Complexity-based approach for El Niño magnitude forecasting before the spring predictability barrier

Jun Meng, Jingfang Fan, Josef Ludescher, Ankit Agarwal, Xiaosong Chen, Armin Bunde, Jürgen Kurths, Hans Joachim Schellnhuber

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


The El Niño Southern Oscillation (ENSO) is one of the most prominent interannual climate phenomena. Early and reliable ENSO forecasting remains a crucial goal, due to its serious implications for economy, society, and ecosystem. Despite the development of various dynamical and statistical prediction models in the recent decades, the “spring predictability barrier” remains a great challenge for long-lead-time (over 6 mo) forecasting. To overcome this barrier, here we develop an analysis tool, System Sample Entropy (SysSampEn), to measure the complexity (disorder) of the system composed of temperature anomaly time series in the Niño 3.4 region. When applying this tool to several near-surface air temperature and sea surface temperature datasets, we find that in all datasets a strong positive correlation exists between the magnitude of El Niño and the previous calendar year’s SysSampEn (complexity). We show that this correlation allows us to forecast the magnitude of an El Niño with a prediction horizon of 1 y and high accuracy (i.e., root-mean-square error = 0.23 C for the average of the individual datasets forecasts). For the 2018 El Niño event, our method forecasted a weak El Niño with a magnitude of 1.11 ± 0.23 C. Our framework presented here not only facilitates long-term forecasting of the El Niño magnitude but can potentially also be used as a measure for the complexity of other natural or engineering complex systems.

Original languageEnglish
Pages (from-to)177-183
Number of pages7
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number1
StatePublished - 7 Jan 2020
Externally publishedYes


  • ENSO
  • Entropy
  • Forecasting
  • Spring barrier
  • System complexity

ASJC Scopus subject areas

  • General


Dive into the research topics of 'Complexity-based approach for El Niño magnitude forecasting before the spring predictability barrier'. Together they form a unique fingerprint.

Cite this