Informativeness of wind data in linear Madden-Julian oscillation prediction

Theodore L. Allen, Brian E Mapes, Nicholas Cavanaugh

Research output: Contribution to journalArticle

Abstract

Linear inverse models (LIMs) are used to explore predictability and information content of the Madden-Julian 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 3 weeks and wind information, mostly at the largest scales, adds 1-2 days of skill.

Original languageEnglish (US)
Pages (from-to)362-367
Number of pages6
JournalAtmospheric Science Letters
Volume17
Issue number6
DOIs
StatePublished - Jun 1 2016

Keywords

  • Linear inverse modeling
  • Madden-Julian Oscillation
  • Sub-seasonal prediction

ASJC Scopus subject areas

  • Atmospheric Science

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