AndreaBozzo/ceres-open-data-index huggingface dataset:
North Pacific Gyre Oscillation from Observations Reprocessing

'''DEFINITION'''

The North Pacific Gyre Oscillation (NPGO) is a climate pattern introduced by Di Lorenzo et al. (2008) and further reported by Tranchant et al. (2019) in the CMEMS Ocean State Report #3. The NPGO is defined as the second dominant mode of variability of Sea Surface Height (SSH) anomaly and SST anomaly in the Northeast Pacific (25°– 62°N, 180°– 250°E). The spatial and temporal pattern of the NPGO has been deduced over the [1950-2004] period using an empirical orthogonal function (EOF) decomposition on sea level and sea surface temperature fields produced by the Regional Ocean Modeling System (ROMS) (Di Lorenzo et al., 2008; Shchepetkin and McWilliams, 2005). Afterward, the sea level spatial pattern of the NPGO is used/projected with satellite altimeter delayed-time sea level anomalies to calculate and update the NPGO index.
The NPGO index disseminated on CMEMS was specifically updated from 2004 onward using up-to-date altimeter products (SEALEVEL_GLO_PHY_L4_MY _008_047 CMEMS and completed with SEALEVEL_GLO_PHY_L4_NRT _008_046 CMEMS products). Users that previously used the index disseminated on www.o3d.org/npgo/ web page will find slight differences induced by this update. They do not impact the general variability of the NPGO.  

""CONTEXT ""

NPGO mode emerges as the leading mode of decadal variability for surface salinity and upper ocean nutrients (Di Lorenzo et al., 2009). The North Pacific Gyre Oscillation (NPGO) term is used because its fluctuations reflect changes in the intensity of the central and eastern branches of the North Pacific gyres circulations (Chhak et al., 2009). This index measures change in the North Pacific gyres circulation and explains key physical-biological ocean variables including temperature, salinity, sea level, nutrients, chlorophyll-a. A positive North Pacific Gyre Oscillation phase is a dipole pattern with negative SSH anomaly north of 40°N and the opposite south of 40°N. (Di Lorenzo et al., 2008) suggested that the North Pacific Gyre Oscillation is the oceanic expression of the atmospheric variability of the North Pacific Oscillation (Walker and Bliss, 1932), which has an expression in both the 2nd EOFs of SSH and Sea Surface Temperature (SST) anomalies (Ceballos et al., 2009). This finding is further supported by the recent work of (Yi et al., 2018) showing consistent pattern features between the atmospheric North Pacific Oscillation and the oceanic North Pacific Gyre Oscillation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) database.

""CMEMS KEY FINDINGS"" 

The NPGO index is presently in a negative phase, associated with a positive SSH anomaly north of 40°N and negative south of 40°N. This reflects a reduced amplitude of the central and eastern branches of the North Pacific gyre, corresponding to a reduced coastal upwelling and thus a lower sea surface salinity and concentration of nutrients. 

'''DOI (product):''' 
https://doi.org/10.48670/moi-00221
South Atlantic Gyre Area Chlorophyll-a time series and trend from Observations Reprocessing

'''DEFINITION'''

Oligotrophic subtropical gyres are regions of the ocean with low levels of nutrients required for phytoplankton growth and low levels of surface chlorophyll-a whose concentration can be quantified through satellite observations. The gyre boundary has been defined using a threshold value of 0.15 mg m-3 chlorophyll for the Atlantic gyres (Aiken et al. 2016), and 0.07 mg m-3 for the Pacific gyres (Polovina et al. 2008). The area inside the gyres for each month is computed using monthly chlorophyll data from which the monthly climatology is subtracted to compute anomalies.  A gap filling algorithm has been utilized to account for missing data inside the gyre. Trends in the area anomaly are then calculated for the entire study period (September 1997 to December 2021).

'''CONTEXT'''

Oligotrophic gyres of the oceans have been referred to as ocean deserts (Polovina et al. 2008). They are vast, covering approximately 50% of the Earth’s surface (Aiken et al. 2016). Despite low productivity, these regions contribute significantly to global productivity due to their immense size (McClain et al. 2004). Even modest changes in their size can have large impacts on a variety of global biogeochemical cycles and on trends in chlorophyll (Signorini et al 2015). Based on satellite data, Polovina et al. (2008) showed that the areas of subtropical gyres were expanding. The Ocean State Report (Sathyendranath et al. 2018) showed that the trends had reversed in the Pacific for the time segment from January 2007 to December 2016.  

'''CMEMS KEY FINDINGS'''

The trend in the South Altantic gyre area for the 1997 Sept – 2021 December period was positive, with a 0.01% increase in area relative to 2000-01-01 values. Note that this trend is lower than the 0.09% rate for the 1997-2020 trend (though within the uncertainties associated with the two estimates) and is not statistically significant (p>0.05). 
During the 1997 Sept – 2021 December period, the trend in chlorophyll concentration was positive (0.73% year-1) relative to 2000-01-01 values. This is a significant increase from the trend of 0.35% year-1 for the 1997-2020 period and is statistically significant (p<0.05).  The last two years of the timeseries show an increased deviation from the mean.

'''DOI (product):''' 
https://doi.org/10.48670/moi-00228
Baltic Sea - Sea Ice Concentration and Thickness Charts

'''Short description:''' 

For the Baltic Sea, the operational sea ice service at FMI provides ice parameters over the Baltic Sea. The parameters are based on ice chart produced on daily basis during the Baltic Sea ice season and show the ice concentration in a 1 km grid. Ice thickness chart (ITC) is a product based on the most recent available ice chart (IC) and a SAR image. The SAR data is used to update the ice information in the IC. The ice regions in the IC are updated according to a SAR segmentation and new ice thickness values are assigned to each SAR segment based on the SAR backscattering and the ice IC thickness range at that location.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00132
Arctic Ocean Sea Ice Reanalysis

'''Short description:'''

The Arctic Sea Ice Reanalysis 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, from Bering Strait to the North Atlantic. neXtSIM is forced by reanalyzed surface atmosphere forcings (ERA5) from the ECMWF (European Centre for Medium-Range Weather Forecasts) and ocean forcings from TOPAZ4b, the ARC MFC MYP system (002_003). neXtSIM assimilates satellite sea ice concentrations from Passive Microwave satellite sensors, and sea ice thickness from CS2SMOS in winter from October 2010 onwards. The output variables are sea ice concentrations (total, young ice, and multi-year ice), sea ice thickness, sea ice velocity, snow depth on sea ice, sea ice type, sea ice age, sea ice ridge volume fraction and sea ice albedo, provided at daily and monthly 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.

'''DOI (product) :'''   
https://doi.org/10.48670/mds-00336
Global Ocean OSTIA Sea Surface Temperature and Sea Ice Reprocessed

'''Short description :'''

The OSTIA (Worsfold et al. 2024) global sea surface temperature reprocessed product provides daily gap-free maps of foundation sea surface temperature and ice concentration (referred to as an L4 product) at 0.05deg.x 0.05deg. horizontal grid resolution, using in-situ and satellite data. This product provides the foundation Sea Surface Temperature, which is the temperature free of diurnal variability.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00168
Global ocean low and mid trophic levels biomass content hindcast

'''Short description:'''
The Low and Mid-Trophic Levels (LMTL) reanalysis for global ocean is produced at [https://www.cls.fr CLS] on behalf of Global Ocean Marine Forecasting Center. It provides 2D fields of biomass content of zooplankton and six functional groups of micronekton. It uses the LMTL component of SEAPODYM dynamical population model (http://www.seapodym.eu). No data assimilation has been done. This product also contains forcing data: net primary production, euphotic depth, depth of each pelagic layers zooplankton and micronekton inhabit, average temperature and currents over pelagic layers.

'''Forcings sources:'''
* Ocean currents and temperature (CMEMS multiyear product)
* Net Primary Production computed from chlorophyll a, Sea Surface Temperature and Photosynthetically Active Radiation observations (chlorophyll from CMEMS multiyear product, SST from NOAA NCEI AVHRR-only Reynolds, PAR from INTERIM) and relaxed by model outputs at high latitudes (CMEMS biogeochemistry multiyear product)

'''Vertical coverage:'''
* Epipelagic layer 
* Upper mesopelagic layer
* Lower mesopelagic layer (max. 1000m)

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00020
High-resolution L3 Sea Surface Wind from NRT Satellite Measurements over the Atlantic Sea

'''Short description:'''

For the Atlantic Ocean - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Near Real-Time Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are updated several times daily to provide the best product timeliness.

