Dynamical Numerical Prediction of Large-Scale Thermal Anomalies in the North Pacific Ocean.

Abstract

A ten-level primitive equation ocean circulation model is used to investigate the formation and evolution of large-scale thermal anomalies observed in the central North Pacific Ocean during the fall and winter of 1976. Several initial value model integrations of 4 months duration are carried out in order to help explain the observed anomaly development. Initial and verifying ocean data down to 400 m depth are obtained from the NORPAX ships of opportunity program. Anomalous atmospheric wind forcing is obtained from Namias' monthly mean sea-level pressure anomalies, while climatological heat fluxes are used. The skill with which the model simulates the observed anomaly evolution in the different experiments is estimated synoptically and measured statistically by calculating root mean square (RMS) temperature errors and S1 skill scores. Analysis indicates that anomalous atmospheric wind forcing improves the model predictions in the upper levels. For this particular winter case using climatological heating, however, knowledge of the initial anomalous temperature conditions does not improve the model results. The model skill at upper levels exceeds both persistence and climatology (forecast of zero anomaly) while at the lower levels it is comparable to persistence but not as good as climatology. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1977
Accession Number
ADA049919

Entities

People

  • Wayne Stuart Shiver

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Atmospheric Sciences
  • Climatology
  • Grids
  • Heat Flux
  • Meteorology
  • North America
  • North Pacific Ocean
  • Ocean Currents
  • Oceanography
  • Oceans
  • Pacific Ocean
  • Ridges
  • Sea Level
  • Sea Surface Temperature
  • Statistics
  • Surface Temperature
  • United States

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation