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

Sukun Cheng,Ali Aydoğdu,Alberto Carrassi,Laurent Bertino,Pierre Rampal

doi:10.3390/oceans1040022

Abstract

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.

Highlights

Sea ice covering the polar oceans is an important component of the Earth System
We focused on simulating sea ice drift in the pan-Arctic Ocean during winter, when the extent and the volume of ice are close to their annual maximum
We look at the uncertainties in the ensemble forecasts (WIND, COHESION and joint wind and cohesion perturbations (JOINT)) using the trajectories of the second set of the virtual drifters mentioned in Section 3.3, which are seeded evenly (50 km distance from each other) over the whole Arctic domain at the beginning of each forecast

Summary

Introduction

Sea ice covering the polar oceans is an important component of the Earth System. The dramatic changes in sea ice extent and volume in the Arctic have been regularly reported in recent decades [1,2,3].It is, crucial to understand the new state and characteristics of Arctic sea ice and how it impacts the regional and global weather and climate [4]. Sea ice covering the polar oceans is an important component of the Earth System. The dramatic changes in sea ice extent and volume in the Arctic have been regularly reported in recent decades [1,2,3]. It is, crucial to understand the new state and characteristics of Arctic sea ice and how it impacts the regional and global weather and climate [4]. A thinner sea ice cover offers opportunities to exploit trans-Arctic shipping routes but its faster dynamics challenge the safety of operations [6]. One specific and important aim of sea ice models is to represent small-scale dynamics such as the formation of leads and ridges, together with the large-scale drift patterns of big ice plates and small ice Oceans 2020, 1, 326–342; doi:10.3390/oceans1040022 www.mdpi.com/journal/oceans

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Discussion

Conclusion