Articles | Volume 17, issue 6
https://doi.org/10.5194/os-17-1815-2021
© Author(s) 2021. 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-17-1815-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Dec 2021
Research article |
| 23 Dec 2021
| 23 Dec 2021
Swell hindcast statistics for the Baltic Sea
Jan-Victor Björkqvist
CORRESPONDING AUTHOR
Norwegian Meteorological Institute, Allégaten 70, 5007, Bergen, Norway
Department of Marine Systems, Tallinn University of Technology, Akadeemia tee 15a, 12611, Tallinn, Estonia
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Siim Pärt
Department of Marine Systems, Tallinn University of Technology, Akadeemia tee 15a, 12611, Tallinn, Estonia
Victor Alari
Department of Marine Systems, Tallinn University of Technology, Akadeemia tee 15a, 12611, Tallinn, Estonia
Sander Rikka
Department of Marine Systems, Tallinn University of Technology, Akadeemia tee 15a, 12611, Tallinn, Estonia
Elisa Lindgren
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Laura Tuomi
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
Related authors
No articles found.
Jan-Victor Björkqvist and Victor Alari
EGUsphere, https://doi.org/10.5194/egusphere-2024-3477, https://doi.org/10.5194/egusphere-2024-3477, 2024
Short summary
Short summary
Surface waves are generated by the wind and wave measurements can also be used to estimate the wind speed. This is beneficial in the open ocean where direct measurements of the wind are difficult. The wind speed deduced from wave measurements serve as a third estimate of the wind speed in addition to satellite measurements or numerical model results. We implemented such and algorithm to be used with wave data from a small buoy and validated it against direct wind measurements and model results.
Jan-Victor Björkqvist, Hedi Kanarik, Laura Tuomi, Lauri Niskanen, and Markus Kankainen
State Planet, 4-osr8, 10, https://doi.org/10.5194/sp-4-osr8-10-2024, https://doi.org/10.5194/sp-4-osr8-10-2024, 2024
Short summary
Short summary
Typical wave statistics do not provide information on how often certain wave heights are exceeded and the length of such events. Our study found a strong seasonal dependence for 2.5 and 4 m wave events in the Baltic Sea. Wave heights of over 7 m occurred less than once per year. The number of 1 m wave events can double within 20 km in nearshore areas. Our results are important for all operations at sea, including ship traffic and fish farming.
Taavi Liblik, Daniel Rak, Enriko Siht, Germo Väli, Johannes Karstensen, Laura Tuomi, Louise C. Biddle, Madis-Jaak Lilover, Māris Skudra, Michael Naumann, Urmas Lips, and Volker Mohrholz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2272, https://doi.org/10.5194/egusphere-2024-2272, 2024
Short summary
Short summary
Eight current meters were deployed to the seafloor across the Baltic to enhance knowledge about circulation and currents. The experiment was complemented by autonomous vehicles. Stable circulation patterns were observed at the sea when weather was steady. Strong and quite persistent currents were observed at the key passage for the deep-water renewal of the Northern Baltic Sea. Deep water renewal mostly occurs during spring and summer periods in the northern Baltic Sea.
Elina Miettunen, Laura Tuomi, Antti Westerlund, Hedi Kanarik, and Kai Myrberg
Ocean Sci., 20, 69–83, https://doi.org/10.5194/os-20-69-2024, https://doi.org/10.5194/os-20-69-2024, 2024
Short summary
Short summary
We studied circulation and transports in the Archipelago Sea (in the Baltic Sea) with a high-resolution hydrodynamic model. Transport dynamics show different variabilities in the north and south, so no single transect can represent transport through the whole area in all cases. The net transport in the surface layer is southward and follows the alignment of the deeper channels. In the lower layer, the net transport is southward in the northern part of the area and northward in the southern part.
Verónica González-Gambau, Estrella Olmedo, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Justino Martínez, Pekka Alenius, Laura Tuomi, Rafael Catany, Manuel Arias, Carolina Gabarró, Nina Hoareau, Marta Umbert, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 2343–2368, https://doi.org/10.5194/essd-14-2343-2022, https://doi.org/10.5194/essd-14-2343-2022, 2022
Short summary
Short summary
We present the first Soil Moisture and Ocean Salinity Sea Surface Salinity (SSS) dedicated products over the Baltic Sea (ESA Baltic+ Salinity Dynamics). The Baltic+ L3 product covers 9 days in a 0.25° grid. The Baltic+ L4 is derived by merging L3 SSS with sea surface temperature information, giving a daily product in a 0.05° grid. The accuracy of L3 is 0.7–0.8 and 0.4 psu for the L4. Baltic+ products have shown to be useful, covering spatiotemporal data gaps and for validating numerical models.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
Short summary
Short summary
Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
Short summary
Short summary
A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
Antti Westerlund, Elina Miettunen, Laura Tuomi, and Pekka Alenius
Ocean Sci., 18, 89–108, https://doi.org/10.5194/os-18-89-2022, https://doi.org/10.5194/os-18-89-2022, 2022
Short summary
Short summary
Water exchange through the Åland Sea (in the Baltic Sea) affects the conditions in the neighbouring Gulf of Bothnia. Pathways and variability of flows were studied with a high-resolution hydrodynamic model. Our analysis showed a northward transport in the deep layer and net transport towards the south in the surface layer. While on the southern edge of the Åland Sea the primary route of deep-water exchange is through Lågskär Deep, some deep water still bypasses it to the Åland Sea.
Tuomas Kärnä, Patrik Ljungemyr, Saeed Falahat, Ida Ringgaard, Lars Axell, Vasily Korabel, Jens Murawski, Ilja Maljutenko, Anja Lindenthal, Simon Jandt-Scheelke, Svetlana Verjovkina, Ina Lorkowski, Priidik Lagemaa, Jun She, Laura Tuomi, Adam Nord, and Vibeke Huess
Geosci. Model Dev., 14, 5731–5749, https://doi.org/10.5194/gmd-14-5731-2021, https://doi.org/10.5194/gmd-14-5731-2021, 2021
Short summary
Short summary
We present Nemo-Nordic 2.0, a novel operational marine model for the Baltic Sea. The model covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. We validate the model's performance against sea level, water temperature, and salinity observations, as well as sea ice charts. The skill analysis demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.
Jan-Victor Björkqvist, Sander Rikka, Victor Alari, Aarne Männik, Laura Tuomi, and Heidi Pettersson
Nat. Hazards Earth Syst. Sci., 20, 3593–3609, https://doi.org/10.5194/nhess-20-3593-2020, https://doi.org/10.5194/nhess-20-3593-2020, 2020
Short summary
Short summary
Wave observations have a fundamental uncertainty due to the randomness of the sea state. Such scatter is absent in model data, and we tried two methods to best account for this difference when combining measured and modelled wave heights. The results were used to estimate how rare a 2019 storm in the Bothnian Sea was. Both methods were found to have strengths and weaknesses, but our best estimate was that, in the current climate, such a storm might on average repeat about once a century.
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
Short summary
Short summary
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Jan-Victor Björkqvist, Laura Tuomi, Niko Tollman, Antti Kangas, Heidi Pettersson, Riikka Marjamaa, Hannu Jokinen, and Carl Fortelius
Nat. Hazards Earth Syst. Sci., 17, 1653–1658, https://doi.org/10.5194/nhess-17-1653-2017, https://doi.org/10.5194/nhess-17-1653-2017, 2017
Short summary
Short summary
We studied the highest wave events in the Baltic Sea using wave measurements available since 1996. Going beyond classifying them based solely on the maximum wave height, we found that they can be divided into two groups based on, for example, the length of the storm. Two of the severest storms show different behaviour, with the most recent (in 2017) being the longest on record. We hope this more in-depth description of the storms will aid in the issuing of warnings for extreme wave conditions.
Cited articles
Alves, J.-H. G. M.: Numerical modeling of ocean swell contributions to the
global wind-wave climate, Ocean Model., 11, 98–122, https://doi.org/10.1016/j.ocemod.2004.11.007, 2006. a
Amores, A. and Marcos, M.: Ocean swells along the global coastlines and their
climate projections for the twenty-first century, J. Climate, 33, 185–199,
https://doi.org/10.1175/JCLI-D-19-0216.1, 2020. a
Ardhuin, F., Chapron, B., and Collard, F.: Observation of swell dissipation
across oceans, Geophys. Res. Lett., 36, L06607, https://doi.org/10.1029/2008GL037030, 2009. a
Babanin, A. V., Rogers, W. E., de Camargo, R., Doble, M., Durrant, T., Filchuk, K., Ewans, K., Hemer, M., Janssen, T., Kelly-Gerreyn, B., Machutchon, K., McComb, P., Qiao, F., Schulz, E., Skvortsov, A., Thomson, J., Vichi, M., Violante-Carvalho, N., Wang, D., Waseda, T., Williams, G., and Young, I. R.: Waves and swells in high wind and extreme fetches, measurements in the Southern Ocean, Front. Mar. Sci., 6, 1–12,
https://doi.org/10.3389/fmars.2019.00361, 2019. a
Barber, N. F. and Ursell, F.: The Generation and Propagation of Ocean Waves
and Swell. I. Wave periods and velocitites, Philos. T. Roy.Soc. Lond., 240, 527–560, https://doi.org/10.1098/rsta.1948.0005, 1948. a
Berkun, U.: Wind and Swell Wave Climate for the Southern Part of Black Sea,
MS thesis, Middle East Technical University, available at:
https://etd.lib.metu.edu.tr/upload/12608139/index.pdf (last access: 20 December 2021), 2007. a
Björkqvist, J.-V., Tuomi, L., Tollman, N., Kangas, A., Pettersson, H.,
Marjamaa, R., Jokinen, H., and Fortelius, C.: Brief communication:
Characteristic properties of extreme wave events observed in the northern
Baltic Proper, Baltic Sea, Nat. Hazards Earth Syst. Sci., 17, 1653–1658,
https://doi.org/10.5194/nhess-17-1653-2017, 2017. a
Björkqvist, J.-V., Lukas, I., Alari, V., van Vledder, G. P., Hulst, S.,
Pettersson, H., Behrens, A., and Männik, A.: Comparing a 41-year model
hindcast with decades of wave measurements from the Baltic Sea, Ocean Eng.,
152, 57–71, https://doi.org/10.1016/J.OCEANENG.2018.01.048, 2018. a, b
Björkqvist, J.-V., Pettersson, H., and Kahma, K. K.: The wave spectrum in archipelagos, Ocean Sci., 15, 1469–1487, https://doi.org/10.5194/os-15-1469-2019, 2019. a, b
Björkqvist, J.-V., Rikka, S., Alari, V., Männik, A., Tuomi, L., and
Pettersson, H.: Wave height return periods from combined measurement–model
data: a Baltic Sea case study, Nat. Hazards Earth Syst. Sci., 20, 3593–3609,
https://doi.org/10.5194/nhess-20-3593-2020, 2020. a
Björkqvist, J.-V., Pärt, S., Alari, V., Rikka, S., Lindgren, E., and Tuomi, L.: Swell hindcast data for the Baltic Sea, Zenodo [data set], https://doi.org/10.5281/zenodo.5733242, 2021. a
Carlsson, B., Rutgersson, A., and Smedman, A. S.: Impact of swell on
simulations using a regional atmospheric climate model, Tellus A, 61,
527–538, https://doi.org/10.1111/j.1600-0870.2009.00403.x, 2009. a
Chen, B., Yang, D., Meneveau, C., and Chameci, M.: Effects of swell on transport and dispersion of oil plumes within the ocean mixed layer, J.
Geophys. Res.-Oceans, 121, 3564–3578, https://doi.org/10.1002/2015JC011380, 2016. a
CMEMS BAL MFC: Baltic Sea Wave Hindcast, Copernicus Monitoring Environment Marine Service (CMEMS) [data set], https://doi.org/10.48670/moi-00014, 2019. a
Divinsky, B. and Kosyan, R.: Parameters of wind seas and swell in the Black
Sea based on numerical modeling, Oceanologia, 60, 277–287,
https://doi.org/10.1016/j.oceano.2017.11.006, 2018. a
Driesenaar, T., Bentamy, A., de Kloe, J., Rivas, M. B., and Giesen, R.:
Quality Information Document for Global Ocean Wind Products
WIND_GLO_WIND_L3_NRT_OBSERVATIONS_012_002,
WIND_GLO_WIND_L3_REP_OBSERVATIONS_012_005, WIND_GLO_PHY_CLIMATE_L4_REP_012_003,
WIND_GLO_PHY_CLIMATE_L4_REP_012_003, Tech. rep., Copernicus Marine
Environment Monitoring Service, available at:
https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-WIND-QUID-012-002-003-005.pdf
(last access: 18 June 2021), 2020. a
Fan, Y., Lin, S.-J., Griffies, S., and Hemer, M. A.: Simulated Global Swell
and Wind-Sea Climate and Their Responses to Anthropogenic Climate Change at
the End of the Twenty-First Century Simulated Global Swell and Wind-Sea
Climate and Their Responses to Anthropogenic Climate Change at the End of the
Twenty, J. Climate, 27, 3516–3536, https://doi.org/10.1175/JCLI-D-13-00198.1, 2014. a
Hanley, K. E., Belcher, S. E., and Sullivan, P. P.: A Global Climatology of
Wind – Wave Interaction, J. Phys. Oceanogr., 40, 1263–1282,
https://doi.org/10.1175/2010JPO4377.1, 2010. a
HELCOM: HELCOM Assessment on maritime activities in the Baltic Sea,
baltic Sea Environment Proceedings No. 152, Helsinki Commission, Helsinki,
253 pp., available at: https://www.helcom.fi/wp-content/uploads/2019/08/BSEP152-1.pdf, (last access: 23 June 2021), 2018. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global
reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Holthuijsen, L. H.: Waves in Oceanic and Coastal Waters, Cambridge University
Press, Cambridge, https://doi.org/10.1017/CBO9780511618536, 2007. a
Hwang, P. A. and Plant, W. J.: An analysis of the effects of swell and surface roughness spectra on microwave backscatter from the ocean, J. Geophys. Res.-Oceans, 115, C04014, https://doi.org/10.1029/2009JC005558, 2010. a
Isæus, M.: Factors Structuring Fucus Communities at Open and Complex
Coastlines in the Baltic Sea, PhD thesis, Stockholm University, Faculty of
Science, Department of Botany, Stockholm, 2004. a
Kahma, K. K., Donelan, M. A., Drennan, W. M., and Terray, E. A.: Evidence of
Energy and Momentum Flux from Swell to Wind, J. Phys. Oceanogr., 46, 2143–2156, https://doi.org/10.1175/JPO-D-15-0213.1, 2016. a, b, c
Komen, G. J., Hasselmann, S., and Hasselmann, K.: On the Existence of a Fully
Developed Wind-Sea Spectrum, J. Phys. Oceanogr., 14, 1271–1285, https://doi.org/10.1175/1520-0485(1984)014<1271:OTEOAF>2.0.CO;2, 1984. a
Komen, G. J., Cavaleri, L., Donelan, M. A., Hasselmann, K., Hasselmann, S., and Janssen, P. A.: Dynamics and Modelling of Ocean Waves, Cambridge University Press, Cambridge, 1994. a
Lindgren, E., Tuomi, L., and Huess, V.: Quality Information Document for
BALTICSEA_REANALYSIS_WAV_003_015, Tech. rep., Copernicus Marine
Environment Monitoring Service, available at:
https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-BAL-QUID-003-015.pdf
(last access: 21 June 2021), 2020. a, b
Moreau, T., Tran, N., Aublanc, J., Tison, C., Le Gac, S., and Boy, F.: Impact
of long ocean waves on wave height retrieval from SAR altimetry data, Adv.
Space Res., 62, 1434–1444, https://doi.org/10.1016/j.asr.2018.06.004, 2018. a
Pettersson, H., Kahma, K. K., and Tuomi, L.: Wave Directions in a Narrow Bay, J. Phys. Oceanogr., 40, 155–169, https://doi.org/10.1175/2009JPO4220.1, 2010. a, b
Portilla, J., Ocampo-Torres, F. J., and Monbaliu, J.: Spectral Partitioning
and Identification of Wind Sea and Swell, J. Atmos. Ocean. Tech., 26, 107–122, https://doi.org/10.1175/2008JTECHO609.1, 2009. a
Post, P. and Kõuts, T.: Characteristics of cyclones causing extreme sea
levels in the northern Baltic Sea, Oceanologia, 56, 241–258,
https://doi.org/10.5697/oc.56-2.241, 2014. a, b
Qian, C., Jiang, H., Wang, X., and Chen, G.: Climatology of Wind-Seas and
Swells in the China Seas from Wave Hindcast, J. Ocean Univers. China, 19, 90–100, https://doi.org/10.1007/s11802-020-3924-4, 2020. a
Quilfen, Y., Chapron, B., Collard, F., and Vandemark, D.: Relationship between ERS Scatterometer Measurement and Integrated Wind and Wave Parameters, J. Atmos. Ocean. Tech., 21, 368–373,
https://doi.org/10.1175/1520-0426(2004)021<0368:RBESMA>2.0.CO;2, 2004. a
Reistad, M., Breivik, Ø., Haakenstad, H., Aarnes, O. J., Furevik, B. R., and Bidlot, J.-R.: A high-resolution hindcast of wind and waves for the North
Sea, the Norwegian Sea, and the Barents Sea, J. Geophys. Res.-Oceans, 116,
1–18, https://doi.org/10.1029/2010JC006402, 2011. a
Rieu, P., Moreau, T., Cadier, E., Raynal, M., Clerc, S., Donlon, C., Borde, F., Boy, F., and Maraldi, C.: Exploiting the Sentinel-3 tandem phase dataset and azimuth oversampling to better characterize the sensitivity of SAR altimeter sea surface height to long ocean waves, Adv. Space Res., 67, 253–265, 2021. a
Semedo, A., Saetra, Ø., Rutgersson, A., Kahma, K. K., and Pettersson, H.:
Wave-Induced Wind in the Marine Boundary Layer, J. Atmos. Sci., 66, 2256–2271, https://doi.org/10.1175/2009jas3018.1, 2009. a
Semedo, A., Vettor, R., Breivik, Ø., Sterl, A., and Reistad, M.: Wind Sea
and Swell Waves in the Baltic Sea, in: Poster presented at 14th Annual
meeting of the European Meteorological Society (EMS) and 10th European
Conference on Applied Climatology (ECAC), available at:
https://www.researchgate.net/publication/268926217_Wind_Sea_and_Swell_Waves_in_the_Baltic_Sea
(last access: 10 September 2021), 2014. a, b, c, d, e, f
Smedman, A., Högström, U., Bergström, H., Rutgersson, A., Kahma, K. K., and Pettersson, H.: A case study of air-sea interaction during swell conditions, J. Geophys. Res.-Oceans, 104, 25833–25851,
https://doi.org/10.1029/1999jc900213, 1999. a, b
SMHI and FIMR: Climatological Ice Atlas for the Baltic Sea, Kattegat, Skagerrak and Lake Vänern (1963–1979), Tech. rep., SMHI and FIMR,
Norrköping, 1982. a
Soomere, T., Behrens, A., Tuomi, L., and Nielsen, J. W.: Wave conditions in
the Baltic Proper and in the Gulf of Finland during windstorm Gudrun, Nat.
Hazards Earth Syst. Sci., 8, 37–46, https://doi.org/10.5194/nhess-8-37-2008, 2008. a
Stopa, J. E., Mouche, A. A., Chapron, B., and Collard, F.: Sea State Impacts on Wind Speed Retrievals From C-Band Radars, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 10, 2147–2155, https://doi.org/10.1109/JSTARS.2016.2609101, 2017. a, b
Tuomi, L., Pettersson, H., Fortelius, C., Tikka, K., Björqvist, J.-V., and Kahma, K. K.: Wave modelling in archipelagos, Coast. Eng., 83, 205–220,
2014. a
Van Vledder, G. and Akpınar, A.: Spectral partitioning and swells in the
Black Sea, Proc. Coast. Eng. Conf., 35, 1–14, https://doi.org/10.9753/icce.v35.waves.21, 2017. a, b, c
Vettor, R., Semedo, A., Soares, C. G., Breivik, Sterl, A., and Reistad, M.:
Wind sea and swell waves in the Northeast Atlantic Ocean, Developments in
Maritime Transportation and Exploitation of Sea Resources, 1029–1036,
https://doi.org/10.1201/b15813-129, 2013. a
WAMDIG: The WAM Model – A Third Generation Ocean Wave Prediction Model, J.
Phys. Oceanogr., 18, 1775–1810,
https://doi.org/10.1175/1520-0485(1988)018<1775:TWMTGO>2.0.CO;2, 1988.
a
Wang, H., Zhu, J., Huang, X., Chen, C., and Zhao, Y.: Assessment of the swell
impact on HY-2 SCAT wind products, in: Remote Sensing of the Ocean, Sea Ice,
Coastal Waters, and Large Water Regions 2014, vol. 9240, edited by: Bostater Jr., C. R., Mertikas, S. P., and Neyt, X., International Society for Optics and Photonics, SPIE, 162–167, https://doi.org/10.1117/12.2067060, 2014.
a
Yang, Z., García-Medina, G., Wu, W. C., Wang, T., Leung, L. R., Castrucci, L., and Mauger, G.: Modeling analysis of the swell and wind-sea
climate in the Salish Sea, Estuar. Coast. Shelf Sci., 224, 289–300, https://doi.org/10.1016/j.ecss.2019.04.043, 2019. a
Short summary
Waves that travel faster than the wind are called swell. Our study presents wave model statistics of swell waves in the Baltic Sea, since such statistics have not yet been reliably compiled. Our results confirm that long, high, and persistent swell is absent in the Baltic Sea. We found that the dependency between swell and wind waves differs in the open sea compared to nearshore areas. These distinctions are important for studies on how waves interact with the atmosphere and the sea floor.
Waves that travel faster than the wind are called swell. Our study presents wave model...
