A single-layer, reduced-gravity, double-gyre primitive equation model in a
2000 km x 2000 km square domain is used to test the accuracy and sensitivit
y of time-dependent Eulerian velocity fields reconstructed from numerically
generated drifter trajectories and climatology. The goal is to determine h
ow much Lagrangian data is needed to capture the Eulerian velocity field wi
thin a specified accuracy. The Eulerian fields are found by projecting, on
an analytic set of divergence-free basis functions, drifter data launched i
n the active western half of the basin supplemented by climatology in the e
astern domain. The time-dependent coefficients are evaluated by least squar
es minimization and the reconstructed fields are compared to the original m
odel output. The authors find that the accuracy of the reconstructed fields
depends critically on the spatial coverage of the drifter observations. Wi
th good spatial coverage, the technique allows accurate Eulerian reconstruc
tions with under 200 drifters deployed in the 1000 km x 1400 km energetic w
estern region. The base reconstruction error, achieved with full observatio
n of the velocity field, ranges from 5% (with 191 basis functions) to 30% (
with 65 basis functions). Specific analysis of the relation between spatial
coverage and reconstruction error is presented using 180 drifters deployed
in 100 different initial configurations that maximize coverage extremes. T
he simulated drifter data is projected on 107 basis functions for a 50-day
period. The base reconstruction error of 15% is achieved when drifters occu
py approximately 110 (out of 285) 70-km cells in the western region. Recons
tructions from simulated mooring data located at the initial positions of r
epresentative good and poor coverage drifter deployments show the effect dr
ifter dispersion has on data voids. The authors conclude that with appropri
ate coverage, drifter data could provide accurate basin-scale reconstructio
n of Eulerian velocity fields.