'''Short description:''' Le modèle biogéochimique ECO-MARS3D sur la façade Manche Atlantique (PREVIMER_B1-ECOMARS3D-MANGA4000) est un modèle 3D de résolution spatiale 4km qui fournit les concentrations de nutriments et de plancton toutes les heures sur 30 niveaux (fenêtre de prévision à 4 jours). '''Paramètres calculés :''' Les paramètres calculés sont les suivants : * SAL : sea_water_salinity * TEMP : sea_water_temperature * suspended_inorganic_particulate_matter : mass_concentration_of_suspended_matter_in_sea_water * nanopicoplankton_nitrogen : mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_water * diatom_nitrogen : mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_water * dinoflagellate_nitrogen : mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_water * microzooplankton_nitrogen : mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_water * mesozooplankton_nitrogen : mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_water * colonial_phaeocystis_nitrogen : mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_water * phaeocystis_mucus : concentration_of_phaeocystis_mucus_expressed_as_mass_in_sea_water * ammonium : mole_concentration_of_ammonium_in_sea_water * nitrate : mole_concentration_of_nitrate_in_sea_water * dissolved_silicate : mole_concentration_of_silicate_in_sea_water * dissolved_phosphate : mole_concentration_of_phosphate_in_sea_water * dissolved_oxygen : dissolved_oxygen_in_water_column * cumulative_nanoflagellate_carbon_production : cumulative_nanoflagellate_production_expressed_as_carbon_in_sea_water * cumulative_diatom_carbon_production : cumulative_diatom_production_expressed_as_carbon_in_sea_water * cumulative_dinoflagellate_carbon_production : cumulative_dinoflagellate_production_expressed_as_carbon_in_sea_water * cumulative_phaeocystis_carbon_production : cumulative_phaeocystis_production_expressed_as_carbon_in_sea_water * organic_nitrogen_benth : mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthos Les paramètres diagnostiques calculés sont les suivants : * XE : sea_surface_height_above_geoid * maximum_de_diat : maximum_diatom_mass_concentration_in_sea_water * maximum_de_dino : maximum_dinoflagellate_mass_concentration_in_sea_water * maximum_de_nano : maximum_nanoflagellate_mass_concentration_in_sea_water * grad_vert_salinite : maximum_vertical_gradient_of_sea_water_salinity * grad_vert_temp : maximum_vertical_gradient_of_sea_water_temperature * extinction_lumineuse : light_extinction_in_sea_water * prod_diat : cumulated_production_of_diatoms_in_sea_water_column_expressed_in_carbon * prod_dino : cumulated_production_of_dinoflagellates_in_sea_water_column_expressed_in_carbon * prod_nano : cumulated_production_of_nanoflagellates_in_sea_water_column_expressed_in_carbon * chlorophylle_a : chlorophyll_mass_concentration_in_sea_water * prod_cumul_chloro : cumulated_total_production_in_sea_water_column_expressed_in_carbon * maximum_de_phaeocystis : maximum_phaeocystis_mass_concentration_in_sea_water * prod_phaeocystis : cumulated_production_of_phaeocystis_in_sea_water_column_expressed_in_carbon * oxygen_saturation : oxygen_saturation * ammoniumGIRON_tracer_sign: mole_concentration_of_ammonium_in_sea_waterGIRON_tracer_sign * ammoniumGIRON_tracer_age: mole_concentration_of_ammonium_in_sea_waterGIRON_tracer_age * nitrateGIRON_tracer_sign: mole_concentration_of_nitrate_in_sea_waterGIRON_tracer_sign * nitrateGIRON_tracer_age: mole_concentration_of_nitrate_in_sea_waterGIRON_tracer_age * nanopicoplankton_nitrogenGIRON_tracer_sign: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * nanopicoplankton_nitrogenGIRON_tracer_age: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * diatom_nitrogenGIRON_tracer_sign: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * diatom_nitrogenGIRON_tracer_age: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * dinoflagellate_nitrogenGIRON_tracer_sign: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * dinoflagellate_nitrogenGIRON_tracer_age: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * microzooplankton_nitrogenGIRON_tracer_sign: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * microzooplankton_nitrogenGIRON_tracer_age: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * mesozooplankton_nitrogenGIRON_tracer_sign: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * mesozooplankton_nitrogenGIRON_tracer_age: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * detrital_nitrogenGIRON_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * detrital_nitrogenGIRON_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * colonial_phaeocystis_nitrogenGIRON_tracer_sign: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * colonial_phaeocystis_nitrogenGIRON_tracer_age: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * phaeocystis_cells_nitrogenGIRON_tracer_sign: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterGIRON_tracer_sign * phaeocystis_cells_nitrogenGIRON_tracer_age: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterGIRON_tracer_age * organic_nitrogen_benthGIRON_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosGIRON_tracer_sign * organic_nitrogen_benthGIRON_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosGIRON_tracer_age * phytoplankton_sign_N_GIRON: nitrogen_fraction_in_phytoplankton_from_source_GIRON * phytoplankton_age_N_GIRON: age_of_nitrogen_fraction_in_phytoplankton_from_source_GIRON * ammoniumLOIRE_tracer_sign: mole_concentration_of_ammonium_in_sea_waterLOIRE_tracer_sign * ammoniumLOIRE_tracer_age: mole_concentration_of_ammonium_in_sea_waterLOIRE_tracer_age * nitrateLOIRE_tracer_sign: mole_concentration_of_nitrate_in_sea_waterLOIRE_tracer_sign * nitrateLOIRE_tracer_age: mole_concentration_of_nitrate_in_sea_waterLOIRE_tracer_age * nanopicoplankton_nitrogenLOIRE_tracer_sign: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * nanopicoplankton_nitrogenLOIRE_tracer_age: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * diatom_nitrogenLOIRE_tracer_sign: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * diatom_nitrogenLOIRE_tracer_age: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * dinoflagellate_nitrogenLOIRE_tracer_sign: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * dinoflagellate_nitrogenLOIRE_tracer_age: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * microzooplankton_nitrogenLOIRE_tracer_sign: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * microzooplankton_nitrogenLOIRE_tracer_age: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * mesozooplankton_nitrogenLOIRE_tracer_sign: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * mesozooplankton_nitrogenLOIRE_tracer_age: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * detrital_nitrogenLOIRE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * detrital_nitrogenLOIRE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * colonial_phaeocystis_nitrogenLOIRE_tracer_sign: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * colonial_phaeocystis_nitrogenLOIRE_tracer_age: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * phaeocystis_cells_nitrogenLOIRE_tracer_sign: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_sign * phaeocystis_cells_nitrogenLOIRE_tracer_age: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterLOIRE_tracer_age * organic_nitrogen_benthLOIRE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosLOIRE_tracer_sign * organic_nitrogen_benthLOIRE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosLOIRE_tracer_age * phytoplankton_sign_N_LOIRE: nitrogen_fraction_in_phytoplankton_from_source_LOIRE * phytoplankton_age_N_LOIRE: age_of_nitrogen_fraction_in_phytoplankton_from_source_LOIRE * ammoniumSEINE_tracer_sign: mole_concentration_of_ammonium_in_sea_waterSEINE_tracer_sign * ammoniumSEINE_tracer_age: mole_concentration_of_ammonium_in_sea_waterSEINE_tracer_age * nitrateSEINE_tracer_sign: mole_concentration_of_nitrate_in_sea_waterSEINE_tracer_sign * nitrateSEINE_tracer_age: mole_concentration_of_nitrate_in_sea_waterSEINE_tracer_age * nanopicoplankton_nitrogenSEINE_tracer_sign: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * nanopicoplankton_nitrogenSEINE_tracer_age: mole_concentration_of_nanoplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * diatom_nitrogenSEINE_tracer_sign: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * diatom_nitrogenSEINE_tracer_age: mole_concentration_of_diatoms_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * dinoflagellate_nitrogenSEINE_tracer_sign: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * dinoflagellate_nitrogenSEINE_tracer_age: mole_concentration_of_dinoflagellates_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * microzooplankton_nitrogenSEINE_tracer_sign: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * microzooplankton_nitrogenSEINE_tracer_age: mole_concentration_of_microzooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * mesozooplankton_nitrogenSEINE_tracer_sign: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * mesozooplankton_nitrogenSEINE_tracer_age: mole_concentration_of_mesozooplankton_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * detrital_nitrogenSEINE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * detrital_nitrogenSEINE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * colonial_phaeocystis_nitrogenSEINE_tracer_sign: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * colonial_phaeocystis_nitrogenSEINE_tracer_age: mole_concentration_of_colonial_phaeocystis_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * phaeocystis_cells_nitrogenSEINE_tracer_sign: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterSEINE_tracer_sign * phaeocystis_cells_nitrogenSEINE_tracer_age: mole_concentration_of_phaeocystis_cells_expressed_as_nitrogen_in_sea_waterSEINE_tracer_age * organic_nitrogen_benthSEINE_tracer_sign: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosSEINE_tracer_sign * organic_nitrogen_benthSEINE_tracer_age: mole_concentration_of_organic_detritus_expressed_as_nitrogen_in_benthosSEINE_tracer_age * phytoplankton_sign_N_SEINE: nitrogen_fraction_in_phytoplankton_from_source_SEINE * phytoplankton_age_N_SEINE: age_of_nitrogen_fraction_in_phytoplankton_from_source_SEINE

Moving 6-year analysis of Water body silicate in the Mediterranean Sea for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of the season. 6-years periods span from 1970-1975 until 2018-2023. Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is dx=dy=0.125 degrees (around 13.5km and 10.9km accordingly). The vertical resolution is 25 depth levels: [0.,5.,10.,20.,30.,50.,75.,100.,125.,150.,200.,250.,300.,400.,500.,600.,700.,800.,900.,1000.,1100.,1200.,1300.,1400.,1500.]. The horizontal correlation length is 200km. The vertical correlation length (in meters) was set twices the vertical resolution: [10.,10.,20.,20.,40.,50.,50.,50.,50.,100.,100.,100.,200.,200.,200.,200.,200.,200.,200.,200.,200.,200.,200.,200.,200.]. Duplicates check was performed using the following criteria for space and time: dlon=0.001deg., dlat=0.001deg., ddepth=1m, dtime=1hour, dvalue=0.1. The error variance (epsilon2) was set equal to 1 for profiles and 10 for time series to reduce the influence of close data near the coasts. An anamorphosis transformation was applied to the data (function DIVAnd.Anam.loglin) to avoid unrealistic negative values: threshold value=200. A background analysis field was used for all years (1970-2023) with correlation length equal to 600km and error variance (epsilon2) equal to 20. Quality control of the observations was applied using the interpolated field (QCMETHOD=3). Residuals (differences between the observations and the analysis (interpolated linearly to the location of the observations) were calculated. Observations with residuals outside the minimum and maximum values of the 99% quantile were discarded from the analysis. Originators of Italian data sets-List of contributors: - Brunetti Fabio (OGS) - Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 - Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 - Cataletto Bruno (OGS) - Cinzia Comici Cinzia (OGS) - Civitarese Giuseppe (OGS) - DeVittor Cinzia (OGS) - Giani Michele (OGS) - Kovacevic Vedrana (OGS) - Mosetti Renzo (OGS) - Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 - Celio Massimo (ARPA FVG) - Malaguti Antonella (ENEA) - Fonda Umani Serena (UNITS) - Bignami Francesco (ISAC/CNR) - Boldrini Alfredo (ISMAR/CNR) - Marini Mauro (ISMAR/CNR) - Miserocchi Stefano (ISMAR/CNR) - Zaccone Renata (IAMC/CNR) - Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D.,Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d'Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011.

The DTM is a compilation of multibeam echosounder surveys acquired in 2013. The resolution is 1/64 arc-minutes (~30m). Surveys are located on the Capbreton Submarine Canyon (France) with depths from -4.7m to -344.9m. Depths are referenced to the Lowest Astronomical Tide and the coordinates are expressed into the WGS84 reference frame. The surveys which compose the DTM are S201306500-09 and S201306500-11. Data and metadata associated to these surveys are available on the website http://diffusion.shom.fr/pro/lots-bathy.html. The DTM is not to be used for navigation.

