Articles | Volume 16, issue 18
https://doi.org/10.5194/gmd-16-5401-2023
© 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/gmd-16-5401-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
22 Sep 2023
Development and technical paper |
| 22 Sep 2023
| 22 Sep 2023
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Yvonne Gusdal
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Edel S. U. Rikardsen
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Marina Durán Moro
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Jostein Brændshøi
Norwegian Defence Research Establishment, Instituttveien 20, 2007 Kjeller, Norway
Nils Melsom Kristensen
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Sindre Fritzner
Department of Physics and Technology, UiT The Arctic University of Norway, P.O. Box 6050 Langnes, 9037 Tromsø, Norway
Keguang Wang
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Ann Kristin Sperrevik
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Martina Idžanović
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Thomas Lavergne
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Jens Boldingh Debernard
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Kai H. Christensen
Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0371 Oslo, Norway
Department of Geosciences, University of Oslo, P.O. Box 1022, Blindern, 0315 Oslo, Norway
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Cyril Palerme, Johannes Röhrs, Thomas Lavergne, Jozef Rusin, Are Frode Kvanum, Atle Macdonald Sørensen, Arne Melsom, Julien Brajard, Martina Idžanović, Marina Durán Moro, and Malte Müller
EGUsphere, https://doi.org/10.5194/egusphere-2025-2001, https://doi.org/10.5194/egusphere-2025-2001, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We present MET-AICE, a sea ice prediction system based on artificial intelligence techniques that has been running operationally since March 2024. The forecasts are produced daily and provide sea ice concentration predictions for the next 10 days. We evaluate the MET-AICE forecasts from the first year of operation, and we compare them to forecasts produced by a physically-based model (Barents-2.5km). We show that MET-AICE is skillful and provides more accurate forecasts than Barents-2.5km.
Mateusz Matuszak, Johannes Röhrs, Pål Erik Isachsen, and Martina Idžanović
Ocean Sci., 21, 401–418, https://doi.org/10.5194/os-21-401-2025, https://doi.org/10.5194/os-21-401-2025, 2025
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Lagrangian coherent structures (LCSs) describe material transport in ocean flow by describing transport and accumulation regions. We discuss the implications of model flow field uncertainty for finite-time Lyapunov exponents (FTLEs), which under certain conditions approximate LCSs. FTLEs add value to forecasting when they are certain and long-lived. Averaging FTLEs reveals where they are more certain and long-lived, often influenced by bottom topography.
Jean Rabault, Trygve Halsne, Ana Carrasco, Anton Korosov, Joey Voermans, Patrik Bohlinger, Jens Boldingh Debernard, Malte Müller, Øyvind Breivik, Takehiko Nose, Gaute Hope, Fabrice Collard, Sylvain Herlédan, Tsubasa Kodaira, Nick Hughes, Qin Zhang, Kai Haakon Christensen, Alexander Babanin, Lars Willas Dreyer, Cyril Palerme, Lotfi Aouf, Konstantinos Christakos, Atle Jensen, Johannes Röhrs, Aleksey Marchenko, Graig Sutherland, Trygve Kvåle Løken, and Takuji Waseda
EGUsphere, https://doi.org/10.48550/arXiv.2401.07619, https://doi.org/10.48550/arXiv.2401.07619, 2024
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We observe strongly modulated waves-in-ice significant wave height using buoys deployed East of Svalbard. We show that these observations likely cannot be explained by wave-current interaction or tide-induced modulation alone. We also demonstrate a strong correlation between the waves height modulation, and the rate of sea ice convergence. Therefore, our data suggest that the rate of sea ice convergence and divergence may modulate wave in ice energy dissipation.
Kai Håkon Christensen, Jon Albretsen, Lars Asplin, Håvard Guldbrandsen Frøysa, Yvonne Gusdal, Silje Christine Iversen, Mari Fjalstad Jensen, Ingrid Askeland Johnsen, Nils Melsom Kristensen, Pål Næverlid Sævik, Anne Dagrun Sandvik, Magne Simonsen, Jofrid Skarðhamar, Ann Kristin Sperrevik, and Marta Trodahl
EGUsphere, https://doi.org/10.5194/egusphere-2025-3986, https://doi.org/10.5194/egusphere-2025-3986, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This paper describes "Norkyst", the operational coastal ocean forecasting system for mainland Norway, which is now in version 3. The system produces five day forecasts of ocean currents, temperature, salinity, and sea surface height every day, and we also maintain an archive of historical data going back to 2012. We show that the outputs of Norkyst have sufficient quality so that it's intended use as a free public service supporting scientists, ocean managers, and industry is justified.
Anton Korosov, Léo Edel, Heather Regan, Thomas Lavergne, Emily Jane Down, and Signe Aaboe
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-477, https://doi.org/10.5194/essd-2025-477, 2025
Preprint under review for ESSD
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We present a new long-term record of Arctic sea ice age spanning from 1991 to 2024. Using satellite data and a new tracking method, it maps fractions of sea ice from first- to sixth-year and includes uncertainty estimates. The dataset shows a decline in older ice and more first-year ice, it agrees well with buoy data, and supports Arctic monitoring, climate research, navigation, and model evaluation.
Cyril Palerme, Johannes Röhrs, Thomas Lavergne, Jozef Rusin, Are Frode Kvanum, Atle Macdonald Sørensen, Arne Melsom, Julien Brajard, Martina Idžanović, Marina Durán Moro, and Malte Müller
EGUsphere, https://doi.org/10.5194/egusphere-2025-2001, https://doi.org/10.5194/egusphere-2025-2001, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
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We present MET-AICE, a sea ice prediction system based on artificial intelligence techniques that has been running operationally since March 2024. The forecasts are produced daily and provide sea ice concentration predictions for the next 10 days. We evaluate the MET-AICE forecasts from the first year of operation, and we compare them to forecasts produced by a physically-based model (Barents-2.5km). We show that MET-AICE is skillful and provides more accurate forecasts than Barents-2.5km.
Mateusz Matuszak, Johannes Röhrs, Pål Erik Isachsen, and Martina Idžanović
Ocean Sci., 21, 401–418, https://doi.org/10.5194/os-21-401-2025, https://doi.org/10.5194/os-21-401-2025, 2025
Short summary
Short summary
Lagrangian coherent structures (LCSs) describe material transport in ocean flow by describing transport and accumulation regions. We discuss the implications of model flow field uncertainty for finite-time Lyapunov exponents (FTLEs), which under certain conditions approximate LCSs. FTLEs add value to forecasting when they are certain and long-lived. Averaging FTLEs reveals where they are more certain and long-lived, often influenced by bottom topography.
Lise Seland Graff, Jerry Tjiputra, Ada Gjermundsen, Andreas Born, Jens Boldingh Debernard, Heiko Goelzer, Yan-Chun He, Petra Margaretha Langebroek, Aleksi Nummelin, Dirk Olivié, Øyvind Seland, Trude Storelvmo, Mats Bentsen, Chuncheng Guo, Andrea Rosendahl, Dandan Tao, Thomas Toniazzo, Camille Li, Stephen Outten, and Michael Schulz
EGUsphere, https://doi.org/10.5194/egusphere-2025-472, https://doi.org/10.5194/egusphere-2025-472, 2025
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The magnitude of future Arctic amplification is highly uncertain. Using the Norwegian Earth system model, we explore the effect of improving the representation of clouds, ocean eddies, the Greenland ice sheet, sea ice, and ozone on the projected Arctic winter warming in a coordinated experiment set. These improvements all lead to enhanced projected Arctic warming, with the largest changes found in the sea-ice retreat regions and the largest uncertainty on the Atlantic side.
Robert Ricker, Thomas Lavergne, Stefan Hendricks, Stephan Paul, Emily Down, Mari Anne Killie, and Marion Bocquet
EGUsphere, https://doi.org/10.5194/egusphere-2025-359, https://doi.org/10.5194/egusphere-2025-359, 2025
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We developed a new method to map Arctic sea ice thickness daily using satellite measurements. We address a problem similar to motion blur in photography. Traditional methods collect satellite data over one month to get a full picture of Arctic sea ice thickness. But like in photos of moving objects, long exposure leads to motion blur, making it difficult to identify certain features in the sea ice maps. Our method corrects for this motion blur, providing a sharper view of the evolving sea ice.
Jean Rabault, Trygve Halsne, Ana Carrasco, Anton Korosov, Joey Voermans, Patrik Bohlinger, Jens Boldingh Debernard, Malte Müller, Øyvind Breivik, Takehiko Nose, Gaute Hope, Fabrice Collard, Sylvain Herlédan, Tsubasa Kodaira, Nick Hughes, Qin Zhang, Kai Haakon Christensen, Alexander Babanin, Lars Willas Dreyer, Cyril Palerme, Lotfi Aouf, Konstantinos Christakos, Atle Jensen, Johannes Röhrs, Aleksey Marchenko, Graig Sutherland, Trygve Kvåle Løken, and Takuji Waseda
EGUsphere, https://doi.org/10.48550/arXiv.2401.07619, https://doi.org/10.48550/arXiv.2401.07619, 2024
Short summary
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We observe strongly modulated waves-in-ice significant wave height using buoys deployed East of Svalbard. We show that these observations likely cannot be explained by wave-current interaction or tide-induced modulation alone. We also demonstrate a strong correlation between the waves height modulation, and the rate of sea ice convergence. Therefore, our data suggest that the rate of sea ice convergence and divergence may modulate wave in ice energy dissipation.
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
Andreas Wernecke, Dirk Notz, Stefan Kern, and Thomas Lavergne
The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024, https://doi.org/10.5194/tc-18-2473-2024, 2024
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The total Arctic sea-ice area (SIA), which is an important climate indicator, is routinely monitored with the help of satellite measurements. Uncertainties in observations of sea-ice concentration (SIC) partly cancel out when summed up to the total SIA, but the degree to which this is happening has been unclear. Here we find that the uncertainty daily SIA estimates, based on uncertainties in SIC, are about 300 000 km2. The 2002 to 2017 September decline in SIA is approx. 105 000 ± 9000 km2 a−1.
Cyril Palerme, Thomas Lavergne, Jozef Rusin, Arne Melsom, Julien Brajard, Are Frode Kvanum, Atle Macdonald Sørensen, Laurent Bertino, and Malte Müller
The Cryosphere, 18, 2161–2176, https://doi.org/10.5194/tc-18-2161-2024, https://doi.org/10.5194/tc-18-2161-2024, 2024
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Sea ice forecasts are operationally produced using physically based models, but these forecasts are often not accurate enough for maritime operations. In this study, we developed a statistical correction technique using machine learning in order to improve the skill of short-term (up to 10 d) sea ice concentration forecasts produced by the TOPAZ4 model. This technique allows for the reduction of errors from the TOPAZ4 sea ice concentration forecasts by 41 % on average.
Marina Durán Moro, Ann Kristin Sperrevik, Thomas Lavergne, Laurent Bertino, Yvonne Gusdal, Silje Christine Iversen, and Jozef Rusin
The Cryosphere, 18, 1597–1619, https://doi.org/10.5194/tc-18-1597-2024, https://doi.org/10.5194/tc-18-1597-2024, 2024
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Individual satellite passes instead of daily means of sea ice concentration are used to correct the sea ice model forecast in the Barents Sea. The use of passes provides a significantly larger improvement of the forecasts even after a 7 d period due to the more precise information on temporal and spatial variability contained in the passes. One major advantage of the use of satellite passes is that there is no need to wait for the daily mean availability in order to update the forecast.
Thomas Lavergne and Emily Down
Earth Syst. Sci. Data, 15, 5807–5834, https://doi.org/10.5194/essd-15-5807-2023, https://doi.org/10.5194/essd-15-5807-2023, 2023
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Sea ice in the Arctic and Antarctic can move several tens of kilometers per day due to wind and ocean currents. By analysing thousands of satellite images, we measured how sea ice has been moving every single day from 1991 through to 2020. We compare our data to how buoys attached to the ice moved and find good agreement. Other scientists will now use our data to better understand if climate change has modified the way sea ice moves and in what way.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Keguang Wang, Alfatih Ali, and Caixin Wang
The Cryosphere, 17, 4487–4510, https://doi.org/10.5194/tc-17-4487-2023, https://doi.org/10.5194/tc-17-4487-2023, 2023
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A simple, efficient. and accurate data assimilation method, local analytical optimal nudging (LAON), is introduced to assimilate high-resolution sea ice concentration in a pan-Arctic high-resolution coupled ocean and sea ice model. The method provides a new vision by nudging the model evolution to the optimal estimate forwardly, continuously, and smoothly. This method is applicable to the general nudging theory and applications in physics, Earth science, psychology, and behavior sciences.
Silje Christine Iversen, Ann Kristin Sperrevik, and Olivier Goux
Ocean Sci., 19, 729–744, https://doi.org/10.5194/os-19-729-2023, https://doi.org/10.5194/os-19-729-2023, 2023
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We present two methods to refine the assimilation of satellite sea surface temperatures (SSTs) into a regional ocean model. First, we correct the SSTs for biases and show that this correction reduces the model SST errors. Then, we implement a special observation operator that handles the spatial resolution mismatch between coarse passive microwave SSTs and the high-resolution model. We find that excluding this operator spatially smooths the modeled SST, whereas its inclusion prevents this.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Pedro Duarte, Jostein Brændshøi, Dmitry Shcherbin, Pauline Barras, Jon Albretsen, Yvonne Gusdal, Nicholas Szapiro, Andreas Martinsen, Annette Samuelsen, Keguang Wang, and Jens Boldingh Debernard
Geosci. Model Dev., 15, 4373–4392, https://doi.org/10.5194/gmd-15-4373-2022, https://doi.org/10.5194/gmd-15-4373-2022, 2022
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Sea ice models are often implemented for very large domains beyond the regions of sea ice formation, such as the whole Arctic or all of Antarctica. In this study, we implement changes in the Los Alamos Sea Ice Model, allowing it to be implemented for relatively small regions within the Arctic or Antarctica and yet considering the presence and influence of sea ice outside the represented areas. Such regional implementations are important when spatially detailed results are required.
Stefan Kern, Thomas Lavergne, Leif Toudal Pedersen, Rasmus Tage Tonboe, Louisa Bell, Maybritt Meyer, and Luise Zeigermann
The Cryosphere, 16, 349–378, https://doi.org/10.5194/tc-16-349-2022, https://doi.org/10.5194/tc-16-349-2022, 2022
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High-resolution clear-sky optical satellite imagery has rarely been used to evaluate satellite passive microwave sea-ice concentration products beyond case-study level. By comparing 10 such products with sea-ice concentration estimated from > 350 such optical images in both hemispheres, we expand results of earlier evaluation studies for these products. Results stress the need to look beyond precision and accuracy and to discuss the evaluation data’s quality and filters applied in the products.
Thomas Lavergne, Montserrat Piñol Solé, Emily Down, and Craig Donlon
The Cryosphere, 15, 3681–3698, https://doi.org/10.5194/tc-15-3681-2021, https://doi.org/10.5194/tc-15-3681-2021, 2021
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Pushed by winds and ocean currents, polar sea ice is on the move. We use passive microwave satellites to observe this motion. The images from their orbits are often put together into daily images before motion is measured. In our study, we measure motion from the individual orbits directly and not from the daily images. We obtain many more motion vectors, and they are more accurate. This can be used for current and future satellites, e.g. the Copernicus Imaging Microwave Radiometer (CIMR).
Ann Keen, Ed Blockley, David A. Bailey, Jens Boldingh Debernard, Mitchell Bushuk, Steve Delhaye, David Docquier, Daniel Feltham, François Massonnet, Siobhan O'Farrell, Leandro Ponsoni, José M. Rodriguez, David Schroeder, Neil Swart, Takahiro Toyoda, Hiroyuki Tsujino, Martin Vancoppenolle, and Klaus Wyser
The Cryosphere, 15, 951–982, https://doi.org/10.5194/tc-15-951-2021, https://doi.org/10.5194/tc-15-951-2021, 2021
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We compare the mass budget of the Arctic sea ice in a number of the latest climate models. New output has been defined that allows us to compare the processes of sea ice growth and loss in a more detailed way than has previously been possible. We find that that the models are strikingly similar in terms of the major processes causing the annual growth and loss of Arctic sea ice and that the budget terms respond in a broadly consistent way as the climate warms during the 21st century.
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
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The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
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Short summary
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents...
