Articles | Volume 14, issue 9
https://doi.org/10.5194/gmd-14-5731-2021
© Author(s) 2021. 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/gmd-14-5731-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
16 Sep 2021
Model description paper |
| 16 Sep 2021
| 16 Sep 2021
Nemo-Nordic 2.0: operational marine forecast model for the Baltic Sea
Finnish Meteorological Institute, Helsinki, Finland
Patrik Ljungemyr
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Saeed Falahat
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Ida Ringgaard
Danish Meteorological Institute, Copenhagen, Denmark
Lars Axell
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Vasily Korabel
Danish Meteorological Institute, Copenhagen, Denmark
Jens Murawski
Danish Meteorological Institute, Copenhagen, Denmark
Ilja Maljutenko
Tallinn University of Technology, Tallinn, Estonia
Anja Lindenthal
Bundesamt für Seeschifffahrt und Hydrographie, Hamburg, Germany
Simon Jandt-Scheelke
Bundesamt für Seeschifffahrt und Hydrographie, Hamburg, Germany
Svetlana Verjovkina
Tallinn University of Technology, Tallinn, Estonia
Ina Lorkowski
Bundesamt für Seeschifffahrt und Hydrographie, Hamburg, Germany
Priidik Lagemaa
Tallinn University of Technology, Tallinn, Estonia
Jun She
Danish Meteorological Institute, Copenhagen, Denmark
Laura Tuomi
Finnish Meteorological Institute, Helsinki, Finland
Adam Nord
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Vibeke Huess
Danish Meteorological Institute, Copenhagen, Denmark
Related authors
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary
Short summary
We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
Amirhossein Barzandeh, Matjaž Ličer, Marko Rus, Matej Kristan, Ilja Maljutenko, Jüri Elken, Priidik Lagemaa, and Rivo Uiboupin
Ocean Sci., 21, 1315–1327, https://doi.org/10.5194/os-21-1315-2025, https://doi.org/10.5194/os-21-1315-2025, 2025
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.
Rita Lecci, Robyn Gwee, Kun Yan, Sanne Muis, Nadia Pinardi, Jun She, Martin Verlaan, Simona Masina, Wenshan Li, Hui Wang, Salvatore Causio, Antonio Novellino, Marco Alba, Etiënne Kras, Sandra Gaytan Aguilar, and Jan-Bart Calewaert
EGUsphere, https://doi.org/10.5194/egusphere-2025-1763, https://doi.org/10.5194/egusphere-2025-1763, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
This study explored how sea level is changing along the China-Europe Sea Route. By combining satellite and in-situ observations with advanced modeling, the research identified ongoing sea level rise and an increasing frequency of extreme water level events in some regions. These findings underscore the importance of continued monitoring and provide useful knowledge to support long-term planning, coastal resilience, and informed decision-making.
Hedi Kanarik, Laura Tuomi, Pekka Alenius, Elina Miettunen, Milla Johansson, Tuomo Roine, Antti Westerlund, and Kimmo K. Kahma
EGUsphere, https://doi.org/10.5194/egusphere-2025-1101, https://doi.org/10.5194/egusphere-2025-1101, 2025
Short summary
Short summary
The Archipelago Sea (AS), part of the Baltic Sea off the northwest coast of Finland, is a fragmented area with intense human activity. This study presents an overview of the observed currents and their main drivers in the area. While local winds primarily drive the AS currents, simultaneous sea level variations in the Bay of Bothnia and Gulf of Finland also significantly impact the area's dynamics.
Ye Liu, Lars Axell, and Jun She
EGUsphere, https://doi.org/10.5194/egusphere-2024-3283, https://doi.org/10.5194/egusphere-2024-3283, 2024
Preprint archived
Short summary
Short summary
The temperature and salinity trends at various depths in the Baltic basins from 1990 to 2020 were analyzed from a reasonable reanalysis data set. Overall, the Baltic Sea showed a clear warming trend in recent decades, the northern Baltic Sea has a slight desalination trend, and the southern Baltic Sea has a salinity increase trend. The temperature and salinity trends in the southern Baltic Sea are greater than those in the northern Baltic Sea.
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.
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, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
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
Revised manuscript accepted 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.
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
Preprint archived
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.
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.
Itzel Ruvalcaba Baroni, Elin Almroth-Rosell, Lars Axell, Sam T. Fredriksson, Jenny Hieronymus, Magnus Hieronymus, Sandra-Esther Brunnabend, Matthias Gröger, Ivan Kuznetsov, Filippa Fransner, Robinson Hordoir, Saeed Falahat, and Lars Arneborg
Biogeosciences, 21, 2087–2132, https://doi.org/10.5194/bg-21-2087-2024, https://doi.org/10.5194/bg-21-2087-2024, 2024
Short summary
Short summary
The health of the Baltic and North seas is threatened due to high anthropogenic pressure; thus, different methods to assess the status of these regions are urgently needed. Here, we validated a novel model simulating the ocean dynamics and biogeochemistry of the Baltic and North seas that can be used to create future climate and nutrient scenarios, contribute to European initiatives on de-eutrophication, and provide water quality advice and support on nutrient load reductions for both seas.
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.
Alexandra Marki, Xin Li, and Simon Jandt-Scheelke
EGUsphere, https://doi.org/10.5194/egusphere-2023-3092, https://doi.org/10.5194/egusphere-2023-3092, 2024
Preprint archived
Short summary
Short summary
Aim of the Oxygen Deficiency Index (ODI) blueprint is to inform about the water-quality in the North and Baltic Seas by using observations and model-simulations. The ODI helps us to calculate the probability if low-oxygen conditions might occur, with low ODI values indicating a low risk and vice-versa. We show that the ODI is able to forecast oxygen deficiency zones between 30 to 75 days. Important points in our study were the simplicity of application, deployment and an easy interpretation.
Urmas Raudsepp, Ilja Maljutenko, Amirhossein Barzandeh, Rivo Uiboupin, and Priidik Lagemaa
State Planet, 1-osr7, 7, https://doi.org/10.5194/sp-1-osr7-7-2023, https://doi.org/10.5194/sp-1-osr7-7-2023, 2023
Short summary
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.
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.
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.
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.
Jan-Victor Björkqvist, Siim Pärt, Victor Alari, Sander Rikka, Elisa Lindgren, and Laura Tuomi
Ocean Sci., 17, 1815–1829, https://doi.org/10.5194/os-17-1815-2021, https://doi.org/10.5194/os-17-1815-2021, 2021
Short summary
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.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary
Short summary
We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
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.
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.
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.
Cited articles
Arheimer, B., Dahné, J., Donnelly, C., Lindström, G., and
Strömqvist, J.: Water and nutrient simulations using the HYPE model for
Sweden vs. the Baltic Sea basin – influence of input-data quality
and scale, Hydrol. Res., 43, 315–329, https://doi.org/10.2166/nh.2012.010, 2012. a
Axell, L.: BSRA-15: A Baltic Sea Reanalysis 1990–2004, Reports
Oceanography 45, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden, 2013. a
Brodeau, L., Barnier, B., Gulev, S. K., and Woods, C.: Climatologically
Significant Effects of Some Approximations in the Bulk Parameterizations of
Turbulent Air–Sea Fluxes, J. Phys. Oceanogr., 47,
5–28, https://doi.org/10.1175/jpo-d-16-0169.1, 2016. a
Burchard, H., Janssen, F., Bolding, K., Umlauf, L., and Rennau, H.: Model
simulations of dense bottom currents in the Western Baltic Sea, Cont.
Shelf Res., 29, 205–220, https://doi.org/10.1016/j.csr.2007.09.010, 2009. a
Copernicus: Copernicus Marine Service, available at: https://marine.copernicus.eu/, last access: 13 September 2021. a
Daewel, U. and Schrum, C.: Simulating long-term dynamics of the coupled North
Sea and Baltic Sea ecosystem with ECOSMO II: Model description and
validation, J. Marine Syst., 119-120, 30–49,
https://doi.org/10.1016/j.jmarsys.2013.03.008, 2013. a
Davies, H. C.: A lateral boundary formulation for multi-level prediction
models, Q. J. Roy. Meteor. Soc., 102, 405–418,
https://doi.org/10.1002/qj.49710243210, 1976. a
Dietze, H., Löptien, U., and Getzlaff, K.: MOMBA 1.1 – a high-resolution Baltic Sea configuration of GFDL's Modular Ocean Model, Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, 2014. a, b, c
Döös, K. and Engqvist, A.: Assessment of water exchange between a
discharge region and the open sea – A comparison of different
methodological concepts, Estuarine, Coastal and Shelf Science, 74, 709–721,
https://doi.org/10.1016/j.ecss.2007.05.022, 2007. a
Fischer, H. and Matthäus, W.: The importance of the Drogden Sill in the
Sound for major Baltic inflows, J. Marine Syst., 9, 137–157,
https://doi.org/10.1016/s0924-7963(96)00046-2, 1996. a
Flather, R. A.: A Storm Surge Prediction Model for the Northern Bay of Bengal
with Application to the Cyclone Disaster in April 1991, J. Phys.
Oceanogr., 24, 172–190,
https://doi.org/10.1175/1520-0485(1994)024<0172:asspmf>2.0.co;2, 1994. a
Graham, J. A., O'Dea, E., Holt, J., Polton, J., Hewitt, H. T., Furner, R., Guihou, K., Brereton, A., Arnold, A., Wakelin, S., Castillo Sanchez, J. M., and Mayorga Adame, C. G.: AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf, Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, 2018. a
Gräwe, U., Holtermann, P., Klingbeil, K., and Burchard, H.: Advantages of
vertically adaptive coordinates in numerical models of stratified shelf seas,
Ocean Model., 92, 56–68, https://doi.org/10.1016/j.ocemod.2015.05.008,
2015a. a, b, c
Gräwe, U., Naumann, M., Mohrholz, V., and Burchard, H.: Anatomizing one of the largest saltwater inflows into the Baltic Sea in December 2014, J. Geophys. Res.-Oceans, 120, 7676–7697, https://doi.org/10.1002/2015jc011269, 2015b. a, b
Griffies, S. M. and Hallberg, R. W.: Biharmonic Friction with a
Smagorinsky-Like Viscosity for Use in Large-Scale Eddy-Permitting Ocean
Models, Mon. Weather Rev., 128, 2935–2946,
https://doi.org/10.1175/1520-0493(2000)128<2935:bfwasl>2.0.co;2, 2000. a
Gustafsson, B.: Interaction between Baltic Sea and North Sea, Deutsche
Hydrographische Zeitschrift, 49, 165–183, https://doi.org/10.1007/bf02764031, 1997. a
Gustafsson, B. G. and Andersson, H. C.: Modeling the exchange of the Baltic Sea from the meridional atmospheric pressure difference across the North Sea,
J. Geophys. Res.-Oceans, 106, 19731–19744,
https://doi.org/10.1029/2000jc000593, 2001. a
Hofmeister, R., Beckers, J.-M., and Burchard, H.: Realistic modelling of the
exceptional inflows into the central Baltic Sea in 2003 using
terrain-following coordinates, Ocean Model., 39, 233–247,
https://doi.org/10.1016/j.ocemod.2011.04.007, 2011. a, b
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. a, b, c, d, e, f, g, h, i
Hourdin, F. and Armengaud, A.: The Use of Finite-Volume Methods for Atmospheric Advection of Trace Species. Part I: Test of Various Formulations in a General Circulation Model, Mon. Weather Rev., 127, 822–837,
https://doi.org/10.1175/1520-0493(1999)127<0822:tuofvm>2.0.co;2, 1999. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci.
Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Ilıcak, M., Adcroft, A. J., Griffies, S. M., and Hallberg, R. W.: Spurious
dianeutral mixing and the role of momentum closure, Ocean Model., 45-46,
37–58, https://doi.org/10.1016/j.ocemod.2011.10.003, 2012. a
IOC, SCOR, and IAPSO: The International thermodynamic equation of seawater–2010:
calculation and use of thermodynamic properties [includes corrections up to
31st October 2015], Intergovernmental Oceanographic Commission, Manuals and
Guides Nb. 56, 2010. a
Klingbeil, K., Mohammadi-Aragh, M., Gräwe, U., and Burchard, H.:
Quantification of spurious dissipation and mixing – Discrete
variance decay in a Finite-Volume framework, Ocean Model., 81, 49–64,
https://doi.org/10.1016/j.ocemod.2014.06.001, 2014. a, b
Lagemaa, P., Suhhova, I., Nomm, M., Pavelson, J., and Elken, J.: Comparison of current simulations by the state-of-the-art operational models in the Gulf of Finland with ADCP measurements, in: 2010 IEEE/OES Baltic International Symposium (BALTIC), IEEE, https://doi.org/10.1109/baltic.2010.5621656, 24–27 August 2010, Riga, Latvia, 2010. a
Large, W. and Yeager, S.: Diurnal to decadal global forcing for ocean and
sea-ice models: The data sets and flux climatologies, Tech. rep., National
Center for Atmospheric Research, Boulder, Colorado, United States,
https://doi.org/10.5065/D6KK98Q6, 2004. a
Lehmann, A.: A three-dimensional baroclinic eddy-resolving model of the Baltic Sea, Tellus A, 47, 1013–1031,
https://doi.org/10.3402/tellusa.v47i5.11969, 1995. a
Lemieux, J.-F., Dupont, F., Blain, P., Roy, F., Smith, G. C., and Flato, G. M.: Improving the simulation of landfast ice by combining tensile strength and a parameterization for grounded ridges, J. Geophys. Res.-Oceans, 121, 7354–7368, https://doi.org/10.1002/2016jc012006, 2016. a
