{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T01:13:57Z","timestamp":1768526037569,"version":"3.49.0"},"reference-count":65,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T00:00:00Z","timestamp":1574640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"North Atlantic Treaty Organization Allied Command Transformation","award":["SAC000807"],"award-info":[{"award-number":["SAC000807"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Exploiting the potential of space-borne oceanic measurements to characterize the sub-surface structure of the ocean becomes critical in areas where deployment of in situ sensors might be difficult or expensive. Sea Surface Temperature (SST) observations potentially provide enormous amounts of information about the upper ocean variability. However, the assimilation of daytime SST retrievals, e.g., from infrared sensors into ocean prediction systems, requires a specific treatment of the diurnal cycle of skin SST, which is generally under-estimated in current ocean models due to poor vertical resolution at the air\u2013sea interface and lack of proper parameterizations. To this end, a simple off-line bias correction scheme is proposed, where the bias predictors include, among others, the warm layer and cool skin warming\/cooling deduced from a prognostic model. Furthermore, a localization procedure that limits the vertical penetration of the SST information in a hybrid variational-ensemble data assimilation system is formulated. These two novelties are implemented and assessed within a regional ocean prediction system in the Ligurian Sea for the assimilation of daytime SST data retrieved with hourly frequency from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary satellite Meteosat-10. Experiments are validated against independent measurements collected by gliders, moorings, and drifters during the Long-term Glider Missions for Environmental Characterization (LOGCMEC17) sea trial. Results suggest that the simple bias correction scheme is effective in improving both the sea surface and mixed layer accuracy, correctly thinning the mixed layer compared to the control experiment, outperforming experiments with night-only data assimilation, and improving the forecast skill scores. Localization further improves the prediction of the mixed layer depth. It is therefore recommended that sophisticated bias correction and localization procedures are adopted for fruitfully assimilating daytime SST data in operational oceanographic analysis systems.<\/jats:p>","DOI":"10.3390\/rs11232776","type":"journal-article","created":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T11:12:21Z","timestamp":1574680341000},"page":"2776","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Optimal Assimilation of Daytime SST Retrievals from SEVIRI in a Regional Ocean Prediction System"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3856-8905","authenticated-orcid":false,"given":"Andrea","family":"Storto","sequence":"first","affiliation":[{"name":"Centre for Maritime Research and Experimentation (CMRE), I-19126 La Spezia, Italy"}]},{"given":"Paolo","family":"Oddo","sequence":"additional","affiliation":[{"name":"Centre for Maritime Research and Experimentation (CMRE), I-19126 La Spezia, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Schiller, A., and Brassington, G.B. (2011). Satellites and Operational Oceanography. Operational Oceanography in the 21st Century, Springer.","DOI":"10.1007\/978-94-007-0332-2"},{"key":"ref_2","first-page":"s63","article-title":"Assessing the impact of observations on ocean forecasts and reanalyses: Part 2, Regional applications","volume":"8","author":"Oke","year":"2015","journal-title":"J. Oper. Oceanogr."},{"key":"ref_3","first-page":"s189","article-title":"The current status of the real-time in situ Global Ocean Observing System for operational oceanography","volume":"8","author":"Legler","year":"2015","journal-title":"J. Oper. Oceanogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1007\/s10236-017-1056-1","article-title":"Assimilation of high-resolution sea surface temperature data into an operational nowcast\/forecast system around Japan using a multi-scale three-dimensional variational scheme","volume":"67","author":"Miyazawa","year":"2017","journal-title":"Ocean Dyn."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1007\/s00376-018-7284-6","article-title":"Assimilation of sea surface temperature in a global Hybrid Coordinate","volume":"35","author":"Chen","year":"2018","journal-title":"Ocean Model. Adv. Atmos. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"525","DOI":"10.5194\/os-14-525-2018","article-title":"Assimilating high-resolution sea surface temperature data improves the ocean forecast potential in the Baltic Sea","volume":"14","author":"Liu","year":"2018","journal-title":"Ocean Sci."},{"key":"ref_7","first-page":"C07033","article-title":"Evaluating the sonic layer depth relative to themixed layer depth","volume":"113","author":"Helber","year":"2008","journal-title":"J. Geophys. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1002\/qj.2388","article-title":"Implementing a variational data assimilation system in an operational 1\/4 degree global ocean model","volume":"141","author":"Waters","year":"2015","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"679","DOI":"10.5194\/essd-8-679-2016","article-title":"C-GLORSv5: An improved multipurpose global ocean eddy-permitting physical reanalysis","volume":"8","author":"Storto","year":"2016","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Marullo, S., Santoleri, R., Ciani, D., le Borgne, P., P\u00e9r\u00e9, S., Pinardi, N., Tonani, M., and Nardone, G. (2014). Combining model and geostationary satellite data to reconstruct hourly SST field over the Mediterranean Sea. Remote Sens. Environ., 146.","DOI":"10.1016\/j.rse.2013.11.001"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1140","DOI":"10.1029\/2002GL016291","article-title":"Diurnal signals in satellite sea surface temperature measurements","volume":"30","author":"Gentemann","year":"2003","journal-title":"Geophys. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8351","DOI":"10.1002\/2016JC012192","article-title":"The diurnal cycle of sea-surface temperature and estimation of the heat budget of the Mediterranean Sea","volume":"121","author":"Marullo","year":"2016","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_13","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_14","unstructured":"(2019, November 19). GHRSST. Available online: https:\/\/www.ghrsst.org\/ghrsst-data-services\/products."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1002\/qj.3036","article-title":"An operational analysis system for the global diurnal cycle of sea surface temperature: Implementation and validation","volume":"143","author":"While","year":"2017","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1002\/qj.2988","article-title":"Assimilation for skin SST in the NASA GEOS atmospheric data assimilation system","volume":"143","author":"Akella","year":"2017","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1002\/2017JC013186","article-title":"Evaluation of NASA GEOS-ADAS modeled diurnal warming through comparisons to SEVIRI and AMSR2 SST observations","volume":"123","author":"Gentemann","year":"2018","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Korres, G., Denaxa, D., Jansen, E., Mirouze, I., Pimentel, S., Tse, W.H., and Storto, A. (2019). Assimilation of SST data in the POSEIDON system using the SOSSTA statistical-dynamical observation operator. Ocean Sci. Discuss.","DOI":"10.5194\/os-2018-158"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Jansen, E., Pimentel, S., Tse, W.H., Denaxa, D., Korres, G., Mirouze, I., and Storto, A. (2019). Using Canonical Correlation Analysis to produce dynamically-based highly-efficient statistical observation operators. Ocean Sci., 1023\u20131032.","DOI":"10.5194\/os-15-1023-2019"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Storto, A., Oddo, P., Cozzani, E., and Coelho, E.F. (2019). Introducing along-track error correlations for altimetry data in a regional ocean prediction system. J. Atmos. Ocean. Technol.","DOI":"10.1175\/JTECH-D-18-0213.1"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.5194\/os-12-1137-2016","article-title":"A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models","volume":"12","author":"Oddo","year":"2016","journal-title":"Ocean Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.ocemod.2018.06.005","article-title":"Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation","volume":"128","author":"Storto","year":"2018","journal-title":"Ocean Model."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Storto, A., Falchetti, S., Oddo, P., Jiang, Y.M., and Tesei, A. (2019). Assessing the Impact of Different Ocean Analysis Schemes On Oceanic and Underwater Acoustic Predictions. J. Geophys. Res. Ocean., in review.","DOI":"10.1029\/2019JC015636"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.ocemod.2008.01.004","article-title":"An oceanographic three-dimensional assimilation scheme","volume":"22","author":"Dobricic","year":"2008","journal-title":"Ocean Model."},{"key":"ref_25","unstructured":"Madec, G., and the NEMO team (2012). NEMO Ocean Engine, Institut Pierre-Simon Laplace. Note du Pole de mod\u00e9lisation."},{"key":"ref_26","unstructured":"Large, W.G., and Yeager, S. (2004). Diurnal to Decadal Global Forcing for Ocean and Sea-Ice Models: The Data Sets And Flux Climatologies, CGD Division of the National Center for Atmospheric Research. NCAR Technical Note, NCAR\/TN-460+STR."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3001","DOI":"10.5194\/gmd-7-3001-2014","article-title":"Sensitivity of the Mediterranean sea level to atmospheric pressure and free surface elevation numerical formulation in NEMO","volume":"7","author":"Oddo","year":"2014","journal-title":"Geosci. Model Dev."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1002\/2015EA000107","article-title":"A new digital bathymetric model of the world\u2019s oceans","volume":"2","author":"Weatherall","year":"2015","journal-title":"Earth Space Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1007\/s10236-006-0082-1","article-title":"Impact of partial steps and momentum advection schemes in a global circulation model at eddy permitting resolution","volume":"56","author":"Barnier","year":"2006","journal-title":"Ocean Dyn."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1007\/s00382-006-0200-2","article-title":"Biophysical feedbacks on the tropical pacific climate in a coupled general circulation model","volume":"28","author":"Lengaigne","year":"2007","journal-title":"Clim. Dyn."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"869","DOI":"10.5194\/os-8-869-2012","article-title":"The Mediterranean Ocean Colour Observing System\u2014System development and product validation","volume":"8","author":"Volpe","year":"2012","journal-title":"Ocean Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1256","DOI":"10.1175\/1520-0493(1996)124<1256:DAUIAU>2.0.CO;2","article-title":"Data Assimilation Using Incremental Analysis Updates","volume":"124","author":"Bloom","year":"1996","journal-title":"Mon. Weather Rev."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4707","DOI":"10.1080\/01431160500166128","article-title":"MSG\/SEVIRI cloud mask and type from SAFNWC","volume":"26","author":"Derrien","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.rse.2008.10.012","article-title":"Sea surface temperature from a geostationary satellite by optimal estimation","volume":"113","author":"Merchant","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_35","first-page":"C05011","article-title":"A diurnal-cycle resolving sea surface temperature product for the tropical Atlantic","volume":"115","author":"Marullo","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.rse.2010.08.004","article-title":"Estimation of sea Surface Temperature from the SEVIRI, improved using numerical weather prediction","volume":"115","author":"Roquet","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_37","unstructured":"OSI-SAF (2019, February 25). Geostationary Sea Surface Temperature Product User Manual, Document SAF\/OSI\/CDOP3\/MF\/TEC\/MA\/181. Available online: http:\/\/www.osi-saf.org\/lml\/doc\/osisaf_cdop2_ss1_pum_geo_sst.pdf."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1175\/1520-0442(2002)015<0353:TIVOSS>2.0.CO;2","article-title":"Toward improved and validation of satellite and sea surface and skin temperature and measurements and for climate and research","volume":"15","author":"Donlon","year":"2002","journal-title":"J. Clim."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"L04601","DOI":"10.1029\/2007GL033071","article-title":"Diurnal warm-layer events in the western Mediterranean and European shelf seas","volume":"35","author":"Merchant","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"745","DOI":"10.5194\/os-10-745-2014","article-title":"Characterisation and quantification of regional diurnal SST cycles from SEVIRI","volume":"10","author":"Karagali","year":"2014","journal-title":"Ocean Sci."},{"key":"ref_41","first-page":"C06009","article-title":"Refinements to a prognostic scheme of sea surface skin temperature","volume":"115","author":"Takaya","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1978","DOI":"10.1029\/2000JC000452","article-title":"Role of surface fluxes in ocean general circulation models using satellite sea surface temperature: Validation of and sensitivity to the forcing frequency of the Mediterranean thermohaline circulation","volume":"107","author":"Artale","year":"2002","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1175\/1520-0469(1967)024<0269:TTATOA>2.0.CO;2","article-title":"The temperature at the ocean-air interface","volume":"24","author":"Saunders","year":"1967","journal-title":"J. Atmos. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"L14605","DOI":"10.1029\/2005GL023030","article-title":"A prognostic scheme of sea surface skin temperature for modeling and data assimilation","volume":"32","author":"Zeng","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"L22602","DOI":"10.1029\/2005GL024252","article-title":"Cool-skin simulation by a one-column ocean model","volume":"32","author":"Tu","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_46","first-page":"1453","article-title":"A satellite radiance-bias correction scheme for data assimilation","volume":"127","author":"Harris","year":"2001","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_47","first-page":"237","article-title":"A New Bias Correction Scheme for Assimilating GPS Zenith Tropospheric Delay Estimates","volume":"114","author":"Storto","year":"2010","journal-title":"Idojaras"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1002\/qj.56","article-title":"Adaptive bias correction for satellite data in a numerical weather prediction system","volume":"133","author":"McNally","year":"2007","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2284","DOI":"10.1002\/qj.2819","article-title":"Observation bias correction schemes in data assimilation systems: A theoretical study of some of their properties","volume":"142","author":"Eyre","year":"2016","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Schroeder, L.D., Sjoquist, D.L., and Stephan, P.E. (1986). Understanding Regression Analysis, Sage Publications.","DOI":"10.4135\/9781412986410"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1002\/qj.145","article-title":"An objective approach to modelling biases in satellite radiances: Application to AIRS and AMSU-A","volume":"133","year":"2007","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.rse.2010.02.023","article-title":"Operational sea surface temperature bias adjustment using AATSR data","volume":"116","author":"Marsouin","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Draper, N.R., and Smith, H. (1998). Applied Regression Analysis, Wiley-Interscience.","DOI":"10.1002\/9781118625590"},{"key":"ref_54","unstructured":"Kutner, M.H., Nachtsheim, C.J., and Neter, J. (2004). Applied Linear Regression Models, McGraw-Hill Irwin. [4th ed.]."},{"key":"ref_55","first-page":"211","article-title":"Sparse Bayesian Learning and the Relevance Vector Machine","volume":"1","author":"Tipping","year":"2001","journal-title":"J. Mach. Learn. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v011.i09","article-title":"Kernlab\u2014An S4 Package for Kernel Methods in R","volume":"11","author":"Karatzoglou","year":"2004","journal-title":"J. Stat. Softw."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1256\/qj.04.15","article-title":"Ensemble-derived stationary and flow-dependent background-error covariances: Evaluation in a quasi-operational NWP setting","volume":"131","author":"Buehner","year":"2005","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1175\/MWR3282.1","article-title":"On the theoretical equivalence of differently proposed ensemble-3DVAR hybrid analysis schemes","volume":"135","author":"Wang","year":"2007","journal-title":"Mon. Weather Rev."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1175\/2007JTECHO558.1","article-title":"Representation error of oceanic observations for data assimilation","volume":"25","author":"Oke","year":"2008","journal-title":"J. Atmos. Oceanic Technol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.ocemod.2007.11.002","article-title":"The Bluelink ocean data assimilation system (BODAS)","volume":"21","author":"Oke","year":"2008","journal-title":"Ocean Model."},{"key":"ref_61","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":"Nardelli","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"211","DOI":"10.2151\/jmsj1965.75.1B_211","article-title":"Variational methods","volume":"75","author":"Courtier","year":"1997","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1016\/j.ocemod.2016.06.011","article-title":"Variational quality control of hydrographic profile data with non-Gaussian errors for global ocean variational data assimilation systems","volume":"104","author":"Storto","year":"2016","journal-title":"Ocean Model."},{"key":"ref_64","unstructured":"Fofonoff, N.P., and Millard, R.C. Algorithms for Computation of Fundamental Properties of Seawater. Available online: https:\/\/unesdoc.unesco.org\/ark:\/48223\/pf0000059832."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1137\/0916069","article-title":"A Limited Memory Algorithm for Bound Constrained Optimization","volume":"16","author":"Byrd","year":"1995","journal-title":"SIAM J. Sci. Comput."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/23\/2776\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:37:22Z","timestamp":1760189842000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/23\/2776"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,25]]},"references-count":65,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2019,12]]}},"alternative-id":["rs11232776"],"URL":"https:\/\/doi.org\/10.3390\/rs11232776","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,25]]}}}