Trajectory prediction using HF radar surface currents: Monte Carlo simulations of prediction uncertainties

David S. Ullman, James O'Donnell, Josh Kohut, Todd Fake, Arthur Allen

Research output: Contribution to journalArticlepeer-review

97 Scopus citations

Abstract

An important aspect of particle trajectory modeling in the ocean is the assessment of the uncertainty in the final particle position. Monte Carlo particle trajectory simulations using surface currents derived from standard-range and long-range CODAR HF radar systems were performed using random-walk and random-flight models of the unresolved velocities. Velocity statistics for these models were derived from the covariance functions of differences between CODAR and drifter estimates of surface currents. Comparison of predicted trajectories and drifter tracks demonstrate that these predictions are superior to assuming the drifters stay at their initial position. Vertical shear between the effective depth of long-range CODAR measurements (∼2.4 m) and that of drifters (0.65 m) causes the drifters to move more rapidly downwind than predicted. This bias is absent when standard-range CODAR currents (effective depth ∼0.5 m) are used, implying that drifter leeway is not the cause of the bias. Particle trajectories were computed using CODAR data and the random-flight model for 24-hour intervals using a Monte Carlo approach to determine the 95% confidence interval of position predictions. Between 80% and 90% of real drifters were located within the predicted confidence interval, in reasonable agreement with the expected 95% success rate. In contrast, predictions using the random-walk approach proved inconsistent with observations unless the diffusion coefficient was increased to approximately the random-flight value. The consistency of the random-flight uncertainty estimates and drifter data supports the use of our methodology for estimating model parameters from drifter-CODAR velocity differences.

Original languageEnglish (US)
Article numberC12005
JournalJournal of Geophysical Research: Oceans
Volume111
Issue number12
DOIs
StatePublished - Dec 8 2006

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Forestry
  • Oceanography
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Palaeontology

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