AndreaBozzo/ceres-open-data-index huggingface dataset:
Mediterranean Sea Waves Reanalysis

'''Short description:'''

MEDSEA_MULTIYEAR_WAV_006_012  is the multi-year wave product of the Mediterranean Sea Waves forecasting system (Med-WAV). It contains a Reanalysis dataset and a monthly climatological dataset (reference period 1993-2016). The Reanalysis dataset is a multi-year wave reanalysis starting from January 1985, composed by hourly wave parameters at 1/24° horizontal resolution, covering the Mediterranean Sea and extending up to 18.125W into the Atlantic Ocean. The dataset is extended every year as well as on a monthly basis through one-month extensions in interim mode, reaching one month before present. The Med-WAV modelling system is based on wave model WAM 4.6.2 and has been developed as a nested sequence of two computational grids (coarse and fine) to ensure that swell propagating from the North Atlantic (NA) towards the strait of Gibraltar is correctly entering the Mediterranean Sea. The coarse grid covers the North Atlantic Ocean from 75°W to 10°E and from 70° N to 10° S in 1/6° resolution while the nested fine grid covers the Mediterranean Sea from 18.125° W to 36.2917° E and from 30.1875° N to 45.9792° N with a 1/24° resolution. The modelling system resolves the prognostic part of the wave spectrum with 24 directional and 32 logarithmically distributed frequency bins. The wave system also includes an optimal interpolation assimilation scheme assimilating significant wave height along track satellite observations available through CMEMS and it is forced with daily averaged currents from Med-Physics and with 1-h, 0.25° horizontal-resolution ERA5 reanalysis 10m-above-sea-surface winds from ECMWF.

''DOI (Product)'': https://doi.org/10.48670/mds-00376

''DOI (Interim dataset)'':    
https://doi.org/10.25423/ CMCC/MEDSEA_MULTIYEAR_WAV_006_012_MEDWAM3I  
                                                                                                                                                      
''DOI (climatological dataset)'':    
https://doi.org/10.25423/ CMCC/MEDSEA_MULTIYEAR_WAV_006_012_CLIM
Mediterranean Sea Waves Analysis and Forecast

'''Short description:'''
                                                             
MEDSEA_ANALYSISFORECAST_WAV_006_017 is the nominal wave product of the Mediterranean Sea Forecasting system, composed by hourly wave parameters at 1/24º horizontal resolution covering the Mediterranean Sea and extending up to 18.125W into the Atlantic Ocean. The waves forecast component (Med-WAV system) is a wave model based on the WAM Cycle 6. The Med-WAV modelling system resolves the prognostic part of the wave spectrum with 24 directional and 32 logarithmically distributed frequency bins and the model solutions are corrected by an optimal interpolation data assimilation scheme of all available along track satellite significant wave height and 10m wind speed observations. The atmospheric forcing is provided by the operational ECMWF Numerical Weather Prediction model and the wave model is forced with hourly averaged surface currents and sea level obtained from MEDSEA_ANALYSISFORECAST_PHY_006_013 at 1/24° resolution. The model uses wave spectra for Open Boundary Conditions from GLOBAL_ANALYSIS_FORECAST_WAV_001_027 product. The wave system includes 2 forecast cycles providing twice per day a Mediterranean wave analysis and 10 days of wave forecasts.

'''DOI (product)''': 
https://doi.org/10.48670/mds-00373
Antarctic Ocean - High Resolution Sea Ice Information

'''Short description:'''
For the Antarctic Sea - A sea ice concentration product based on satellite SAR imagery and microwave radiometer data: The algorithm uses SENTINEL-1 SAR EW and IW mode dual-polarized HH/HV data combined with AMSR2 radiometer data.

'''DOI (product) :'''   
https://doi.org/10.48670/mds-00320
Global Ocean Sea Ice Concentration CDRs and ICDRs from PMW data (OSI-SAF)

Two sets of CDR and ICDR sea ice concentration datasets from the EUMETSAT OSI SAF. One set based on AMSR-E/AMSR2 data: OSI-458+OSI-438 (covering 2002-present), and one set based on SMMR/SSMI/SSMIS data, OSI-450-a1+OSI-430-a (covering 1978-2025). The sea ice concentration is computed from atmospherically corrected PMW brightness temperatures, using a combination of state-of-the-art algorithms and dynamic tie points. It includes error bars for each grid cell (uncertainties). OSI-458 and OSI-430 were released in November 2022, OSI-450-a1 in June 2025 and OSI-438 will be released in May 2026. OSI-450 and OSI-430 will be frozen in April 2026.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00136
Global Ocean - High Resolution SAR Sea Ice Drift

'''Short description:'''

DTU Space produces polar covering Near Real Time gridded ice displacement fields obtained by MCC processing of Sentinel-1 SAR, Envisat ASAR WSM swath data or RADARSAT ScanSAR Wide mode data . The nominal temporal span between processed swaths is 24hours, the nominal product grid resolution is a 10km.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00135
Baltic Sea significant wave height extreme variability mean and anomaly (observations)

'''DEFINITION'''

The OMI_EXTREME_WAVE_BALTIC_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).  

'''CONTEXT'''

Projections 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).
In the Baltic Sea, the particular bathymetry and geography of the basin intensify the seasonal and spatial fluctuations in wave conditions. No clear statistically significant trend in the sea state has been appreciated except a rising trend in significant wave height in winter season, linked with the reduction of sea ice coverage (Soomere, 2023; Tuomi et al., 2019).

'''COPERNICUS MARINE SERVICE KEY FINDINGS'''

The mean 99th percentiles shown in the area are from 3 to 4 meters and the standard deviation ranges from 0.2 m to 0.4 m. 
Results for this year show a slight positive or negative anomaly in all the stations, from -0.19 m to +0.28 m, inside the margin of the standard deviation.

'''DOI (product):''' 
https://doi.org/10.48670/moi-00199
Baltic Sea Biogeochemistry Analysis and Forecast

'''Short description:'''

This Baltic Sea biogeochemical model product provides forecasts for the biogeochemical conditions in the Baltic Sea. The Baltic forecast is updated twice daily from a 00Z production proving a 10 days forecast and from a 12Z production providing a 6 days forecast. 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, dissolved iron, dissolved cdom, hydrogen sulfide, 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 et al, 2021) one way coupled to a Baltic Sea set up of  the NEMO ocean model, which provides the Baltic Sea 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 with 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).

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00009
Arctic Ocean - Sea and Ice Surface Temperature L3S REPROCESSED

'''Short description:''' 

Arctic Sea and Ice surface temperature
'''Detailed description:'' 'Arctic Sea and Ice surface temperature product based upon reprocessed AVHRR, (A)ATSR and SLSTR SST observations from the ESA CCI project, the Copernicus C3S project and the AASTI dataset. The product is a daily supercollated field using all available sensors with a 0.05 degrees resolution, and covers surface temperatures in the ocean, the sea ice and the marginal ice zone.

'''DOI (product) :'''
https://doi.org/10.48670/moi-00315
Atlantic - European North West Shelf - Ocean Biogeochemistry Analysis and Forecast

'''Short description:'''

The NWSHELF_ANALYSISFORECAST_BGC_004_002 is produced by a coupled hydrodynamic-biogeochemical model, implemented over the North East Atlantic and Shelf Seas at about 7 km of horizontal resolution and 24 vertical levels.
The product is daily, providing 7-day forecast of the main biogeochemical variables.
Products are provided as daily and monthly means.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00056
Global Ocean - In Situ reprocessed carbon observations - SOCATv2025 / GLODAPv2.2023

'''Short description:'''

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 SOCATv2025 and GLobal Ocean Data Analysis Project GLODAPv2.2023. The SOCATv2025-OBS dataset contains nearly 50 million observations of fugacity of CO2 of the surface global ocean from 1957 to early 2025. The quality control procedures are described in Bakker et al. (2016). These observations form the basis of the gridded products included in SOCATv2025-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. GLODAPv2.2023-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 Lauvset et al. (2024). 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. SOCAT 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 and datasets (see References below) in order to support future sustainability of the data products.

'''DOI (product) :'''   
https://doi.org/10.17882/99089
Baltic Sea Subsurface Salinity trend from Reanalysis

'''DEFINITION'''

Subsurface salinity trend ocean monitoring indicator was introduced in Copernicus Marine Service Ocean State Report, Issue 2 (Mulet et al, 2018) and is derived from regional reanalysis product BALTICSEA_MULTIYEAR_PHY_003_011. The salinity trend has been obtained through a linear fit for each time series of horizontally averaged (13 °E - 31 °E and 53 °N - 66 °N; excluding the Skagerrak strait) annual salinity and at each depth level. 

'''CONTEXT'''

The Baltic Sea is a brackish semi-enclosed sea in North-Eastern Europe. The surface salinity varies horizontally from ~10 near the Danish Straits down to ~2 at the northernmost and easternmost sub-basins of the Baltic Sea. The halocline, a vertical layer with rapid changes of salinity with depth that separates the well-mixed surface layer from the weakly stratified layer below, is located at the depth range of 60-80 metres (Matthäus, 1984). The bottom layer salinity below the halocline depth varies from 15 in the south down to 3 in the northern Baltic Sea (Väli et al., 2013). The long-term salinity is determined by net precipitation and river discharge as well as saline water inflows from the North Sea (Lehmann et al., 2022). Long-term salinity decrease may reduce the occurrence and biomass of the Fucus vesiculosus - Idotea balthica association/symbiotic aggregations (Kotta et al., 2019). Changes in salinity and oxygen content affect the survival of the Baltic cod eggs (Raudsepp et al, 2019; von Dewitz et al., 2018).

'''CMEMS KEY FINDINGS'''

The subsurface salinity from 1993 to 2024 exhibits distinct variations at different depths. In the surface layer up to 25 meters, which aligns with the average upper mixed layer depth in the Baltic Sea, there is no discernible trend. The salinity trend increases steadily from zero at a 25-meter depth to 0.04 per year at 70 meters. The most pronounced trend, 0.045 per year, is found within the extended halocline layer ranging from 70 to 150 meters. It is noteworthy that there is a slight reduction in the salinity trend to 0.04 per year between depths of 150 and 220 meters. Although this decrease is minor, it suggests that salt transport into the extended halocline layer is more pronounced than into the deeper layers. The Major Baltic Inflows are responsible for the significant salinity trend of 0.05 per year observed in the deepest layer of the Baltic Sea.     

'''DOI (product):''' 
https://doi.org/10.48670/moi-00207
EUROPEAN SEAS ALONG-TRACK L3 SEA LEVEL ANOMALIES NRT

'''Short description:'''

Altimeter satellite along-track sea surface heights anomalies (SLA) computed with respect to a twenty-year [1993, 2012] mean with a 1Hz (~7km) and 5Hz (~1km) sampling. It serves in near-real time applications.
This product is processed by the DUACS multimission altimeter data processing system. It processes data from all altimeter missions available (e.g. Sentinel-6A, Jason-3, Sentinel-3A, Sentinel-3B, Saral/AltiKa, Cryosat-2, HY-2B). The system exploits the most recent datasets available based on the enhanced OGDR/NRT+IGDR/STC production. All the missions are homogenized with respect to a reference mission. Part of the processing is fitted to the European Seas. (see QUID document or http://duacs.cls.fr [http://duacs.cls.fr] pages for processing details). 
The product gives additional variables (e.g. Mean Dynamic Topography, Dynamic Atmospheric Correction, Ocean Tides, Long Wavelength Errors) that can be used to change the physical content for specific needs (see PUM document for details)

'''Associated products'''

A time invariant product http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_PHY_NOISE_L4_STATIC_008_033 [http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_PHY_NOISE_L4_STATIC_008_033] describing the noise level of along-track measurements is available. It is associated to the sla_filtered variable. It is a gridded product. One file is provided for the global ocean and those values must be applied for Arctic and Europe products. For Mediterranean and Black seas, one value is given in the QUID document.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00140
Arctic Ocean Colour Plankton and Transparency L4 NRT monthly observations

'''Short description:'''

For the '''Arctic''' Ocean '''Satellite Observations''', Italian National Research Council (CNR – Rome, Italy) is providing '''Bio-Geo_Chemical (BGC)''' products.
* Upstreams: OLCI-S3A & OLCI-S3B for the '''""olci""''' products.
* Variables: Chlorophyll-a ('''CHL''') and Diffuse Attenuation ('''KD490''').

* Temporal resolutions:'''monthly'''.
* Spatial resolutions:  '''300 meters''' (olci).
* Recent products are organized in datasets called Near Real Time ('''NRT''').

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00291
Global Ocean in situ - Delayed Mode temperature and salinity CORA -objective analysis

'''Short description:''''
Global Ocean in situ - Delayed Mode temperature and salinity CORA -objective analysis 
The global ocean objective analysis (gridded) fields of temperature and salinity are produced from the in situ profiles available in the reprocessed (or multiyear) in-situ CORA product INSITU_GLO_PHY_TS_DISCRETE_MY_013_001, with the exception of moorings, thermosalinographs and surface drifters. The objective analysis is based on the ISAS method (Gaillard et al. 2009), a statistical estimation approach that enables the mapping of ocean in situ profiles onto three-dimensional gridded fields.
The resulting gridded product has a spatial resolution of 0.5° in latitude and 0.5° in longitude at the equator and includes 187 vertical levels. It provides monthly temperature and salinity fields centered the 15th of the month.  It is updated twice a year by a full reprocessing covering  the whole period from 1960 to December of the last year before present time (produced generally in November) and a temporal extension of the first 6 months of the ongoing year (done generally in July). 
A monthly file (data file) gathering the observed profiles used to calculate the analysis, which are interpolated on the vertical grid, is also provided.

