Subseasonal Week 3–5 Surface Air Temperature Prediction During Boreal Wintertime in a GFDL Model

Baoqiang Xiang, Shian Jiann Lin, Ming Zhao, Nathaniel C. Johnson, Xiaosong Yang, Xianan Jiang

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

With a Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the subseasonal prediction of wintertime (December–February) surface air temperature (SAT) is investigated through the analysis of 11-year hindcasts. Significant subseasonal week 3–5 correlation skill exists over a large portion of the global land domain, and the predictability originates primarily from the eight most predictable SAT modes. The first three modes, identified as the El Niño-Southern Oscillation mode, the North Atlantic Oscillation mode, and the Eurasia Meridional Dipole mode, can be skillfully predicted more than 5 weeks in advance. The North Atlantic Oscillation and Eurasia Meridional Dipole modes are strongly correlated with the initial stratospheric polar vortex strength, highlighting the role of stratosphere in subseasonal prediction. Interestingly, the Madden-Julian Oscillation is not essential for the subseasonal land SAT prediction in the Northern Hemisphere extratropics. The spatial correlation skill exhibits considerable intraseasonal and interannual fluctuations, indicative of the importance to identify the time window of opportunity for subseasonal prediction.

Original languageEnglish
Pages (from-to)416-425
Number of pages10
JournalGeophysical Research Letters
Volume46
Issue number1
DOIs
StatePublished - Jan 16 2019

Keywords

  • ENSO
  • MJO
  • NAO
  • average predictability time
  • subseasonal prediction
  • surface air temperature

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