{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T15:47:23Z","timestamp":1771688843571,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T00:00:00Z","timestamp":1623974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000128147\/19\/I-DT"],"award-info":[{"award-number":["4000128147\/19\/I-DT"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Measuring the ocean surface currents at high spatio-temporal resolutions is crucial for scientific and socio-economic applications. Since the early 1990s, the synoptic and global-scale monitoring of the ocean surface currents has been provided by constellations of radar altimeters. By construction, altimeter constellations provide only the geostrophic component of the marine surface currents. In addition, given the effective spatial-temporal resolution of the altimeter-derived products (O (100 km) and O (10 days), respectively), only the largest ocean mesoscale features can be resolved. In order to enhance the altimeter system capabilities, we propose a synergistic use of high resolution sea surface Chlorophyll observations (Chl) and altimeter-derived currents\u2019 estimates. The study is focused on the Mediterranean Sea, where the most energetic signals are found at spatio-temporal scales up to 10 km and a few days. The proposed method allows for inferring the marine surface currents from the evolution of the Chl field, relying on altimeter-derived currents as a first-guess estimate. The feasibility of this approach is tested through an Observing System Simulation Experiment, starting from biogeochemical model outputs distributed by the European Copernicus Marine Service. Statistical analyses based on the 2017 daily data showed that our approach can improve the altimeter-derived currents accuracy up to 50%, also enhancing their effective spatial resolution up to 30 km. Moreover, the retrieved currents exhibit larger temporal variability than the altimeter estimates over annual to weekly timescales. Our method is mainly limited to areas\/time periods where\/when Chl gradients are larger and are modulated by the marine currents\u2019 advection. Its application is thus more efficient when the surface Chl evolution is not dominated by the biological activity, mostly occurring in the mid-February to mid-March time window in the Mediterranean Sea. Preliminary tests on the method applicability to satellite-derived data are also presented and discussed.<\/jats:p>","DOI":"10.3390\/rs13122389","type":"journal-article","created":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T11:19:20Z","timestamp":1624015160000},"page":"2389","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Ocean Currents Reconstruction from a Combination of Altimeter and Ocean Colour Data: A Feasibility Study"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8767-4379","authenticated-orcid":false,"given":"Daniele","family":"Ciani","sequence":"first","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}]},{"given":"Elodie","family":"Charles","sequence":"additional","affiliation":[{"name":"Collecte Localisation Satellites (CLS), 31520 Ramonville St-Agne, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3416-7189","authenticated-orcid":false,"given":"Bruno","family":"Buongiorno Nardelli","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 80133 Naples, Italy"}]},{"given":"Marie-H\u00e9l\u00e8ne","family":"Rio","sequence":"additional","affiliation":[{"name":"European Space Agency, European Space Research Institute (ESA-ESRIN), 00044 Frascati, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2900-5054","authenticated-orcid":false,"given":"Rosalia","family":"Santoleri","sequence":"additional","affiliation":[{"name":"Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine (CNR-ISMAR), 00133 Rome, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,18]]},"reference":[{"key":"ref_1","unstructured":"Robinson, I.S. (2004). Measuring the Oceans from Space: The Principles and Methods of Satellite Oceanography, Springer."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/0011-7471(76)90001-2","article-title":"A technique for objective analysis and design of oceanographic experiments applied to MODE-73","volume":"23","author":"Bretherton","year":"1976","journal-title":"Deep Sea Res. Oceanogr. Abstr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1175\/1520-0426(1998)015<0522:AIMMOM>2.0.CO;2","article-title":"An improved mapping method of multisatellite altimeter data","volume":"15","author":"Nadal","year":"1998","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2010.10.017","article-title":"The operational sea surface temperature and sea ice analysis (OSTIA) system","volume":"116","author":"Donlon","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1175\/1520-0442(1994)007<0929:IGSSTA>2.0.CO;2","article-title":"Improved global sea surface temperature analyses using optimum interpolation","volume":"7","author":"Reynolds","year":"1994","journal-title":"J. Clim."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1583","DOI":"10.1175\/JTECH-D-13-00241.1","article-title":"Spatial optimal interpolation of Aquarius sea surface salinity: Algorithms and implementation in the North Atlantic","volume":"31","author":"Melnichenko","year":"2014","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1175\/JTECH-D-11-00099.1","article-title":"A novel approach for the high-resolution interpolation of in situ sea surface salinity","volume":"29","year":"2012","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2012.10.012","article-title":"High and Ultra-High resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project","volume":"129","author":"Tronconi","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"84","DOI":"10.3389\/fmars.2018.00084","article-title":"A New Global Sea Surface Salinity and Density Dataset From Multivariate Observations (1993\u20132016)","volume":"5","author":"Droghei","year":"2018","journal-title":"Front. Mar. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1175\/1520-0426(2003)020<1839:ECADFF>2.0.CO;2","article-title":"EOF calculations and data filling from incomplete oceanographic datasets","volume":"20","author":"Beckers","year":"2003","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.rse.2011.09.020","article-title":"Seasonal to interannual phytoplankton response to physical processes in the Mediterranean Sea from satellite observations","volume":"117","author":"Volpe","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6156513","DOI":"10.1155\/2016\/6156513","article-title":"Neural networks technique for filling gaps in satellite measurements: Application to ocean color observations","volume":"2016","author":"Krasnopolsky","year":"2016","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1029\/2018MS001472","article-title":"Applications of deep learning to ocean data inference and subgrid parameterization","volume":"11","author":"Bolton","year":"2019","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.5194\/gmd-13-1609-2020","article-title":"DINCAE 1.0: A convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations","volume":"13","author":"Barth","year":"2020","journal-title":"Geosci. Model Dev."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.rse.2018.10.029","article-title":"Evaluation of GlobCurrent surface ocean current products: A case study in Australia","volume":"220","author":"Cancet","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2827","DOI":"10.1002\/2013JC009710","article-title":"Evaluation of altimetry-derived surface current products using Lagrangian drifter trajectories in the eastern Gulf of Mexico","volume":"119","author":"Liu","year":"2014","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1175\/JTECH-D-12-00032.1","article-title":"Using high-resolution altimetry to observe mesoscale signals","volume":"29","author":"Pujol","year":"2012","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.5194\/os-12-1067-2016","article-title":"DUACS DT2014: The new multi-mission altimeter data set reprocessed over 20 years","volume":"12","author":"Pujol","year":"2016","journal-title":"Ocean Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Pascual, A., Faug\u00e8re, Y., Larnicol, G., and Le Traon, P.Y. (2006). Improved description of the ocean mesoscale variability by combining four satellite altimeters. Geophys. Res. Lett., 33.","DOI":"10.1029\/2005GL024633"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.5194\/os-15-1207-2019","article-title":"DUACS DT2018: 25 years of reprocessed sea level altimetry products","volume":"15","author":"Taburet","year":"2019","journal-title":"Ocean Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.5194\/os-15-1091-2019","article-title":"On the resolutions of ocean altimetry maps","volume":"15","author":"Ballarotta","year":"2019","journal-title":"Ocean Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1029\/2008EO480003","article-title":"Observing oceanic submesoscale processes from space","volume":"89","author":"Fu","year":"2008","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1175\/JTECH-D-14-00152.1","article-title":"Dynamic interpolation of sea surface height and potential applications for future high-resolution altimetry mapping","volume":"32","author":"Ubelmann","year":"2015","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.1175\/JTECH-D-20-0030.1","article-title":"Dynamic Mapping of Along-Track Ocean Altimetry: Performance from Real Observations","volume":"37","author":"Ballarotta","year":"2020","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.asr.2019.12.024","article-title":"Synergy between surface drifters and altimetry to increase the accuracy of sea level anomaly and geostrophic current maps in the Gulf of Mexico","volume":"68","author":"Mulet","year":"2020","journal-title":"Adv. Space Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3693","DOI":"10.1016\/j.apm.2008.12.006","article-title":"A simple method for computing velocities from tracer observations and a model output","volume":"33","author":"Piterbarg","year":"2009","journal-title":"Appl. Math. Model."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2769","DOI":"10.1175\/JTECH-D-16-0017.1","article-title":"Improving the Altimeter-Derived Surface Currents Using High-Resolution Sea Surface Temperature Data: A Feasability Study Based on Model Outputs","volume":"33","author":"Rio","year":"2016","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1016\/j.rse.2018.06.003","article-title":"Improved global surface currents from the merging of altimetry and Sea Surface Temperature data","volume":"216","author":"Rio","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ciani, D., Rio, M.H., Menna, M., and Santoleri, R. (2019). A Synergetic Approach for the Space-Based Sea Surface Currents Retrieval in the Mediterranean Sea. Remote Sens., 11.","DOI":"10.3390\/rs11111285"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Menna, M., Poulain, P.M., Ciani, D., Doglioli, A., Notarstefano, G., Gerin, R., Rio, M.H., Santoleri, R., Gauci, A., and Drago, A. (2019). New insights of the Sicily Channel and southern Tyrrhenian Sea variability. Water, 11.","DOI":"10.3390\/w11071355"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ciani, D., Rio, M.H., Nardelli, B.B., Etienne, H., and Santoleri, R. (2020). Improving the Altimeter-Derived Surface Currents Using Sea Surface Temperature (SST) Data: A Sensitivity Study to SST Products. Remote Sens., 12.","DOI":"10.3390\/rs12101601"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6993","DOI":"10.1002\/2016JC011814","article-title":"Estimation of ocean surface currents from maximum cross correlation applied to GOCI geostationary satellite remote sensing data over the Tsushima (Korea) Straits","volume":"121","author":"Warren","year":"2016","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Li, G., He, Y., Liu, G., Zhang, Y., Hu, C., and Perrie, W. (2020). Multi-Sensor Observations of Submesoscale Eddies in Coastal Regions. Remote Sens., 12.","DOI":"10.3390\/rs12040711"},{"key":"ref_34","first-page":"91","article-title":"Evolution of the Loop Current system during the Deepwater Horizon oil spill event as observed with drifters and satellites","volume":"195","author":"Liu","year":"2011","journal-title":"Monit. Model. Deep. Horiz. Oil Spill Rec.-Break. Enterp. Geophys. Monogr. Ser."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1002\/2012GB004518","article-title":"The influence of mesoscale and submesoscale heterogeneity on ocean biogeochemical reactions","volume":"27","author":"Levy","year":"2013","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"281","DOI":"10.5194\/os-10-281-2014","article-title":"Physical forcing and physical\/biochemical variability of the Mediterranean Sea: A review of unresolved issues and directions of future research","volume":"10","year":"2014","journal-title":"Ocean Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"139","DOI":"10.5194\/bg-6-139-2009","article-title":"On the trophic regimes of the Mediterranean Sea: A satellite analysis","volume":"6","year":"2009","journal-title":"Biogeosciences"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1901","DOI":"10.5194\/bg-13-1901-2016","article-title":"Interannual variability of the Mediterranean trophic regimes from ocean color satellites","volume":"13","author":"Mayot","year":"2016","journal-title":"Biogeosciences"},{"key":"ref_39","unstructured":"Clementi, E., Pistoia, J., Escudier, R., Delrosso, D., Drudi, M., Grandi, A., Lecci, R., Cret\u00ed, S., Ciliberti, S.A., and Coppini, G. (2019). Mediterranean Sea Analysis and Forecast (CMEMS MED-Currents EAS5 System) [Data Set], Copernicus Monitoring Environment Marine Service (CMEMS)."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"217","DOI":"10.5194\/bg-9-217-2012","article-title":"Seasonal and inter-annual variability of plankton chlorophyll and primary production in the Mediterranean Sea: A modelling approach","volume":"9","author":"Lazzari","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.dsr.2015.12.006","article-title":"Spatial variability of phosphate and nitrate in the Mediterranean Sea: A modeling approach","volume":"108","author":"Lazzari","year":"2016","journal-title":"Deep Sea Res. Part I Oceanogr. Res. Pap."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.5194\/gmd-10-1423-2017","article-title":"Development of BFMCOUPLER (v1.0), the coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations","volume":"10","author":"Cossarini","year":"2017","journal-title":"Geosci. Model Dev."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Carr\u00e8re, L., and Lyard, F. (2003). Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing-comparisons with observations. Geophys. Res. Lett., 30.","DOI":"10.1029\/2002GL016473"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1175\/JTECH-D-15-0160.1","article-title":"The challenge of using future SWOT data for oceanic field reconstruction","volume":"33","author":"Gaultier","year":"2016","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.4319\/lo.1989.34.8.1545","article-title":"Surface pigments, algal biomass profiles, and potential production of the euphotic layer: Relationships reinvestigated in view of remote-sensing applications","volume":"34","author":"Morel","year":"1989","journal-title":"Limnol. Oceanogr."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1321","DOI":"10.5194\/bg-16-1321-2019","article-title":"Bio-optical characterization of subsurface chlorophyll maxima in the Mediterranean Sea from a Biogeochemical-Argo float database","volume":"16","author":"Barbieux","year":"2019","journal-title":"Biogeosciences"},{"key":"ref_47","unstructured":"Vichi, M., Lovato, T., Mlot, E.G., and McKiver, W. (2015). Coupling BFM with Ocean Models, Nucleus for the European Modelling of the Ocean, Release 1.0, BFM."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5999","DOI":"10.1029\/2019JC015034","article-title":"Effects of oceanic mesoscale and submesoscale frontal processes on the vertical transport of phytoplankton","volume":"124","author":"Ruiz","year":"2019","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5609","DOI":"10.1002\/jgrc.20345","article-title":"Vortex waves and vertical motion in a mesoscale cyclonic eddy","volume":"118","year":"2013","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.rse.2015.12.052","article-title":"Multi-dimensional interpolation of SMOS sea surface salinity with surface temperature and in situ salinity data","volume":"180","author":"Nardelli","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Vallis, G.K. (2006). Atmospheric and Oceanic Fluid Dynamics, Cambridge University Press.","DOI":"10.1017\/CBO9780511790447"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.measurement.2018.05.022","article-title":"Detecting the drogue presence of SVP drifters from wind slippage in the Mediterranean Sea","volume":"125","author":"Menna","year":"2018","journal-title":"Measurement"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1146\/annurev-marine-010816-060641","article-title":"Advances in the application of surface drifters","volume":"9","author":"Lumpkin","year":"2017","journal-title":"Annu. Rev. Mar. Sci."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Claustre, H., Bishop, J., Boss, E., Bernard, S., Berthon, J.F., Coatanoan, C., Johnson, K., Lotiker, A., Ulloa, O., and Perry, M.J. (2009, January 21\u201325). Bio-optical profiling floats as new observational tools for biogeochemical and ecosystem studies: Potential synergies with ocean color remote sensing. Proceedings of the OceanObs\u201909: Sustained Ocean Observations and Information for Society, Venice, Italy.","DOI":"10.5270\/OceanObs09.cwp.17"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"4274","DOI":"10.1364\/OE.382029","article-title":"Correcting non-photochemical quenching of Saildrone chlorophyll-a fluorescence for evaluation of satellite ocean color retrievals","volume":"28","author":"Scott","year":"2020","journal-title":"Opt. Express"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/12\/2389\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:18:40Z","timestamp":1760163520000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/12\/2389"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,18]]},"references-count":55,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["rs13122389"],"URL":"https:\/\/doi.org\/10.3390\/rs13122389","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,18]]}}}