Articles | Volume 14, issue 6
https://doi.org/10.5194/os-14-1503-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-14-1503-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Dec 2018
Research article |
| 07 Dec 2018
| 07 Dec 2018
Synergy of wind wave model simulations and satellite observations during extreme events
Anne Wiese
CORRESPONDING AUTHOR
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
Joanna Staneva
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
Johannes Schulz-Stellenfleth
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
Arno Behrens
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
Luciana Fenoglio-Marc
Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany
Jean-Raymond Bidlot
European Centre for Medium-Range Weather Forecasts, Reading, UK
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Jérôme Benveniste, Salvatore Dinardo, Luciana Fenoglio-Marc, Christopher Buchhaupt, Michele Scagliola, Marcello Passaro, Karina Nielsen, Marco Restano, Américo Ambrózio, Giovanni Sabatino, Carla Orrù, and Beniamino Abis
Proc. IAHS, 385, 457–463, https://doi.org/10.5194/piahs-385-457-2024, https://doi.org/10.5194/piahs-385-457-2024, 2024
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This paper presents the RDSAR, SAR/SARin & FF-SAR altimetry processors available in the ESA Altimetry Virtual Lab (AVL) hosted on the EarthConsole® platform. An overview on processors and features as well as preliminary analyses using AVL output data are reported to demonstrate the quality of the ESA Altimetry Virtual Lab altimetry services in providing innovative solutions to the radar altimetry community. https://earthconsole.eu//
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Alexei Koldunov, Tobias Kölling, Josh Kousal, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Domokos Sármány, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
EGUsphere, https://doi.org/10.5194/egusphere-2024-913, https://doi.org/10.5194/egusphere-2024-913, 2024
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale"), and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Roderik S. W. van de Wal, Angélique Melet, Debora Bellafiore, Michalis Vousdoukas, Paula Camus, Christian Ferrarin, Gualbert Oude Essink, Ivan D. Haigh, Piero Lionello, Arjen Luijendijk, Alexandra Toimil, and Joanna Staneva
State Planet Discuss., https://doi.org/10.5194/sp-2023-38, https://doi.org/10.5194/sp-2023-38, 2023
Revised manuscript under review for SP
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Sea level rise has major impacts in Europe which vary from place to place and in time depending on the source of the impacts. Flooding, erosion and saltwater intrusion lead via different pathways to various consequences in coastal regions across Europe. It causes damage to assets, environment and people for all three categories of impacts discussed in this paper. The paper provides an overview of the various impacts in Europe.
Carolina B. Gramcianinov, Joanna Staneva, Celia R. G. Souza, Priscila Linhares, Ricardo de Camargo, and Pedro L. da Silva Dias
State Planet, 1-osr7, 12, https://doi.org/10.5194/sp-1-osr7-12-2023, https://doi.org/10.5194/sp-1-osr7-12-2023, 2023
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We analyse extreme wave event trends in the south-western South Atlantic in the last 29 years using wave products and coastal hazard records. The results show important regional changes associated with increased mean sea wave height, wave period, and wave power. We also find a rise in the number of coastal hazards related to waves affecting the state of São Paulo, Brazil, which partially agrees with the increase in extreme waves in the adjacent ocean sector but is also driven by local factors.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Wei Chen and Joanna Staneva
State Planet Discuss., https://doi.org/10.5194/sp-2023-33, https://doi.org/10.5194/sp-2023-33, 2023
Revised manuscript accepted for SP
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Marine heatwaves (MHWs), which are the unusually warm periods in the ocean, are becoming more frequent and lasting longer in the North West European Shelf (NWES), particularly near the coast, from 1993 to 2023. However, thermal stratification is weakening, implying that the sea surface warming caused by MHWs is insufficient to counteract the overall stratification decline due to global warming. Moreover, the varying salinity has a notable impact on the trend of density stratification change.
Kathrin Wahle, Emil V. Stanev, and Joanna Staneva
Nat. Hazards Earth Syst. Sci., 23, 415–428, https://doi.org/10.5194/nhess-23-415-2023, https://doi.org/10.5194/nhess-23-415-2023, 2023
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Knowledge of what causes maximum water levels is often key in coastal management. Processes, such as storm surge and atmospheric forcing, alter the predicted tide. Whilst most of these processes are modeled in present-day ocean forecasting, there is still a need for a better understanding of situations where modeled and observed water levels deviate from each other. Here, we will use machine learning to detect such anomalies within a network of sea-level observations in the North Sea.
Wei Chen, Joanna Staneva, Sebastian Grayek, Johannes Schulz-Stellenfleth, and Jens Greinert
Nat. Hazards Earth Syst. Sci., 22, 1683–1698, https://doi.org/10.5194/nhess-22-1683-2022, https://doi.org/10.5194/nhess-22-1683-2022, 2022
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This study links the occurrence and persistence of density stratification in the southern North Sea to the increased number of extreme marine heat waves. The study further identified the role of the cold spells at the early stage of a year to the intensity of thermal stratification in summer. In a broader context, the research will have fundamental significance for further discussion of the secondary effects of heat wave events, such as in ecosystems, fisheries, and sediment dynamics.
Guillaume Dodet, Jean-François Piolle, Yves Quilfen, Saleh Abdalla, Mickaël Accensi, Fabrice Ardhuin, Ellis Ash, Jean-Raymond Bidlot, Christine Gommenginger, Gwendal Marechal, Marcello Passaro, Graham Quartly, Justin Stopa, Ben Timmermans, Ian Young, Paolo Cipollini, and Craig Donlon
Earth Syst. Sci. Data, 12, 1929–1951, https://doi.org/10.5194/essd-12-1929-2020, https://doi.org/10.5194/essd-12-1929-2020, 2020
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Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent. The CCI is a program of the European Space Agency, whose objective is to realize the full potential of global Earth Observation archives in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset.
Astrid Lampert, Konrad Bärfuss, Andreas Platis, Simon Siedersleben, Bughsin Djath, Beatriz Cañadillas, Robert Hunger, Rudolf Hankers, Mark Bitter, Thomas Feuerle, Helmut Schulz, Thomas Rausch, Maik Angermann, Alexander Schwithal, Jens Bange, Johannes Schulz-Stellenfleth, Thomas Neumann, and Stefan Emeis
Earth Syst. Sci. Data, 12, 935–946, https://doi.org/10.5194/essd-12-935-2020, https://doi.org/10.5194/essd-12-935-2020, 2020
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With the research aircraft Do-128 of TU Braunschweig, meteorological measurements were performed in the wakes of offshore wind parks during the project WIPAFF. During stable atmospheric conditions, the areas of reduced wind speed and enhanced turbulence behind wind parks had an extension larger than 45 km downwind. The data set consisting of 41 measurement flights is presented. Parameters include wind vector, temperature, humidity and significant wave height.
Simon K. Siedersleben, Andreas Platis, Julie K. Lundquist, Bughsin Djath, Astrid Lampert, Konrad Bärfuss, Beatriz Cañadillas, Johannes Schulz-Stellenfleth, Jens Bange, Tom Neumann, and Stefan Emeis
Geosci. Model Dev., 13, 249–268, https://doi.org/10.5194/gmd-13-249-2020, https://doi.org/10.5194/gmd-13-249-2020, 2020
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Wind farms affect local weather and microclimates. These effects can be simulated in weather models, usually by removing momentum at the location of the wind farm. Some debate exists whether additional turbulence should be added to capture the enhanced mixing of wind farms. By comparing simulations to measurements from airborne campaigns near offshore wind farms, we show that additional turbulence is necessary. Without added turbulence, the mixing is underestimated during stable conditions.
Stefan Schröder, Anne Springer, Jürgen Kusche, Bernd Uebbing, Luciana Fenoglio-Marc, Bernd Diekkrüger, and Thomas Poméon
Hydrol. Earth Syst. Sci., 23, 4113–4128, https://doi.org/10.5194/hess-23-4113-2019, https://doi.org/10.5194/hess-23-4113-2019, 2019
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We propose deriving altimetric rating curves by
bridginggaps between time series from gauge and altimeter measurements using hydrological model simulations. We investigate several stations at the Niger River, which is a challenging region. We show that altimetry reproduces discharge well and enables continuing the gauge time series, albeit at a lower temporal resolution.
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265, https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
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The Elbe estuary is subject to vigorous tidal forcing from the sea side and considerable biological inputs from the land side. Our 3D numerical coupled physical-biogeochemical integrates these forcing signals and provides highly realistic hindcasts of the associated dynamics. Model simulations show that the freshwater part of Elbe estuary is inhabited by plankton. According to simulations these organism play a key role in converting organic inputs into nitrate, the major inorganic nutrient.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
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Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
Johannes Schulz-Stellenfleth and Joanna Staneva
Ocean Sci., 15, 249–268, https://doi.org/10.5194/os-15-249-2019, https://doi.org/10.5194/os-15-249-2019, 2019
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Errors of observations and numerical model data are analysed with a focus on heterogeneous coastal areas. An extension of the triple collocation method is proposed, which takes into account gradients in the collocation of datasets separated by distances which may not be acceptable for a nearest-neigbour approximation, but still be feasible for linear or higher order interpolations. The technique is applied to wave height data from in situ stations, models, and the Sentinel-3A altimeter.
Jean-François Legeais, Michaël Ablain, Lionel Zawadzki, Hao Zuo, Johnny A. Johannessen, Martin G. Scharffenberg, Luciana Fenoglio-Marc, M. Joana Fernandes, Ole Baltazar Andersen, Sergei Rudenko, Paolo Cipollini, Graham D. Quartly, Marcello Passaro, Anny Cazenave, and Jérôme Benveniste
Earth Syst. Sci. Data, 10, 281–301, https://doi.org/10.5194/essd-10-281-2018, https://doi.org/10.5194/essd-10-281-2018, 2018
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Sea level is one of the best indicators of climate change and has been listed as one of the essential climate variables. Sea level measurements have been provided by satellite altimetry for 25 years, and the Climate Change Initiative (CCI) program of the European Space Agency has given the opportunity to provide a long-term, homogeneous and accurate sea level record. It will help scientists to better understand climate change and its variability.
Kai Håkon Christensen, Ana Carrasco, Jean-Raymond Bidlot, and Øyvind Breivik
Ocean Sci., 13, 589–597, https://doi.org/10.5194/os-13-589-2017, https://doi.org/10.5194/os-13-589-2017, 2017
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In this note we investigate when and where we would expect the bottom to influence the dynamics of surface waves. In deep water, where the presence of the bottom is not felt by the waves, modelers can use a simpler description of wave-mean flow interactions; hence, the results are relevant for coupled wave-ocean modeling systems. The most pronounced influence is on the Northwest Shelf during winter, and can sometimes be significant even far from the coast.
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
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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.
Kathrin Wahle, Joanna Staneva, Wolfgang Koch, Luciana Fenoglio-Marc, Ha T. M. Ho-Hagemann, and Emil V. Stanev
Ocean Sci., 13, 289–301, https://doi.org/10.5194/os-13-289-2017, https://doi.org/10.5194/os-13-289-2017, 2017
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Reduction of wave forecasting errors is a challenge, especially in dynamically complicated coastal ocean areas such as the southern part of the North Sea area. We study the effects of coupling between an atmospheric and two nested-grid wind wave models. Comparisons with data from in situ and satellite altimeter observations indicate that two-way coupling improves the simulation of wind and wave parameters of the model and justifies its implementation for both operational and climate simulation.
Joanna Staneva, Kathrin Wahle, Wolfgang Koch, Arno Behrens, Luciana Fenoglio-Marc, and Emil V. Stanev
Nat. Hazards Earth Syst. Sci., 16, 2373–2389, https://doi.org/10.5194/nhess-16-2373-2016, https://doi.org/10.5194/nhess-16-2373-2016, 2016
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This study addresses the impact of wind, waves, tidal forcing and baroclinicity on the sea level of the German Bight during extreme storm events. The role of wave-induced processes, tides and baroclinicity is quantified, and the results are compared with in situ measurements and satellite data. Considering a wave-dependent approach and baroclinicity, the surge is significantly enhanced in the coastal areas and the model results are closer to observations, especially during the extreme storm.
Emil V. Stanev, Johannes Schulz-Stellenfleth, Joanna Staneva, Sebastian Grayek, Sebastian Grashorn, Arno Behrens, Wolfgang Koch, and Johannes Pein
Ocean Sci., 12, 1105–1136, https://doi.org/10.5194/os-12-1105-2016, https://doi.org/10.5194/os-12-1105-2016, 2016
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This paper describes coastal ocean forecasting practices exemplified for the North Sea and Baltic Sea. It identifies new challenges, most of which are associated with the nonlinear behavior of coastal oceans. It describes the assimilation of remote sensing, in situ and HF radar data, prediction of wind waves and storm surges, as well as applications to search and rescue operations. Seamless applications to coastal and estuarine modeling are also presented.
Joanna Staneva, Kathrin Wahle, Heinz Günther, and Emil Stanev
Ocean Sci., 12, 797–806, https://doi.org/10.5194/os-12-797-2016, https://doi.org/10.5194/os-12-797-2016, 2016
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This study addresses the impact of coupling between wind wave and circulation models on the quality of coastal ocean predicting systems. This topic reflects the increased interest in operational oceanography to reduce prediction errors of state estimates at coastal scales. The improved skill of the coupled forecasts compared to the non-coupled ones, in particular during extreme events, justifies the further enhancements of coastal operational systems by including wind wave models.
Cited articles
Appendini, C. M., Torres-Freyermuth, A., Oropeza, F., Salles, P., López,
J., and Mendoza, E. T.: Wave modeling performance in the Gulf of Mexico and
Western Caribbean: wind reanalyses assessment, Appl. Ocean Res., 39,
20–30, 2013. a
Beneviste, J. and Vignudelli, S.: Challenges in Coastal Satellite Radar
Altemitry, Eos, 90, p. 225, 2009. a
Berrisford, P., Dee, D., Fielding, K., Fuentes, M., Kallberg, P., Kobayashi,
S., and Uppala, S.: The ERA-interim archive,
https://www.ecmwf.int/sites/default/files/elibrary/2011/8174-era-interim-archive-version-20.pdf
(last access: 1 March 2018), 2009. a
Bidlot, J. and Holt, M.: Verification of operational global and regional wave
forecasting systems against measurements from moored buoys,
Geneva, Switzerland, WMO & IOC, 11 pp., WMO TD: 1333, JCOMM Technical
Report: 30, available at: http://hdl.handle.net/11329/101 (last access:
16 November 2018), 2006. a
Björnsson, H. and Venegas, S.: A Manual for EOF and SVD analyses of
Climatic Data, CCGCR Report, 97, 112–134, 1997. a
Bolaños-Sanchez, R., Sanchez-Arcilla, A., and Cateura, J.: Evaluation of
two atmospheric models for wind–wave modelling in the NW Mediterranean,
J. Marine Syst., 65, 336–353, 2007. a
Cavaleri, L.: Wave modeling-Missing the peaks, J. Phys. Oceanogr., 39, 2757–2778, 2009. a
Cavaleri, L. and Bertotti, L.: In search of the correct wind and wave fields
in
a minor basin, Mon. Weather Rev., 125, 1964–1975, 1997. a
Cavaleri, L. and Bertotti, L.: The characteristics of wind and wave fields
modelled with different resolutions, Q. J. Roy. Meteor. Soc., 129, 1647–1662, 2003a. a
Cavaleri, L., Alves, J.-H., Ardhuin, F., Babanin, A., Banner, M.,
Belibassakis,
K., Benoit, M., Donelan, M., Groeneweg, J., Herbers, T., Hwang, P., Janssen, P. A. E. M.,
Janssen, T., Lavrenov, I. V., Magne, R., Monbaliu, J., Onorato, M., Polnikov, V.,
Resio, D., Rogers, W. E., Sheremet, A., McKee Smith, J., Tolman, H. L., van Vledder, G.,
Wolf, J., and Young, I.:
Wave
Modelling – The State of the Art, Prog. Oceanogr., 75, 603–674,
2007. a, b
Chelton, D. B. and Freilich, M. H.: Scatterometer-based assessment of 10-m
wind
analyses from the operational ECMWF and NCEP numerical weather prediction
models, Mon. Weather Rev., 133, 409–429, 2005. a
Cipollini, P., Benviste, J., Bouffard, J., Emery, W., Fenoglio-Marc, L.,
Gommenginger, C., Høyer, J., Kurapov, A., Madsen, K., Mercier, F., Miller,
L., PAscual, A., Ravichandran, M., Shillington, F., Snaith, H., Strub, P. T.,
Vandemark, D., Vignudelli, S., Wilkin, J., Woodworth, P., and Zavala-Garay,
J.: The role of coastal altimetry in coastal observing systems, Proceedings of OceanObs, 9, 181–191, 2010. a, b
CryoSat-2 SAR: satellite data, available at: https://gpod.eo.esa.int, last
access: 16 November 2018.
CryoSat-2 RDSAR:
satellite data, available at: http://rads.tudelft.nl/rads/rads.shtml, last access: 5 December 2018.
Dee, D. P., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S.,
Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C.
M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M.,
Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L.,
Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M.,
Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut,
J.-N., and Vitart, F.: The ERA-Interim
reanalysis: Configuration and performance of the data assimilation system,
Q. J. Roy. Meteor. Soc., 137, 553–597, 2011. a
de León, S. P. and Soares, C. G.: Sensitivity of wave model predictions
to
wind fields in the Western Mediterranean sea, Coast. Eng., 55,
920–929, 2008. a
de León, S. P., Orfila, A., Gómez-Pujol, L., Renault, L., Vizoso, G.,
and Tintoré, J.: Assessment of wind models around the Balearic Islands
for operational wave forecast, Appl. Ocean Res., 34, 1–9, 2012. a
ECMWF: IFS documentation, available at:
https://www.ecmwf.int/en/forecasts/documentation-and-support/changes-ecmwf-model/ifs-documentation
(last access: 5 July 2018), 2017a. a
ECMWF: ERA5 data documentation, available at:
https://software.ecmwf.int/wiki/display/CKB/ERA5+data+documentation#ERA5datadocumentation-Spatialgrid
(last access: 1 March 2018), 2017b. a
ERA-5: wind forcing data, available at:
https://cds.climate.copernicus.eu/cdsapp#!/search?type=dataset, last
access: 30 November 2018.
Feng, H., Vandemark, D., Quilfen, Y., Chapron, B., and Beckley, B.:
Assessment
of wind-forcing impact on a global wind-wave model using the TOPEX altimeter,
Ocean Eng., 33, 1431–1461, 2006. a
Gautier, C. and Caires, S.: Operational Wave Forecasts in the Southern North
Sea, in: 36th IAHR World Congress, 28 June–3 July, 1, 2–5, 2015. a
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. a
Hersbach, H. and Dee, D.: ERA5 reanalysis is in production, available at:
https://software.ecmwf.int/wiki/display/CKB/What+is+ERA5?preview=/58140637/58140636/16299-newsletter-no147-spring-2016_p7.pdf (last
access: 16 November 2018), 2016. a
HZG: coastDat-3_COSMO-CLM_ERAi. World Data Center for Climate (WDCC) at
DKRZ, available at:
https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=coastDat-3_COSMO-CLM_ERAi (last
access: 13 March 2018), 2017. a
Janssen, P. A. and Bidlot, J.-R.: Progress in operational wave forecasting,
Procedia IUTAM, 26, 14–29, 2018. a
Jason-2: satellite data, available at: ftp://avisoftp.cnes.fr, last
access: 16 November 2018.
Komen, G. J., Cavaleri, L., and Donelan, M.: Dynamics and modelling of ocean
waves, Cambridge university press, 1994. a
Nose, T., Webb, A., Waseda, T., Inoue, J., and Sato, K.: Predictability of
storm wave heights in the ice-free Beaufort Sea, Ocean Dynam., 68, 1–20,
2018. a
Reinert, D., Prill, F., Frank, H., Denhard, M., and Zängl, G.: Database
Reference Manual for ICON and ICON-EPS, available at:
https://isabel.dwd.de/DWD/forschung/nwv/fepub/icon_database_main.pdf,
last access: 16 November 2018. a
Rockel, B., Will, A., and Hense, A.: The regional climate model COSMO-CLM
(CCLM), Meteorol. Z., 17, 347–348, 2008. a
Schulz-Stellenfleth, J. and Stanev, E.: Statistical assessment of ocean
observing networks – A study of water level measurements in the German Bight,
Ocean Model., 33, 270–282, 2010. a
Signell, R. P., Carniel, S., Cavaleri, L., Chiggiato, J., Doyle, J. D.,
Pullen,
J., and Sclavo, M.: Assessment of wind quality for oceanographic modelling in
semi-enclosed basins, J. Marine Syst., 53, 217–233, 2005. a
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, 2017. a
Stopa, J. E.: Wind forcing calibration and wave hindcast comparison using
multiple reanalysis and merged satellite wind datasets, Ocean Model.,
127, 55–69,
2018. a
Teixeira, J., Abreu, M., and Soares, C. G.: Uncertainty of ocean wave
hindcasts
due to wind modeling, J. Offshore Mech. Arct.,
117, 294–297, 1995. a
WAM: WAM model code, available at: http://mywave.github.io/WAM/, last
access: 30 November 2018.
WAMDI Group: The WAM model – A third generation ocean wave prediction
model,
J. Phys. Oceanogr., 18, 1775–1810, 1988. a
Short summary
The increase of data quality of wind and wave measurements provided by the new Sentinel-3A satellite in coastal areas is demonstrated compared to measurements of older satellites with in situ data and spectral wave model simulations. Furthermore, the sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, where an hourly temporal resolution is necessary to represent the peak of extreme events better.
The increase of data quality of wind and wave measurements provided by the new Sentinel-3A...