'''DOI (product) :'''  
https://doi.org/10.48670/mds-00331
Atlantic-Iberian Biscay Irish- Ocean Wave Analysis and Forecast

'''Short description:'''

The IBI-MFC provides a high-resolution wave analysis and forecast product (run twice a day by Nologin with the support of CESGA in terms of supercomputing resources), covering the European waters, and more specifically the Iberia–Biscay–Ireland (IBI) area. The last 2 years before now (historic best estimates), as well as hourly instantaneous forecasts with a horizon of up to 10 days (updated on a daily basis) are available on the catalogue.
The IBI wave model system is based on the MFWAM model and runs on a grid of 1/36º of horizontal resolution forced with the ECMWF hourly wind data. The system assimilates significant wave height (SWH) altimeter data and CFOSAT wave spectral data (supplied by Météo-France), and it is forced by currents provided by the IBI ocean circulation system. 
The product offers hourly instantaneous fields of different wave parameters, including Wave Height, Period and Direction for total spectrum; fields of Wind Wave (or wind sea), Primary Swell Wave and Secondary Swell for partitioned wave spectra; and the highest wave variables, such as maximum crest height and maximum crest-to-trough height. Additionally, the IBI wave system is set up to provide internally some key parameters adequate to be used as forcing in the IBI NEMO ocean model forecast run.

'''DOI (Product)''': 
https://doi.org/10.48670/moi-00025
Iberia Biscay Ireland Sea Surface Temperature time series and trend from Observations Reprocessing

'''DEFINITION'''

The omi_climate_sst_ibi_area_averaged_anomalies product for 2024 includes Sea Surface Temperature (SST) anomalies, given as monthly mean time series starting on 1982 and averaged over the IBI areas. The IBI SST OMI is built from the CMEMS Reprocessed European North West Shelf Iberai-Biscay-Irish areas (SST_MED_SST_L4_REP_OBSERVATIONS_010_026, see e.g. the OMI QUID, http://marine.copernicus.eu/documents/QUID/CMEMS-OMI-QUID-CLIMATE-SST- IBI_v3.pdf), which provided the SSTs used to compute the evolution of SST anomalies over the IBI areas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps over the European North West Shelf Iberai-Biscay-Irish areas built from re-processed ESA SST CCI, C3S (Embury et al., 2019).  Anomalies are computed against the 1991-2020 reference period. The reference for this OMI can be found in the first and second issue of the Copernicus Marine Service Ocean State Report (OSR), Section 1.1 (Roquet et al., 2016; Mulet et al., 2018).

'''CONTEXT'''

Sea surface temperature (SST) is a key climate variable since it deeply contributes in regulating climate and its variability (Deser et al., 2010). SST is then essential to monitor and characterise the state of the global climate system (GCOS 2010). Long-term SST variability, from interannual to (multi-)decadal timescales, provides insight into the slow variations/changes in SST, i.e. the temperature trend (e.g., Pezzulli et al., 2005). In addition, on shorter timescales, SST anomalies become an essential indicator for extreme events, as e.g. marine heatwaves (Hobday et al., 2018). 

'''CMEMS KEY FINDINGS '''

The overall trend in the SST anomalies in this region is 0.012 ±0.002 °C/year over the period 1982-2024.  

'''DOI (product):''' 
https://doi.org/10.48670/moi-00256
Baltic Sea - L3S Sea Surface Temperature Reprocessed

'''Short description:''' 

For the Baltic Sea- The DMI Sea Surface Temperature reprocessed analysis provides daily Level 3 Super-Collated fields of the sea surface temperature fields, at 0.02deg. x 0.02deg. horizontal resolution. It is produced by the DMI Optimal Interpolation (DMIOI) system (Høyer and She, 2007) as the first step prior to providing the high resolution (1/50deg. - approx. 2km grid resolution) daily analysis of the daily average sea surface temperature (SST) at 20 cm depth. It uses satellite data from infra-red radiometers, from the ESA SST_cci v3.0 (Embury et al., 2024) and Copernicus C3S projects, namely L2P data from (A)ATSRs, SLSTR and AVHRR for the period 1982-2021, L3U data from SLSTR and AVHRR for 2022-July 19 2024 and L2P data from SLSTR and AVHRR from July 20 2024 onward. For the Sea Ice Concentration it uses the Baltic high resolution sea ice concentration data from the Copernicus Marine Service SI TAC (SEAICE_BAL_PHY_L4_MY_011_019). 

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00312
Mediterranean Sea, Bio-Geo-Chemical, L4, monthly means, daily gapfree and climatology Satellite Observations (1997-ongoing)

'''Short description:'''

For the '''Mediterranean Sea''' Ocean '''Satellite Observations''', the Italian National Research Council (CNR – Rome, Italy), is providing multi-years '''Bio-Geo_Chemical (BGC)''' regional datasets:
* '''''plankton''''' with the phytoplankton chlorophyll concentration (CHL) evaluated via region-specific algorithms (Case 1 waters: Volpe et al., 2019, with new coefficients; Case 2 waters, Berthon and Zibordi, 2004), and the interpolated '''gap-free''' Chl concentration (to provide a "cloud free" product) estimated by means of a modified version of the DINEOF algorithm (Volpe et al., 2018); moreover, daily climatology for chlorophyll concentration is provided.
* '''''pp''''' with the Integrated Primary Production (PP).

'''Upstreams''': SeaWiFS, MODIS, MERIS, VIIRS-SNPP & JPSS1, OLCI-S3A & S3B for the '''"multi"''' products, and OLCI-S3A & S3B for the '''"olci"''' products

'''Temporal resolutions''': monthly and daily (for '''"gap-free"''' and climatology data)

'''Spatial resolution''': 1 km for '''"multi"''' and 300 meters for '''"olci"'''

To find this product in the catalogue, use the search keyword '''"OCEANCOLOUR_MED_BGC_L4_MY"'''.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00300
Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L3 (daily) from Satellite Observations (1997-ongoing)

'''Short description: '''

For the '''Global''' Ocean '''Satellite Observations''', ACRI-ST company (Sophia Antipolis, France) is providing '''Bio-Geo-Chemical (BGC)''' products based on the '''Copernicus-GlobColour''' processor.

* Upstreams: SeaWiFS, MODIS, MERIS, VIIRS-SNPP & JPSS1, OLCI-S3A & S3B for the '''multi''' products, and S3A & S3B only for the '''olci''' products.

* Variables: Chlorophyll-a ('''CHL'''), Gradient of Chlorophyll-a ('''CHL_gradient'''), Phytoplankton Functional types and sizes ('''PFT'''), Suspended Matter ('''SPM'''), Secchi Transparency Depth ('''ZSD'''), Diffuse Attenuation ('''KD490'''), Particulate Backscattering ('''BBP'''), Absorption Coef. ('''CDM''') and Reflectance ('''RRS''').


* Temporal resolutions: '''daily'''.

* Spatial resolutions: '''4 km''' and a finer resolution based on olci '''300 meters''' inputs.

* Recent products are organized in datasets called Near Real Time ('''NRT''') and long time-series (from 1997) in datasets called Multi-Years ('''MY''').


To find the '''Copernicus-GlobColour''' products in the catalogue, use the search keyword '''GlobColour'''. 

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00280
European North West Shelf/Iberia Biscay Irish Seas - High Resolution L4 Sea Surface Temperature Reprocessed

'''Short description:''' 

For the European North West Shelf Ocean Iberia Biscay Irish Seas. The IFREMER Sea Surface Temperature reprocessed analysis aims at providing daily gap-free maps of sea surface temperature, referred as L4 product, at 0.05deg. x 0.05deg. horizontal resolution, over the 1982-present period, using satellite data from the European Space Agency Sea Surface Temperature Climate Change Initiative (ESA SST CCI) L3 products (1982-2016) and from the Copernicus Climate Change Service (C3S) L3 product (2017-present). The gridded SST product is intended to represent a daily-mean SST field at 20 cm depth.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00153
North West Shelf Sea Surface Temperature extreme from Reanalysis

