EGU21-5141
https://doi.org/10.5194/egusphere-egu21-5141
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

Sukun Cheng1, Ali Aydoğdu2, Pierre Rampal1,3, Alberto Carrassi4,5, and Laurent Bertino1
Sukun Cheng et al.
  • 1Nansen Environmental and Remote Sensing Center, Bergen 5006, Norway
  • 2Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Bologna 40127, Italy
  • 3Institut de Géophysique de l’Environnement, Université Grenoble Alpes/CNRS/IRD/G-INP, CS 40700, 38 058 Grenoble Cedex 9, France
  • 4Department of Meteorology and National Centre for Earth Observation, University of Reading, Reading RG6 6AH, UK
  • 5Mathematical Institute, Utrecht University, Utrecht 3584 CS, The Netherlands

We evaluate the impact of uncertainties in surface wind and sea ice cohesion on sea ice forecasts by the neXtSIM sea ice model. neXtSIM includes the Maxwell-elasto-brittle rheology describing the ice dynamics. Ensemble forecasts are done every 10 days from January to April 2008. The ensembles are generated by perturbing the wind forcing and ice cohesion field both separately and jointly. The wind forcing, an external forcing of the model, is perturbed continuously during the forecast. While the sea-ice cohesion, an internal parameter of the model, is randomized on the initial field of each sea ice forecast. The model uncertainties are assessed statistically using ensemble forecasts, in which virtual drifters are seeded over the Arctic Ocean. We analyze the spread of Lagrangian sea ice trajectories of the ensemble of virtual drifters and compare them with the IABP buoys. We demonstrate that the wind perturbations usually contribute more to the forecast uncertainty, but the ice cohesion perturbations significantly increase the degree of anisotropy in the spread and become occasionally important during strong wind events.

How to cite: Cheng, S., Aydoğdu, A., Rampal, P., Carrassi, A., and Bertino, L.: Probabilistic Forecasts of Sea Ice Trajectories in the Arctic: Impact of Uncertainties in Surface Wind and Ice Cohesion, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5141, https://doi.org/10.5194/egusphere-egu21-5141, 2021.

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