Statistical Analysis of the Surface Circulation in the California Current System Using Satellite-Tracked Drifters

Poulain, Pierre-Marie; Niiler, Pearn P.

doi:10.1175/1520-0485(1989)019<1588:saotsc>2.0.co;2

Cited by 125 publications

(116 citation statements)

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“…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 now becoming a standard analysis tool for sea-ice dynamics (Lukovich et al, 2011(Lukovich et al, , 2015Gabrielski et al, 2015).…”

Section: Introductionmentioning

confidence: 63%

“…We note that the integral timescale (about 1.71 days) and the diffusivity K (1.17 × 10 3 m 2 s −1 ) are of the same order of magnitude as those found for ocean drifters (e.g., Poulain and Niiler, 1989;Zhang et al, 2001).…”

Section: Discussionmentioning

confidence: 99%

“…where t 0 is the first time χ (τ ) crosses zero (see for instance Poulain and Niiler, 1989;Rampal et al, 2009b). In the example of Fig.…”

Section: Application Of Taylor's Diffusion Theorymentioning

confidence: 99%

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Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

et al. 2016

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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)(2008)(2009)(2010)(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.

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Section: Introductionmentioning

confidence: 63%

Section: Discussionmentioning

confidence: 99%

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Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

et al. 2016

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“…His methodology has been widely applied to ocean data, and different bin sizes and even different bin shapes and orientations have been explored (Poulain and Niiler 1989;Falco et al 2000;Poulain 2001;Ursella et al 2006;Poulain and Zambianchi 2007). Improvements such as fitting the binned velocities with cubic splines (Bauer et al 2002), or grouping a specified amount of data into spatially localized subsets using a "clustering" algorithm (Koszalka and LaCasce 2010) have been tested.…”

Section: Methodsmentioning

confidence: 99%

“…In the last decades, in order to understand Lagrangian motion at sea, several studies (e.g., Poulain and Niiler 1989;Falco et al 2000;Poulain 2001;Maurizi et al 2004;Ursella et al 2006;Poulain and Zambianchi 2007;Sallée et al 2008) analysed surface drifter data and computed the mean and fluctuating velocity components and diffusivities. The theoretical framework used in those analyses is Taylor's (1921) theory of stationary and homogenous turbulence, but even inside relatively small subdomains, different regimes of dispersion may exist, because of the huge variability of Lagrangian behaviours.…”

Section: Introductionmentioning

confidence: 98%

Eddy diffusivity derived from drifter data for dispersion model applications

et al. 2012

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Ocean transport and dispersion processes are at the present time simulated using Lagrangian stochastic models coupled with Eulerian circulation models that are sup- plying analyses and forecasts of the ocean currents at unprecedented time and space resolution. Using the Lagrangian approach, each particle displacement is described by an average motion and a fluctuating part. The first one represents the advection associated with the Eulerian current field of the circulation models while the second one describes the sub-grid scale diffusion. The focus of this study is to quantify the sub-grid scale diffusion of the Lagrangian models written in terms of a horizontal eddy diffusivity. Using a large database of drifters released in different regions of the Mediterranean Sea, the Lagrangian sub-grid scale diffusion has been computed, by considering different regimes when averaging statistical quantities. In addition, the real drifters have been simulated using a trajectory model forced by OGCM currents, focusing on how the Lagrangian properties are reproduced by the simulated trajectories. © Springer-Verlag 2012

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Steepest Ascent Low/Non‐Low‐Frequency Ratio in Empirical Mode Decomposition to Separate Deterministic and Stochastic Velocities From a Single Lagrangian Drifter

Chu

2018

JGR Oceans

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SOund Fixing And Ranging (RAFOS) floats deployed by the Naval Postgraduate School (NPS) in the California Current system from 1992 to 2001 at depth between 150 and 600 m (http://www.oc.nps.edu/npsRAFOS/) are used to study 2‐D turbulent characteristics. Each drifter trajectory is adaptively decomposed using the empirical mode decomposition (EMD) into a series of intrinsic mode functions (IMFs) with corresponding specific scale for each IMF. A new steepest ascent low/non‐low‐frequency ratio is proposed in this paper to separate a Lagrangian trajectory into low‐frequency (nondiffusive, i.e., deterministic) and high‐frequency (diffusive, i.e., stochastic) components. The 2‐D turbulent (or called eddy) diffusion coefficients are calculated on the base of the classical turbulent diffusion with mixing length theory from stochastic component of a single drifter. Statistical characteristics of the calculated 2‐D turbulence length scale, strength, and diffusion coefficients from the NPS RAFOS data are presented with the mean values (over the whole drifters) of the 2‐D diffusion coefficients comparable to the commonly used diffusivity tensor method.

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Statistical Analysis of the Surface Circulation in the California Current System Using Satellite-Tracked Drifters

Cited by 125 publications

References 0 publications

Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

Eddy diffusivity derived from drifter data for dispersion model applications

Steepest Ascent Low/Non‐Low‐Frequency Ratio in Empirical Mode Decomposition to Separate Deterministic and Stochastic Velocities From a Single Lagrangian Drifter

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