Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: Jeffrey L. Hanson x
  • Refine by Access: All Content x
Clear All Modify Search
Jeffrey L. Hanson
and
Owen M. Phillips

Abstract

Wind sea growth and dissipation in a swell-dominated, open ocean environment is investigated to explore the use of wave parameters in air–sea process modeling. Wind, wave, and whitecap observations are used from the Gulf of Alaska surface scatter and air–sea interaction experiment (Critical Sea Test-7, Phase 2), conducted 24 February through 1 March 1992. Wind sea components are extracted from buoy directional wave spectra using an inverted catchment area approach for peak isolation with both wave age criteria and an equilibrium range threshold used to classify the wind sea spectral domain. Dimensionless wind sea energy is found to scale with inverse wave age independently of swell. However, wind trend causes significant variations, such as underdeveloped seas during rising winds. These important effects are neglected in wind-forced air–sea process models.

The total rate of wave energy dissipation is conveniently estimated using concepts from the Phillips equilibrium range theory. Replacing wind speed with wave dissipation rate in the standard power-law description of oceanic whitecap fraction decreases the range of data scatter by two to three orders of magnitude. The improved modeling of whitecaps demonstrates that wave spectral parameters can be used to enhance air–sea process models.

Full access
Jeffrey L. Hanson
and
Owen M. Phillips

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.

Full access