Articles | Volume 18, issue 5
https://doi.org/10.5194/os-18-1491-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-1491-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Oct 2022
Research article |
| 20 Oct 2022
| 20 Oct 2022
Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods
Georges Baaklini
CORRESPONDING AUTHOR
LOCEAN Laboratory, Sorbonne University, UPMC Univ Paris 06 CNRS-IRD-MNHN, 4 place Jussieu, 75005 Paris, France
National Centre for Marine Sciences-CNRSL, P.O. Box 189, Jounieh, Lebanon
Roy El Hourany
Laboratoire d'Océanologie et de Géosciences, Univ. Littoral Côte d'Opale, Univ. Lille, CNRS, IRD, UMR 8187, LOG, 62930 Wimereux, France
Milad Fakhri
National Centre for Marine Sciences-CNRSL, P.O. Box 189, Jounieh, Lebanon
Julien Brajard
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Leila Issa
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon
Gina Fifani
LOCEAN Laboratory, Sorbonne University, UPMC Univ Paris 06 CNRS-IRD-MNHN, 4 place Jussieu, 75005 Paris, France
National Centre for Marine Sciences-CNRSL, P.O. Box 189, Jounieh, Lebanon
Laurent Mortier
LOCEAN Laboratory, Sorbonne University, UPMC Univ Paris 06 CNRS-IRD-MNHN, 4 place Jussieu, 75005 Paris, France
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Cited articles
Abdalla, S., Kolahchi, A. A., Ablain, M., Adusumilli, S., Bhowmick, S. A.,
Alou-Font, E., Amarouche, L., Andersen, O. B., Antich, H., Aouf, L., and Arbic, B.:
Altimetry for the future: Building on 25 years of progress, Adv. Space
Res., 68, 319–363, 2021. a
Alhoniemi, E., Himberg, J., Parviainen, J., and Vesanto, J.: SOM-Toolbox, Github [code], https://github.com/ilarinieminen/SOM-Toolbox (last access: 25 November 2021), 2012. a
Amitai, Y., Lehahn, Y., Lazar, A., and Heifetz, E.: Surface circulation of the
eastern Mediterranean Levantine basin: Insights from analyzing 14 years of
satellite altimetry data, J. Geophys. Res.-Oceans, 115, C10, https://doi.org/10.1029/2010JC006147, 2010. a, b, c
Amores, A., Jordà, G., and Monserrat, S.: Ocean eddies in the Mediterranean
Sea from satellite altimetry: Sensitivity to satellite track location,
Front. Mar. Sci., 6, 703, https://doi.org/10.3389/fmars.2019.00703, 2019. a, b
Baaklini, G.: SOM-HAC_Levantine_Sea, Github [data set], https://github.com/gbaaklini/SOM-HAC_Levantine_Sea, last access: 19 September 2022. a
Baaklini, G., Issa, L., Fakhri, M., Brajard, J., Fifani, G., Menna, M.,
Taupier-Letage, I., Bosse, A., and Mortier, L.: Blending drifters and
altimetric data to estimate surface currents: Application in the Levantine
Mediterranean and objective validation with different data types, Ocean
Modell., 166, 101850, https://doi.org/10.1016/j.ocemod.2021.101850, 2021. a
Barboni, A., Lazar, A., Stegner, A., and Moschos, E.: Lagrangian eddy tracking reveals the Eratosthenes anticyclonic attractor in the eastern Levantine Basin, Ocean Sci., 17, 1231–1250, https://doi.org/10.5194/os-17-1231-2021, 2021. a
Barceló-Llull, B., Pascual, A., Sánchez-Román, A., Cutolo, E.,
d'Ovidio, F., Fifani, G., Ser-Giacomi, E., Ruiz, S., Mason, E., Cyr, F.,
and Doglioli, A.: Fine-Scale Ocean Currents Derived From in situ Observations in
Anticipation of the Upcoming SWOT Altimetric Mission, Front. Mar. Sci., 8, 1070, https://doi.org/10.3389/fmars.2021.679844, 2021. a
Basterretxea, G., Font-Muñoz, J. S., Salgado-Hernanz, P. M., Arrieta, J.,
and Hernández-Carrasco, I.: Patterns of chlorophyll interannual
variability in Mediterranean biogeographical regions, Remote Sens. Environ., 215, 7–17, 2018. a
Bosch, W., Dettmering, D., and Schwatke, C.: Multi-mission cross-calibration of
satellite altimeters: Constructing a long-term data record for global and
regional sea level change studies, Remote Sens., 6, 2255–2281, 2014. a
CNES/CLS/European Copernicus Marine Service: Ssalto/Duacs multimission altimeter products, Aviso [data set], http://www.aviso.altimetry.fr/duacs/, last access: 20 September 2021. a
d’Ovidio, F., Pascual, A., Wang, J., Doglioli, A. M., Jing, Z., Moreau, S.,
Grégori, G., Swart, S., Speich, S., Cyr, F., and Legresy, B.: Frontiers in
fine-scale in situ studies: Opportunities during the swot fast sampling
phase, Front. Mar. Sci., 6, 168, https://doi.org/10.3389/fmars.2019.00168, 2019. a
El Hourany, R., Abboud-abi Saab, M., Faour, G., Aumont, O., Crépon, M., and
Thiria, S.: Estimation of secondary phytoplankton pigments from satellite
observations using self-organizing maps (SOMs), J. Geophys. Res.-Oceans, 124, 1357–1378, 2019. a
El Hourany, R., Abboud-abi Saab, M., Faour, G., Mejia, C., Crépon, M.,
and Thiria, S.: Phytoplankton diversity in the Mediterranean Sea from
satellite data using self-organizing maps, J. Geophys. Res.-Oceans, 124, 5827–5843, 2019. a
Elsharkawy, M. S., Radwan, A. A., and Sharaf El-Din, S. H.: General
characteristics of current in front of Port Said, Egypt, Egypt. J. Aquat. Res., 43, 123–128, https://doi.org/10.1016/j.ejar.2017.02.001,
2017. a, b
Escudier, R., Mourre, B., Juza, M., and Tintoré, J.: Subsurface circulation
and mesoscale variability in the Algerian subbasin from altimeter-derived
eddy trajectories: Algerian eddies propagation, J. Geophys. Res.-Oceans, 121, 6310–6322, https://doi.org/10.1002/2016JC011760, 2016. a
Fifani, G., Baudena, A., Fakhri, M., Baaklini, G., Faugère, Y., Morrow, R.,
Mortier, L., and d’Ovidio, F.: Drifting Speed of Lagrangian Fronts and Oil
Spill Dispersal at the Ocean Surface, Remote Sens., 13, 4499, https://doi.org/10.3390/rs13224499, 2021. a
Fu, L.-L. and Cazenave, A.: Satellite altimetry and earth sciences: a handbook
of techniques and applications, PhD thesis, Elsevier, ISBN 9780080516585, 2000. a
Gerin, R., Poulain, P.-M., Taupier-Letage, I., Millot, C., Ben Ismail, S., and Sammari, C.: Surface circulation in the Eastern Mediterranean using drifters (2005–2007), Ocean Sci., 5, 559–574, https://doi.org/10.5194/os-5-559-2009, 2009. a, b, c
Gertman, I., Zodiatis, G., Murashkovsky, A., Hayes, D., and Brenner, S.:
Determination of the locations of southeastern Levantine anticyclonic eddies
from CTD data, Rapp. Commun. Int. Mer. Mediterr, 38, p. 151, 2007. a
Hamlington, B., Leben, R., Strassburg, M., Nerem, R., and Kim, K.-Y.:
Contribution of the Pacific Decadal Oscillation to global mean sea level
trends, Geophys. Res. Lett., 40, 5171–5175, 2013. a
Horton, C., Kerling, J., Athey, G., Schmitz, J., and Clifford, M.: Airborne
expendable bathythermograph surveys of the eastern Mediterranean, J. Geophys. Res.-Oceans, 99, 9891–9905, 1994. a
International Hydrographic Organization (IHO) and the Intergovernmental Oceanographic Commission (IOC): The General Bathymetric Chart of the Oceans, GEBCO [data set], https://download.gebco.net/ (last access: 10 December 2022),
2022. a
Ioannou, A., Stegner, A., Le Vu, B., Taupier-Letage, I., and Speich, S.:
Dynamical evolution of intense Ierapetra eddies on a 22 year long period,
J. Geophys. Res.-Oceans, 122, 9276–9298, 2017. a
Issa, L., Brajard, J., Fakhri, M., Hayes, D., Mortier, L., and Poulain, P.-M.:
Modelling surface currents in the Eastern Levantine Mediterranean using
surface drifters and satellite altimetry, Ocean Modell., 104, 1–14, 2016. a
Kalinić, H., Mihanović, H., Cosoli, S., Tudor, M., and Vilibić, I.:
Predicting ocean surface currents using numerical weather prediction model
and Kohonen neural network: a northern Adriatic study, Neur. Comput. Appl., 28, 611–620, 2017. a
Larnicol, G., Ayoub, N., and Le Traon, P.-Y.: Major changes in Mediterranean
Sea level variability from 7 years of TOPEX/Poseidon and ERS-1/2 data,
J. Mar. Syst., 33, 63–89, 2002. a
Lehahn, Y., d'Ovidio, F., Lévy, M., and Heifetz, E.: Stirring of the northeast
Atlantic spring bloom: A Lagrangian analysis based on multisatellite
data, J. Geophys. Res., 112, C08005,
https://doi.org/10.1029/2006JC003927, 2007. a
Liu, Y., Weisberg, R. H., and Shay, L. K.: Current patterns on the West Florida
Shelf from joint self-organizing map analyses of HF radar and ADCP data,
J. Atmos. Ocean. Tech., 24, 702–712, 2007. a
Manzella, G., Cardin, V., Cruzado, A., Fusco, G., Gacic, M., Galli, C.,
Gasparini, G., Gervais, T., Kovacevic, V., Millot, C., and DeLa Villeon, L. P.: EU-sponsored
effort improves monitoring of circulation variability in the Mediterranean,
Eos, Transactions American Geophysical Union, 82, 497–504, 2001. a
Martínez-Moreno, J., Hogg, A. M., England, M. H., Constantinou, N. C.,
Kiss, A. E., and Morrison, A. K.: Global changes in oceanic mesoscale
currents over the satellite altimetry record, Nat. Clim. Change, 11,
397–403, 2021. a
Matteoda, A. M. and Glenn, S. M.: Observations of recurrent mesoscale eddies in
the eastern Mediterranean, J. Geophys. Res.-Oceans, 101,
20687–20709, 1996. a
Mau, J.-C., Wang, D.-P., Ullman, D. S., and Codiga, D. L.: Characterizing Long
Island Sound outflows from HF radar using self-organizing maps, Estuar.
Coast. Shelf Sci., 74, 155–165, 2007. a
Mauri, E., Sitz, L., Gerin, R., Poulain, P.-M., Hayes, D., and Gildor, H.: On
the variability of the circulation and water mass properties in the Eastern
Levantine Sea between September 2016–August 2017, Water, 11, 1741, https://doi.org/10.3390/w11091741, 2019. a, b, c
Menna, M., Gerin, R., Bussani, A., and Poulain, P.-M.: db_med24_nc_1986_2016_kri05, National Oceanographic
Data Centre [data set], https://doi.org/10.6092/7a8499bc-c5ee-472c-b8b5-03523d1e73e9, last access: 23 April 2020. a
Mihanović, H., Cosoli, S., Vilibić, I., Ivanković, D., Dadić,
V., and Gačić, M.: Surface current patterns in the northern
Adriatic extracted from high-frequency radar data using self-organizing map
analysis, J. Geophys. Res.-Oceans, 116, C8, https://doi.org/10.1029/2011JC007104, 2011. a
Millot, C. and Gerin, R.: The Mid-Mediterranean Jet Artefact, Geophys. Res. Lett., 37, 12, https://doi.org/10.1029/2010GL043359, 2010. a, b
Morrow, R., Fu, L.-L., Ardhuin, F., Benkiran, M., Chapron, B., Cosme, E.,
d’Ovidio, F., Farrar, J. T., Gille, S. T., Lapeyre, G., et al.: Global
observations of fine-scale ocean surface topography with the Surface Water
and Ocean Topography (SWOT) mission, Front. Mar. Sci., 6, 232, https://doi.org/10.3389/fmars.2019.00232,
2019. a
Özsoy, E., Hecht, A., Ünlüata, Ü., Brenner, S., Oǧuz, T.,
