Informativeness of Wind Data in Linear Madden-Julian Oscillation Prediction

Abstract

Linear inverse models (LIMs) are used to explore predictability and information content of the MaddenJulian Oscillation (MJO). Hindcast skill for outgoing longwave radiation (OLR)related to the MJO on intraseasonal timescales in the tropics has been examined for a variety of LIMs using OLR and optionally 200 and 850 hPa zonal wind information channels. The dependence of OLR hindcast skill on wind channels was evaluated by randomizing in time, averaging in space, or omitting data entirely. Results show positive prediction skill (relative to climatology) up to 3weeks and wind information, mostly at the largest scales, adds 12 days of skill.

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Document Details

Document Type
Technical Report
Publication Date
Aug 15, 2016
Accession Number
AD1010491

Entities

People

  • Brian Mapes
  • Nicholas Cavanaugh
  • Theodore Allen

Organizations

  • University of Miami

Tags

DTIC Thesaurus Topics

  • Atmospheric Sciences
  • Central America
  • Climate
  • Climate Change
  • Climatology
  • Coefficients
  • Continents
  • Dynamics
  • Equations
  • Errors
  • Lead Time
  • Longitude
  • Oscillation
  • Sea Surface Temperature
  • Surface Temperature
  • Training
  • Verification

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Regression Analysis.

Technology Areas

  • Space