Articles | Volume 12, issue 1
https://doi.org/10.5194/gmd-12-363-2019
© Author(s) 2019. 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-12-363-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
21 Jan 2019
Model description paper |
| 21 Jan 2019
| 21 Jan 2019
Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applications
Robinson Hordoir
CORRESPONDING AUTHOR
Institute of Marine Research, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Lars Axell
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Anders Höglund
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Christian Dieterich
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Filippa Fransner
Department of Meteorology, Stockholm University and Bolin Centre for Climate Research, Stockholm, Sweden
Geophysical Institute, Bergen University, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Matthias Gröger
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Ye Liu
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Per Pemberton
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Semjon Schimanke
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Helen Andersson
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Patrik Ljungemyr
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Petter Nygren
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Saeed Falahat
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Adam Nord
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Anette Jönsson
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Iréne Lake
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Kristofer Döös
Department of Meteorology, Stockholm University and Bolin Centre for Climate Research, Stockholm, Sweden
Magnus Hieronymus
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Heiner Dietze
GEOMAR, Helmholtz Centre for Ocean Research, Kiel, Germany
Ulrike Löptien
GEOMAR, Helmholtz Centre for Ocean Research, Kiel, Germany
Ivan Kuznetsov
Institute of Coastal Research, Helmholtz-Zentrum, Geesthacht, Germany
Antti Westerlund
Finnish Meteorological Institute, Helsinki, Finland
Laura Tuomi
Finnish Meteorological Institute, Helsinki, Finland
Jari Haapala
Finnish Meteorological Institute, Helsinki, Finland
Related authors
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.
Imke Sievers, Andrea M. U. Gierisch, Till A. S. Rasmussen, Robinson Hordoir, and Lars Stenseng
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-84, https://doi.org/10.5194/tc-2022-84, 2022
Preprint withdrawn
Short summary
Short summary
To predict Arctic sea ice models are used. Many ice models exists. They all are skill full, but give different results. Often this differences result from forcing as for example air temperature. Other differences result from the way the physical equations are solved in the model. In this study two commonly used models are compared under equal forcing, to find out how much the models differ under similar external forcing. The results are compared to observations and to eachother.
Alex C. Ruane, Charlotte L. Pascoe, Claas Teichmann, David J. Brayshaw, Carlo Buontempo, Ibrahima Diouf, Jesus Fernandez, Paula L. M. Gonzalez, Birgit Hassler, Vanessa Hernaman, Ulas Im, Doroteaciro Iovino, Martin Juckes, Iréne L. Lake, Timothy Lam, Xiaomao Lin, Jiafu Mao, Negin Nazarian, Sylvie Parey, Indrani Roy, Wan-Ling Tseng, Briony Turner, Andrew Wiebe, Lei Zhao, and Damaris Zurell
EGUsphere, https://doi.org/10.5194/egusphere-2025-3408, https://doi.org/10.5194/egusphere-2025-3408, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This paper describes how the Coupled Model Intercomparison Project organized its 7th phase (CMIP7) to encourage the production of Earth system model outputs relevant for impacts and adaptation. Community engagement identified 13 opportunities for application across human and natural systems, 60 variable groups and 539 unique variables. We also show how simulations can more efficiently meet applications needs by targeting appropriate resolution, time slices, experiments and variable groups.
Igor V. Polyakov, Andrey V. Pnyushkov, Eddy C. Carmack, Matthew Charette, Kyoung-Ho Cho, Steven Dykstra, Jari Haapala, Jinyoung Jung, Lauren Kipp, and Eun Jin Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2316, https://doi.org/10.5194/egusphere-2025-2316, 2025
Short summary
Short summary
The Siberian Arctic Ocean greatly influences the Arctic climate system. Moreover, the region is experiencing some of the most notable Arctic climate change. In the summer, strong near-inertial currents in the upper (<30m) ocean account for more than half of the current speed and shear. In the winter, upper ocean ventilation due to atlantification distributes wind energy to far deeper (>100m) layers. Understanding the implications for mixing and halocline weakening depends on these findings.
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.
Heiner Dietze and Ulrike Löptien
Biogeosciences, 22, 1215–1236, https://doi.org/10.5194/bg-22-1215-2025, https://doi.org/10.5194/bg-22-1215-2025, 2025
Short summary
Short summary
We introduce argon saturation as a prognostic variable in a suite of coupled general ocean circulation biogeochemical models off Mauritania. Our results indicate that the effect of increasing the spatial horizontal model resolutions from 12 km to 1.5 km leads to changes comparable to other infamous spurious effects of state-of-the-art numerical advection numerics.
