Articles | Volume 16, issue 18
https://doi.org/10.5194/gmd-16-5401-2023
https://doi.org/10.5194/gmd-16-5401-2023
Development and technical paper
 | 
22 Sep 2023
Development and technical paper |  | 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

Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen

Related authors

Uncertainties in the finite-time Lyapunov exponent in an ocean ensemble prediction model
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
Buoy measurements of strong waves in ice amplitude modulation: a signature of complex physics governing waves in ice attenuation
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
The effect of vertical mixing on the horizontal drift of oil spills
Johannes Röhrs, Knut-Frode Dagestad, Helene Asbjørnsen, Tor Nordam, Jørgen Skancke, Cathleen E. Jones, and Camilla Brekke
Ocean Sci., 14, 1581–1601, https://doi.org/10.5194/os-14-1581-2018,https://doi.org/10.5194/os-14-1581-2018, 2018
Short summary
Revisiting the DeepWater Horizon spill: High resolution model simulations of effects of oil droplet size distribution and river fronts
Lars R. Hole, Knut-Frode Dagestad, Johannes Röhrs, Cecilie Wettre, Vassiliki H. Kourafalou, Ioannis Androulidakis, Matthieu Le Hénaff, Heesook Kang, and Oscar Garcia-Pineda
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-130,https://doi.org/10.5194/os-2018-130, 2018
Revised manuscript not accepted
Short summary
OpenDrift v1.0: a generic framework for trajectory modelling
Knut-Frode Dagestad, Johannes Röhrs, Øyvind Breivik, and Bjørn Ådlandsvik
Geosci. Model Dev., 11, 1405–1420, https://doi.org/10.5194/gmd-11-1405-2018,https://doi.org/10.5194/gmd-11-1405-2018, 2018
Short summary

Related subject area

Oceanography
A new global high-resolution wave model for the tropical ocean using WAVEWATCH III version 7.14
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
Geosci. Model Dev., 18, 1929–1946, https://doi.org/10.5194/gmd-18-1929-2025,https://doi.org/10.5194/gmd-18-1929-2025, 2025
Short summary
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025,https://doi.org/10.5194/gmd-18-1561-2025, 2025
Short summary
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025,https://doi.org/10.5194/gmd-18-1375-2025, 2025
Short summary
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025,https://doi.org/10.5194/gmd-18-1189-2025, 2025
Short summary
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025,https://doi.org/10.5194/gmd-18-605-2025, 2025
Short summary

Cited articles

Anderson, J. L.: Spatially and temporally varying adaptive covariance inflation for ensemble filters, Tellus A, 61, 72–83, https://doi.org/10.1111/j.1600-0870.2008.00361.x, 2009. a, b
Anderson, J. L.: A Quantile-Conserving Ensemble Filter Framework. Part I: Updating an Observed Variable, Mon. Weather Rev., 150, 1061–1074, https://doi.org/10.1175/MWR-D-21-0229.1, 2022. a
Asbjørnsen, H., Årthun, M., Skagseth, O., and Eldevik, T.: Mechanisms Underlying Recent Arctic Atlantification, Geophys. Res. Lett., 47, e2020GL088036, https://doi.org/10.1029/2020GL088036, 2020. a
Batrak, Y. and Müller, M.: On the warm bias in atmospheric reanalyses induced by the missing snow over Arctic sea-ice, Nat. Commun., 10, 4170, https://doi.org/10.1038/s41467-019-11975-3, 2019. a
Bishop, C. H.: The GIGG-EnKF: ensemble Kalman filtering for highly skewed non-negative uncertainty distributions, Q. J. Roy. Meteor. Soc., 142, 1395–1412, https://doi.org/10.1002/qj.2742, 2016. a, b
Download
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.
Share