Effectiveness of Two Forecast Models for Stratiform Precipitation

Abstract

The U.S. Army Research Laboratory has developed a mesoscale weather model called the Battlescale Forecast Model (BFM). After model initialization, the BFM produces forecast variables for a 24-h period. Since the Army required a longer-term prediction, the Mesoscale Model Version 5 (MM5) gridded data are received from the U.S. Air Force Weather Agency to provide forecast information for up to a 48-h period. Due to the importance of precipitation on the tactical decision aids, as well as military operations in general, both models forecast stratiform and convective precipitation, which are made available to the user in a database and graphically. This report describes the basic meteorological theory applied to the precipitation processes and forecasts for both the BFM and MM5. The effectiveness of the BFM and MM5 precipitation output are analyzed as well. Precipitation forecasts are derived from numerical model data, such as the BFM and MM5. These data provide the forecaster and users with a detailed overview of the atmospheric conditions that might produce precipitation along with the general precipitation rates, amounts, and types. These precipitation parameters are later placed into other programs, such as the Integrated Weather Effects Decision Aid, can attain this information.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2004
Accession Number
ADA424348

Entities

People

  • Jeffrey E. Passner

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Air Force
  • Boundaries
  • Boundary Layer
  • Computational Fluid Dynamics
  • Databases
  • Environment
  • Grids
  • Heat Energy
  • Humidity
  • Information Science
  • Latent Heat
  • Layers
  • Meteorology
  • Military Research
  • Precipitation
  • Statistical Analysis
  • Water Vapor

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation