An Experiment in Numerical Prediction in Equatorial Latitudes

Abstract

In order to obtain the dynamical structure of the tropical atmosphere in equatorial latitudes a short range prediction experiment is proposed. The initial field contains the intertropical convergence zone and associated disturbances over western Pacific Ocean during March 1965. A complete initial state is constructed using a consistent balance system of equations. The procedure involves construction of pressure, temperature and vertical motion distributions starting from an observed rotational part of the wind field. It is shown that this procedure, whose validity assumes a small Rossby number, does not yield a realistic structure of the vertical motion. A short range prediction with a multi-level prediction model yields some interesting solutions in the vicinity of the intertropical convergence zone. During the first 18 hours of prediction an adjustment of the motion and the mass field ensues with gravity inertia oscillations. A detailed discussion of some dynamical aspects at 24 hours is presented. An important feature of the model is a parameterization of cumulus convection as a function of large-scale moisture convergence. The role of cumulus scale heating in the vicinity of the intertropical convergence zone is explored by carrying out experiments with and without diabatic heating. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1968
Accession Number
AD0678080

Entities

People

  • T. N. Krishnamurti

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Coefficients
  • Convection
  • Convergence Zones (Sonar)
  • Diffusion Coefficient
  • Energy
  • Energy Conversion
  • Energy Transfer
  • Equations
  • Grids
  • Heat Energy
  • Humidity
  • Kinetic Energy
  • Latent Heat
  • Meteorology
  • Pacific Ocean

Readers

  • Coastal Oceanography
  • Fluid Dynamics.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers