Articles | Volume 13, issue 2
Research article
08 Feb 2019
Research article |  | 08 Feb 2019

Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean–sea ice modelling system

Sindre Fritzner, Rune Graversen, Kai H. Christensen, Philip Rostosky, and Keguang Wang

Related authors

Bringing it all together: Science and modelling priorities to support international climate policy
Colin Gareth Jones, Fanny Adloff, Ben Booth, Peter Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene Hewitt, Hazel Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm Roberts, Benjamin Sanderson, Roland Séférian, Samuel Somot, Pier-Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco J. Doblas-Reyes, Markus G. Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Froelicher, Neven Fuckar, Matthew Gidden, Helge Goessling, Rune Grand Graversen, Silvio Gualdi, Jose Manuel Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason A. Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Melia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard Wood, Shuting Yang, and Sönke Zaehle
EGUsphere,,, 2024
Short summary
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530,,, 2023
Short summary
Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model
Keguang Wang, Alfatih Ali, and Caixin Wang
The Cryosphere, 17, 4487–4510,,, 2023
Short summary
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
Geosci. Model Dev., 16, 5401–5426,,, 2023
Short summary
Relevance of warm air intrusions for Arctic satellite sea ice concentration time series
Philip Rostosky and Gunnar Spreen
The Cryosphere, 17, 3867–3881,,, 2023
Short summary

Related subject area

Discipline: Sea ice | Subject: Data Assimilation
Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model
Keguang Wang, Alfatih Ali, and Caixin Wang
The Cryosphere, 17, 4487–4510,,, 2023
Short summary
Towards improving short-term sea ice predictability using deformation observations
Anton Korosov, Pierre Rampal, Yue Ying, Einar Ólason, and Timothy Williams
The Cryosphere, 17, 4223–4240,,, 2023
Short summary
Assimilating CryoSat-2 freeboard to improve Arctic sea ice thickness estimates
Imke Sievers, Till A. S. Rasmussen, and Lars Stenseng
The Cryosphere, 17, 3721–3738,,, 2023
Short summary
Assimilation of satellite swaths versus daily means of sea ice concentration in a regional coupled ocean-sea ice model
Marina Durán Moro, Ann Kristin Sperrevik, Thomas Lavergne, Laurent Bertino, Yvonne Gusdal, Silje Christine Iversen, and Jozef Rusin
The Cryosphere Discuss.,,, 2023
Revised manuscript accepted for TC
Short summary
The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system
Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Andrew Ridout, and Lars Nerger
The Cryosphere, 17, 2509–2532,,, 2023
Short summary

Cited articles

Allard, R. A., Farrell, S. L., Hebert, D. A., Johnston, W. F., Li, L., Kurtz, N. T., Phelps, M. W., Posey, P. G., Tilling, R., Ridout, A., and Wallcraft, A. J.: Utilizing CryoSat-2 sea ice thickness to initialize a coupled ice-ocean modeling system, Adv. Space Res., 62, 1265–1280,, 2018. a
Andersen, S., Tonboe, R., Kern, S., and Schyberg, H.: Improved retrieval of sea ice total concentration from spaceborne passive microwave observations using Numerical Weather Prediction model fields: An intercomparison of nine algorithms, Remote Sens. Environ., 104, 374–392, 2006. a
Bell, M., Barciela, R., Hines, A., Martin, M., McCulloch, M., and Storkey, D.: The forecasting ocean assimilation model (FOAM) system, in: Elsevier oceanography series, Elsevier, vol. 69, 197–202, 2003. a
Blockley, E. W. and Peterson, K. A.: Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness, The Cryosphere, 12, 3419–3438,, 2018. a
Burgers, G., van Leeuwen, P., and Evensen, G.: Analysis Scheme in the Ensemble Kalman Filter, Mon. Weather Rev., 126, 1719–1791,<1719:ASITEK>2.0.CO;2, 1998. a

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
In this work, a coupled ocean and sea-ice ensemble-based assimilation system is used to assess the impact of different observations on the assimilation system. The focus of this study is on sea-ice observations, including the use of satellite observations of sea-ice concentration, sea-ice thickness and snow depth for assimilation. The study showed that assimilation of sea-ice thickness in addition to sea-ice concentration has a large positive impact on the coupled model.