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.
27 Sep 2023
| OSR7 | Chapter 2.5
| 27 Sep 2023 | OSR7 | Chapter 2.5
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
Related authors
Jüri Elken, Ilja Maljutenko, Priidik Lagemaa, Rivo Uiboupin, and Urmas Raudsepp
State Planet, 4-osr8, 9, https://doi.org/10.5194/sp-4-osr8-9-2024, https://doi.org/10.5194/sp-4-osr8-9-2024, 2024
Short summary
Short summary
Baltic deep water is generally warmer than surface water during winter when district heating is required. Depending on the location, depth, and oceanographic situation, bottom water of Tallinn Bay can be used as an energy source for seawater heat pumps until the end of February, covering the major time interval when heating is needed. Episodically, there are colder-water events when seawater heat extraction has to be complemented by other sources of heating energy.
Anja Lindenthal, Claudia Hinrichs, Simon Jandt-Scheelke, Tim Kruschke, Priidik Lagemaa, Eefke M. van der Lee, Ilja Maljutenko, Helen E. Morrison, Tabea R. Panteleit, and Urmas Raudsepp
State Planet, 4-osr8, 16, https://doi.org/10.5194/sp-4-osr8-16-2024, https://doi.org/10.5194/sp-4-osr8-16-2024, 2024
Short summary
Short summary
In 2022, large parts of the Baltic Sea experienced the third-warmest to warmest summer and autumn temperatures since 1997 and several marine heatwaves (MHWs). Using remote sensing, reanalysis, and in situ data, this study characterizes regional differences in MHW properties in the Baltic Sea in 2022. Furthermore, it presents an analysis of long-term trends and the relationship between atmospheric warming and MHW occurrences, including their propagation into deeper layers.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Urmas Raudsepp, Ilja Maljutenko, Priidik Lagemaa, and Karina von Schuckmann
State Planet Discuss., https://doi.org/10.5194/sp-2024-19, https://doi.org/10.5194/sp-2024-19, 2024
Preprint under review for SP
Short summary
Short summary
Over the last three decades, the Baltic Sea has experienced rising temperature and salinity, reflecting broader atmospheric warming. Heat content fluctuations are driven by subsurface temperature changes in the upper 100 meters, including the thermocline and halocline, influenced by air temperature, evaporation, and wind stress. Freshwater content changes mainly result from salinity shifts in the halocline, with saline water inflow, precipitation, and wind stress as key factors.
Urmas Raudsepp and Ilja Maljutenko
Geosci. Model Dev., 15, 535–551, https://doi.org/10.5194/gmd-15-535-2022, https://doi.org/10.5194/gmd-15-535-2022, 2022
Short summary
Short summary
A model's ability to reproduce the state of a simulated object is always a subject of discussion. A new method for the multivariate assessment of numerical model skills uses the K-means algorithm for clustering model errors. All available data that fall into the model domain and simulation period are incorporated into the skill assessment. The clustered errors are used for spatial and temporal analysis of the model accuracy. The method can be applied to different types of geoscientific models.
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
Ocean Sci., 17, 699–728, https://doi.org/10.5194/os-17-699-2021, https://doi.org/10.5194/os-17-699-2021, 2021
Short summary
Short summary
This modelling study describes a methodology for describing pollutant discharges from ships to the sea. The pilot area used is the Baltic Sea area and discharges of bilge, ballast, sewage, wash water as well as stern tube oil are reported for the year 2012. This work also reports the release of SOx scrubber effluents. This technique may be used by ships to comply with tight sulfur limits inside Emission Control Areas, but it also introduces a new pollutant stream from ships to the sea.
Lasse Johansson, Erik Ytreberg, Jukka-Pekka Jalkanen, Erik Fridell, K. Martin Eriksson, Maria Lagerström, Ilja Maljutenko, Urmas Raudsepp, Vivian Fischer, and Eva Roth
Ocean Sci., 16, 1143–1163, https://doi.org/10.5194/os-16-1143-2020, https://doi.org/10.5194/os-16-1143-2020, 2020
Short summary
Short summary
Very little is currently known about the activities and emissions of private leisure boats. To change this, a new model was created (BEAM). The model was used for the Baltic Sea to estimate leisure boat emissions, also considering antifouling paint leach. When compared to commercial shipping, the modeled leisure boat emissions were seen to be surprisingly large for some pollutant species, and these emissions were heavily concentrated on coastal inhabited areas during summer and early autumn.
Amirhossein Barzandeh, Marko Rus, Matjaž Ličer, Ilja Maljutenko, Jüri Elken, Priidik Lagemaa, and Rivo Uiboupin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3691, https://doi.org/10.5194/egusphere-2024-3691, 2024
Short summary
Short summary
We evaluated a deep-learning model, HIDRA2, for predicting sea levels along the Estonian coast and compared it to traditional numerical models. HIDRA2 performed better overall, offering faster forecasts and valuable uncertainty estimates using ensemble predictions.
Jüri Elken, Ilja Maljutenko, Priidik Lagemaa, Rivo Uiboupin, and Urmas Raudsepp
State Planet, 4-osr8, 9, https://doi.org/10.5194/sp-4-osr8-9-2024, https://doi.org/10.5194/sp-4-osr8-9-2024, 2024
Short summary
Short summary
Baltic deep water is generally warmer than surface water during winter when district heating is required. Depending on the location, depth, and oceanographic situation, bottom water of Tallinn Bay can be used as an energy source for seawater heat pumps until the end of February, covering the major time interval when heating is needed. Episodically, there are colder-water events when seawater heat extraction has to be complemented by other sources of heating energy.
Anja Lindenthal, Claudia Hinrichs, Simon Jandt-Scheelke, Tim Kruschke, Priidik Lagemaa, Eefke M. van der Lee, Ilja Maljutenko, Helen E. Morrison, Tabea R. Panteleit, and Urmas Raudsepp
State Planet, 4-osr8, 16, https://doi.org/10.5194/sp-4-osr8-16-2024, https://doi.org/10.5194/sp-4-osr8-16-2024, 2024
Short summary
Short summary
In 2022, large parts of the Baltic Sea experienced the third-warmest to warmest summer and autumn temperatures since 1997 and several marine heatwaves (MHWs). Using remote sensing, reanalysis, and in situ data, this study characterizes regional differences in MHW properties in the Baltic Sea in 2022. Furthermore, it presents an analysis of long-term trends and the relationship between atmospheric warming and MHW occurrences, including their propagation into deeper layers.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Urmas Raudsepp, Ilja Maljutenko, Priidik Lagemaa, and Karina von Schuckmann
State Planet Discuss., https://doi.org/10.5194/sp-2024-19, https://doi.org/10.5194/sp-2024-19, 2024
Preprint under review for SP
Short summary
Short summary
Over the last three decades, the Baltic Sea has experienced rising temperature and salinity, reflecting broader atmospheric warming. Heat content fluctuations are driven by subsurface temperature changes in the upper 100 meters, including the thermocline and halocline, influenced by air temperature, evaporation, and wind stress. Freshwater content changes mainly result from salinity shifts in the halocline, with saline water inflow, precipitation, and wind stress as key factors.
Shakti Singh, Ilja Maljutenko, and Rivo Uiboupin
EGUsphere, https://doi.org/10.5194/egusphere-2024-1701, https://doi.org/10.5194/egusphere-2024-1701, 2024
Short summary
Short summary
The sea ice statistics study highlights the bias in model estimations compared to satellite data and provides a simple approach to minimise that. During the study period, the model estimates sea ice forming slightly earlier but aligns well with the satellite data for ice season's end. Rapid decrease in the sea ice parameters is observed across the Baltic Sea, especially the ice thickness in the Bothnian Bay sub-basin. These statistics could be crucial for regional adaptation strategies.
Jan Åström, Fredrik Robertsen, Jari Haapala, Arttu Polojärvi, Rivo Uiboupin, and Ilja Maljutenko
The Cryosphere, 18, 2429–2442, https://doi.org/10.5194/tc-18-2429-2024, https://doi.org/10.5194/tc-18-2429-2024, 2024
Short summary
Short summary
The HiDEM code has been developed for analyzing the fracture and fragmentation of brittle materials and has been extensively applied to glacier calving. Here, we report on the adaptation of the code to sea-ice dynamics and breakup. The code demonstrates the capability to simulate sea-ice dynamics on a 100 km scale with an unprecedented resolution. We argue that codes of this type may become useful for improving forecasts of sea-ice dynamics.
Urmas Raudsepp and Ilja Maljutenko
Geosci. Model Dev., 15, 535–551, https://doi.org/10.5194/gmd-15-535-2022, https://doi.org/10.5194/gmd-15-535-2022, 2022
Short summary
Short summary
A model's ability to reproduce the state of a simulated object is always a subject of discussion. A new method for the multivariate assessment of numerical model skills uses the K-means algorithm for clustering model errors. All available data that fall into the model domain and simulation period are incorporated into the skill assessment. The clustered errors are used for spatial and temporal analysis of the model accuracy. The method can be applied to different types of geoscientific models.
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.
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
Ocean Sci., 17, 699–728, https://doi.org/10.5194/os-17-699-2021, https://doi.org/10.5194/os-17-699-2021, 2021
Short summary
Short summary
This modelling study describes a methodology for describing pollutant discharges from ships to the sea. The pilot area used is the Baltic Sea area and discharges of bilge, ballast, sewage, wash water as well as stern tube oil are reported for the year 2012. This work also reports the release of SOx scrubber effluents. This technique may be used by ships to comply with tight sulfur limits inside Emission Control Areas, but it also introduces a new pollutant stream from ships to the sea.
Mihhail Zujev, Jüri Elken, and Priidik Lagemaa
Ocean Sci., 17, 91–109, https://doi.org/10.5194/os-17-91-2021, https://doi.org/10.5194/os-17-91-2021, 2021
Short summary
Short summary
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
Ocean Sci., 16, 1143–1163, https://doi.org/10.5194/os-16-1143-2020, https://doi.org/10.5194/os-16-1143-2020, 2020
Short summary
Short summary
Very little is currently known about the activities and emissions of private leisure boats. To change this, a new model was created (BEAM). The model was used for the Baltic Sea to estimate leisure boat emissions, also considering antifouling paint leach. When compared to commercial shipping, the modeled leisure boat emissions were seen to be surprisingly large for some pollutant species, and these emissions were heavily concentrated on coastal inhabited areas during summer and early autumn.
L. Sipelgas, A. Aavaste, and R. Uiboupin
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 627–632, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-627-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-627-2020, 2020
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
Short summary
Short summary
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...
Altmetrics
Final-revised paper
Preprint