Articles | Volume 12, issue 3
https://doi.org/10.5194/tc-12-935-2018
https://doi.org/10.5194/tc-12-935-2018
Research article
 | 
16 Mar 2018
Research article |  | 16 Mar 2018

Impact of rheology on probabilistic forecasts of sea ice trajectories: application for search and rescue operations in the Arctic

Matthias Rabatel, Pierre Rampal, Alberto Carrassi, Laurent Bertino, and Christopher K. R. T. Jones

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Cited articles

Abi-Zeid, I. and Frost, J. R.: SARPlan: A decision support system for Canadian Search and Rescue Operations, Eur. J. Oper. Res., 162, 630–653, 2005.
Bertino, L., Bergh, J., and Xie, J.: Evaluation of uncertainties by ensemble simulation, Tech. Rep. Tech. Rep. 355, NERSC, ART JIP Deliverable 3.3, Bergen, Norway, 2015.
Bonan, B., Nichols, N. K., Baines, M. J., and Partridge, D.: Data assimilation for moving mesh methods with an application to ice sheet modelling, Nonlin. Processes Geophys., 24, 515–534, https://doi.org/10.5194/npg-24-515-2017, 2017.
Bouillon, S. and Rampal, P.: Presentation of the dynamical core of neXtSIM, a new sea ice model, Ocean Model., 91, 23–37, 2015a.
Bouillon, S. and Rampal, P.: On producing sea ice deformation data sets from SAR-derived sea ice motion, The Cryosphere, 9, 663–673, https://doi.org/10.5194/tc-9-663-2015, 2015b.
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Short summary
Large deviations still exist between sea ice forecasts and observations because of both missing physics in models and uncertainties on model inputs. We investigate how the new sea ice model neXtSIM is sensitive to uncertainties in the winds. We highlight and quantify the role of the internal forces in the ice on this sensitivity and show that neXtSIM is better at predicting sea ice drift than a free-drift (without internal forces) ice model and is a skilful tool for search and rescue operations.