The North American multimodel ensemble: Phase-1 seasonal-to-interannual prediction; phase-2 toward developing intraseasonal prediction

Ben P. Kirtman, Dughong Min, Johnna M. Infanti, James L. Kinter, Daniel A. Paolino, Qin Zhang, Huug Van Den Dool, Suranjana Saha, Malaquias Pena Mendez, Emily Becker, Peitao Peng, Patrick Tripp, Jin Huang, David G. Dewitt, Michael K. Tippett, Anthony G. Barnston, Shuhua Li, Anthony Rosati, Siegfried D. Schubert, Michele RieneckerMax Suarez, Zhao E. Li, Jelena Marshak, Young Kwon Lim, Joseph Tribbia, Kathleen Pegion, William J. Merryfield, Bertrand Denis, Eric F. Wood

Research output: Contribution to journalArticlepeer-review

792 Scopus citations

Abstract

The first change in prediction strategy naturally follows from the fact that climate variability includes a chaotic or irregular component, and, because of this, forecasts must include a quantitative assessment of this uncertainty. More importantly, the climate prediction community now understands that the potential utility of climate forecasts is based on end-user decision support. The forecasts are provided to the NOAA CPC on an experimental basis for evaluation and consolidation as a multimodel ensemble ISI prediction system. The experimental prediction system developed by this NMME team is as an 'NMME of opportunity' in that the seasonal-to-interannual prediction systems are readily available and each team member has independently developed the initialization and prediction protocol. In the months before August 2011, the hindcast data were collected and climatologies and skill assessments for each model to be applied to subsequent real-time predictions were calculated.

Original languageEnglish (US)
Pages (from-to)585-601
Number of pages17
JournalBulletin of the American Meteorological Society
Volume95
Issue number4
DOIs
StatePublished - Apr 2014

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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