Abstract
Abstract. We characterize sea-ice drift by applying a Lagrangian diffusion analysis to buoy trajectories from the International Arctic Buoy Programme (IABP) dataset and from two different models: the standalone Lagrangian sea-ice model neXtSIM and the Eulerian coupled ice–ocean model used for the TOPAZ reanalysis. By applying the diffusion analysis to the IABP buoy trajectories over the period 1979–2011, we confirm that sea-ice diffusion follows two distinct regimes (ballistic and Brownian) and we provide accurate values for the diffusivity and integral timescale that could be used in Eulerian or Lagrangian passive tracers models to simulate the transport and diffusion of particles moving with the ice. We discuss how these values are linked to the evolution of the fluctuating displacements variance and how this information could be used to define the size of the search area around the position predicted by the mean drift. By comparing observed and simulated sea-ice trajectories for three consecutive winter seasons (2007–2011), we show how the characteristics of the simulated motion may differ from or agree well with observations. This comparison illustrates the usefulness of first applying a diffusion analysis to evaluate the output of modeling systems that include a sea-ice model before using these in, e.g., oil spill trajectory models or, more generally, to simulate the transport of passive tracers in sea ice.
Highlights
Sea-ice motion can be viewed as a superposition of a mean circulation and turbulent-like fluctuations (Rampal et al, 2009b)
We characterize sea-ice drift by applying a Lagrangian diffusion analysis to buoy trajectories from the International Arctic Buoy Programme (IABP) dataset and from two different models: the standalone Lagrangian sea-ice model neXtSIM and the Eulerian coupled ice–ocean model used for the TOPAZ reanalysis
By applying the diffusion analysis to the IABP buoy trajectories over the period 1979– 2011, we confirm that sea-ice diffusion follows two distinct regimes and we provide accurate values for the diffusivity and integral timescale that could be used in Eulerian or Lagrangian passive tracers models to simulate the transport and diffusion of particles moving with the ice
Summary
Sea-ice motion can be viewed as a superposition of a mean circulation and turbulent-like fluctuations (Rampal et al, 2009b). The appropriate averaging scales (about 400 km and 5.5 months for winter conditions) were found small enough to clearly separate the interannual variability of the mean circulation from the fluctuating motion due to passing atmospheric perturbations, local oceanic eddies and inertial and tidal motion This approach, based on the analysis of single particle trajectories, has been widely used to study diffusion properties of Lagrangian drifters in the ocean (see, e.g., Zhang et al, 2001; Poulain and Niiler, 1989) and is becoming a standard analysis tool for sea-ice dynamics (Lukovich et al, 2011, 2015; Gabrielski et al, 2015). Single particle analysis (here referred to as diffusion analysis) is useful for characterizing long-term trajectories as it clearly decomposes the motion into mean (predictable) and fluctuating (unpredictable) parts (Colony and Thorndike, 1985) It allowed Rampal et al (2009b) to show that sea-ice diffusion exhibits a clear transition from the so-called ballistic regime to the Brownian regime. The information coming from the diffusion analysis (mean flow and diffusivity) statistically describe the ensemble of all the potential trajectories that a particle, released at a given location
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