Articles | Volume 13, issue 5
https://doi.org/10.5194/os-13-799-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-13-799-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Surface drifters in the German Bight: model validation considering windage and Stokes drift
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Nikolaus Groll
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Jochen Horstmann
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Hartmut Kapitza
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Holger Klein
Federal Maritime and Hydrographic Agency (BSH), Bernhard-Nocht-Str. 78, 20359 Hamburg, Germany
Silvia Maßmann
Federal Maritime and Hydrographic Agency (BSH), Bernhard-Nocht-Str. 78, 20359 Hamburg, Germany
Fabian Schwichtenberg
Federal Maritime and Hydrographic Agency (BSH), Bernhard-Nocht-Str. 78, 20359 Hamburg, Germany
Related authors
Ulrich Callies
Ocean Sci., 17, 527–541, https://doi.org/10.5194/os-17-527-2021, https://doi.org/10.5194/os-17-527-2021, 2021
Short summary
Short summary
An analysis of simulated German Bight surface currents reveals linear structures along which water bodies of different origin converge. Identification of these non-stationary structures supports the interpretation of monitoring data; observations gathered at stations that are neighbouring but separated by a line of convergence may substantially differ. The analysis could also be helpful for organizing field campaigns such that new observations do not just duplicate information already available.
Onur Kerimoglu, Yoana G. Voynova, Fatemeh Chegini, Holger Brix, Ulrich Callies, Richard Hofmeister, Knut Klingbeil, Corinna Schrum, and Justus E. E. van Beusekom
Biogeosciences, 17, 5097–5127, https://doi.org/10.5194/bg-17-5097-2020, https://doi.org/10.5194/bg-17-5097-2020, 2020
Short summary
Short summary
In this study, using extensive field observations and a numerical model, we analyzed the physical and biogeochemical structure of a coastal system following an extreme flood event. Our results suggest that a number of anomalous observations were driven by a co-occurrence of peculiar meteorological conditions and increased riverine discharges. Our results call for attention to the combined effects of hydrological and meteorological extremes that are anticipated to increase in frequency.
Ulrich Callies, Ruben Carrasco, Jens Floeter, Jochen Horstmann, and Markus Quante
Ocean Sci., 15, 865–889, https://doi.org/10.5194/os-15-865-2019, https://doi.org/10.5194/os-15-865-2019, 2019
Short summary
Short summary
We analyse how surface drifters separate after being released as pairs or triplets in close proximity to wind farms. There is some tentative evidence that these drifters experience turbulent flows arising from an interaction between tidal currents and wind turbine towers. However, more comprehensive studies would be needed to clearly distinguish such wind-farm-related effects from the effects of turbulence that naturally occurs in a complex coastal environment.
Nikolaus Groll, Lidia Gaslikova, and Ralf Weisse
EGUsphere, https://doi.org/10.5194/egusphere-2024-2664, https://doi.org/10.5194/egusphere-2024-2664, 2024
Short summary
Short summary
In recent years, the western Baltic Sea has experienced severe storm surges. By analysing the individual contributions and the total water level, these events can be put into a climate perspective. It was found that individual contributions were not exceptional in all events and no clear trend can be identified, often the combination of the individual contributions leads to the extreme events of recent years. This points to the importance of analysing composite events.
Ulrich Callies
Ocean Sci., 17, 527–541, https://doi.org/10.5194/os-17-527-2021, https://doi.org/10.5194/os-17-527-2021, 2021
Short summary
Short summary
An analysis of simulated German Bight surface currents reveals linear structures along which water bodies of different origin converge. Identification of these non-stationary structures supports the interpretation of monitoring data; observations gathered at stations that are neighbouring but separated by a line of convergence may substantially differ. The analysis could also be helpful for organizing field campaigns such that new observations do not just duplicate information already available.
Onur Kerimoglu, Yoana G. Voynova, Fatemeh Chegini, Holger Brix, Ulrich Callies, Richard Hofmeister, Knut Klingbeil, Corinna Schrum, and Justus E. E. van Beusekom
Biogeosciences, 17, 5097–5127, https://doi.org/10.5194/bg-17-5097-2020, https://doi.org/10.5194/bg-17-5097-2020, 2020
Short summary
Short summary
In this study, using extensive field observations and a numerical model, we analyzed the physical and biogeochemical structure of a coastal system following an extreme flood event. Our results suggest that a number of anomalous observations were driven by a co-occurrence of peculiar meteorological conditions and increased riverine discharges. Our results call for attention to the combined effects of hydrological and meteorological extremes that are anticipated to increase in frequency.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford B. Hooker, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Hubert Loisel, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 11, 1037–1068, https://doi.org/10.5194/essd-11-1037-2019, https://doi.org/10.5194/essd-11-1037-2019, 2019
Short summary
Short summary
A compiled set of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2018) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Ulrich Callies, Ruben Carrasco, Jens Floeter, Jochen Horstmann, and Markus Quante
Ocean Sci., 15, 865–889, https://doi.org/10.5194/os-15-865-2019, https://doi.org/10.5194/os-15-865-2019, 2019
Short summary
Short summary
We analyse how surface drifters separate after being released as pairs or triplets in close proximity to wind farms. There is some tentative evidence that these drifters experience turbulent flows arising from an interaction between tidal currents and wind turbine towers. However, more comprehensive studies would be needed to clearly distinguish such wind-farm-related effects from the effects of turbulence that naturally occurs in a complex coastal environment.
Nikolaus Groll and Ralf Weisse
Earth Syst. Sci. Data, 9, 955–968, https://doi.org/10.5194/essd-9-955-2017, https://doi.org/10.5194/essd-9-955-2017, 2017
Short summary
Short summary
A wave hindcast for the North Sea covering the period 1949–2014 using the third-generation spectral wave model WAM was produced. The hindcast is part of the coastDat database representing a consistent and homogeneous met-ocean data set. It is shown that, despite not being perfect, data from the wave hindcast are generally suitable for wave climate analysis.
Burkard Baschek, Friedhelm Schroeder, Holger Brix, Rolf Riethmüller, Thomas H. Badewien, Gisbert Breitbach, Bernd Brügge, Franciscus Colijn, Roland Doerffer, Christiane Eschenbach, Jana Friedrich, Philipp Fischer, Stefan Garthe, Jochen Horstmann, Hajo Krasemann, Katja Metfies, Lucas Merckelbach, Nino Ohle, Wilhelm Petersen, Daniel Pröfrock, Rüdiger Röttgers, Michael Schlüter, Jan Schulz, Johannes Schulz-Stellenfleth, Emil Stanev, Joanna Staneva, Christian Winter, Kai Wirtz, Jochen Wollschläger, Oliver Zielinski, and Friedwart Ziemer
Ocean Sci., 13, 379–410, https://doi.org/10.5194/os-13-379-2017, https://doi.org/10.5194/os-13-379-2017, 2017
Short summary
Short summary
The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the heavily used German Bight in the North Sea. The automated observing and modelling system is designed to monitor real-time conditions, to provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change.
Ruben Carrasco, Michael Streßer, and Jochen Horstmann
Ocean Sci., 13, 95–103, https://doi.org/10.5194/os-13-95-2017, https://doi.org/10.5194/os-13-95-2017, 2017
Short summary
Short summary
The significant wave height (Hs) is one of the most relevant parameters to describe a sea state statistically. This parameter is commonly monitored by measurement devices placed in the water (wave rider buoy, ADCP), which require expensive maintenance. In this study, X-band radar, generally used for ship navigation, was modified to measure water particle speeds using the Doppler effect. Based on the obtained data, a simple method is introduced to remotely estimate Hs with a reasonable accuracy.
Cited articles
Ardhuin, F., Marié, L., Rascle, N., Forget, P., and Roland, A.: Observation and estimation of Lagrangian, Stokes and Eulerian currents induced by wind and waves at the sea surface, J. Phys. Oceanogr., 39, 2820–2838, 2009.
Barron, C. N., Smedstad, L. F., Dastugue, J. M., and Smedstad, O. M.: Evaluation of ocean models using observed and simulated drifter trajectories: Impact of sea surface height on synthetic profiles for data assimilation, J. Geophys. Res., 112, C07019, https://doi.org/10.1029/2006JC003982, 2007.
Beron-Vera, F. J. and LaCasce, J. H.: Statistics of simulated and observed pair separations in the Gulf of Mexico, J. Phys. Oceanogr., 46, 2183–2199, https://doi.org/10.1175/JPO-D-15-0127.1, 2016.
Brandt, G., Wehrmann, A., and Wirtz, K. W.: Rapid invasion of Crassostrea gigas into the German Wadden Sea dominated by larval supply, J. Sea Res., 59, 279–296, 2008.
Breivik, Ø. and Allen, A. A.: An operational search and rescue model for the Norwegian Sea and the North Sea, J. Marine Syst., 69, 99–113, 2008.
Breivik, Ø., Allen, A. A., Maisondieu, C., and Olagnon, M.: Advances in search and rescue at sea, Ocean Dynam., 63, 83–88, 2013.
Breivik, Ø., Bidlot, J.-R., and Janssen, P. A. E. M.: A Stokes drift approximation based on the Phillips spectrum, Ocean Model., 100, 49–56, 2016.
Broström, G., Carrasco, A., Hole, L. R., Dick, S., Janssen, F., Mattsson, J., and Berger, S.: Usefulness of high resolution coastal models for operational oil spill forecast: the “Full City” accident, Ocean Sci., 7, 805–820, https://doi.org/10.5194/os-7-805-2011, 2011.
Callies, U.: coastDat-2 Hydrodynamic Model TRIM-NP Principal Component Analysis Residual Currents, World Data Center for Climate, https://doi.org/10.1594/WDCC/TRIM-NP-2d-PCA_ResCurr, 2016.
Callies, U., Plüß, A., Kappenberg, J., and Kapitza, H.: Particle tracking in the vicinity of Helgoland, North Sea: a model comparison, Ocean Dynam., 61, 2121–2139, 2011.
Callies, U., Gaslikova, L., Kapitza, H., and Scharfe, M.: German Bight residual current variability on a daily basis: principal components of multi-decadal barotropic simulations, Geo-Mar. Lett., 37, 151–162, https://doi.org/10.1007/s00367-016-0466-2, 2017.
Carrasco, R. and Horstmann, J.: German Bight surface drifter data from Heincke cruise HE 445, 2015, https://doi.org/10.1594/PANGAEA.874511, 2017.
Casulli, V. and Stelling, G.: Numerical simulation of 3D quasi-hydrostatic, free-surface flows, J. Hydraul. Eng., 124, 678–686, 1998.
Coelho, E. F., Hogan, P., Jacobs, G., Thoppil, P., Huntley, H. S., Haus, B. K., Lipphardt Jr., B. L., Kirwan Jr., A. D., Ryan, E. H., Olascoaga, J., Beron-Vera, F., Poje, A. C., Griffa, A., Özgökmen, T. M., Mariano, A. J., Novelli, G., Haza, A. C., Bogucki, D., Chen, S. S., Curcic, M., Iskandarani, M., Judt, F., Laxague, N., Renier, A. J. H. M., Valle-Levinson, A., and Wei, M.: Ocean current estimation using a Multi-Model Ensemble Kalman Filter during the Grand Lagrangian Deployment experiment (GLAD), Ocean Model., 87, 86–106, 2015.
Daewel, U., Schrum, C., and Gupta, A. K.: The predictive potential of early life stage individual-based models (IBMs): an example for Atlantic cod Gadus morhua in the North Sea, Mar. Ecol.-Prog. Ser., 534, 199–219, 2015.
De Dominicis, M., Leuzzi, G., Pinardi, N., and Poulain, P.-M.: Eddy diffusivity derived from drifter data for dispersion model applications, Ocean Dynam., 62, 1381–1398, 2012.
Dick, S., Kleine, E., Müller-Navarra, S., Klein, H., and Komo, H.: The operational circulation model of BSH (BSHcmod), Model description and validation, Tech. Rep. 29/2001, BSH, 2001.
Dick, S., Kleine, E., and Janssen, F.: A new operational circulation model for the North Sea and Baltic Sea using a novel vertical co-oordinate setup and first results, in: Coastal to Global Operational Oceanography: Achievements and Challenges. Proceedings of the Fifth International Conference on EuroGOOS, 20–22 May 2008, Exeter, UK, edited by: Dalhin, H., Bell, M. J., Flemming, N. C., and Petersen, S. E., 2008.
Döös, K., Rupolo, V., and Brodeau, L.: Dispersion of surface drifters and model-simulated trajectories, Ocean Model., 39, 301–310, 2011.
Drivdal, M., Broström, G., and Christensen, K. H.: Wave-induced mixing and transport of buoyant particles: application to the Statfjord A oil spill, Ocean Sci., 10, 977–991, https://doi.org/10.5194/os-10-977-2014, 2014.
Edwards, K. P., Werner, F. E., and Blanton, B. O.: Comparison of observed and modeled drifter trajectories in coastal regions: an improvement through adjustments for observed drifter slip and errors in wind fields, J. Atmos. Ocean. Tech., 23, 1614–1620, 2006.
