Tropical Weather System and Ocean Modeling.

Abstract

The interactions between atmospheric vortex pairs are simulated and studied with a nondivergent barotropic model and a three-dimensional tropical cyclone model. Numerical experiments with nondivergent barotropic vortex pairs show that the relative movements of the vortices are sensitive to the separation distance and the characteristics of the swirling wind of the vortex. No mutual attraction is found in any of the nondivergent, barotropic vortex pairs tested. Results from the 3D tropical cyclone model show that on a constant-f plane with no mean wind, the movements of the two interacting tropical cyclones consist of a mutual cyclonic rotation, attraction, and eventual merging, in agreement with Fujiwhara's description. The displacement of one interacting storm in the mutual rotation is proportional to the combined strength of the binary system, but inversely proportional to the size of the storm and to the square of the separation distance. The rate of merging is related to the development of a mean secondary circulation on the radial-vertical plane, and is quite independent of the strength of the two cyclones. The latitudinal variation of the Coriolis parameter adds a northwest beta drift to the trajectories. Depending on their relative strength and location, the beta drift either speeds up the merging process or separates the two interacting tropical cyclones. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1983
Accession Number
ADA137421

Entities

People

  • Shi Chang

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Atmospheric Sciences
  • Boundary Layer
  • Convection
  • Cyclones
  • Displacement
  • Equations
  • Geometry
  • Grids
  • Kinetic Energy
  • Pacific Ocean
  • Radial Velocity
  • Rotation
  • Simulations
  • Space Sciences
  • Three Dimensional
  • Trajectories
  • Tropical Cyclones

Readers

  • Atmospheric Science/Meteorology
  • Control Systems Engineering.
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.