Using flow geometry for drifter deployment in Lagrangian data assimilation

Abstract

Methods of Lagrangian data assimilation (LaDA) require carefully chosen sites for optimal drifter deployments. In this work, we investigate a directed drifter deployment strategy with a recently developed LaDA method employing an augmented state vector formulation for an Ensemble Kalman filter. We test our directed drifter deployment strategy by targeting Lagrangian coherent flow structures of an unsteady double gyre flow to analyse how different release sites influence the performance of the method. We consider four different launch methods; a uniform launch, a saddle launch in which hyperbolic trajectories are targeted, a vortex centre launch, and a mixed launch targeting both saddles and centres. We show that global errors in the flow field require good dispersion of the drifters which can be realized with the saddle launch. Local errors on the other hand are effectively reduced by targeting specific flow features. In general, we conclude that it is best to target the strongest hyperbolic trajectories for shorter forecasts although vortex centres can produce good drifter dispersion upon bifurcating on longer time‐scales.

A hybrid grid/particle filter for Lagrangian data assimilation. I: Formulating the passive scalar approximation

“…This means that rather than solving Equation (11) directly, each point of our ensemble is evolved using the dynamical model given by Equation (1). Salman et al (2006Salman et al ( , 2008 extended the approach of Evensen (1994) by approximating the PDF φ(x, t) of the augmented state vector using an analogous expression to Equation (13). This follows from the fact that both Equations (5) and (11) have identical forms.…”

“…The highly nonlinear nature of Lagrangian trajectories is our primary motivation for developing a new method that directly targets these highly nonlinear attributes of Lagrangian data. A second motivation is driven by recent efforts to develop an optimum drifter deployment strategy by analyzing the underlying flow geometry (Molcard et al, 2006;Salman et al, 2008). These studies have revealed that optimum drifter deployment sites can be realized by targeting hyperbolic trajectories of the flow.…”

A Lagrangian analysis of a developing and non-developing disturbance observed during the PREDICT experiment

“…These methods detect LCSs, which form finite-time boundaries and govern the mixing and transport of tracers (Shadden et al, 2005;Haller and Yuan, 2000; and have proven useful in a variety of geophysical flows, see e.g. Salman et al (2008);Tang et al (2009);Koh and Legras (2002); Joseph and Legras (2002); Cohen and Schultz (2005).…”

Assimilating en-route Lagrangian observations

“…The resulting observation operator in this methodology is then the identity in the instrument coordinate at observation instances, for example, times at which the instrument has surfaced and where it can report its location. Several theoretical and applied studies have successfully assimilated Lagrangian data in the context of ocean modelling (Salman et al, 2006;Taillandier et al, 2006Taillandier et al, , 2008Restrepo, 2008;Salman et al, 2008;Mariano et al, 2011).…”