Garraffo, Z. D., Mariano, A. J., Griffa, A., Veneziani, C., and Chassignet, E. P.: Lagrangian data in a high-resolution numerical simulation of the North Atlantic, J. Marine Syst., 29, 157–176, 2001.
Gästgifvars, M., Lauri, H., Sarkanen, A., Myrberg, K., Andrejev, O., and Ambjörn, C.: Modelling surface drifting of buoys during a rapidly-moving weather front in the Gulf of Finland, Baltic Sea, Estuar. Coast. Shelf S., 70, 567–576, 2006.
Geyer, B.: High-resolution atmospheric reconstruction for Europe 1948–2012: coastDat2, Earth Syst. Sci. Data, 6, 147–164, https://doi.org/10.5194/essd-6-147-2014, 2014.
Groll, N. and Weisse, R.: A multi-decadal wind-wave hindcast for the North Sea 19492014: coastDat2, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2017-36, in review, 2017.
Hasselmann, K.: Wave driven inertial oscillations, Geophys. Fluid Dyn., 1, 463–502, https://doi.org/10.1080/03091927009365783, 1970.
Havens, H., Luther, M. E., Meyers, S. D., and Heil, C. A.: Lagrangian particle tracking of a toxic dinoflagellate bloom within the Tampa Bay estuary, Mar. Pollut. Bull., 60, 2233–2241, 2010.
Horstmann, J., Schlick, T., Cysewski, M., Perthun, P., Stell, J., Boedewadt, J., Helzel, T., Seemann, J., Ziemer, F., Gurgel, K.-W., Meywerk, J., and Breitbach, G.: Sea surface current deduced from Doppler-shift of high-frequency radar backscatter, 2010-10-29 to 2016-12-31, https://doi.org/10.1594/PANGAEA.876437, 2017.
Hufnagl, M., Payne, M., Lacroix, G., Bolle, L. J., Daewel, U., Dickey-Collas, M., Gerkema, T., Huret, M., Janssen, F., Kreus, M., Pätsch, J., Pohlmann, T., Ruardij, P., Schrum, C., Skogen, M. D., Tiessen, M. C., Petitgas, P., van Beek, J. K., van der Veer, H. W., and Callies, U.: Variation that can be expected when using particle tracking models in connectivity studies, J. Sea Res., https://doi.org/10.1016/j.seares.2017.04.009, in press, 2017.
Huhn, F., von Kameke, A., Allen-Perkins, S., Montero, P., Venancio, A., and Pérez-Muñuzuri, V.: Horizontal Lagrangian transport in a tidal-driven estuary – Transport barriers attached to prominent coastal boundaries, Cont. Shelf Res., 39–40, 1–13, 2012.
Huntley, H. S., Lipphardt Jr., B. L., and Kirwan Jr., A. D.: Lagrangian predictability assessed in the East China Sea, Ocean Model., 36, 163–178, https://doi.org/10.1016/j.ocemod.2010.11.001, 2011.
Kapitza, H.: MOPS – a morphodynamical prediciton system on cluster computers, in: High performance computing for computational science, in: VECPAR 2008, 8th International Conference, Toulouse, France, June 2008, edited by: Laginha, J., Palma, M., Amestoy, P., Dayde, M., Mattoso, M., and Lopez, J., 63–68, Springer, Heidelberg, Berlin, New York, 2008.
Kistler, R., Kalnay, E., Collins, W., Saha, S., White, G., Woollen, J., Chelliah, M., Ebisuzaki, W., Kanamitsu, M., Kousky, V., van den Dool, H., Jenne, R., and Fiorino, M.: The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation, B. Am. Meteorol. Soc., 82, 247–267, 2001.
Kjellsson, J. and Döös, K.: Surface drifters and model trajectories in the Baltic Sea, Boreal Environ. Res., 17, 447–459, 2012.
Komen, G. J., Cavaleri, L., Hasselmann, H., Hasselmann, S., and Janssen, P. A. E. M.: Dynamics and Modelling of Ocean Waves, Cambridge University Press, Cambridge, UK, 1996.
Koszalka, I., LaCasce, J. H., and Orvik, K. A.: Relative dispersion in the Nordic Seas, J. Mar. Res., 16, 431–447, 2009.
Li, Q., Fox-Kemper, B., Breivik, Ø., and Webb, A.: Statistical models of global Langmuir mixing, Ocean Model., 113, 95–114, 2017.
Lyard, F., Lefevre, F., Letellier, T., and Francis, O.: Modelling the global ocean tides: modern insights from FES2004, Ocean Dynam., 56, 394–415, 2006.
Mariano, A. J., Griffa, A., Özgökmen, T. M., and Zambianchi, E.: Lagrangian analysis and predictability of coastal and ocean dynamics 2000, J. Atmos. Ocean. Tech., 19, 1114–1126, 2002.
Maßmann, S., Janssen, F., Brüning, T., Kleine, E., Komo, H., Menzenhauer-Schumacher, I., and Dick, S.: An operational oil drift forecasting system for German coastal waters, Die Küste, 81, 255–271, 2014.
Nicolle, A., Dumas, F., Foveau, A., Foucher, E., and Thiébaut, E.: Modelling larval dispersal of the king scallop (Pecten maximus) in the English Channel: examples from the bay of Saint-Brieuc and the bay of Seine, Ocean Dynam., 63, 661–678, 2013.
Niiler, P. P., Johnson, W. R., and Baturin, N.: Surface Current and Lagrangian-drift Program, Tech. rep., U. S. Dept. of the Interior, Minerals Management Service, 1997.
Ohlmann, J. C., LaCasce, J. H., Washburn, L., Mariano, A. J., and Emery, B.: Relative dispersion observations and trajectory modelling in the Santa Barbara Channel, J. Geophys. Res., 117, 1–14, 2012.
Olascoaga, M. J., Beron-Vera, F. J., Haller, G., J.Triñanes, Iskandarani, M., Coelho, E. F., Haus, B. K., Huntley, H. S., Jacobs, G., Kirwan Jr., A. D., Lipphardt Jr., B. L., Özgökmen, T. M., Reniers, A. J. H. M., and Valle-Levinson, A.: Drifter motion in the Gulf of Mexico constrained by altimetric Lagrangian coherent structures, Geophys. Res. Lett., 40, 6171–6175, https://doi.org/10.1002/2013GL058624, 2013.
Pätsch, J., Burchard, H., Dieterich, C., Gräwe, U., Gröger, M., Mathis, M., Kapitza, H., Bersch, M., Moll, A., Pohlmann, T., Su, J., Ho-Hagemann, H. T. M., Schulz, A., Elizalde, A., and Eden, C.: An evaluation of the North Sea circulation in global and regional models relevant for ecosystem simulations, Ocean Model., 116, 70–95, https://doi.org/10.1016/j.ocemod.2017.06.005, 2017.
Peacock, T. and Haller, G.: Lagrangian coherent structures: The hidden skeleton of fluid flows, Phys. Today, 66, 41–47, 2013.
Perrie, W., Tang, C. L., Hu, Y., and DeTracy, B. M.: The impact of waves on surface currents, J. Phys. Oceanogr., 33, 2126–2140, 2003.
Polton, J. A., Lewis, D. M., and Belcher, S. E.: The role of wave-induced Coriolis-Stokes forcing on the wind-driven mixed layer, J. Phys. Oceanogr., 35, 444–457, 2005.
Port, A., Gurgel, K.-W., Staneva, J., Schulz-Stellenfleth, J., and Stanev, E. V.: Tidal and wind-driven surface currents in the German Bight: HFR observations versus model simulations, Ocean Dynam., 61, 1567–1585, 2011.
Poulain, P.-M., Gerin, R., Mauri, E., and Pennel, R.: Wind effects on drogued and undrogued drifters in the Eastern Mediterranean, J. Atmos. Ocean. Tech., 26, 1144–1156, 2009.
Price, J. M., Reed, M., Howard, M. K., Johnson, W. R., Ji, Z.-G., Marshall, C. F., Guinasso Jr., N. L., and Rainey, G. B.: Preliminary assessment of an oil-spill trajectory model using satellite-tracked, oil-spill-simulating drifters, Environ. Modell. Softw., 21, 258–270, 2006.
Puls, W., Pohlmann, T., and Sündermann, J.: Suspended particulate matter in the Southern North Sea: application of a numerical model to extend NERC North Sea Project data interpretation, Dt. hydrogr. Z., 49, 307–327, 1997.
Robins, P. E., Neill, S. P., Giménez, L., Jenkons, S. R., and Malham, S. K.: Physical and biological controls on larval dispersal and connectivity in a highly energetic shelf sea, Limnol. Oceanogr., 58, 505–524, 2013.
