Assessing seasonal predictability sources and windows of high predictability in the climate forecast system, version 2

Douglas E. Miller, Zhuo Wang

Research output: Contribution to journalArticlepeer-review


The representation of ENSO and NAO are examined in the Climate Forecast System, version 2 (CFSv2), reforecasts with a focus on the physical processes related to teleconnections and predictability. CFSv2 predicts ENSO well, but an eastward shift of the tropical Pacific sea surface temperature (SST) anomalies is evident. Although it appears minor on the global scale, the shift in convection and the large-scale wave train affects the model prediction of regional climate. In contrast, NAO is predicted poorly. The anomaly correlation coefficient (ACC) between the model ensemble mean and the observation is 0.27 during 1982-2010, and the ensemble spread is large. The representation of three sources of NAO predictability-SST, the stratospheric polar vortex, and the Arctic sea ice concentration-is investigated. It is found that the link between tropical Pacific SST and NAO is not well represented in CFSv2, and that the tropospheric- stratospheric interactions are too weak, both contributing to the poor prediction of NAO. Additionally, the impact of ENSO and NAO on prediction skill of CFSv2 in boreal winter is analyzed in terms of the spatial ACC of geopotential height. Active ENSO events exhibit larger prediction skill than neutral years, especially during the ENSO+/NAO2 and ENSO-/NAO+ winters. Spatial patterns of prediction skill are also examined, and larger skill of geopotential height and 2-m air temperature is found outlined by the nodes of the PNA pattern, consistent with the large signal-to-noise ratios associated with the ENSO teleconnection.

Original languageEnglish (US)
Pages (from-to)1307-1326
Number of pages20
JournalJournal of Climate
Issue number4
StatePublished - Feb 1 2019


  • ENSO
  • Forecast verification/skill
  • North Atlantic Oscillation
  • Seasonal forecasting

ASJC Scopus subject areas

  • Atmospheric Science


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