A Method for Evaluation of Model-Generated Vertical Profiles of Meteorological Variables

Abstract

Meteorological centers compare global and large-scale regional model output vs. radiosonde data more or less continuously for specific models and also make intermodel comparisons. They normally provide comparisons of meteorological variables at standard pressure levels, and similar comparisons for finer-scale models may be found as output from field tests and other experiments. Additional means to more fully evaluate vertical profiles derived from model output should help provide a more complete evaluation of model output as compared to observations. Here we develop methods to produce vertical profiles of meteorological variables in terms of height and pressure levels, and generate integrated mean value profiles of those variables for layers as defined by user input. These output profiles were entered into spreadsheets for calculation of the derived variables of density and vector wind speed. The level and mean layer values from the Weather Research and Forecasting model (version 3.6.1) were compared to level and layer values from co-incident World Meteorological Organization radiosonde observation data and the differences computed for the several variables. The methods developed here may be used for a variety of model-generated and observed vertical profiles with only minimal changes, primarily to the input function.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2016
Accession Number
AD1004526

Entities

People

  • J. L. Cogan

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Boundary Layer
  • Delphi Method
  • Field Tests
  • Information Science
  • Layers
  • Meteorology
  • Military Research
  • Observation
  • Radiosondes
  • Scale Models
  • Sea Level
  • Sea Surface Temperature
  • Standards
  • Surface Temperature
  • Test And Evaluation
  • United States
  • Weather Forecasting

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computer Science.