Seasonal Characteristics of Bottom Boundary Layer Detachment at the Shelfbreak Front in the Middle Atlantic Bight

Abstract

The seasonality of various characteristics of the detached bottom boundary layer of the Middle Atlantic Bight shelfbreak front is examined using a collection of high resolution transects across the front. The analysis follows previous methodology in which accumulated temperature change along isopycnals within the front is used to infer the location of the detached layer. The seasonal mean isopycnal at which detachment occurs (approximately 26.0 kg cu.m) is fairly constant throughout the year. However, the vertical scale of the detached layer varies significantly with season, extending 60-80 m above the bottom in winter and spring, but only 20-40 m above the bottom in summer. The vertical scale is controlled by the strength and depth of the seasonal pycnocline. The observations suggest that the detached layer is capable of extending into the euphotic zone during winter and spring. INDEX TERMS: 4528 Oceanography: Physical: Fronts and jets; 4211 Oceanography: General: Benthic boundary layers; 4219 Oceanography: General: Continental shelf processes; 4279 Oceanography: General: Upwelling and convergences.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA422980

Entities

People

  • Christopher A. Linder
  • Glen G. Gawarkiewicz
  • Robert G. Pickart

Organizations

  • Woods Hole Oceanographic Institution

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Boundaries
  • Boundary Layer
  • Climate Change
  • Computer Programs
  • Continental Shelves
  • Euphotic Zones
  • High Resolution
  • Isotherms
  • Layers
  • New England
  • Observation
  • Oceanography
  • Oceans
  • Regions
  • Temperature Gradients
  • Topography
  • Upwelling

Fields of Study

  • Environmental science

Readers

  • Aquatic Ecology
  • Coastal Oceanography
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms