STATISTICAL FLUCTUATIONS OF AN OCEAN SURFACE INFERRED FROM SHOES AND SHIPS

This paper shows that it is possible to roughly estimate some ocean pr operties using simple time-dependent statistical models of ocean fluct uations. Based on a real incident, the loss by a vessel of a Nike shoe s container in the North Pacific Ocean, a statistical model was tested on data sets consisting of the Nike shoes found by beachcombers a few months later. This statistical treatment of the shoes' motion allows one to infer velocity trends of the Pacific Ocean, together with their fluctuation strengths. The idea is to suppose that there is a mean bu lk flow speed that can depend on location on the ocean surface and tim e. The fluctuations of the surface flow speed are then treated as stat istically random. The distribution of shoes is described in space and time using Markov probability processes related to the mean and fluctu ating ocean properties. The aim of the exercise is to provide some of the properties of the Pacific Ocean that are otherwise calculated usin g a sophisticated numerical model, OSCURS, where numerous data are nee ded. Relevant quantities are sharply estimated, which can be useful to (1) constrain output results from OSCURS computations, and (2) elucid ate the behavior patterns of ocean flow characteristics on long time s cales.