Matias Uusinoka, Jari Haapala, Jan Åström, Mikko Lensu, and Arttu Polojärvi
EGUsphere, https://doi.org/10.5194/egusphere-2025-311, https://doi.org/10.5194/egusphere-2025-311, 2025
Short summary
Short summary
We tracked sea ice deformation over a nine-month period using high-resolution ship radar data and a state-of-the-art deep learning technique. We observe that the typically consistent scale-invariant pattern in sea ice deformation has a lower limit of about 102 meters in winter, but this behavior disappears during summer. Our findings provide critical insights for considering current modeling assumptions and for connecting the scales of interest in sea ice 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.
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.
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.
Jenny Hieronymus, Magnus Hieronymus, Matthias Gröger, Jörg Schwinger, Raffaele Bernadello, Etienne Tourigny, Valentina Sicardi, Itzel Ruvalcaba Baroni, and Klaus Wyser
Biogeosciences, 21, 2189–2206, https://doi.org/10.5194/bg-21-2189-2024, https://doi.org/10.5194/bg-21-2189-2024, 2024
Short summary
Short summary
The timing of the net primary production annual maxima in the North Atlantic in the period 1750–2100 is investigated using two Earth system models and the high-emissions scenario SSP5-8.5. It is found that, for most of the region, the annual maxima occur progressively earlier, with the most change occurring after the year 2000. Shifts in the seasonality of the primary production may impact the entire ecosystem, which highlights the need for long-term monitoring campaigns in this area.
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.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
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.
Thomas Spangehl, Michael Borsche, Deborah Niermann, Frank Kaspar, Semjon Schimanke, Susanne Brienen, Thomas Möller, and Maren Brast
Adv. Sci. Res., 20, 109–128, https://doi.org/10.5194/asr-20-109-2023, https://doi.org/10.5194/asr-20-109-2023, 2023
Short summary
Short summary
The quality of the global reanalysis ERA5, the regional reanalysis COSMO-REA6 and a successor version (R6G2), the new Copernicus European Regional Re-Analysis (CERRA) and a regional downscaling simulation with COSMO-CLM (HoKliSim-De) is assessed for offshore wind farm planning in the German Exclusive Economic Zone (EEZ) of the North Sea. The quality is assessed using in-situ wind measurements at the research platform FINO1 and satellite-based data of the near-surface wind speed as reference.
Dipanjan Dey, Aitor Aldama Campino, and Kristofer Döös
Hydrol. Earth Syst. Sci., 27, 481–493, https://doi.org/10.5194/hess-27-481-2023, https://doi.org/10.5194/hess-27-481-2023, 2023
Short summary
Short summary
One of the most striking and robust features of climate change is the acceleration of the atmospheric water cycle branch. Earlier studies were able to provide a quantification of the global atmospheric water cycle, but they missed addressing the atmospheric water transport connectivity within and between ocean basins and land. These shortcomings were overcome in the present study and presented a complete synthesised and quantitative view of the atmospheric water cycle.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
Short summary
Short summary
Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
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.
Imke Sievers, Andrea M. U. Gierisch, Till A. S. Rasmussen, Robinson Hordoir, and Lars Stenseng
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-84, https://doi.org/10.5194/tc-2022-84, 2022
Preprint withdrawn
Short summary
Short summary
To predict Arctic sea ice models are used. Many ice models exists. They all are skill full, but give different results. Often this differences result from forcing as for example air temperature. Other differences result from the way the physical equations are solved in the model. In this study two commonly used models are compared under equal forcing, to find out how much the models differ under similar external forcing. The results are compared to observations and to eachother.
Dmitry V. Sein, Anton Y. Dvornikov, Stanislav D. Martyanov, William Cabos, Vladimir A. Ryabchenko, Matthias Gröger, Daniela Jacob, Alok Kumar Mishra, and Pankaj Kumar
Earth Syst. Dynam., 13, 809–831, https://doi.org/10.5194/esd-13-809-2022, https://doi.org/10.5194/esd-13-809-2022, 2022
Short summary
Short summary
The effect of the marine biogeochemical variability upon the South Asian regional climate has been investigated. In the experiment where its full impact is activated, the average sea surface temperature is lower over most of the ocean. When the biogeochemical coupling is included, the main impacts include the enhanced phytoplankton primary production, a shallower thermocline, decreased SST and water temperature in subsurface layers.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
Short summary
Short summary
The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Matthias Gröger, Christian Dieterich, Cyril Dutheil, H. E. Markus Meier, and Dmitry V. Sein
Earth Syst. Dynam., 13, 613–631, https://doi.org/10.5194/esd-13-613-2022, https://doi.org/10.5194/esd-13-613-2022, 2022
Short summary
Short summary
Atmospheric rivers transport high amounts of water from subtropical regions to Europe. They are an important driver of heavy precipitation and flooding. Their response to a warmer future climate in Europe has so far been assessed only by global climate models. In this study, we apply for the first time a high-resolution regional climate model that allow to better resolve and understand the fate of atmospheric rivers over Europe.
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.
H. E. Markus Meier, Christian Dieterich, Matthias Gröger, Cyril Dutheil, Florian Börgel, Kseniia Safonova, Ole B. Christensen, and Erik Kjellström
Earth Syst. Dynam., 13, 159–199, https://doi.org/10.5194/esd-13-159-2022, https://doi.org/10.5194/esd-13-159-2022, 2022
Short summary
Short summary
In addition to environmental pressures such as eutrophication, overfishing and contaminants, climate change is believed to have an important impact on the marine environment in the future, and marine management should consider the related risks. Hence, we have compared and assessed available scenario simulations for the Baltic Sea and found considerable uncertainties of the projections caused by the underlying assumptions and model biases, in particular for the water and biogeochemical cycles.
Ole Bøssing Christensen, Erik Kjellström, Christian Dieterich, Matthias Gröger, and Hans Eberhard Markus Meier
Earth Syst. Dynam., 13, 133–157, https://doi.org/10.5194/esd-13-133-2022, https://doi.org/10.5194/esd-13-133-2022, 2022
Short summary
Short summary
The Baltic Sea Region is very sensitive to climate change, whose impacts could easily exacerbate biodiversity stress from society and eutrophication of the Baltic Sea. Therefore, there has been a focus on estimations of future climate change and its impacts in recent research. Models show a strong warming, in particular in the north in winter. Precipitation is projected to increase in the whole region apart from the south during summer. New results improve estimates of future climate change.
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.
Henrike Schmidt, Julia Getzlaff, Ulrike Löptien, and Andreas Oschlies
Ocean Sci., 17, 1303–1320, https://doi.org/10.5194/os-17-1303-2021, https://doi.org/10.5194/os-17-1303-2021, 2021
Short summary
Short summary
Oxygen-poor regions in the open ocean restrict marine habitats. Global climate simulations show large uncertainties regarding the prediction of these areas. We analyse the representation of the simulated oxygen minimum zones in the Arabian Sea using 10 climate models. We give an overview of the main deficiencies that cause the model–data misfit in oxygen concentrations. This detailed process analysis shall foster future model improvements regarding the oxygen minimum zone in the Arabian Sea.
Matthias Gröger, Christian Dieterich, Jari Haapala, Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Jaromir Jakacki, Wilhelm May, H. E. Markus Meier, Paul A. Miller, Anna Rutgersson, and Lichuan Wu
Earth Syst. Dynam., 12, 939–973, https://doi.org/10.5194/esd-12-939-2021, https://doi.org/10.5194/esd-12-939-2021, 2021
Short summary
Short summary
Regional climate studies are typically pursued by single Earth system component models (e.g., ocean models and atmosphere models). These models are driven by prescribed data which hamper the simulation of feedbacks between Earth system components. To overcome this, models were developed that interactively couple model components and allow an adequate simulation of Earth system interactions important for climate. This article reviews recent developments of such models for the Baltic Sea region.
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.
Heiner Dietze and Ulrike Löptien
Biogeosciences, 18, 4243–4264, https://doi.org/10.5194/bg-18-4243-2021, https://doi.org/10.5194/bg-18-4243-2021, 2021
Short summary
Short summary
In recent years fish-kill events caused by oxygen deficit have been reported in Eckernförde Bight (Baltic Sea). This study sets out to understand the processes causing respective oxygen deficits by combining high-resolution coupled ocean circulation biogeochemical modeling, monitoring data, and artificial intelligence.
Britta Munkes, Ulrike Löptien, and Heiner Dietze
Biogeosciences, 18, 2347–2378, https://doi.org/10.5194/bg-18-2347-2021, https://doi.org/10.5194/bg-18-2347-2021, 2021
Short summary
Short summary
Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their controls are, however, not comprehensively understood, which impedes effective management and protection plans. Here we review the current understanding of cyanobacteria blooms. Juxtaposition of respective field and laboratory studies with state-of-the-art mathematical models reveals substantial uncertainty associated with nutrient demands, grazing, and death of cyanobacteria.
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.
Stelios Myriokefalitakis, Matthias Gröger, Jenny Hieronymus, and Ralf Döscher
Ocean Sci., 16, 1183–1205, https://doi.org/10.5194/os-16-1183-2020, https://doi.org/10.5194/os-16-1183-2020, 2020
Short summary
Short summary
Global inorganic and organic nutrient deposition fields are coupled to PISCES to investigate their effect on ocean biogeochemistry. Pre-industrial deposition fluxes are lower compared to the present day, resulting in lower oceanic productivity. Future changes result in a modest decrease in the nutrients put into the global ocean. This work provides a first assessment of the atmospheric organic nutrients' contribution, highlighting the importance of their representation in biogeochemistry models.
Cited articles
Ådlandsvik, B. and Bentsen, M.: Downscaling a twentieth century global
climate simulation to the North Sea, Ocean Dynam., 57, 453–466, 2007. a
Andersen, J. H., Carstensen, J., Conley, D. J., Dromph, K., Fleming-Lehtinen,
V., Gustafsson, B. G., Josefson, A. B., Norkko, A., Villnäs, A., and
Murray, C.: Long-term temporal and spatial trends in eutrophication status of
the Baltic Sea, Biol. Rev., 92, 135–149, https://doi.org/10.1111/brv.12221,
2017. a
Baretta-Bekker, J., Baretta, J., Latuhihin, M., Desmit, X., and Prins, T.:
Description of the long-term (1991–2005) temporal and spatial distribution
of phytoplankton carbon biomass in the Dutch North Sea, J. Sea
Res., 61, 50–59, https://doi.org/10.1016/j.seares.2008.10.007,
2009. a
Berg, P., Döscher, R., and Koenigk, T.: Impacts of using spectral nudging
on regional climate model RCA4 simulations of the Arctic, Geosci. Model Dev.,
6, 849–859, https://doi.org/10.5194/gmd-6-849-2013, 2013. a
Bersch, M., Gouretski, V., Sadikni, R., and Hinrichs, I.: Hydrographic
climatology of the North Sea and surrounding regions, Centre for Earth System
Research and Sustainability (CEN), University of Hamburg,
available at: https://icdc.cen.unihamburg.de/1/projekte/knsc.html (last access: 17 January 2019),
2013. a, b
Boesch, D., Hecky, R., O'Melia, C., Schindler, D., and Seitzinger, D.:
Eutrophication of Swedish seas,
Swedish Environmental Protection Agency Report, 1–72, 2006. 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
Carstensen, J., Andersen, J. H., Gustafsson, B. G., and Conley, D. J.:
Deoxygenation of the Baltic Sea during the last century, P.
Natl. Acad. Sci. USA, 111, 5628–5633, https://doi.org/10.1073/pnas.1323156111,
2014. 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, b, c
Dahlgren, P., Landelius, T., Kallberg, P., and Gollvik, S.: A high resolution
regional reanalysis for Europe Part 1: 3-dimensional reanalysis with the
regional HIgh Resolution Limited Area Model (HIRLAM), Q. J. Roy. Meteor.
Soc., 698, 2119–2131, https://doi.org/10.1002/qj.2807, 2016. a
Donnelly, C., Andersson, J. C., and Arheimer, B.: Using flow signatures and
catchment similarities to evaluate the E-HYPE multi-basin model across
Europe, Hydrolog. Sci. J., 61, 255–273,
https://doi.org/10.1080/02626667.2015.1027710,
2016. a
Döös, K., Meier, M., and Döscher, R.: The Baltic Haline Conveyor Belt
or The Overturning Circulation and Mixing in the Baltic, Ambio, 33, 261–267,
https://doi.org/10.1579/0044-7447-33.4.261, 2004. a, b
Egbert, G., Bennett, A., and Foreman, M.: TOPEX/Poseidon tides estimated
using
a global inverse model, J. Geophys. Res., 99, 24821–24852,
https://doi.org/10.1029/94JC01894, 1994. a
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic
Ocean Tides, J. Atmos. Ocean. Tech., 19, 183–204,
https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2,
2002. a
Eilola, K., Meier, H. M., and Almroth, E.: On the dynamics of oxygen,
phosphorus and cyanobacteria in the Baltic Sea; A model study, J.
Marine Syst., 75, 163–184,
https://doi.org/10.1016/j.jmarsys.2008.08.009,
2009. a, b
Elken, J. and Matthäus, W.: Physical system Description, in: Assmesment
of
Climate Change for the Baltic Sea Basin, edited by: BACC Author Team, chap.