'''DEFINITION'''

The CMEMS NORTHWESTSHELF_OMI_tempsal_extreme_var_temp_mean_and_anomaly OMI indicator is based on the computation of the annual 99th percentile of Sea Surface Temperature (SST) from model data. Two different CMEMS products are used to compute the indicator: The North-West Shelf Multi Year Product (NWSHELF_MULTIYEAR_PHY_004_009) and the Analysis product (NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013).
Two parameters are included on this OMI:
* Map of the 99th mean percentile: It is obtained from the Multi Year Product, the annual 99th percentile is computed for each year of the product. The percentiles are temporally averaged over the whole period (1993-2019).
* Anomaly of the 99th percentile in 2020: The 99th percentile of the year 2020 is computed from the Analysis product. The anomaly is obtained by subtracting the mean percentile from the 2020 percentile.
This indicator is aimed at monitoring the extremes of sea surface temperature every year and at checking their variations in space. The use of percentiles instead of annual maxima, makes this extremes study less affected by individual data. This study of extreme variability was first applied to the sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, such as sea surface temperature and significant wave height (Pérez Gómez et al 2018 and Alvarez Fanjul et al., 2019). More details and a full scientific evaluation can be found in the CMEMS Ocean State report (Alvarez Fanjul et al., 2019).

'''CONTEXT'''

This domain comprises the North West European continental shelf where depths do not exceed 200m and deeper Atlantic waters to the North and West. For these deeper waters, the North-South temperature gradient dominates (Liu and Tanhua, 2021). Temperature over the continental shelf is affected also by the various local currents in this region and by the shallow depth of the water (Elliott et al., 1990). Atmospheric heat waves can warm the whole water column, especially in the southern North Sea, much of which is no more than 30m deep (Holt et al., 2012). Warm summertime water observed in the Norwegian trench is outflow heading North from the Baltic Sea and from the North Sea itself.

'''CMEMS KEY FINDINGS'''

The 99th percentile SST product can be considered to represent approximately the warmest 4 days for the sea surface in Summer. Maximum anomalies for 2020 are up to 4oC warmer than the 1993-2019 average in the western approaches, Celtic and Irish Seas, English Channel and the southern North Sea. For the atmosphere, Summer 2020 was exceptionally warm and sunny in southern UK (Kendon et al., 2021), with heatwaves in June and August. Further north in the UK, the atmosphere was closer to long-term average temperatures. Overall, the 99th percentile SST anomalies show a similar pattern, with the exceptional warm anomalies in the south of the domain.

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

'''DOI (product)'''
https://doi.org/10.48670/moi-00273
Arctic Ocean - Sea and Ice Surface Temperature L4 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 interpolated field 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-00123
Atlantic - European North West Shelf - Ocean Physics Analysis and Forecast

'''Short description:'''

The NWSHELF_ANALYSISFORECAST_PHY_004_013 is produced by a coupled hydrodynamic-wave model system with tides, implemented over the North East Atlantic and Shelf Seas at 1.5 km of horizontal resolution and 33 vertical levels.
The product is updated daily, providing 7-day forecast for temperature, salinity, currents, sea level and mixed layer depth.
Products are provided at quarter-hourly, hourly, daily de-tided (with Doodson filter), and monthly frequency.

'''DOI (product) :'''   
https://doi.org/10.48670/moi-00054
EUROPEAN SEAS ALONG-TRACK L3 SEA SURFACE HEIGHTS REPROCESSED (1993-ONGOING) TAILORED FOR DATA ASSIMILATION

'''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) sampling. It serves in delayed-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, Jason-1, Jason-2, Topex/Poseidon, ERS-1, ERS-2, Envisat, Geosat Follow-On, HY-2A, HY-2B, etc). The system exploits the most recent datasets available based on the enhanced GDR/NTC production. All the missions are homogenized with respect to a reference mission. Part of the processing is fitted to the European Sea area. (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 https://resources.marine.copernicus.eu/product-detail/SEALEVEL_GLO_PHY_NOISE_L4_STATIC_008_033/INFORMATION 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-00139