Abstract
To facilitate investigations of surface wave processes in the open ocean, a wave spectral partitioning method with automated swell tracking and storm source identification capabilities has been developed. These tools collectively form the Wave Identification and Tracking System (WITS) and have been assembled entirely within the Matlab programming environment. A series of directional wave spectra, with supporting wind observations, is the only required input. Wave spectrum peaks representing specific wind sea and swell wave systems are extracted based on topographic minima, with wind sea peaks identified by wave age criteria. A swell tracking algorithm, combined with linear wave theory, provides a unique approach to storm source identification using the assimilated wave system statistics. The nature of the partitioned spectra allows the continuous, automated identification and tracking of multiple swell generation areas over space and time. Over a 6-day wave record in the Gulf of Alaska, 44 specific swell systems are identified, with up to three systems coexisting at any given time. The presence of atmospheric disturbances on surface weather charts validated the storm source predictions for more than 85% of these systems. The results are synthesized to depict the wave evolution history over the duration of the observations.
Corresponding author address: Jeffrey L. Hanson, The Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723-6099.
Email: jeffrey.hanson@jhuapl.edu
