{'fraction_non_alphanumeric': 0.012808783165599268, 'fraction_numerical': 0.0027447392497712718, 'mean_word_length': 4.945652173913044, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Predictability of Drifter Trajectories in the Tropical Pacific Ocean

Abstract Predictability of particle motion in the ocean over a timescale of one week is studied using three clusters of buoys consisting of 5–10 drifters deployed in the tropical Pacific Ocean. The analysis is conducted by using three techniques with increasing complexity: the center of mass of the cluster, advection by climatological currents, and a new technique that relies on the assimilation of both velocity and position data from the surrounding drifters into a Markov model for particle motion. A detailed mathematical description of the theory leading to this model is given. The predictability of drifter motion in these clusters is characterized using the data density Nd, defined as the number of drifters over an area scaled by the mean diameter of the cluster. The data density Nd decreases along the drifter trajectories due to the tendency of particles to disperse by turbulent fluid motion. In the first regime, which corresponds to the period after the release of drifters in a tight cluster when Nd ...