Lévy, M., Estublier, A., and Madec, G.: Choice of an advection scheme for biogeochemical models, Geophys. Res. Lett., 28, 3725–3728,
https://doi.org/10.1029/2001gl012947, 2001. a
Madec, G., Bourdallé-Badie, R., Chanut, J., Clementi, E., Coward, A., Ethé,
C., Iovino, D., Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S.,
Mocavero, S., Rousset, C., Storkey, D., Vancoppenolle, M., Müeller, S.,
Nurser, G., Bell, M., and Samson, G.: NEMO ocean engine, Zenodo,
https://doi.org/10.5281/zenodo.3878122, 2019. a, b, c
Met Office: Iris: A Python package for analysing and visualising
meteorological and oceanographic data sets, Exeter, Devon, v2.4 edn., available at: https://scitools.org.uk/iris/docs/v2.4.0/ (last access: 29 March 2021), 2010–2020. a
Mohrholz, V.: Major Baltic Inflow Statistics – Revised, Frontiers
in Marine Science, 5, 384, https://doi.org/10.3389/fmars.2018.00384, 2018. a
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. a, b, c
Nemo-Nordic development team: Nemo-Nordic ocean model source code (Version
2.0), Zenodo [code], https://doi.org/10.5281/zenodo.4665840, 2021. a
O'Dea, E., Bell, M. J., Coward, A., and Holt, J.: Implementation and assessment of a flux limiter based wetting and drying scheme in NEMO, Ocean Model., 155, 101708, https://doi.org/10.1016/j.ocemod.2020.101708, 2020. a
Pätsch, J., Burchard, H., Dieterich, C., Gräwe, U., Gröger, M.,
Mathis, M., Kapitza, H., Bersch, M., Moll, A., Pohlmann, T., Su, J.,
Ho-Hagemann, H. T., Schulz, A., Elizalde, A., and Eden, C.: An evaluation of
the North Sea circulation in global and regional models relevant for
ecosystem simulations, Ocean Model., 116, 70–95,
https://doi.org/10.1016/j.ocemod.2017.06.005, 2017. a
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. a
Reffray, G., Bourdalle-Badie, R., and Calone, C.: Modelling turbulent vertical mixing sensitivity using a 1-D version of NEMO, Geosci. Model Dev., 8, 69–86, https://doi.org/10.5194/gmd-8-69-2015, 2015. a
Rennau, H. and Burchard, H.: Quantitative analysis of numerically induced
mixing in a coastal model application, Ocean Dynam., 59, 671–687,
https://doi.org/10.1007/s10236-009-0201-x, 2009. a
Roquet, F., Madec, G., McDougall, T. J., and Barker, P. M.: Accurate polynomial expressions for the density and specific volume of seawater using the TEOS-10 standard, Ocean Model., 90, 29–43,
https://doi.org/10.1016/j.ocemod.2015.04.002, 2015. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a
She, J., Berg, P., and Berg, J.: Bathymetry impacts on water exchange modelling through the Danish Straits, J. Marine Syst., 65, 450–459,
https://doi.org/10.1016/j.jmarsys.2006.01.017, 2007. a, b, c
She, J., Meier, H. E. M., Darecki, M., Gorringe, P., Huess, V., Kouts, T.,
Reissmann, J. H., and Tuomi, L.: Baltic Sea Operational
Oceanography – A Stimulant for Regional Earth System Research,
Frontiers in Earth Science, 8, 7, https://doi.org/10.3389/feart.2020.00007, 2020. a
Stanev, E., Pein, J., Grashorn, S., Zhang, Y., and Schrum, C.: Dynamics of the Baltic Sea straits via numerical simulation of exchange flows, Ocean
Model., 131, 40–58, https://doi.org/10.1016/j.ocemod.2018.08.009, 2018. a, b
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192,
https://doi.org/10.1029/2000jd900719, 2001. a
Umlauf, L. and Burchard, H.: A generic length-scale equation for geophysical
turbulence models, J. Mar. Res., 61, 235–265,
https://doi.org/10.1357/002224003322005087, 2003.
a
Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., and
Maqueda, M. A. M.: Simulating the mass balance and salinity of Arctic and
Antarctic sea ice. 1. Model description and validation, Ocean Model., 27,
33–53, https://doi.org/10.1016/j.ocemod.2008.10.005, 2009. a
Zalesak, S. T.: Fully multidimensional flux-corrected transport algorithms for fluids, J. Comput. Phys., 31, 335–362,
https://doi.org/10.1016/0021-9991(79)90051-2, 1979. a
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.
We present Nemo-Nordic 2.0, a novel operational marine model for the Baltic Sea. The model...
Special issue