Röhrs, J. and Christensen, K. H.: Drift in the uppermost part of the ocean, Geophys. Res. Lett., 42, 10,349–10,356, https://doi.org/10.1002/2015GL066733, 2015.
Röhrs, J., Christensen, K. H., Hole, L. R., Broström, G., Drivdal, M., and Sundby, S.: Observation-based evaluation of surface wave effects on currents and trajectory forecasts, Ocean Dynam., 62, 1519–1533, 2012.
Sansón, L. Z., Pérez-Brunius, P., and Sheinbaum, J.: Surface relative dispersion in the Southwestern Gulf of Mexico, J. Phys. Oceanogr., 47, 387–403, https://doi.org/10.1175/JPO-D-16-0105.1, 2017.
Schönfeld, W.: Numerical Simulation of the dispersion of artificial radionuclides in the English Channel and the North Sea, J. Marine Syst., 6, 529–544, 1995.
Schulz, J.-P., and Schättler, U.: Kurze Beschreibung des Lokal-Modells Europa COSMO-EU (LME) und seiner Datenbanken auf dem Datenserver des DWD, available at: https://www.dwd.de/SharedDocs/downloads/DE/modelldokumentationen/nwv/cosmo_eu/cosmo_eu_dbbeschr_201406.pdf?__blob=publicationFile&v=3 (last access: 12 September 2017), 2014.
Semedo, A., Vettor, R., Breivik, Ø., Sterl, A., Reistad, M., Soares, C. G., and Lima, D.: The wind sea and swell waves climate in the Nordic Seas, Ocean Dynam., 65, 223–240, https://doi.org/10.1007/s10236-014-0788-4, 2015.
Sentchev, A. and Korotenko, K.: Dispersion processes and transport pattern in the ROFI system of the Eastern English Channel derived from a particle-tracking model, Cont. Shelf Res., 25, 2294–2308, 2005.
Shadden, S. C., Lekien, F., Paduan, J. D., Chavez, F. P., and Marsden, J. E.: The correlation between surface drifters and coherent structures based on high-frequency radar data in Monterey Bay, Deep-Sea Res. Pt. II, 56, 161–172, 2009.
Smith, J. A.: Wave-current interactions in finite depth, J. Phys. Oceanogr., 36, 1403–1419, 2006.
Smith, S. and Banke, E.: Variation of the sea surface drag coefficient with wind speed, Q. J. Roy. Meteor. Soc., 101, 665–673, 1975.
Sobey, R. J. and Barker, C. H.: Wave-driven transport of surface oil, J. Coastal Res., 13, 490–496, 1997.
Staneva, J., Alari, V., Breivik, Ø., Bidlot, J.-R., and Mogensen, K.: Effects of wave-induced forcing on a circulation model of the North Sea, Ocean Dynam., 67, 81–101, https://doi.org/10.1007/s10236-016-1009-0, 2017.
Tang, C. L., Perrie, W., Jenkins, A. D., DeTracey, B. M., Hu, Y., Toulany, B., and Smith, P. C.: Observation and modeling of surface currents on the Grand Banks: A study of the wave effects on surface currents, J. Geophys. Res., 112, C10025, 1–16, 2007.
Ullman, D. S., O'Donnell, J., Kohut, J., Fake, T., and Allen, A.: Trajectory prediction using HF radar surface currents: Monte Carlo simulations of prediction uncertainties, J. Geophys. Res., 111, C12005, https://doi.org/10.1029/2006JC003715, 2006.
von Storch, H. and Zwiers, F. W.: Statistical Analysis in Climate Research, Cambridge University Press, Cambridge, UK, 1999.
von Storch, H., Langenberg, H., and Feser, F.: A spectral nudging technique for dynamical downscaling purposes, Mon. Weather Rev., 128, 3664–3673, 2000.
WAMDI-Group: The WAM model – a third generation ocean wave prediction model, J. Phys. Oceanogr., 18, 1775–1810, 1988.
Short summary
Six surface drifters were tracked in the inner German Bight for between 9 and 54 days. Corresponding simulations were conducted based on currents from two hydrodynamic models. Effects of including either a direct wind drag or simulated Stokes drift were similar during most of the time. Results suggest that main sources of simulation errors were inaccurate Eulerian currents and lacking representation of sub-grid-scale processes. Substantial model errors often occurred under low wind conditions.
Six surface drifters were tracked in the inner German Bight for between 9 and 54 days....