'''DOI (product) :'''  
https://doi.org/10.48670/mds-00383
Global Ocean Daily Gridded Sea Surface Winds from Scatterometer

'''Short description:'''

For the Global Ocean - The product contains daily L3 gridded sea surface wind observations from available scatterometers with resolutions corresponding to the L2 swath products:

*0.5 degrees grid for the 40 and 50 km scatterometer L2 inputs,
*0.25 degrees grid based on 20 and 25 km scatterometer swath observations,
*and 0.125 degrees based on 12.5 km scatterometer swath observations, i.e., from the coastal products.

Data from ascending and descending passes are gridded separately.
The product provides stress-equivalent wind and stress variables as well as their divergence and curl. The NRT L3 products follow the NRT availability of the EUMETSAT OSI SAF L2 products and are available for:
*The ASCAT scatterometers on Metop-A (discontinued on 15/11/2021), Metop-B and Metop-C at 0.125 and 0.25 degrees;
*The OSCAT scatterometer on Scatsat-1 (discontinued on 28/02/2021) and Oceansat-3 at 0.25 and 0.5 degrees; 
*The HSCAT scatterometer on HY-2B, HY-2C and HY-2D (discontinued on 03/11/2024) at 0.25 and 0.5 degrees;
*The WindRAD scatterometer on FY-3E at 0.25 and 0.5 degrees.

In addition, the product includes European Centre for Medium-Range Weather Forecasts (ECMWF) operational model forecast wind and stress variables collocated with the scatterometer observations at L2 and processed to L3 in exactly the same way as the scatterometer observations.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00182
Global Ocean - High Resolution SAR Sea Ice Drift Time Series

'''Short description:'''

The  product contains a reprocessed multi year version of the daily composite dataset from SEAICE_GLO_SEAICE_L4_NRT_OBSERVATIONS_011_006 covering the Sentinel1 years from autumn 2014 until 1 year before present

'''DOI (product) :'''   
https://doi.org/10.48670/mds-00328
Global Ocean Biogeochemistry Analysis and Forecast

'''Short description:'''

The Operational Mercator Ocean biogeochemical global ocean analysis and forecast system  at 1/4 degree is providing 10 days of 3D global ocean forecasts updated daily. The time series is aggregated in time, in order to reach a two full year’s time series sliding window. This product includes daily and monthly mean files of biogeochemical parameters (chlorophyll, nitrate, phosphate, silicate, dissolved oxygen, dissolved iron, primary production, phytoplankton, zooplankton, PH, and surface partial pressure of carbon dioxyde) over the global ocean. The global ocean output files are displayed with a 1/4 degree horizontal resolution with regular longitude/latitude equirectangular projection. 50 vertical levels are ranging from 0 to 5700 meters.

* NEMO version (v3.6_STABLE)
* Forcings: GLOBAL_ANALYSISFORECAST_PHYS_001_024 at daily frequency.                                                                           
* Outputs mean fields are interpolated on a standard regular grid in NetCDF format.
* Initial conditions: World Ocean Atlas 2013 for nitrate, phosphate, silicate and dissolved oxygen, GLODAPv2 for DIC and Alkalinity, and climatological model outputs for Iron and DOC 
* Quality/Accuracy/Calibration information: See the related QuID[https://documentation.marine.copernicus.eu/QUID/CMEMS-GLO-QUID-001-028.pdf]

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00015
Arctic Freshwater Content from Reanalysis

'''DEFINITION'''

Estimates 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:
* obtain the mean FWC as expressed in cubic km (km3) 
* monitor the large-scale variability and change of liquid freshwater stored in the Arctic Ocean (i.e. the change of FWC in time).

'''CONTEXT'''

The 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.  

'''CMEMS KEY FINDINGS'''

Since 1993, the Arctic Ocean freshwater has experienced a significant increase of 423 ± 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. 

Note: The key findings will be updated annually in November, in line with OMI evolutions.

'''DOI (product):'''
https://doi.org/10.48670/moi-00193
GLOBAL OCEAN MEAN DYNAMIC TOPOGRAPHY

'''Short description:'''

Mean Dynamic Topography that combines the global CNES-CLS-2022 MDT, the Black Sea CMEMS2020 MDT and the Med Sea CMEMS2020 MDT. It  is an estimate of the mean over the 1993-2012 period of the sea surface height above geoid. This is consistent with the reference time period also used in the  DUACS products

'''DOI (product) :'''  
https://doi.org/10.48670/moi-00150