Evidence map›Paper›PMID 34504151›Full record

ArticleScientific reports2021

El Niño Modoki can be mostly predicted more than 10 years ahead of time.

X San Liang, Fen Xu, Yineng Rong, Renhe Zhang, Xu Tang, Feng Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

X San LiangDepartment of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, No. 2005 Songhu Rd, Yangpu District, Shanghai, 200438, China. sanliang@courant.nyu.edu.
Fen XuNanjing Center for Ocean-Atmosphere Dynamical Studies, Nanjing Institute of Meteorology, Nanjing, 210044, China.
Yineng RongNanjing Center for Ocean-Atmosphere Dynamical Studies, Nanjing Institute of Meteorology, Nanjing, 210044, China.
Renhe ZhangDepartment of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, No. 2005 Songhu Rd, Yangpu District, Shanghai, 200438, China.
Xu TangDepartment of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, No. 2005 Songhu Rd, Yangpu District, Shanghai, 200438, China.
Feng ZhangDepartment of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, No. 2005 Songhu Rd, Yangpu District, Shanghai, 200438, China.

Funding

Jiangsu Program for Innovation Research and Entrepreneurship Groups 2015National Natural Science Foundation of China 41975064
6 · The paper itself

Abstract

The 2014-2015 "Monster"/"Super" El Niño failed to be predicted one year earlier due to the growing importance of a new type of El Niño, El Niño Modoki, which reportedly has much lower forecast skill with the classical models. In this study, we show that, so far as of today, this new El Niño actually can be mostly predicted at a lead time of more than 10 years. This is achieved through tracing the predictability source with an information flow-based causality analysis, which has been rigorously established from first principles during the past 16 years (e.g., Liang in Phys Rev E 94:052201, 2016). We show that the information flowing from the solar activity 45 years ago to the sea surface temperature results in a causal structure resembling the El Niño Modoki mode. Based on this, a multidimensional system is constructed out of the sunspot number series with time delays of 22-50 years. The first 25 principal components are then taken as the predictors to fulfill the prediction, which through causal AI based on the Liang-Kleeman information flow reproduces rather accurately the events thus far 12 years in advance.

Identifiers

PMID34504151
PMCPMC8429568

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.