Articles | Volume 1-osr7
https://doi.org/10.5194/sp-1-osr7-7-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/sp-1-osr7-7-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Baltic Sea freshwater content
Urmas Raudsepp
Department of Marine Systems, Tallinn University of Technology, Tallinn, 12618, Estonia
Ilja Maljutenko
CORRESPONDING AUTHOR
Department of Marine Systems, Tallinn University of Technology, Tallinn, 12618, Estonia
Amirhossein Barzandeh
Department of Marine Systems, Tallinn University of Technology, Tallinn, 12618, Estonia
Rivo Uiboupin
Department of Marine Systems, Tallinn University of Technology, Tallinn, 12618, Estonia
Priidik Lagemaa
Department of Marine Systems, Tallinn University of Technology, Tallinn, 12618, Estonia
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Jukka-Pekka Jalkanen, Lasse Johansson, Magda Wilewska-Bien, Lena Granhag, Erik Ytreberg, K. Martin Eriksson, Daniel Yngsell, Ida-Maja Hassellöv, Kerstin Magnusson, Urmas Raudsepp, Ilja Maljutenko, Hulda Winnes, and Jana Moldanova
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The proposed method of data assimilation is capable of effectively correcting basin-scale mismatch of oceanographic models when the domain is under nearly coherent external forcing. The method uses basin-scale EOF modes, calculated from the long-term model statistics. These modes are used to reconstruct gridded fields from point observations, which are further fed to the model using relaxation. Tests with sea surface temperature and salinity in the NE Baltic Sea were successful.
Lasse Johansson, Erik Ytreberg, Jukka-Pekka Jalkanen, Erik Fridell, K. Martin Eriksson, Maria Lagerström, Ilja Maljutenko, Urmas Raudsepp, Vivian Fischer, and Eva Roth
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L. Sipelgas, A. Aavaste, and R. Uiboupin
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Edith Soosaar, Ilja Maljutenko, Rivo Uiboupin, Maris Skudra, and Urmas Raudsepp
Ocean Sci., 12, 417–432, https://doi.org/10.5194/os-12-417-2016, https://doi.org/10.5194/os-12-417-2016, 2016
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Remote sensing imagery and numerical model study of river bulge evolution and dynamics in a non-tidal sea showed an anti-cyclonically rotating bulge during the studied low wind period in the Gulf of Riga. In about 7–8 days the bulge grew up to 20 km in diameter, before being diluted. Both model and satellite images showed river water mainly contained in the bulge. The study shows significant effects of the wind in the evolution of the river bulge, even if the wind speed was moderate (3–4 m s−1).
Cited articles
Axell, L.: EU Copernicus Marine Service Product User Manual for Baltic Sea Physical Reanalysis Product, BALTICSEA_REANALYSIS_PHY_003_011, Issue 2.1, Mercator Ocean International, https://doi.org/10.5281/zenodo.7935113, 2021.
Boyer, T., Levitus, S., Antonov, J., Locarnini, R., Mishonov, A., Garcia,
H., and Josey, S. A.: Changes in freshwater content in the North Atlantic
Ocean 1955–2006, Geophys. Res. Lett., 34, L16603, https://doi.org/10.1029/2007GL030126, 2007.
Buga, L., Sarbu, G., Fryberg, L., Magnus, W., Wesslander, K., Gatti, J., Leroy, D., Iona, S., Larsen, M., Koefoed Rømer, J., Østrem, A. K., Lipizer, M., and Giorgetti A.: EMODnet Chemistry Eutrophication and Acidity aggregated datasets v2018, EMODnet, Thematic Lot no. 4/SI2.749773, https://doi.org/10.6092/EC8207EF-ED81-4EE5-BF48-E26FF16BF02E, 2018.
Durack, P. J., Wijffels, S. E., and Matear, R. J.: Ocean Salinities Reveal
Strong Global Water Cycle Intensification during 1950 to 2000, Science, 336,
6080455–6080458, https://doi.org/10.1126/science.1212222, 2012.
Eilola, K. and Stigebrandt, A.: Spreading of juvenile freshwater in the
Baltic proper, J. Geophys. Res., 103, 27795–27807,
https://doi.org/10.1029/98JC02369, 1998.
EU Copernicus Marine Service Product: Baltic Sea Physics Reanalysis, cmems_mod_bal_phy_my_P1D-m, Mercator Ocean International [data set],
https://doi.org/10.48670/moi-00013, 2023.
Giorgetti, A., Lipizer, M., Molina Jack, M. E., Holdsworth, N., Jensen, H. M., Buga, L., Sarbu, G., Iona, A., Gatti, J., Larsen, M., and Fyrberg, L.: Aggregated and Validated Datasets for the European Seas: The Contribution of EMODnet Chemistry, Front. Mar. Sci., 7, 583657, https://doi.org/10.3389/fmars.2020.583657, 2020.
Gröger, M., Placke, M., Meier, H. E. M., Börgel, F., Brunnabend, S.-E., Dutheil, C., Gräwe, U., Hieronymus, M., Neumann, T., Radtke, H., Schimanke, S., Su, J., and Väli, G.: The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment, Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, 2022.
Gustafsson, B. and Stigebrandt, A.: Dynamics of the freshwater influenced
surface layers in the Skagerrak, J. Sea Res., 35, 39–53,
https://doi.org/10.1016/S1385-1101(96)90733-9, 1996.
Gustafsson, E. and Omstedt, A.: Sensitivity of Baltic Sea deep water
salinity and oxygen concentration to variations in physical forcing, Boreal
Environ. Res., 14, 18–30, 2009.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., and Simmons, A.: The ERA5 global reanalysis, Q. J. Roy. Meteor., 146, 1999–2049, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Hordoir, R., Axell, L., Höglund, A., Dieterich, C., Fransner, F., Gröger, M., Liu, Y., Pemberton, P., Schimanke, S., Andersson, H., Ljungemyr, P., Nygren, P., Falahat, S., Nord, A., Jönsson, A., Lake, I., Döös, K., Hieronymus, M., Dietze, H., Löptien, U., Kuznetsov, I., Westerlund, A., Tuomi, L., and Haapala, J.: Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applications, Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, 2019.
IOC, SCOR and IAPSO: The international thermodynamic equation of
seawater – 2010: calculation and use of thermodynamic properties.
Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
UNESCO, 196 pp., http://www.teos-10.org (last access: 11 October 2021), 2010.
IOW THREDDS: The IOW thredds at Leibniz Institute for Baltic Sea
Research Warnemuende, IOW THREDDS [data set], https://thredds-iow.io-warnemuende.de/thredds/catalogs/projects/bmip/catalog_bmip_rivers.html (last access: 7 March 2023), 2019.
Jain, A. K.: Data clustering: 50 years beyond K-means, Pattern
Recogn. Lett., 31, 651–666, https://doi.org/10.1016/j.patrec.2009.09.011, 2010.
Kniebusch, M., Meier, H. E. M., and Radtke, H.: Changing salinity
gradients in the Baltic Sea as a consequence of altered freshwater budgets,
Geophys. Res. Lett., 46, 9739–9747, https://doi.org/10.1029/2019GL083902, 2019.
Lass, H. U. and Matthäus, W.: On temporal wind variations forcing
salt water inflows into the Baltic Sea, Tellus A, 48, 663–671,
https://doi.org/10.1034/j.1600-0870.1996.t01-4-00005.x, 1996.
Lehmann, A. and Post, P.: Variability of atmospheric circulation patterns associated with large volume changes of the Baltic Sea, Adv. Sci. Res., 12, 219–225, https://doi.org/10.5194/asr-12-219-2015, 2015.
Lehmann, A., Höflich, K., Post, P., and Myrberg, K.: Pathways of deep
cyclones associated with large volume changes (LVCs) and major Baltic
inflows (MBIs), J. Marine Syst., 167, 11–18,
https://doi.org/10.1016/j.jmarsys.2016.10.014, 2017.
Lehmann, A., Myrberg, K., Post, P., Chubarenko, I., Dailidiene, I., Hinrichsen, H.-H., Hüssy, K., Liblik, T., Meier, H. E. M., Lips, U., and Bukanova, T.: Salinity dynamics of the Baltic Sea, Earth Syst. Dynam., 13, 373–392, https://doi.org/10.5194/esd-13-373-2022, 2022.
Leppäranta M. and Myrberg, K.: Physical Oceanography of the Baltic
Sea, Springer-Verlag, 378 pp., ISBN 978-3-540-79702-9, 2009.
Liblik, T., Naumann, M., Alenius, P., Hansson, M., Lips, U., Nausch, G.,
Tuomi, L., Wesslander, K., Laanemets, J., and Viktorsson, L.: Propagation
of impact of the recent Major Baltic Inflows from the Eastern Gotland basin
to the Gulf of Finland, Front. Mar. Sci., 5, 222,
https://doi.org/10.3389/fmars.2018.00222, 2018.
Liu, Y. and Fu, W.: Assimilating high-resolution sea surface temperature data improves the ocean forecast potential in the Baltic Sea, Ocean Sci., 14, 525–541, https://doi.org/10.5194/os-14-525-2018, 2018.
Liu, Y., Axell, L., Jandt-Scheelke S., Lorkowski, I., Lindenthal, A.,
Verjovkina S., and Schwichtenberg, F.: EU Copernicus Marine Service
Quality Information Document for Baltic Sea Physical Reanalysis Product,
BALTICSEA_REANALYSIS_PHY_003_011, Issue 2.5, Mercator Ocean International, https://doi.org/10.5281/zenodo.7935113, 2019.
Maljutenko, I. and Raudsepp, U.: Long-term mean, interannual and seasonal
circulation in the Gulf of Finland – The wide salt wedge estuary or gulf
type ROFI, J. Marine Syst., 195, 1–19, https://doi.org/10.1016/j.jmarsys.2019.03.004, 2019.
Meier, H. E. M. and Kauker, F.: Modeling decadal variability of the
Baltic Sea: 2. Role of freshwater inflow and large-scale atmospheric
circulation for salinity, J. Geophys. Res., 108, 3368,
https://doi.org/10.1029/2003JC001799, 2003.
Meier, H. E. M., Höglund, A., Eilola, K., and Almroth-Rosell, E.:
Impact of accelerated future global mean sea level rise on hypoxia in the
Baltic Sea, Clim. Dynam., 49, 163–172, https://doi.org/10.1007/s00382-016-3333-y, 2017.
Meier, H. E. M., Eilola, K., Almroth-Rosell, E., Schimanke, S., Kniebusch,
M., Höglund, A., Pemberton, P., Liu, Y., Väli, G., and Saraiva, S.: Disentangling the impact of nutrient load and climate changes on Baltic Sea hypoxia and eutrophication since 1850, Clim. Dynam., 53, 1145–1166, https://doi.org/10.1007/s00382-018-4296-y, 2019a.
Meier, H. E. M., Eilola, K., Almroth-Rosell, E., Schimanke, S., Kniebusch,
M., Höglund, A., Pemberton, P., Liu, Y., Väli, G., and Saraiva, S.: Correction to: Disentangling the impact of nutrient load and climate changes on Baltic Sea hypoxia and eutrophication since 1850, Clim. Dynam., 53, 1167–1169. https://doi.org/10.1007/s00382-018-4483-x, 2019b.
Meier, H. E. M., Dieterich, C., and Gröger, M.: Natural variability is
a large source of uncertainty in future projections of hypoxia in the Baltic
Sea, Commun. Earth Environ., 2, 50, https://doi.org/10.1038/s43247-021-00115-9, 2021.
Meier, H. E. M., Kniebusch, M., Dieterich, C., Gröger, M., Zorita, E., Elmgren, R., Myrberg, K., Ahola, M. P., Bartosova, A., Bonsdorff, E., Börgel, F., Capell, R., Carlén, I., Carlund, T., Carstensen, J., Christensen, O. B., Dierschke, V., Frauen, C., Frederiksen, M., Gaget, E., Galatius, A., Haapala, J. J., Halkka, A., Hugelius, G., Hünicke, B., Jaagus, J., Jüssi, M., Käyhkö, J., Kirchner, N., Kjellström, E., Kulinski, K., Lehmann, A., Lindström, G., May, W., Miller, P. A., Mohrholz, V., Müller-Karulis, B., Pavón-Jordán, D., Quante, M., Reckermann, M., Rutgersson, A., Savchuk, O. P., Stendel, M., Tuomi, L., Viitasalo, M., Weisse, R., and Zhang, W.: Climate change in the Baltic Sea region: a summary, Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, 2022.
Mohrholz, V.: Major Baltic inflow statistics–revised, Front.
Mar. Sci., 5, 384, https://doi.org/10.3389/fmars.2018.00384, 2018.
Mohrholz, V., Naumann, M., Nausch, G., Krüger, S., and Gräwe, U.:
Fresh oxygen for the Baltic Sea – An exceptional saline inflow after a
decade of stagnation, J. Marine Syst., 148, 152–166,
https://doi.org/10.1016/j.jmarsys.2015.03.005, 2015.