Annex A1, Springer-Verlag, Berlin, 379–386, 2008. a
Emeis, K.-C., van Beusekom, J., Callies, U., Ebinghaus, R., Kannen, A.,
Kraus, G., Kröncke, I., Lenhart, H., Lorkowski, I., Matthias, V.,
Möllmann, C., Pätsch, J., Scharfe, M., Thomas, H., Weisse, R., and
Zorita, E.: The North Sea – A shelf sea in the Anthropocene, J. Marine
Syst.,
141, 18–33, https://doi.org/10.1016/j.jmarsys.2014.03.012,
2015. a
Fonselius, S. and Valderrama, J.: One hundred years of hydrographic
measurements in the Baltic Sea, J. Sea Res., 49, 229–241,
https://doi.org/10.1016/S1385-1101(03)00035-2,
2003. a
Fransner, F., Nycander, J., Mörth, C.-M., Humborg, C., Markus Meier,
H. E.,
Hordoir, R., Gustafsson, E., and Deutsch, B.: Tracing terrestrial DOC in the
Baltic Sea – A 3-D model study, Global Biogeochem. Cy., 30, 134–148,
https://doi.org/10.1002/2014GB005078,
2016. a
Fransner, F., Gustafsson, E., Tedesco, L., Vichi, M., Hordoir, R., Roquet,
F.,
Spilling, K., Kuznetsov, I., Eilola, K., Mörth, C. M., Humborg, C., and
Nycander, J.: Non-Redfieldian dynamics explain seasonal pCO2 drawdown in the
Gulf of Bothnia, J. Geophys. Res.-Oceans, 123, 166–188,
https://doi.org/10.1002/2017JC013019,
2018. a, b
Fredrik Wulff, Anders Stigebrandt, L. R.: Nutrient Dynamics of the Baltic
Sea,
Ambio, 19, 126–133,
1990. a
Galperin, B., Kantha, L. H., Hassid, S., and Rosati, A.: A Quasi-equilibrium
Turbulent Energy Model for Geophysical Flows, J. Atmos. Sci.,
45, 55–62, 1988. a
Godhe, A., Egardt, J., Kleinhans, D., Sundqvist, L., Hordoir, R., and
Jonsson,
P.: Seascape analysis reveals regional gene flow patterns among populations
of a marine planktonic diatom, P. R. Soc. B, 280, 1773, https://doi.org/10.1098/rspb.2013.1599,
2013. 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., Burchard, H., Naumann, M., and Mohrholz, V.: 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,
2015a. a, b
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,
2015b. a
Gröger, M., Maier-Reimer, E., Mikolajewicz, U., Moll, A., and Sein, D.: NW
European shelf under climate warming: implications for open ocean – shelf
exchange, primary production, and carbon absorption, Biogeosciences, 10,
3767–3792, https://doi.org/10.5194/bg-10-3767-2013, 2013. a
Gröger, M., Dieterich, C., Meier, M., and Schimanke, S.: Thermal air–sea
coupling in hindcast simulations for the North Sea and Baltic Sea on the NW
European shelf, Tellus A, 67, 26911, https://doi.org/10.3402/tellusa.v67.26911,
2015. a, b
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
Hjøllo, S. S., Skogen, M. D., and Svendsen, E.: Exploring
currents and heat within the North Sea using a numerical model, J. Marine
Syst, 78, 180–192, https://doi.org/10.1016/j.jmarsys.2009.06.001, 2009.
Höglund, A., Pemberton, P., Hordoir, R., and Schimanke, S.: Ice conditions
for maritime traffic in the Baltic Sea in future climate, Boreal Environ. Res.,
22, 245–265, 2017. a
Holt, J., Wakelin, S., Lowe, J., and Tinker, J.: The potential impacts of
climate change on the hydrography of the northwest European continental
shelf, Prog. Oceanogr., 86, 361–379, 2010. a
Holt, J., Butenschön, M., Wakelin, S. L., Artioli, Y., and Allen, J. I.:
Oceanic controls on the primary production of the northwest European
continental shelf: model experiments under recent past conditions and a
potential future scenario, Biogeosciences, 9, 97–117,
https://doi.org/10.5194/bg-9-97-2012, 2012. a
Hordoir, R. and Meier, H. E. M.: Freshwater Fluxes in the Baltic Sea – A
Model Study, J. Geophys. Res., 15, C08028, https://doi.org/10.1029/2009JC005604,
2010. a
Hordoir, R., Dieterich, C., Basu, C., Dietze, H., and Meier, M.: Freshwater
outflow of the Baltic Sea and transport in the Norwegian current: A
statistical correlation analysis based on a numerical experiment, Cont.
Shelf Re., 64, 1–9,
https://doi.org/10.1016/j.csr.2013.05.006,
2013. a, b, c, d
Hordoir, R., Axell, L., Höglund, A., Dieterich, C.,
Fransner, F., Gröger, M., and Haapala, J.: Nemo-Nordic 1.0: A NEMO based
ocean model for Baltic & North Seas, research and operational applications,
Zenodo, https://doi.org/10.5281/zenodo.1493117, 2018. a
Huthnance, J. M., Holt, J. T., and Wakelin, S. L.: Deep ocean exchange with
west-European shelf seas, Ocean Sci., 5, 621–634,
https://doi.org/10.5194/os-5-621-2009, 2009. a
Janssen, F., Schrum, C., and Backhaus, J. O.: A climatological data set of
temperature and salinity for the Baltic Sea and the North Sea, Deutsche
Hydrografische Zeitschrift, 51, 5 pp., https://doi.org/10.1007/BF02933676,
1999. a, b, c
Köster, F. W., Möllmann, C., Neuenfeldt, S., Vinther, M., Kraus, G.,
and Voss, R.: Fish stock development in the central Baltic Sea (1974–1999)
in relation to variability in the environment, ICES Marine Science Symposia,
219, available at: http://www.ices.dk/sites/pub/CM Doccuments/2001/U/U0601.pdf (last access: 17 January 2019), 2003. a
Landelius, T., Dahlgren, P., Gollvik, S., Jansson, A., and Olsson, E.: A high
resolution regional reanalysis for Europe Part 2: 2D analysis of surface
temperature, precipitation and wind, Q. J. Roy. Meteor. Soc., 142, 2132–2142, https://doi.org/10.1002/qj.2813, 2016. a, b, c, d
Large, W. and Yeager, S.: The global climatology of an interannually varying
air-sea flux data set, Clim. Dynam., 33, 341–364,
10.1007/s00382-008-0441-3, 2009. a
Lyard, F., Lefevre, F., Letellier, T., and Francis, O.: Modelling the global
ocean tides: modern insights from FES2004, Ocean Dynam., 56, 394–
415,
https://doi.org/10.1007/s10236-006-0086-x,
2006. a
Madsen, K. S., Høyer, J. L., Fu, W., and Donlon, C.: Blending of satellite
and tide gauge sea level observations and its assimilation in a storm surge
model of the North Sea and Baltic Sea, J. Geophys. Res.-Oceans, 120, 6405–6418, https://doi.org/10.1002/2015JC011070,
2015. a
Maraldi, C., Chanut, J., Levier, B., Ayoub, N., De Mey, P., Reffray, G.,
Lyard, F., Cailleau, S., Drévillon, M., Fanjul, E. A., Sotillo, M. G.,
Marsaleix, P., and the Mercator Research and Development Team: NEMO on the
shelf: assessment of the Iberia–Biscay–Ireland configuration, Ocean Sci.,
9, 745–771, https://doi.org/10.5194/os-9-745-2013, 2013. a, b, c
Mathis, M. and Pohlmann, T.: Projection of physical conditions in the North
Sea
for the 21st century, Clim. Res., 61, 1–17, https://doi.org/10.3354/cr01232,
2014. a, b
Mathis, M., Mayer, B., and Pohlmann, T.: An uncoupled dynamical downscaling
for
the North Sea: Method and evaluation, Ocean Model., 72, 153–166,
https://doi.org/10.1016/j.ocemod.2013.09.004,
2013. a, b, c
Mathis, M., Elizalde, A., Mikolajewicz, U., and Pohlmann, T.: Variability
patterns of the general circulation and sea water temperature in the North
Sea, Prog. Oceanogr., 135, 91–112,
https://doi.org/10.1016/j.pocean.2015.04.009,
2015. a
Meier, H. and Kauker, F.: Sensitivity of the Baltic Sea salinity to the
freshwater supply, Clim. Res., 24, 231–242, 2003. a
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. a
Meier, H. E. M., Döscher, R., and Faxén, T.: A multiprocessor coupled
ice-ocean model for the Baltic Sea: Application to salt inflow, J.
Geophys. Res., 108, 3273, https://doi.org/10.1029/2000JC000521, 2003. a, b, c
Meier, M.: Simulated sea level in past and future climates of the Baltic Sea,
Clim. Res., 27, 59–75,
2004. a
Meyer, E. M., Pohlmann, T., and Weisse, R.: Thermodynamic variability and
change in the North Sea (1948–2007) derived from a multidecadal hindcast,
J. Marine Syst., 86, 35–44,
https://doi.org/10.1016/j.jmarsys.2011.02.001,
2011. a
Moksnes, P.-O., Corell, H., Tryman, K., Hordoir, R., and Jonsson, P. R.:
Larval
behavior and dispersal mechanisms in shore crab larvae (Carcinus maenas):
Local adaptations to different tidal environments?, Limnol.
Oceanogr., 59, 588–602, https://doi.org/10.4319/lo.2014.59.2.0588,
2014. a
Moll, A.: Regional distribution of primary production simulated by a three
dimensional model, J. Marine Syst., 16, 150–170, 1998. a
Neumann, T., Eilola, K., Gustafsson, B., Müller-Karulis, B., Kuznetsov,
I.,
Meier, H. E. M., and Savchuk, O. P.: Extremes of Temperature, Oxygen and
Blooms in the Baltic Sea in a Changing Climate, Ambio, 41, 574–585,
https://doi.org/10.1007/s13280-012-0321-2,
2012. a
Nielsen, M. H.: The baroclinic surface currents in the Kattegat, J.
Marine Syst., 55, 97–121,
https://doi.org/10.1016/j.jmarsys.2004.08.004,
2005. a
Otto, L., Zimmerman, J., Furnes, G., Mork, M., Saetre, R., and Becker, G.:
Review of the physical oceanography of the North Sea, Neth. J.
Sea Res., 26, 161–238,
https://doi.org/10.1016/0077-7579(90)90091-T,
1990. a, b, c, d
Pätsch, J. and Kühn, W.: Nitrogen and carbon cycling in the North Sea
and exchange with the North Atlantic – A model study. Part I. Nitrogen budget
and fluxes, Cont. Shelf Res., 28, 767–787,
https://doi.org/10.1016/j.csr.2007.12.013,
2008. 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, 2017. a, b
Pawlak., J., Laamanen, M., and Andersen, J.: Eutrophication in the Baltic Sea
– an integrated thematic assessment of the effects of nutrient enrichment
in the Baltic Sea region. An executive summary, Baltic Sea Environment
Proceedings, Helsinki Commision, 2009. 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, b
Pham, T. V., Brauch, J., Dieterich, C., Frueh, B., and Ahrens, B.: New
coupled
atmosphere-ocean-ice system COSMO-CLM/NEMO: assessing air temperature
sensitivity over the North and Baltic Seas, Oceanologia, 56, 167–189,
https://doi.org/10.5697/oc.56-2.167,
2014. a
Pohlmann, T.: Calculating the development of the thermal vertical
stratification in the North Sea with a three-dimensional baroclinic
circulation model, Cont. Shelf Res., 16, 163–194,
https://doi.org/10.1016/0278-4343(95)00018-V,
1996. a
Radach, G. and Moll, A.: Review of three-dimensional ecological modelling
related to the North Sea shelf system Part 2: model validation and data
needs, Oceanogr. Mar. Biol., 44, 1–60, 2006.
Savchuk, O. P.: Resolving the Baltic Sea into seven subbasins: N and P
budgets
for 1991–1999, J. Marine Syst., 56, 1–15, 2005. a
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. a
Schrum, C.: Regionalization of climate change for the North Sea and Baltic
Sea,
Clim. Res., 18, 31–37, 2001. a
Schrum, C. and Backhaus, J.: Sensitivity of atmosphere–ocean heat exchange
and
heat content in the North Sea and the Baltic Sea, Tellus A, 51, 526–549,
2011. a
Schrum, C., Hübner, U., Jacob, D., and Podzun, R.: A coupled
atmosphere/ice/ocean model for the North Sea and the Baltic Sea, Clim.
Dynam., 21, 131–151, https://doi.org/10.1007/s00382-003-0322-8,
2003. a
Shapiro, G., Luneva, M., Pickering, J., and Storkey, D.: The effect of
various vertical discretization schemes and horizontal diffusion
parameterization on the performance of a 3-D ocean model: the Black Sea case
study, Ocean Sci., 9, 377–390, https://doi.org/10.5194/os-9-377-2013, 2013. a
Simpson, J. and Souza, A.: Semidiurnal switching of stratification in the
region of freshwater influence of the Rhine, J. Geophys. Res., 100,
7037–7044, 1995. a
Skagseth, Ø., Drinkwater, K. F., and Terrile, E.: Wind- and
buoyancy-induced
transport of the Norwegian Coastal Current in the Barents Sea, J.
Geophys. Res.-Oceans, 116, c08007, https://doi.org/10.1029/2011JC006996,
2011. a
Skogen, M. D., Drinkwater, K., Hjøllo, S. S., and Schrum, C.: North Sea
sensitivity to atmospheric forcing, J. Marine Syst., 85, 106–114, https://doi.org/10.1016/j.jmarsys.2010.12.008,
2011. a, b, c
Staneva, J., Wahle, K., Günther, H., and Stanev, E.: Coupling of wave and
circulation models in coastal–ocean predicting systems: a case study for the
German Bight, Ocean Sci., 12, 797–806,
https://doi.org/10.5194/os-12-797-2016, 2016. a
Stigebrandt, A.: Physical Oceanography of the Baltic Sea, Springer
Berlin Heidelberg, Berlin, Heidelberg, 19–74, https://doi.org/10.1007/978-3-662-04453-7_2,
2001. a
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, 2001. a
Thomas, H., Bozec, Y., de Baar, H. J. W., Elkalay, K., Frankignoulle, M.,
Schiettecatte, L.-S., Kattner, G., and Borges, A. V.: The carbon budget of
the North Sea, Biogeosciences, 2, 87–96,
https://doi.org/10.5194/bg-2-87-2005, 2005. a, b
Tian, T., Boberg, F., Christensen, O., Christensen, J., She, J., and Vihma,
T.:
Resolved complex coastlines and land-sea contrasts in a high-resolution
regional climate model: a comparative study using prescribed and modelled
SSTs, Tellus A, 65, 19951, https://doi.org/10.3402/tellusa.v65i0.19951,
2013. a, b
Uppala, S. M., Kallberg, P. W., Simmons, A. J., Andrae, U., añd M. Fiorino,
V. D. C. B., Gibson, J. K., Haseler, J., Kelly, A. H. G. A., Li, X., Onogi,
K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K.,
Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J. ., Bormann,
N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M.,
Fuentes, M., Hagemann, S. ., Holm, E., Hoskins, B. J., Isaksen, L., Janssen,
P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette, J.-J.,
Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., tch,
A. U., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40
re-analysis, Q. J. Roy. Meteor. Soc., 131,
2961–3012, https://doi.org/10.1256/qj.04.176, 2005. a
Vahtera, E., Conley, D. J., Gustafsson, B. G., Kuosa, H., Pitkänen, H.,
Savchuk, O. P., Tamminen, T., Viitasalo, M., Voss, M., Wasmund, N.,
and Wulff, F.:
Internal ecosystem feedbacks enhance nitrogen-fixing cyanobacteria blooms and
complicate management in the Baltic Sea, Ambio, 36, 186–194, 2007. 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
van Haren, H., Howarth, M., Jones, K., and Ezzi, I.: Autumnal reduction of
stratification in the northern North Sea and its impact, Cont. Shelf
Res., 23, 177–191, 2003. a
Vichi, M., Masina, S., and Navarra, A.: A generalized model of pelagic
biogeochemistry for the global ocean ecosystem. Part II: Numerical
simulations, J. Marine Syst., 64, 110–134,
https://doi.org/10.1016/j.jmarsys.2006.03.014,
2007. a
Vichi, M., Lovato, T., Lazzari, P., Cossarini, G., Gutierrez Mlot, E.,
Mattia,
G., Masina, S., McKiver, W. J., Pinardi, N., Solidoro, C., Tedesco, L., and
Zavatarelli, M.: The Biogeochemical Flux Model (BFM): Equation Description
and User Manual, BFM version 5.1, BFM Consortium, 2015. a
Wang, S., Dieterich, C., Döscher, R., Höglund, A., Hordoir, R.,
Meier,
H. E. M., Samuelsson, P., and Schimanke, S.: Development and evaluation of a
new regional coupled atmosphere–ocean model in the North Sea and Baltic Sea,
Tellus A, 67, 24284,
https://doi.org/10.3402/tellusa.v67.24284, 2015. a
Wasmund, N. and Uhlig, S.: Phytoplankton trends in the Baltic Sea, J.
Conseil, 60, 177–186,
https://doi.org/10.1016/S1054-3139(02)00280-1,
2003.
a
Westerlund, A. and Tuomi, L.: Vertical temperature dynamics in the Northern
Baltic Sea based on 3D modelling and data from shallow-water Argo floats,
J. Marine Syst., 158, 34–44,
https://doi.org/10.1016/j.jmarsys.2016.01.006,
2016. a, b, c
Westerlund, A., Tuomi, L., Alenius, P., Miettunen, E., and Vankevich, R. E.:
Attributing mean circulation patterns to physical phenomena in the Gulf of
Finland, Oceanologia, 60, 16–31, https://doi.org/10.1016/j.oceano.2017.05.003,
2018. a
Wieland, K., Waller, U., and Schnack, D.: Development of Baltic cod eggs at
different levels of temperature and oxygen content, Dana, 10, 163–177, 1994. a
Winther, N. G. and Johannessen, J. A.: North Sea circulation: Atlantic inflow
and its destination, J. Geophys. Res.-Oceans, 111, c12018,
https://doi.org/10.1029/2005JC003310,
2006. a
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.
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and...
Special issue