Bishop, J., Latif, M., and Rozentraub, Z.: A review of the Levantine Basin
circulation and its variability during 1985–1988, Dynam. Atmos. Ocean., 15, 421–456, 1991. a
Pascual, A., Faugère, Y., Larnicol, G., and Le Traon, P.-Y.: Improved
description of the ocean mesoscale variability by combining four satellite
altimeters, Geophys. Res. Lett., 33, 2, https://doi.org/10.1029/2005GL024633, 2006. a
Poulain, P.-M., Menna, M., and Mauri, E.: Surface geostrophic circulation of
the Mediterranean Sea derived from drifter and satellite altimeter data,
J. Phys. Ocean., 42, 973–990, 2012. a
Randriamihamison, N., Vialaneix, N., and Neuvial, P.: Applicability and
interpretability of Ward’s hierarchical agglomerative clustering with or
without contiguity constraints, J. Classif., 38, 363–389,
2021. a
Ren, L., Chu, N., Hu, Z., and Hartnett, M.: Investigations into Synoptic
Spatiotemporal Characteristics of Coastal Upper Ocean Circulation Using High
Frequency Radar Data and Model Output, Remote Sens., 12, 2841, https://doi.org/10.3390/rs12172841, 2020. a
Richardson, A. J., Risien, C., and Shillington, F. A.: Using self-organizing
maps to identify patterns in satellite imagery, Prog. Ocean., 59,
223–239, 2003. a
Rio, M.-H., Poulain, P.-M., Pascual, A., Mauri, E., Larnicol, G., and
Santoleri, R.: A mean dynamic topography of the Mediterranean Sea computed
from altimetric data, in-situ measurements and a general circulation model,
J. Mar. Syst., 65, 484–508, 2007. a
Taupier-Letage, I., Puillat, I., Raimbault, P., and Millot, C.: Biological
response to mesoscale eddies in the Algerian Basin, J. Geophys. Res.,
108, 3245–3267, https://doi.org/10.1029/1999JC000117, 2003. a
Willis, J. K.: Can in situ floats and satellite altimeters detect long-term
changes in Atlantic Ocean overturning?, Geophys. Res. Lett., 37, 6, https://doi.org/10.1029/2010GL042372,
2010. a
Wolfe, C. L. and Cenedese, C.: Laboratory experiments on eddy generation by a
buoyant coastal current flowing over variable bathymetry, J. Phys. Ocean., 36, 395–411, 2006. a
Zervakis, V., Papadoniou, G., Tziavos, C., and Lascaratos, A.: Seasonal variability and geostrophic circulation in the eastern Mediterranean as revealed through a repeated XBT transect, Ann. Geophys., 21, 33–47, https://doi.org/10.5194/angeo-21-33-2003, 2003. a
Zodiatis, G., Lardner, R., Lascaratos, A., Georgiou, G., Korres, G., and Syrimis, M.: High resolution nested model for the Cyprus, NE Levantine Basin, eastern Mediterranean Sea: implementation and climatological runs, Ann. Geophys., 21, 221–236, https://doi.org/10.5194/angeo-21-221-2003, 2003. a
Zodiatis, G., Drakopoulos, P., Brenner, S., and Groom, S.: Variability of the
Cyprus warm core Eddy during the CYCLOPS project, Deep Sea Res. Pt. II, 52, 2897–2910, 2005. a
Short summary
We use machine learning to analyze the long-term variation of the surface currents in the Levantine Sea, located in the eastern Mediterranean Sea. We decompose the circulation into groups based on their physical characteristics and analyze their spatial and temporal variability. We show that most structures of the Levantine Sea are becoming more energetic over time, despite those of the western area remaining the most dominant due to their complex bathymetry and strong currents.
We use machine learning to analyze the long-term variation of the surface currents in the...