Pemberton, P., Löptien, U., Hordoir, R., Höglund, A., Schimanke, S., Axell, L., and Haapala, J.: Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO–LIM3.6-based ocean–sea-ice model setup for the North Sea and Baltic Sea, Geosci. Model Dev., 10, 3105–3123, https://doi.org/10.5194/gmd-10-3105-2017, 2017.
Pratap, S. and Markonis, Y.: The response of the hydrological cycle to
temperature changes in recent and distant climatic history, Prog. Earth Planet. Sci., 9, 30, https://doi.org/10.1186/s40645-022-00489-0, 2022.
Radtke, H., Brunnabend, S.-E., Gräwe, U., and Meier, H. E. M.: Investigating interdecadal salinity changes in the Baltic Sea in a 1850–2008 hindcast simulation, Clim. Past, 16, 1617–1642, https://doi.org/10.5194/cp-16-1617-2020, 2020.
Raudsepp, U. and Maljutenko, I.: A method for assessment of the general circulation model quality using the K-means clustering algorithm: a case study with GETM v2.5, Geosci. Model Dev., 15, 535–551, https://doi.org/10.5194/gmd-15-535-2022, 2022.
Reissmann, J. H., Burchard, H., Feistel,R., Hagen, E., Lass, H. U.,
Mohrholz, V., Nausch, G., Umlauf, L., and Wiecczorek, G.: Vertical mixing
in the Baltic Sea and consequences for eutrophication a review, Progr.
Oceanogr., 82, 47–80, https://doi.org/10.1016/j.pocean.2007.10.004, 2009.
Saraiva, S., Meier, H. E. M., Andersson, H., Höglund, A., Dieterich, C.,
Gröger, M., Hordoir, R., and Eilola, K.: Uncertainties in Projections
of the Baltic Sea Ecosystem Driven by an Ensemble of Global Climate Models,
Front. Earth Sci., 6, 244, https://doi.org/10.3389/feart.2018.00244, 2019.
Schimanke, S. and Meier, H. E. M.: Decadal to centennial variability of
salinity in the Baltic Sea, J. Climate, 29, 7173–7188,
https://doi.org/10.1175/JCLI-D-15-0443.1, 2016.
Schimanke, S., Dieterich, C., and Meier, H. E. M.: An algorithm based on
sea-level pressure fluctuations to identify major Baltic inflow events,
Tellus A, 66, 23452, https://doi.org/10.3402/tellusa.v66.23452, 2014.
Schinke, H. and Matthäus, W.: On the causes of major Baltic inflows
– an analysis of long time series, Cont. Shelf Res., 18, 67–97,
https://doi.org/10.1016/S0278-4343(97)00071-X, 1998.
SMHI: Baltic Sea – Eutrophication and Acidity aggregated datasets
1902/2017 v2018, Swedish Meteorological and Hydrological Institute, EMODnet Chemistry [data set], https://doi.org/10.6092/595D233C-3F8C-4497-8BD2-52725CEFF96B, 2023.
Väli, G., Meier, M., Dieterich, C., and Placke, M.: River runoff
forcing for ocean modeling within the Baltic Sea Model Intercomparison
Project, Meereswiss. Ber., Warnemünde, Marine Science Reports No. 113, https://doi.org/10.12754/msr-2019-0113, 2019.
Westerlund, A., Tuomi, L., Alenius, P., Myrberg, K., Miettunen, E.,
Vankevich, R. E., and Hordoir, R.: Circulation patterns in the Gulf of
Finland from daily to seasonal timescales, Tellus A, 71, 1627149,
https://doi.org/10.1080/16000870.2019.1627149, 2019.
Winsor, P., Rodhe, J., and Omstedt, A.: Baltic Sea ocean climate: an
analysis of 100 yr of hydrographic data with focus on the freshwater budget,
Clim. Res., 18, 5–15, https://doi.org/10.3354/cr018005, 2001.
Short summary
The freshwater content in the Baltic Sea has wide sub-regional variability characterized by the local climate dynamics. The total freshwater content trend is negative due to the recent increased inflows of saltwater, but there are also regions where the increase in runoff and decrease in ice content have led to an increase in the freshwater content.
The freshwater content in the Baltic Sea has wide sub-regional variability characterized by the...
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