Derivation of Kinematic Fields Using Wind Profiler Data from the 1985 Pre-Storm Experiment

Abstract

During the May and June 1985 PRE-STORM experiment, three 50 MHz wind profilers were installed for the first time on the Great Plains to enhance the understanding of mesoscale system development and evolution. In order to utilize these profiler data for the computation of kinematic quantities, many instances of poor or missing data must be dealt with. Often, this requires the performance of separate screening, filing, interpolation, and filtering steps. This study proposes the accomplishment of the latter three steps at once through the adaption of a Barnes objective analysis technique. Using wind covariance statistics from a Colorado profiler, a weight function is designed which assigns equal weight to equally correlated data in time and in the vertical. Features within vertical motion fields derived after application of this technique corresponds well with features seen in satellite imagery and contain detail unobtainable via analysis of rawinsonde data. The development of clear air wind observation systems through advances in Doppler radar technology has provided the meteorologist with a new generation measuring device - the wind profiler. Wind profilers can provide tropospheric wind profiles every few minutes at height intervals of 200 meters or less. It has long been known, via satellite imagery, that small-scale upper air features exist and could partially be responsible for poor forecasts. (KR)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA217952

Entities

People

  • Jeffrey D. Powell

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Boundary Layer
  • Convection
  • Data Sets
  • Doppler Radar
  • Elevation
  • Grids
  • Layers
  • Measurement
  • Meteorology
  • Quality Control
  • Radar Beams
  • Satellite Imaging
  • Standards
  • Statistics
  • Stratified Fluids
  • Weather Forecasting

Fields of Study

  • Environmental science

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Radar Systems Engineering.
  • Regression Analysis.

Technology Areas

  • Space