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Estimating ENSO predictability based on multi-model hindcasts

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Abstract

Based on hindcasts of seasonal forecast systems participating in the North American Multi-Model Ensemble, the seasonal dependence of predictability of the El Niño–Southern Oscillation (ENSO) was estimated. The results were consistent with earlier analyses in that the predictability of ENSO was highest in winter and lowest in spring and summer. Further, predictability as measured by the relative amplitude of predictable and unpredictable components was dominated by the ensemble mean instead of the spread (or dispersion) among ensemble members. This result was consistent with previous analysis that most of ENSO predictability resides in the shift of the probability density function (PDF) of ENSO sea surface temperature (SST) anomalies (i.e., changes in the first moment of the PDF that is associated with the ensemble mean of ENSO SST anomalies) rather than due to changes in the spread of the PDF. The analysis establishes our current best estimate of ENSO predictability that can serve as a benchmark for quantifying further improvements resulting from advances in observing, assimilation, and seasonal prediction systems.

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Acknowledgments

The NMME project and data dissemination is supported by NOAA, NSF, NASA and DOE. The help of NCEP, IRI and NCAR personnel in creating, updating and maintaining the NMME archive is acknowledged. All the data used in this paper are available at NOAA Climate Prediction Center (CPC) (http://www.cpc.ncep.noaa.gov/products/NMME/). We appreciate constructive comments and suggestions from two reviewers as well as from our colleagues, Drs. Qin Zhang and Emily Becker, and their help in processing the NMME data. The scientific results and conclusions, as well as any view or opinions expressed herein, are those of the authors and do not necessarily reflect the views of NWS, NOAA, or the Department of Commerce.

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  1. Climate Prediction Center, NCEP/NWS/NOAA, 5830 University Research Court, College Park, MD, 20740, USA

    Arun Kumar, Zeng-Zhen Hu, Bhaskar Jha & Peitao Peng

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  1. Arun Kumar
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  2. Zeng-Zhen Hu
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  3. Bhaskar Jha
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  4. Peitao Peng
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Correspondence to Zeng-Zhen Hu.

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Kumar, A., Hu, ZZ., Jha, B. et al. Estimating ENSO predictability based on multi-model hindcasts. Clim Dyn 48, 39–51 (2017). https://doi.org/10.1007/s00382-016-3060-4

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