Probabilistic Forecasts of Sea Ice Trajectories in the Arctic: Impact of Uncertainties in Surface Wind and Ice Cohesion

• Published in: Oceans
• Main Authors: Cheng, Sukun, Aydoğdu, Ali, Rampal, Pierre, Carrassi, Alberto, Bertino, Laurent
• Other Authors: Nansen Environmental and Remote Sensing Center Bergen (NERSC), Centro Euro-Mediterraneo per i Cambiamenti Climatici Bologna (CMCC), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Department of Meteorology Reading, University of Reading (UOR)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2020
• Subjects: Arctic sea ice drift; neXtSIM; ensemble forecasting; wind perturbation; ice cohesion perturbation; [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology; [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography; Arctic; Arctic Ocean; Sea ice
• Online Access: https://hal.univ-grenoble-alpes.fr/hal-03405336; https://hal.univ-grenoble-alpes.fr/hal-03405336/document; https://hal.univ-grenoble-alpes.fr/hal-03405336/file/Chen2020Oceans.pdf; https://doi.org/10.3390/oceans1040022

International audience We study the response of the Lagrangian sea ice model neXtSIM to the uncertainty in sea surface wind and sea ice cohesion. The ice mechanics in neXtSIM are based on a brittle-like rheological framework. The study considers short-term ensemble forecasts of Arctic sea ice from January to April 2008. Ensembles are generated by perturbing the wind inputs and ice cohesion field both separately and jointly. The resulting uncertainty in the probabilistic forecasts is evaluated statistically based on the analysis of Lagrangian sea ice trajectories as sampled by virtual drifters seeded in the model to cover the Arctic Ocean and using metrics borrowed from the search-and-rescue literature. The comparison among the different ensembles indicates that wind perturbations dominate the forecast uncertainty (i.e., the absolute spread of the ensemble), while the inhomogeneities in the ice cohesion field significantly increase the degree of anisotropy in the spread-i.e., trajectories drift divergently in different directions. We suggest that in order to obtain enough uncertainties in a sea ice model with brittle-like rheologies, to predict sea ice drift and trajectories, one should consider using ensemble-based simulations where at least wind forcing and sea ice cohesion are perturbed.