Probabilistic forecast using a Lagrangian sea ice model: application for search and rescue operations

Abstract

We present a sensitivity analysis, and discuss the probabilistic forecast capabilities, of the novel sea ice model <i>neXtSIM</i>. The study pertains to the response of the model to the uncertainty on winds using probabilistic forecasts of ice trajectories. <i>neXtSIM</i> is a continuous Lagrangian numerical model, and uses an elasto-brittle rheology to simulate the ice response to external forces. The sensitivity analysis is based on a Monte Carlo sampling of 12 members. The response of the model to the uncertainties is evaluated in terms of simulated ice drift distances from their initial positions, and from the mean position of the ensemble, over the mid-term forecast horizon of 10-days. The simulated ice drift is decomposed into advective and diffusive parts that are characterised separately both spatially and temporally and compared to what is obtained with a free-drift model, that is, when the ice rheology does not play any role on the modelled physics of the ice. The seasonal variability of the model sensitivity is presented, and shows the role of the ice compactness and rheology in the ice drift response at both local and regional scales in Arctic. Indeed, the ice drift simulated by <i>neXtSIM</i> in summer is close to the one obtained with the free-drift model, while the more compact and solid ice pack shows a significantly different mechanical and drift behaviour in winter. For the winter period analysed in this study, we also show that, in contrast to of free-drift model, <i>neXtSIM</i> reproduces the sea ice Lagrangian diffusion regimes as found from observed trajectories. The forecast capability of <i>neXtSIM</i> is also evaluated using a large set of real buoys' trajectories, and compared to the capability of the free-drift model. We found that <i>neXtSIM</i> performs significantly better in simulating sea ice drift, both in terms of forecast error and as a tool to assist search-and-rescue operations, although the sources of uncertainties assumed for the present experiment are not sufficient for a complete coverage of the observed IABP positions.