Estimating Subpycnocline Density Fluctuations in the California Current Region from Upper Ocean Observations

Abstract

A method for extending upper ocean density observations to the deep ocean is tested using a large number of deep CTD stations in the California Current. The specific problem considered is that of constructing the best estimate for the density profile below a certain depth, D, given an observed profile above that depth. For this purpose, the estimated disturbance profile is modeled as a weighted sum of empirical vertical modes (EOFs). The EOFs were computed from the surface to 2000 m using 126 largely independent CTD stations off Pt. Sur, California. Separate computations were made for the summer half- year (mid-April to mid-October) and the winter half-year ( mid-October to-mid- April). For each observed density provile, the EOF weights that determine the estimated profile were obtained by performing a successive least squares fit of the disturbance density profile above D to the first N EOFs. In this study, N was taken to be 7, which is the number of EOFs considered necessary to account for the 'signal' in the profiles as determined by the methods of Preisendorfer et al. (1981) and Smith et al. (1985). The estimated profiles were then verified against the observed profiles to 2000 m, and the results are presented as a function of the depth D.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1994
Accession Number
ADA277278

Entities

People

  • Curtis Collins
  • Robert A. Hale
  • Robert L. Haney

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • C4I

DTIC Thesaurus Topics

  • California
  • Classification
  • Confidence Limits
  • Deep Oceans
  • Eigenvalues
  • Gulf Stream
  • Military Research
  • North America
  • Observation
  • Ocean Currents
  • Oceanography
  • Oceans
  • Regions
  • Sea Surface Temperature
  • Security
  • Surface Temperature
  • Water

Readers

  • Approximation Theory.
  • Atmospheric Science/Meteorology
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers