(C202) <<< Previous | Back to Abstracts Page | Next >>> (C204)
Application of a random flight model in a search and rescue model systems
M. L. Spaulding, T. Isaji, A. Allen, P. Hall, and E. Howlett
University of Rhode Island
spaulding@oce.uri.edu(Abstract received 04/12/2005 for session D)
ABSTRACT
Random walk, Lagrangian (particle) trajectory models are typically used to predict the transport of objects drifting at sea in most search and rescue planning systems. The movement of an object is approximated as the vector sum of the current field plus an empirically based down and cross (leeway) drift in response to wind forcing, based on the classification of the drifting object. The principal goal of the trajectory model is to predict the location and size of the search area as a function of time, starting from one to several days in the past to about the same number of days in the future. The center of the search area is determined by the advective properties of the surface current and wind fields and the object's mean drift characteristics, while the size of the area is normally dependent on the evolution of the ocean turbulence fields, the shear in the mean current, and the uncertainty in the empirically based leeway estimator. The turbulence and current shear are characteristically parameterized in terms of horizontal dispersion coefficients. Spaulding et al (2005) have recently extended SARMAP, a widely used, state of the art search and rescue model which uses a random walk approach, to include an option to perform the trajectory simulation using a random flight technique. The motivation for using a random flight model is the possibility to improve the accuracy of the predictions and to optimize the size of the predicted search area. Random walk and flight options also being included in the next generation of search and rescue model, SAROPS, being developed for the US Coast Guard for use in US coastal waters and the Great Lakes. To evaluate random walk and flight techniques statistically independent, advective simulations were performed using SARMAP to predict the daylong trajectories at successive (non-overlapping) locations along the paths of the seven US Coast Guard, Self Locating Datum Marker Buoys (SLDMB) Argos tracked drifters (Davis like), deployed for 35 days in three separate clusters in the Mid Atlantic Bight. High frequency coastal radar (CODAR) measurements were collected during the same time period for the study area and used as input to the simulations. Model predicted (advection only) and observed locations at the end of one day (typical search and rescue model prediction time scale) showed an averaged difference comparable to the distance the drifter traveled in one day. Differences were significantly higher in areas where the CODAR data return rates were lower. Estimates of the random walk dispersion coefficients, necessary as input to the search and rescue model to ensure that the predicted and observed locations of the drifters were within the model predicted search area, were made and gave values ranging from 20 to 500 m2/sec, with a median value of 90 m2/sec. This range of dispersion coefficient is comparable to independent estimates based on drifter cluster analysis and radar velocity variances and errors. A random flight model was used, with velocity variance based estimates of the dispersion coefficient and autocorrelation times, to simulate the trajectories of the drifters. The random flight model offered no improvement in predictive perform over the corresponding random walk model due to the substantial uncertainty in estimates of the dispersion coefficient and the short (4 to 7 hr) velocity autocorrelation time scale.
(C202) <<< Previous | Back to Abstracts Page | Next >>> (C204)
2005 LAPCOD Meeting, Lerici, Italy, June 13-17, 2005