean-mixed-layer-thickness-defined-by-sigma-theta,oceanographic-geographical-features,s,sea-ice-area-fraction,sea-ice-thickness,sea-surface-height-above-geoid-assuming-no-tide,sea-surface-height-above-sea-level,sea-water-potential-temperature,sea-water-potential-temperature-at-sea-floor,sea-water-salinity,sst,t,target-application#seaiceservices,upward-sea-water-velocity,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "2020-10-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "SMHI (Sweden)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Baltic Sea Physics Analysis and Forecast"}, "BALTICSEA_ANALYSISFORECAST_WAV_003_010": {"abstract": "This Baltic Sea wave model product provides forecasts for the wave conditions in the Baltic Sea. The Baltic forecast is updated twice a day providing a new six days forecast with hourly instantaneous data for significant wave height, wave period and wave direction for total sea, wind sea and swell, the Stokes drift, and two paramters for the maximum wave. The product is based on the wave model WAM cycle 4.7. The wave model is forced with surface currents, sea level anomaly and ice information from the CMEMS BAL MFC ocean forecast product (BALTICSEA_ANALYSISFORECAST_PHY_003_006). The product grid has a horizontal resolution of 1 nautical mile. The area covers the Baltic Sea including the transition area towards the North Sea (i.e. the Danish Belts, the Kattegat and Skagerrak).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00011", "doi": "10.48670/moi-00011", "instrument": null, "keywords": "baltic-sea,balticsea-analysisforecast-wav-003-010,coastal-marine-environment,forecast,level-4,marine-resources,marine-safety,near-real-time,none,numerical-model,oceanographic-geographical-features,sea-binary-mask,sea-floor-depth-below-geoid,sea-surface-primary-swell-wave-from-direction,sea-surface-primary-swell-wave-mean-period,sea-surface-primary-swell-wave-significant-height,sea-surface-secondary-swell-wave-from-direction,sea-surface-secondary-swell-wave-mean-period,sea-surface-secondary-swell-wave-significant-height,sea-surface-wave-from-direction,sea-surface-wave-from-direction-at-spectral-peak,sea-surface-wave-maximum-crest-height,sea-surface-wave-maximum-height,sea-surface-wave-mean-period-from-variance-spectral-density-inverse-frequency-moment,sea-surface-wave-mean-period-from-variance-spectral-density-second-frequency-moment,sea-surface-wave-period-at-variance-spectral-density-maximum,sea-surface-wave-significant-height,sea-surface-wave-stokes-drift-x-velocity,sea-surface-wave-stokes-drift-y-velocity,sea-surface-wind-wave-from-direction,sea-surface-wind-wave-mean-period,sea-surface-wind-wave-significant-height,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "2018-12-01T01:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "FMI (Finland)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Baltic Sea Wave Analysis and Forecast"}, "BALTICSEA_MULTIYEAR_BGC_003_012": {"abstract": "This Baltic Sea Biogeochemical Reanalysis product provides a biogeochemical reanalysis for the whole Baltic Sea area, inclusive the Transition Area to the North Sea, from January 1993 and up to minus maximum 1 year relative to real time. The product is produced by using the biogeochemical model ERGOM one-way online-coupled with the ice-ocean model system Nemo. All variables are avalable as daily, monthly and annual means and include nitrate, phosphate, ammonium, dissolved oxygen, ph, chlorophyll-a, secchi depth, surface partial co2 pressure and net primary production. The data are available at the native model resulution (1 nautical mile horizontal resolution, and 56 vertical layers).\n\n**DOI (product):**\n\nhttps://doi.org/10.48670/moi-00012", "doi": "10.48670/moi-00012", "instrument": null, "keywords": "baltic-sea,balticsea-multiyear-bgc-003-012,cell-thickness,coastal-marine-environment,level-4,marine-resources,marine-safety,mass-concentration-of-chlorophyll-a-in-sea-water,model-level-number-at-sea-floor,mole-concentration-of-ammonium-in-sea-water,mole-concentration-of-dissolved-molecular-oxygen-in-sea-water,mole-concentration-of-dissolved-molecular-oxygen-in-sea-water(at-bottom),mole-concentration-of-nitrate-in-sea-water,mole-concentration-of-phosphate-in-sea-water,multi-year,net-primary-production-of-biomass-expressed-as-carbon-per-unit-volume-in-sea-water(daily-accumulated),none,numerical-model,oceanographic-geographical-features,sea-binary-mask,sea-floor-depth-below-geoid,sea-water-ph-reported-on-total-scale,secchi-depth-of-sea-water,surface-partial-pressure-of-carbon-dioxide-in-sea-water,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "DMI (Denmark)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Baltic Sea Biogeochemistry Reanalysis"}, "BALTICSEA_MULTIYEAR_PHY_003_011": {"abstract": "This Baltic Sea Physical Reanalysis product provides a reanalysis for the physical conditions for the whole Baltic Sea area, inclusive the Transition Area to the North Sea, from January 1993 and up to minus maximum 1 year relative to real time. The product is produced by using the ice-ocean model system Nemo. All variables are avalable as daily, monthly and annual means and include sea level, ice concentration, ice thickness, salinity, temperature, horizonal velocities and the mixed layer depths. The data are available at the native model resulution (1 nautical mile horizontal resolution, and 56 vertical layers).\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00013", "doi": "10.48670/moi-00013", "instrument": null, "keywords": "baltic-sea,balticsea-multiyear-phy-003-011,cell-thickness,coastal-marine-environment,eastward-sea-water-velocity,in-situ-ts-profiles,level-4,marine-resources,marine-safety,model-level-number-at-sea-floor,multi-year,northward-sea-water-velocity,numerical-model,ocean-mixed-layer-thickness-defined-by-sigma-theta,oceanographic-geographical-features,sea-binary-mask,sea-floor-depth-below-geoid,sea-ice-area-fraction,sea-ice-thickness,sea-surface-height-above-geoid,sea-surface-height-above-sea-level,sea-water-potential-temperature,sea-water-potential-temperature-at-sea-floor,sea-water-salinity,sea-water-salinity(at-bottom),sst,target-application#seaiceclimate,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T00:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "DMI (Denmark)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Baltic Sea Physics Reanalysis"}, "BALTICSEA_REANALYSIS_WAV_003_015": {"abstract": "This Baltic Sea wave model hindcast product provides a hindcast for the wave conditions in the Baltic Sea since 1/1 1993 and up to 0.5-1 year compared to real time.\nThis hindcast product consists of a dataset with hourly data for significant wave height, wave period and wave direction for total sea, wind sea and swell, and also Stokes drift. Additionally a dataset with monthly climatology are provided for the significant wave height and the wave period. The product is based on the wave model WAM cycle 4.6.2, and surface forcing from ECMWF's ERA5 reanalysis products. The product grid has a horizontal resolution of 1 nautical mile. The area covers the Baltic Sea including the transition area towards the North Sea (i.e. the Danish Belts, the Kattegat and Skagerrak). The product provides hourly instantaneously model data.\n\n**DOI (product):**\nhttps://doi.org/10.48670/moi-00014", "doi": "10.48670/moi-00014", "instrument": null, "keywords": "baltic-sea,balticsea-reanalysis-wav-003-015,coastal-marine-environment,level-4,marine-resources,marine-safety,multi-year,numerical-model,oceanographic-geographical-features,sea-surface-wave-mean-period-from-variance-spectral-density-second-frequency-moment,sea-surface-wave-significant-height,weather-climate-and-seasonal-forecasting", "license": "proprietary", "missionStartDate": "1993-01-01T01:00:00Z", "platform": null, "platformSerialIdentifier": null, "processingLevel": "Level 4", "providers": [{"name": "FMI (Finland)", "roles": ["producer"]}, {"name": "Copernicus Marine Service", "roles": ["host", "processor"], "url": "https://marine.copernicus.eu"}], "title": "Baltic Sea Wave Hindcast"}, "BALTIC_OMI_HEALTH_codt_volume": {"abstract": "**DEFINITION**\n\nThe cod reproductive volume has been derived from regional reanalysis modelling results for the Baltic Sea BALTICSEA_MULTIYEAR_PHY_003_011 and BALTICSEA_MULTIYEAR_BGC_003_012. The volume has been calculated taking into account the three most important influencing abiotic factors of cod reproductive success: salinity > 11 g/kg, oxygen concentration\u2009>\u20092 ml/l and water temperature over 1.5\u00b0C (MacKenzie et al., 1996; Heikinheimo, 2008; Plikshs et al., 2015). The daily volumes are calculated as the volumes of the water with salinity > 11 g/kg, oxygen content\u2009>\u20092 ml/l and water temperature over 1.5\u00b0C in the Baltic Sea International Council for the Exploration of the Sea subdivisions of 25-28 (ICES, 2019).\n\n**CONTEXT**\n\nCod (Gadus morhua) is a characteristic fish species in the Baltic Sea with major economic importance. Spawning stock biomasses of the Baltic cod have gone through a steep decline in the late 1980s (Bryhn et al., 2022). Water salinity and oxygen concentration affect cod stock through the survival of eggs (Westin and Nissling, 1991; Wieland et al., 1994). Major Baltic Inflows provide a suitable environment for cod reproduction by bringing saline oxygenated water to the deep basins of the Baltic Sea (see the OMIs: BALTIC_OMI_WMHE_mbi_bottom_salinity_arkona_bornholm and BALTIC_OMI_WMHE_mbi_sto2tz_gotland). Increased cod reproductive volume has a positive effect on cod reproduction success, which should reflect an increase of stock size indicator 4\u20135 years after the Major Baltic Inflow (Raudsepp et al., 2019). Eastern Baltic cod reaches maturity around age 2\u20133, depending on the population density and environmental conditions. There are a number of environmental factors affecting cod populations (Bryhn et al., 2022). Low oxygen and salinity cause stress, which negatively affects cod recruitment, whereas sufficient conditions may bring about male cod maturation even at the age of 1.5 years (Cardinale and Modin, 1999; Karasiova et al., 2008). \n\n**CMEMS KEY FINDINGS**\n\nIn general, the cod reproductive volume fluctuates between 200 and 400 km3. There are two separate periods when cod reproductive volume has significantly increased where maximum values reach 1200 km3. These periods, from 2003 to 2005 and from 2015 to 2018, correspond to the post Major Baltic Inflow periods (BALTIC_OMI_WMHE_mbi_bottom_salinity_arkona_bornholm and BALTIC_OMI_WMHE_mbi_sto2tz_gotland). In 2022, the cod reproductive volume was at its base level between 200 and 400 km3. According to the study by Bryhn et al. (2022) an increase of spawning stock biomass in the eastern Baltic Sea has not been observed.\n\n**Figure caption**\n\nThe time series of cod reproductive volume in the Baltic Sea from 1993 to 2022. The volume has been calculated from salinity, temperature and oxygen data extracted from Copernicus Marine Service regional reanalysis products BALTICSEA_MULTIYEAR_PHY_003_011 and BALTICSEA_MULTIYEAR_BGC_003_012.\"\n\n**DOI (product):** \nhttps://doi.org/10.48670/moi-00196\n\n**References:**\n\n* Cardinale, M., Modin, J., 1999. Changes in size-at-maturity of Baltic cod (Gadus morhua) during a period of large variations in stock size and environmental conditions. Vol. 41 (3), 285-295. https://doi.org/10.1016/S0165-7836(99)00021-1\n* Heikinheimo, O., 2008. Average salinity as an index for environmental forcing on cod recruitment in the Baltic Sea. Boreal Environ Res 13:457\n* ICES, 2005. Report of the Study Group on Multispecies Assessment in the Baltic (SGMAB), 13\u201317 June 2005, Riga, Latvia. ICES Document CM 2005/H:06.\n* ICES, 2019. Baltic Sea Ecoregion \u2013 Fisheries overview, ICES Advice, DOI:10.17895/ices.advice.5566 Karasiova, E.M., Voss, R., Eero, M., 2008. Long-term dynamics in eastern Baltic cod spawning time: from small scale reversible changes to a recent drastic shift. ICES CM 2008/J:03\n* MacKenzie, B., St. John, M., Wieland, K., 1996. Eastern Baltic cod: perspectives from existing data on processes affecting growth and survival of eggs and larvae. Mar Ecol Prog Ser Vol. 134: 265-281.\n* Plikshs, M., Hinrichsen, H. H., Elferts, D., Sics, I., Kornilovs, G., K\u00f6ster, F., 2015. Reprodu
Update external product types reference from daily fetch. See Python API User Guide / Product types discovery
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