Verification of MM5 Cloud Microphysics Schemes for East Asia

Abstract

This research compares biases of the Reisner Mixed-Phase Explicit Moisture Microphysics graupel and non-granpel schemes to determine if including graupel and riming processes within the Fifth Generation Mesoscale Model (MM5) will lead to improved forecasts of winter precipitation for Korea and Japan. MM5 forecasts were generated every 12 hours for a 20 days case period from January 1998. Model derived meteorological fields were interpolated to the station coordinates of four verification sites within the East Asian domain and radiosonde observations were used to compare the differences between the average temperature and water vapor errors of the two cloud microphysics schemes. Analysis of the results shows significant differences between the schemes in the magnitude of humidity errors within the lower atmosphere of the model and provides evidence that the more complicated graupel and riming scheme will not increase the skill of the MM5 in forecasting winter precipitation for Japan and Korea. The underlying conclusion of this research is that AFWA should not alter the cloud microphysics scheme currently employed to determine winter precipitation type for its East Asian forecast window.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2002
Accession Number
ADA404556

Entities

People

  • Dean J. Carter

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Databases
  • Geography
  • Heat Energy
  • Humidity
  • Isotherms
  • Latent Heat
  • Meteorology
  • Military Operations
  • Precipitation
  • Spreadsheet Software
  • Statistical Analysis
  • Surface Temperature
  • United States
  • Water Vapor
  • Weather Forecasting
  • Wet Bulb Temperature

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)