Monitoring Black Sea environmental changes from space: New products for altimetry, ocean colour and salinity. Potentialities and requirements for a dedicated in-situ observing system
altimetry; Black Sea; environment monitoring; observing system; ocean colour; salinity; satellite; Oceanography; Global and Planetary Change; Aquatic Science; Water Science and Technology; Environmental Science (miscellaneous); Ocean Engineering
Abstract :
[en] In this paper, satellite products developed during the Earth Observation for Science and Innovation in the Black Sea (EO4SIBS) ESA project are presented. Ocean colour, sea level anomaly and sea surface salinity datasets are produced for the last decade and validated with regional in-situ observations. New data processing is tested to appropriately tackle the Black Sea’s particular configuration and geophysical characteristics. For altimetry, the full rate (20Hz) altimeter measurements from Cryosat-2 and Sentinel-3A are processed to deliver a 5Hz along-track product. This product is combined with existing 1Hz product to produce gridded datasets for the sea level anomaly, mean dynamic topography, geostrophic currents. This new set of altimetry gridded products offers a better definition of the main Black Sea current, a more accurate reconstruction and characterization of eddies structure, in particular, in coastal areas, and improves the observable wavelength by a factor of 1.6. The EO4SIBS sea surface salinity from SMOS is the first satellite product for salinity in the Black Sea. Specific data treatments are applied to remedy the issue of land-sea and radio frequency interference contamination and to adapt the dielectric constant model to the low salinity and cold waters of the Black Sea. The quality of the SMOS products is assessed and shows a significant improvement from Level-2 to Level -3 and Level-4 products. Level-4 products accuracy is 0.4-0.6 psu, a comparable value to that in the Mediterranean Sea. On average SMOS sea surface salinity is lower than salinity measured by Argo floats, with a larger error in the eastern basin. The adequacy of SMOS SSS to reproduce the spatial characteristics of the Black Sea surface salinity and, in particular, plume patterns is analyzed. For ocean colour, chlorophyll-a, turbidity and suspended particulate materials are proposed using regional calibrated algorithms and satellite data provided by OLCI sensor onboard Sentinel-3 mission. The seasonal cycle of ocean colour products is described and a water classification scheme is proposed. The development of these three types of products has suffered from important in-situ data gaps that hinder a sound calibration of the algorithms and a proper assessment of the datasets quality. We propose recommendations for improving the in-situ observing system that will support the development of satellite products.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Grégoire, Marilaure ; Université de Liège - ULiège > Freshwater and OCeanic science Unit of reSearch (FOCUS)
Alvera Azcarate, Aida ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER)
Buga, Luminita; Department of Physical Oceanography and Coastal Engineering, National Institute for Marine Research and Development "Grigore Antipa", Constanta, Romania
Capet, Arthur ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > MAST (Modeling for Aquatic Systems)
Constantin, Sorin; Terrasigna, Bucharest, Romania
D’ortenzio, Fabrizio; Laboratoire d’Oceéanographie de Villefranche-sur-mer, CNRS / Sorbonne Université, Villefranche-sur-mer, France
Doxaran, David; Laboratoire d’Oceéanographie de Villefranche-sur-mer, CNRS / Sorbonne Université, Villefranche-sur-mer, France
Faugeras, Yannis; Collecte Localisation Satelliltes (CLS), Toulouse, France
Garcia-Espriu, Aina; Barcelona Expert Center (BEC), Institute of Marine Sciences (ICM), Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
Golumbeanu, Mariana; Department of Physical Oceanography and Coastal Engineering, National Institute for Marine Research and Development "Grigore Antipa", Constanta, Romania
González-Haro, Cristina; Barcelona Expert Center (BEC), Institute of Marine Sciences (ICM), Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
González-Gambau, Verónica; Barcelona Expert Center (BEC), Institute of Marine Sciences (ICM), Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
Kasprzyk, Jean-Paul ; Université de Liège - ULiège > Département de géographie > Unité de Géomatique - Topographie et géométrologie
Ivanov, Evgeny ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > MAST (Modeling for Aquatic Systems)
Mason, Evan ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > MAST (Modeling for Aquatic Systems) ; IMEDIA, Spain
Mateescu, Razvan; Department of Physical Oceanography and Coastal Engineering, National Institute for Marine Research and Development "Grigore Antipa", Constanta, Romania
Meulders, Catherine ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > MAST (Modeling for Aquatic Systems)
Olmedo, Estrella; Barcelona Expert Center (BEC), Institute of Marine Sciences (ICM), Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
Pons, Leonard; Laboratoire d’Oceéanographie de Villefranche-sur-mer, CNRS / Sorbonne Université, Villefranche-sur-mer, France
Pujol, Marie-Isabelle; Collecte Localisation Satelliltes (CLS), Toulouse, France
Sarbu, George; Department of Physical Oceanography and Coastal Engineering, National Institute for Marine Research and Development "Grigore Antipa", Constanta, Romania
Turiel, Antonio; Barcelona Expert Center (BEC), Institute of Marine Sciences (ICM), Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
Vandenbulcke, Luc ; Université de Liège - ULiège > Freshwater and OCeanic science Unit of reSearch (FOCUS)
Rio, Marie-Hélène; European Space Agency, Center for Earth Observations (ESRIN), Frascati, Italy
Monitoring Black Sea environmental changes from space: New products for altimetry, ocean colour and salinity. Potentialities and requirements for a dedicated in-situ observing system
This work has been carried out as part of the European Space Agency contract Earth Observation data For Science and Innovations in the Black Sea (EO4SIBS, ESA contract n° 4000127237/19/I-EF). MG received fundings from the Copernicus Marine Service (CMEMS), the European Union’s Horizon 2020 BRIDGE-BS project under grant agreement No. 101000240 and by the Project CE2COAST funded by ANR(FR), BELSPO (BE), FCT (PT), IZM (LV), MI (IE), MIUR (IT), Rannis (IS), and RCN (NO) through the 2019 “Joint Transnational Call on Next Generation Climate Science in Europe for Oceans” initiated by JPI Climate and JPI Oceans. The research on SMOS SSS has been also supported in part by the Spanish R&D project INTERACT (PID2020-114623RB-C31), which is funded by MCIN/AEI/10.13039/501100011033, funding from the Spanish government through the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) and the CSIC Thematic Interdisciplinary Platform Teledetect. AcknowledgmentsThis work has been carried out as part of the European Space Agency contract Earth Observation data For Science and Innovations in the Black Sea (EO4SIBS, ESA contract n° 4000127237/19/I-EF). MG received fundings from the Copernicus Marine Service (CMEMS), the European Union’s Horizon 2020 BRIDGE-BS project under grant agreement No. 101000240 and by the Project CE2COAST funded by ANR(FR), BELSPO (BE), FCT (PT), IZM (LV), MI (IE), MIUR (IT), Rannis (IS), and RCN (NO) through the 2019 “Joint Transnational Call on Next Generation Climate Science in Europe for Oceans” initiated by JPI Climate and JPI Oceans. The research on SMOS SSS has been also supported in part by the Spanish R&D project INTERACT (PID2020-114623RB-C31), which is funded by MCIN/AEI/10.13039/501100011033, funding from the Spanish government through the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) and the CSIC Thematic Interdisciplinary Platform Teledetect.
Akpinar A. Fach B. A. Oguz T. (2017). Observing the subsurface thermal signature of the black Sea cold intermediate layer with argo profiling floats. Deep Sea Res. Part I: Oceanographic Res. Papers 124, 140–152. doi: 10.1016/j.dsr.2017.04.002
Alvera-Azcárate A. Barth A. Rixen M. Beckers J.-M. (2005). Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature. Ocean Model. 9, 325–346. doi: 10.1016/j.ocemod.2004.08.001
Alvera-Azcárate A. Sirjacobs D. Barth A. Beckers J.-M. (2012). Outlier detection in satellite data using spatial coherence. Remote Sens. Environ. 119, 84–91. doi: 10.1016/j.rse.2011.12.009
Alvera-Azcárate A. Barth A. Troupin C. Beckers J.-M. Van der Zande D. (2021). Creation of high resolution suspended particulate matter data in the North Sea from Sentinel-2 and Sentinel-3 data. In 2021 IGARSS: IEEE International Geoscience & Remote Sensing Symposium. Proceedings. Brussels (Belgium). doi: 10.1109/IGARSS47720.2021.9554197
Antoine D. Morel A. (1999). A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument): principle and implementation for atmospheres carrying various aerosols including absorbing ones. Int. J. Remote Sens. 20, 1875–1916. doi: 10.1080/014311699212533
Babin M. Morel A. Fournier-Sicre V. Fell F. Stramski D. (2003). Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration. Limnol. Oceanogr. 48 (2), 843–859. doi: 10.4319/lo.2003.48.2.0843
Beckers J.-M. Barth A. Alvera-Azcárate A. (2006). DINEOF reconstruction of clouded images including error maps – application to the Sea-surface temperature around Corsican island. Ocean Sci. 2, 183–199. doi: 10.5194/os-2-183-2006
Beckers J.-M. Rixen M. (2003). EOF calculations and data filling from incomplete oceanographic datasets. J. Atmos. Ocean. Tech. 20, 1839–1856. doi: 10.1175/1520-0426(2003)020<1839:ECADFF>2.0.CO;2
Bouzaiene M. Menna M. Elhmaidi D. Dilmahamod A. F. Poulain P.-M. (2021). Spreading of Lagrangian particles in the black Sea: A comparison between drifters and a high-resolution ocean model. Remote Sens 13 (13), 2603. doi: 10.3390/rs13132603
Breitburg D. Levin L. A. Oschlies A. Grégoire M. Chavez F. P. Conley D. J. et al. (2018). Declining oxygen in the global ocean and coastal waters. Science 359:1–11. doi: 10.1126/science.aam7240
Buesseler K. Livingston H. Ivanov L. Romanov A. (1991). Stability of the oxic–anoxic interface in the black Sea. Deep Sea Res. 41, 283–296. doi: 10.1016/0967-0637(94)90004-3
Capet A. Beckers J.-M. Grégoire M. (2013). Drivers, mechanisms and long-term variability of seasonal hypoxia on the black Sea northwestern shelf – is there any recovery after eutrophication? Biogeosciences 10, 3943–3962. doi: 10.5194/bg-10-3943-2013
Capet A. Troupin C. Cartensen J. Grégoire M. Beckers J.-M. (2014). Untangling spatial and temporal trends in the variability of the Black Sea Cold Intermediate Layer and mixed Layer Depth using the DIVA detrending procedure. Ocean Dynamics 64 (3), 315–324. doi: 10.1007/s10236-013-0683-4
Capet A. Stanev E. V. Beckers J.-M. Murray J. W. Grégoire M. (2016). Decline of the black Sea oxygen inventory. Biogeosciences 13, 1287–1297. doi: 10.5194/bg-13-1287-2016
Capet A. Taburet G. Mason E. Pujol M. I. Grégoire M. Rio M. H. (2022). Using argo floats to characterize altimetry products: a study of eddy-induced subsurface oxygen anomalies in the black Sea. Front. Mar. Sci 9, 875653. doi: 10.3389/fmars.2022.875653
Capet A. Vandenbulcke L. Grégoire M. (2020). A new intermittent regime of convective ventilation threatens the black Sea oxygenation status. Biogeosciences 17, 6507–6525. doi: 10.5194/bg-17-6507-2020
Cazenave A. Bonnefond P. Mercier F. Dominh K. Toumazou V. (2002). Sea Level variations in the Mediterranean Sea and black Sea from satellite altimetry and tide gauges. Global Planet. Change 34, 59–86. doi: 10.1016/S0921-8181(02)00106-6
Ciliberti S. A. Grégoire M. Staneva J. Palazov A. Coppini G. Lecci R. et al. (2021). Monitoring and forecasting the ocean state and biogeochemical processes in the black Sea: Recent developments in the Copernicus marine service. J. Mar. Sci. Eng. 9, 1146. doi: 10.3390/jmse9101146
Constantin S. Constantinescu Ș. Doxaran D. (2017). Long-term analysis of turbidity patterns in Danube delta coastal area based on MODIS satellite data. J. Mar. Syst. 170, 10–21. doi: 10.1016/j.jmarsys.2017.01.016
Constantin S. Doxaran D. Constantinescu Ș. (2016). Estimation of water turbidity and analysis of its spatio-temporal variability in the Danube river plume (Black Sea) using MODIS satellite data. Cont. Shelf Res. 112, 14–30. doi: 10.1016/j.csr.2015.11.009
Davis R. E. (1998). Preliminary results from directly measuring mid-depth circulation in the tropical and south pacific. J. Geophys. Res.-Oceans 103, 24619–24639. doi: 10.1029/98JC01913
Degens E. T. Ross D. A. (1972). Chronology of the black Sea over the last 25,000 years. Chem. Geol. 10, 1–16. doi: 10.1016/0009-2541(72)90073-3
Doerffer R. Schiller H. (2007). The MERIS case 2 water algorithm. Int. J. Remote Sens. 28, 517–535. doi: 10.1080/01431160600821127
Dogliotti A. I. Ruddick K. Nechad B. Doxaran D. Knaeps E. (2015). A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters. Remote Sens. Environ. 156, 157–168. doi: 10.1016/j.rse.2014.09.020
Dufau C. Orsztynowicz M. Dibarboure G. Morrow R. Le Traon P.-Y. (2016). Mesoscale resolution capability of altimetry: Present and future. J. Geophys. Res.-Oceans 121, 4910–4927. doi: 10.1002/2015JC010904
Dussurget R. Birol F. Morrow R. Mey P. D. (2011). Fine resolution altimetry data for a regional application in the bay of Biscay. Mar. Geod. 34, 447–476. doi: 10.1080/01490419.2011.584835
Escudier R. Bouffard J. Pascual A. Poulain P.-M. Pujol M.-I. (2013). Improvement of coastal and mesoscale observation from space: Application to the northwestern Mediterranean Sea. Geophys. Res. Lett. 40, 2148–2153. doi: 10.1002/grl.503242
EUMETSAT (2021) Sentinel-3 OLCI L2 report for baseline collection OL_L2M_003. doc. no. EUM/RSP/REP/21/1211386. Available at: https://www.eumetsat.int/media/47794.
Fennel K. Testa J. M. (2019). Biogeochemical controls on coastal hypoxia. Annu. Rev. Mar. Sci. 11, 105–130. doi: 10.1146/annurev-marine-010318-095138
González-Gambau V. Olmedo E. Turiel A. González-Haro C. García- Espriu A. Martínez J. et al. (2022). First SMOS Sea surface salinity dedicated products over the Baltic Sea. Earth Syst. Sci. Data Discussions 14 (5), 2343–2368. doi: 10.5194/essd-2021-461
González-Gambau V. Olmedo E. Turiel A. Martínez J. Ballabrera-Poy J. Portabella M. et al. (2016). Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique. Remote Sens. Environ. 180, 205–220. doi: 10.1016/j.rse.2015.12.032
González-Gambau V. Turiel A. González-Haro C. Martínez J. Olmedo E. Oliva R. et al. (2020). Triple collocation analysis for two error-correlated datasets: Application to l-band brightness temperatures over land. Remote Sens-Basel 12, 3381. doi: 10.3390/rs12203381
González-Haro C. Olmedo E. González-Gambau V. García-Espriu A. Turiel A. (2021). “EO4SIBS experimental SMOS Colored Detrital Matter (CDM) L4 (V.1.0) [Dataset]”; DIGITAL.CSIC. doi: 10.20350/digitalCSIC/14000. Available at: http://hdl.handle.net/10261/252461.
Goyens C. Jamet C. Schroeder T. (2013). Evaluation of four atmospheric correction algorithms for MODIS-aqua images over contrasted coastal waters. Remote Sens. Environ. 131, 63–75. doi: 10.1016/j.rse.2012.12.006
Grégoire M. Alvera-Azcarate A. Buga L. Capet A. Constantin S. D’ortenzio F. et al. (2022) EO4SIBS products, ESA, dataset (Zenodo). doi: 10.5281/zenodo.6397224
Grégoire M. Beckers J.-M. (2004). Modeling the nitrogen fluxes in the black Sea using a 3D coupled hydrodynamical-biogeochemical model: transport versus biogeochemical processes, exchanges across the shelf break and comparison of the shelf and deep sea ecodynamics. Biogeosciences 1, 33–61. doi: 10.5194/bg-1-33-2004
Grégoire M. Gilbert D. Oschlies A. Rose K. (2019). What is ocean deoxygenation? In Laffoley D. Baxter J. M. (eds.) (2019) Ocean deoxygenation: Everyone’s problem - Causes, impacts, consequences and solutions, (Gland, Switzerland: IUCN) xxii+562pp. doi: 10.2305/IUCN.CH.2019.13.en
Grégoire M. Lacroix G. (2001). Study of the oxygen budget of the black Sea waters using a 3D coupled hydrodynamical-biogeochemical model. J. Mar. Syst. 31, 175–202. doi: 10.1016/S0924-7963(01)00052-5
Grégoire M. Soetaert K. Nezlin N. P. Kostianoy A. G. (2004). Modeling the nitrogen cycling and plankton productivity in the black Sea using a three-dimensional interdisciplinary model. J. Geophys. Res.-Oceans 109 (C5), C05007. doi: 10.1029/2001JC001014
Groom S. Sathyendranath S. Ban Y. Bernard S. Brewin R. Brotas V. et al. (2019). Satellite ocean colour: current status and future perspective. Front. Mar. Sci. 6, 485. doi: 10.3389/fmars.2019.00485
Kajiyama T. D’Alimonte D. Zibordi G. (2018). Algorithms merging for the determination of chlorophyll-a concentration in the black sea. IEEE Geosci. Remote S. 16, 677–681. doi: 10.1109/LGRS.2018.2883539
Karstensen J. Fiedler B. Schütte F. Brandt P. Körtzinger A. Fischer G. et al. (2015). Open ocean dead zones in the tropical north Atlantic ocean. Biogeosciences 12, 2597–2605. doi: 10.5194/bg-12-2597-2015
Konovalov S. Murray J. (2001). Variations in the chemistry of the black Sea on a time scale of decades, (1960 – 1995). J. Mar. Syst., 31 (1-3), 217–243. doi: 10.1016/S0924-7963(01)00054-9
Kopelevich O. Sheberstov S. Yunev O. Basturk O. Finenko Z. Nikonov S. et al. (2002). Surface chlorophyll in the black Sea over 1978–1986 derived from satellite and in situ data. J. Mar. Syst. 36, 145–160. doi: 10.1016/S0924-7963(02)00184-7
Kubryakova E. Kubryakov A. Mikaelyan A. (2021). Winter coccolithophore blooms in the black Sea: Interannual variability and driving factors. J. Mar. Syst., 213, 103461. doi: 10.1016/j.jmarsys.2020.103461
Kubryakova E. Kubryakov A. Mikaelyan A (2019). Summer and winter coccolithophore blooms in the black Sea and their impact on production of dissolved organic matter from bio-argo data. J. Mar. Syst. 199, 103220. doi: 10.1016/j.jmarsys.2019.103220
Kubryakov A. A. Stanichny S. V. (2015). Seasonal and interannual variability of the black Sea eddies and its dependence on characteristics of the large-scale circulation. Deep Sea Res. Part I: Oceanographic Res. Papers 97, 80–91. doi: 10.1016/j.dsr.2014.12.002
Kubryakov A. Stanichnyi S. (2013). The black Sea level trends from tide gages and satellite altimetry. Russian Meteorology Hydrology 38, 329–333. doi: 10.3103/S1068373913050051
Kurkin A. Kurkina O. Rybin A. Talipova T. (2020). Comparative analysis of the first baroclinic rossby radius in the Baltic, black, Okhotsk, and Mediterranean seas. Russian J. Earth Sci. 20, ES4008. doi: 10.2205/2020ES000737
Legeais J.-F. Meyssignac B. (2021). C3S, Sea level product quality assessment report. D2.SL.2-v2.0_PQAR_of_v2DT2021_SeaLevel_products_v1.0 (Copernicus Climate Change Service & ECMWF). Available at: https://datastore.copernicus-climate.eu/documents/satellite-sea-level/vDT2021/D2.SL.2-v2.0_PQAR_of_v2DT2021_SeaLevel_products_v1.0_APPROVED_Ver1.pdf.
Le Traon P. Nadal F. Ducet N. (1998). An improved mapping method of multisatellite altimeter data. J. Atmos. Ocean. Tech. 15, 522–534. doi: 10.1175/1520-0426(1998)015<0522:AIMMOM>2.0.CO;2
Leymarie E. Penkerc’h C. Vellucci V. Lerebourg C. Antoine D. Boss E. et al. (2018). ProVal: A new autonomous profiling float for high quality radiometric measurements. Front. Mar. Sci. 5, 437. doi: 10.3389/fmars.2018.00437
Martín-Neira M. Oliva R. Corbella I. Torres F. Duffo N. Durán I. et al. (2016). SMOS instrument performance and calibration after six years in orbit. Remote Sens. Environ. 180, 19–39. doi: 10.1016/j.rse.2016.02.036
Mee L. D. Friedrich J. Gomoiu M. T. (2005). Restoring the black Sea in times of uncertainty. Oceanography 18 (2), 32–43. doi: 10.5670/oceanog.2005.45
Meissner T. Wentz F. J. (2004). The complex dielectric constant of pure and sea water from microwave satellite observations. IEEE T. Geosci. Remote 42, 1836–1849. doi: 10.1109/TGRS.2004.831888
Miladinova S. Stips A. Garcia-Gorriz E. Macias Moy D. (2017). Black Sea thermohaline properties: Long-term trends and variations. J. Geophys. Res.-Oceans 122, 5624–5644. doi: 10.1002/2016JC012644
Moore G. Mazeran C. Huot J.-P. (2017) Case II. s bright pixel atmospheric correction. MERIS ATBD 2.6, issue 5.3. (mesotrophic to high turbidity). Available at: https://www.eumetsat.int/website/home/Data/CopernicusServices/Sentinel3Services/OceanColour/index.html.
Moreau T. Cadier E. Boy F. Aublanc J. Rieu P. Raynal M. et al. (2021). High-performance altimeter Doppler processing for measuring sea level height under varying sea state conditions. Adv. Space Res. 67, 1870–1886. doi: 10.1016/j.asr.2020.12.038
Morel A. Bélanger S. (2006). Improved detection of turbid waters from ocean color sensors information. Remote Sens. Environ. 102, 237–249. doi: 10.1016/j.rse.2006.01.022
Morrow R. Fu L-L Farrar T. Seo H. Le Traon P-Y. (2018). Ocean eddies and mesoscale variability. In “Satellite altimetry and its use for earth observation”, in ‘Earth Observation of Global Changes’, in ed. CRC Press.
Mulet S. Rio M.-H. Etienne H. Artana C. Cancet M. Dibarboure G. et al. (2021). The new CNES-CLS18 global mean dynamic topography. Ocean Sci. 17, 789–808. doi: 10.5194/os-17-789-2021
Müller G. Stoffers P. (1974). Mineralogy and petrology of black Sea basin sediments. The Black Sea—Geology, Chemistry, and BiologyDegens E. T. Ross D. A.. doi: 10.1306/M20377C22
Murray J. (1991). Black Sea knorr expedition: Black sea oceanography: results from the 1988 black Sea expedition. Deep Sea Res. II 38 (Supplementary Issue No. 2A), 1266–S1266.
Nechad B. Ruddick K. Neukermans G. (2009). Calibration and validation of a generic multisensory algorithm for mapping of turbidity in coastal waters. Remote Sens. Ocean Sea Ice Large Water Regions 2009 7473, 161–171. doi: 10.1117/12.830700
Nechad B. Ruddick K. G. Park Y. (2010). Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sens. Environ. 114, 854–866. doi: 10.1016/j.rse.2009.11.022
Novoa S. Doxaran D. Ody A. Vanhellemont Q. Lafon V. Lubac B. et al. (2017). Atmospheric corrections and multi-conditional algorithm for multi-sensor remote sensing of suspended particulate matter in low-to-high turbidity levels coastal waters. Remote Sens-Basel 9, 61. doi: 10.3390/rs9010061
Oguz T. Dippner J. W. Kaymaz Z. (2006). Climatic regulation of the black Sea hydro-meteorological and ecological properties at interannual-to-decadal time scales. J. Mar. Syst. 60, 235–254. doi: 10.1016/j.jmarsys.2005.11.011
Oguz T. Ediger D. (2006). Comparision of in situ and satellite-derived chlorophyll pigment concentrations, and impact of phytoplankton bloom on the suboxic layer structure in the western black Sea during may–June 2001. Deep Sea Res. Part II: Topical Stud. Oceanography 53, 17–19. doi: 10.1016/j.dsr2.2006.07.001
Oguz T. La Violette P. E. Unluata U. (1992). The upper layer circulation of the black Sea: Its variability as inferred from hydrographic and satellite observations. J. Geophys. Res.-Oceans 97, 12569–12584. doi: 10.1029/92JC00812
Oliva R. Daganzo E. Richaume P. Kerr Y. Cabot F. Soldo Y. et al. (2016). Status of radio frequency interference (RFI) in the 1400 – 1427 MHz passive band based on six years of SMOS mission. Remote Sens. Environ. 180, 64–75. doi: 10.1016/j.rse.2016.01.013
Olmedo E. González-Gambau V. Turiel A. González-Haro C. García- Espriu A. Grégoire M. et al. (2022). New SMOS SSS maps in the framework of the Earth Observation data For Science and Innovation in the Black Sea. Remote Sens. Environ. doi: 10.5194/essd-2021-364
Olmedo E. González-Haro C. Hoareau N. Umbert M. González- Gambau V. Martínez J. et al. (2021). Nine years of SMOS sea surface salinity global maps at the Barcelona expert center. Earth Syst. Sci. Data discussion 13, 857–888. doi: 10.5194/essd-13-857-2021
Olmedo E. Martínez J. Turiel A. Ballabrera-Poy J. Portabella M. (2017). Debiased non-Bayesian retrieval: A novel approach to SMOS Sea surface salinity. Remote Sens. Environ. 193, 103–126. doi: 10.1016/j.rse.2017.02.023
Olmedo E. Martínez J. Umbert M. Hoareau N. Portabella M. Ballabrera-Poy J. et al. (2016). Improving time and space resolution of SMOS salinity maps using multifractal fusion. Remote Sens. Environ. 180, 246–263. doi: 10.1016/j.rse.2016.02.038
Olmedo E. Taupier-Letage I. Turiel A. Alvera-Azcárate A. (2018). Improving SMOS sea surface salinity in the western Mediterranean Sea through multivariate and multifractal analysis. Remote Sens-Basel 10, 485. doi: 10.3390/rs10030485
Organelli E. Barbieux M. Claustre H. Schmechtig C. Poteau A. Bricaud A. et al. (2017). Two databases derived from BGC-argo float measurements for marine biogeochemical and bio-optical applications. Earth Syst. Sci. Data 9, 861–880. doi: 10.5194/essd-9-861-2017
Palazov A. Ciliberti S. Peneva E. Gregoire M. Staneva J. Lemieux-Dudon B. et al. (2019). Black Sea observing system. Front. Mar. Sci. 6. doi: 10.3389/fmars.2019.00315
Pitcher G. C. Aguirre-Velarde A. Breitburg D. Cardich J. Carstensen J. Conley D. J. et al. (2021). System controls of coastal and open ocean oxygen depletion. Prog. Oceanogr. 197, 102613. doi: 10.1016/j.pocean.2021.102613
Pujol M.-I. Dupuy S. Vergara O. Sánchez-Román A. Faugere Y. Prandi P. et al. (2022). Refining the resolution of DUACS along track (level 3) Sea level products. Earth System Sci. Data Discussion. doi: 10.5194/essd-2022-292
Pujol M.-I. Faugère Y. Taburet G. Dupuy S. Pelloquin C. Ablain M. et al. (2016). DUACS DT2014: the new multi-mission altimeter data set reprocessed over 20 years. Ocean Sci. 12, 1067–1090. doi: 10.5194/os-12-1067-2016
Renosh P. R. Doxaran D. Keukelaere L. D. Gossn J. I. (2020). Evaluation of atmospheric correction algorithms for sentinel-2-MSI and sentinel-3-OLCI in highly turbid estuarine waters. Remote Sens-Basel 12, 1285. doi: 10.3390/rs12081285
Ricour F. Capet A. d’Ortenzio F. Delille B. Grégoire M. (2021). Dynamics of the deep chlorophyll maximum in the black Sea as depicted by BGC-argo floats. Biogeosciences 18, 755–774. doi: 10.5194/bg-18-755-2021
Stanev E. V. (1990). On the mechanisms of the black Sea circulation. Earth-Sci. Rev. 28, 285–319. doi: 10.1016/0012-8252(90)90052-W
Staneva J. V. Dietrich D. E. Stanev E. V. Bowman M. J. (2001). Rim current and coastal eddy mechanisms in an eddy-resolving black Sea general circulation model. J.Mar.Syst 31, 137–157. doi: 10.1016/S0924-7963(01)00050-1
Stanev E. V. Bowman M. J. Peneva E. L. Staneva J. V. (2003). Control of black Sea intermediate water mass formation by dynamics and topography: Comparison of numerical simulations, surveys and satellite data. J. Mar. Res. 61, 59–99. doi: 10.1357/002224003321586417
Stanev E. V. Kandilarov R. (2012). Sediment dynamics in the black Sea: numerical modelling and remote sensing observations. Ocean Dynam. 62, 533–553. doi: 10.1007/s10236-012-0520-1
Stanev E. V. Peneva E. Chtirkova B. (2019). Climate change and regional ocean water mass disappearance: case of the black Sea. J. Geophys. Res.-Oceans 124, 4803–4819. doi: 10.1029/2019JC015076
Steinmetz F. Deschamps P.-Y. Ramon D. (2011). Atmospheric correction in presence of sun glint: application to MERIS. Opt. Express 19, 9783–9800. doi: 10.1364/OE.19.009783
Taburet G. Sanchez-Roman A. Ballarotta M. Pujol M.-I. Legeais J.-F. Fournier F. et al. (2019). DUACS DT2018: 25 years of reprocessed sea level altimetry products. Ocean Sci. 15, 1207–1224. doi: 10.5194/os-15-1207-2019
Umbert M. Hoareau N. Turiel A. Ballabrera-Poy J. (2014). New blending algorithm to synergize ocean variables: The case of SMOS sea surface salinity maps. Remote Sens. Environ. 146, 172–187. doi: 10.1016/j.rse.2013.09.018
Vinogradova N. Lee T. Boutin J. Drushka K. Fournier S. Sabia R. et al. (2019). Satellite salinity observing system: Recent discoveries and the way forward. Front. Mar. Sci. 6. doi: 10.3389/fmars.2019.00243
Volpe G. Santoleri R. Vellucci V. d’Alcalà M. R. Marullo S. d’Ortenzio F. (2007). The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates. Remote Sens. Environ. 107 (4), 625–638. doi: 10.1016/j.rse.2006.10.017
Wijsman J. W. Herman P. M. Gomoiu M.-T. (1999). Spatial distribution in sediment characteristics and benthic activity on the northwestern black Sea shelf. Mar. Ecol. Prog. Ser. 181, 25–39. doi: 10.3354/meps181025
Xing X. Boss E. Zhang J. Chai F. (2020). Evaluation of ocean color remote sensing algorithms for diffuse attenuation coefficients and optical depths with data collected on BGC-argo floats. Remote Sens-Basel 12, 2367. doi: 10.3390/rs12152367
Yu L. (2010). On sea surface salinity skin effect induced by evaporation and implications for remote sensing of ocean salinity. J. Phys. Oceanogr. 40, 85–102. doi: 10.1175/2009JPO4168.1
Yunev O. A. Moncheva S. Carstensen J. (2005). Long-term variability of vertical chlorophyll a and nitrate profiles in the open black Sea: eutrophication and climate change. Mar. Ecol. Prog. Ser. 294, 95–107. doi: 10.3354/meps294095