The SWOT KaRIn Level-3 Wind Wave product (L3_LR_WIND_WAVE) is an innovative product derived from the Unsmoothed L3_LR_SSH product (DOI: 10.24400/527896/A01-2024.003), which is based on the algorithm presented by Ardhuin et al. (2024). L3_LR_WIND_WAVE takes advantage of the KaRIn Low Rate (LR) chain's ability to resolve waves with wavelengths greater than 500 meters (approximately 18 seconds) and provides detailed information on the characteristics of these wave regimes. This includes significant wave height (SWH), dominant wavelength, and wave propagation direction. These regimes are associated with long-period swells and extreme events that play a critical role in ocean dynamics, coastal processes, and maritime operations. The SWOT L3_LR_WIND_WAVE product is organized into two subproducts, "Light" and "Extended". The L2_LR_SSH "Light" product is described in this metadata sheet. The "Light" L3_LR_WIND_WAVE (also known as the "lightweight" product) includes the SWOT L3_LR_SSH 250-m SSHA spectrum, corrected for instrumental effects and expressed in both Cartesian and polar coordinates. It also includes the swell partition of the spectrum and the wave parameters integrated over this partition, for both the WW3 model and the KaRIn model (significant wave height, wavelength, and direction). The "Extended" L3_LR_WIND_WAVE includes the aforementioned variables plus the WW3 spectrum in the same frequency grid as the KaRIn spectrum and the KaRIn transfer functions used for correction, as well as some parameters derived from KaRIn observations (e.g., coherence, mean backscatter).

Unveiling the implications of hybridization on fitness stands as a primary focus in the realms of ecology and evolution. Numerous investigations elucidate how evolutionary mechanisms regulate the intricate pattern of introgression across genomes, yet few have examined the consequential impact of genetic admixture on fitness attributes. Leveraging the Western Mediterranean population of the European seabass (Dicentrarchus labrax), a population formed through hybridization of the Atlantic and Mediterranean lineages in the Alboran Sea, we utilized the Axiom Sea Bass 57k SNP DlabChip array to genotype 1850 hybrid individuals. This enabled us to evaluate the correlation between individual admixture levels and fitness traits under varying thermal conditions (19°C, 21°C, 23°C, and 25°C). Our initial findings unveil a male-biased sex ratio and high temperature sensitivity among admixed individuals with a greater proportion of Atlantic ancestry. Subsequently, our analysis demonstrates that individuals with a higher Atlantic genetic background also exhibit reduced body weight (a parameter linked to fecundity in fish) compared to those with lower Atlantic ancestry. These outcomes underscore the disadvantageous nature of Atlantic ancestry introgression in the Mediterranean region, aligning with previous observations of the elimination of Atlantic ancestry segments subsequent to hybridization.

"'Short description:''' The High-Resolution Ocean Colour (HR-OC) Consortium (Brockmann Consult, Royal Belgian Institute of Natural Sciences, Flemish Institute for Technological Research) distributes Level 4 (L4) Turbidity (TUR, expressed in FNU), Solid Particulate Matter Concentration (SPM, expressed in mg/l), particulate backscattering at 443nm (BBP443, expressed in m-1) and chlorophyll-a concentration (CHL, expressed in µg/l) for the Sentinel 2/MSI sensor at 100m resolution for a 20km coastal zone. The products are delivered on a geographic lat-lon grid (EPSG:4326). BBP443, constitute the category of the 'optics' products. The BBP443 product is generated from the L3 RRS products using a quasi-analytical algorithm (Lee et al. 2002). he 'tur_tsm_chl' products include TUR, SPM and CHL. They are retrieved through the application of automated switching algorithms to the RRS spectra adapted to varying water conditions (Novoa et al. 2017). The GEOPHYSICAL product consists of the Chlorophyll-a concentration (CHL) retrieved via a multi-algorithm approach with optimized quality flagging (O'Reilly et al. 2019, Gons et al. 2005, Lavigne et al. 2021). Monthly products (P1M) are temporal aggregates of the daily L3 products. Daily products contain gaps in cloudy areas and where there is no overpass at the respective day. Aggregation collects the non-cloudy (and non-frozen) contributions to each pixel. Contributions are averaged per variable. While this does not guarantee data availability in all pixels in case of persistent clouds, it provides a more complete product compared to the sparsely filled daily products. The Monthly L4 products (P1M) are generally provided withing 4 days after the last acquisition date of the month. Daily gap filled L4 products (P1D) are generated using the DINEOF (Data Interpolating Empirical Orthogonal Functions) approach which reconstructs missing data in geophysical datasets by using a truncated Empirical Orthogonal Functions (EOF) basis in an iterative approach. DINEOF reconstructs missing data in a geophysical dataset by extracting the main patterns of temporal and spatial variability from the data. While originally designed for low resolution data products, recent research has resulted in the optimization of DINEOF to handle high resolution data provided by Sentinel-2 MSI, including cloud shadow detection (Alvera-Azcárate et al., 2021). These types of L4 products are generated and delivered one month after the respective period. '''Processing information:''' The HR-OC processing system is deployed on Creodias where Sentinel 2/MSI L1C data are available. The production control element is being hosted within the infrastructure of Brockmann Consult. The processing chain consists of: * Resampling to 60m and mosaic generation of the set of Sentinel-2 MSI L1C granules of a single overpass that cover a single UTM zone. * Application of a glint correction taking into account the detector viewing angles * Application of a coastal mask with 20km water + 20km land. The result is a L1C mosaic tile with data just in the coastal area optimized for compression. * Level 2 processing with pixel identification (IdePix), atmospheric correction (C2RCC and ACOLITE or iCOR), in-water processing and merging (HR-OC L2W processor). The result is a 60m product with the same extent as the L1C mosaic, with variables for optics, transparency, and geophysics, and with data filled in the water part of the coastal area. * invalid pixel identification takes into account corrupted (L1) pixels, clouds, cloud shadow, glint, dry-fallen intertidal flats, coastal mixed-pixels, sea ice, melting ice, floating vegetation, non-water objects, and bottom reflection. * Daily L3 aggregation merges all Level 2 mosaics of a day intersecting with a target tile. All valid water pixels are included in the 20km coastal stripes; all other values are set to NaN. There may be more than a single overpass a day, in particular in the northern regions. This step comprises resampling to the 100m target grid. * Monthly L4 aggregation combines all Level 3 products of a month and a single tile. The output is a set of 3 NetCDF datasets for (1) optics and (2) turbidity, suspended matter and chlorophyll concentration, respectively for the month. * Gap filling combines all daily products of a period and generates (partially) gap-filled daily products again. The output of gap filling are 2 datasets for (1) optics (BBP443 only) and (2) turbidity, suspended mattr and chlorophyll concentration per day. '''Description of observation methods/instruments:''' Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so-called ocean colour which is affected by the presence of phytoplankton. '''Quality / Accuracy / Calibration information:''' A detailed description of the calibration and validation activities performed over this product can be found on the CMEMS web portal and in CMEMS-BGP_HR-QUID-009-201_to_212. '''Suitability, Expected type of users / uses:''' This product is meant for use for educational purposes and for the managing of the marine safety, marine resources, marine and coastal environment and for climate and seasonal studies. '''Dataset names: ''' *cmems_obs_oc_med_bgc_tur_spm_chl_nrt_l4-hr-mosaic_P1M-v01 *cmems_obs_oc_med_bgc_optics_nrt_l4-hr-mosaic_P1M-v01 *cmems_obs_oc_med_bgc_tur_spm_chl_nrt_l4-hr-mosaic_P1D-v01 *cmems_obs_oc_med_bgc_optics_nrt_l4-hr-mosaic_P1D-v01 '''Files format:''' *netCDF-4, CF-1.7 *INSPIRE compliant." '''DOI (product) :''' https://doi.org/10.48670/moi-00110

This dataset contains the dynamical outputs of a global ocean simulation coupling dynamics and biogeochemistry at ¼° over the year 2019. The simulation has been performed using the coupled circulation/ecosystem model NEMO/PISCES (https://www.nemo-ocean.eu/), which is here enhanced to perform an ensemble simulation with explicit simulation of modeling uncertainties in the physics and in the biogeochemistry. This dataset is one of the 40 members of the ensemble simulation. This study was part of the Horizon Europe project SEAMLESS (https://seamlessproject.org/Home.html), with the general objective of improving the analysis and forecast of ecosystem indicators.   See Popov et al. (https://os.copernicus.org/articles/20/155/2024/) for more details on the study.