Diverse NPMM conditions deviate the 2023/24 El Niño from the 1997/1998 and 2015/2016 extreme El Niño events

Abstract The 2023/24 El Niño commenced with an exceptionally large warm water volume in the equatorial western Pacific, comparable to the extreme 1997/98 and 2015/16 events, but did not develop into a super El Niño. This study highlights the critical role of contrasting Northern Pacific Meridional Mode (NPMM) conditions in this divergence. Warm NPMM conditions during the 1997/98 and 2015/16 events created a positive zonal sea surface temperature (SST) gradient in the equatorial western-central Pacific and enhanced Madden-Julian Oscillation (MJO) propagation, driving sustained westerly wind bursts (WWBs) and downwelling Kelvin waves that intensified both events. In contrast, the cold NPMM during 2023/24 induced a negative SST gradient and suppressed MJO activity, resulting in weaker WWBs and limited eastward wave activity, preventing the event from reaching super El Niño intensity. A 2,200-year CESM1 pre-industrial simulation corroborates these observational findings, underscoring the importance of NPMM interference in improving El Niño intensity predictions.

Authors

Institutions

Publication Details

Journal
npj Climate and Atmospheric Science
Published
2025-03-31
DOI
https://doi.org/10.1038/s41612-025-01013-z
Citations
3
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
3.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diverse NPMM conditions deviate the 2023/24 El Niño from the 1997/1998 and 2015/2016 extreme El Niño events

Ting‐Hui Lee, Jin‐Yi Yu, Ruiqiang Ding, Jiepeng Chen et al.
3 citations
npj Climate and Atmospheric Science
Climate variability and models
3.32
article

Diverse NPMM conditions deviate the 2023/24 El Niño from the 1997/1998 and 2015/2016 extreme El Niño events

Ting‐Hui Lee, Jin‐Yi Yu, Ruiqiang Ding, Jiepeng Chen, Min‐Hui Lo, Huang‐Hsiung Hsu, Fei Zheng, Xin Wang, Lingling Liu, Chau-Ron Wu, Mengyan Chen, Yong-Fu Lin
article en
3 citations

Abstract

Abstract The 2023/24 El Niño commenced with an exceptionally large warm water volume in the equatorial western Pacific, comparable to the extreme 1997/98 and 2015/16 events, but did not develop into a super El Niño. This study highlights the critical role of contrasting Northern Pacific Meridional Mode (NPMM) conditions in this divergence. Warm NPMM conditions during the 1997/98 and 2015/16 events created a positive zonal sea surface temperature (SST) gradient in the equatorial western-central Pacific and enhanced Madden-Julian Oscillation (MJO) propagation, driving sustained westerly wind bursts (WWBs) and downwelling Kelvin waves that intensified both events. In contrast, the cold NPMM during 2023/24 induced a negative SST gradient and suppressed MJO activity, resulting in weaker WWBs and limited eastward wave activity, preventing the event from reaching super El Niño intensity. A 2,200-year CESM1 pre-industrial simulation corroborates these observational findings, underscoring the importance of NPMM interference in improving El Niño intensity predictions.

npj Climate and Atmospheric ScienceVol. 8(1)
National Taiwan Normal University (TW), National Taiwan University (TW), Chinese Academy of Sciences (CN), University of California, Irvine (US), Beijing Normal University (CN), Institute of Oceanology (CN), South China Sea Institute Of Oceanology (CN), Irvine University (US), Research Center for Environmental Changes, Academia Sinica (TW), Institute of Atmospheric Physics (CN), Academia Sinica (TW)
Openalex Percentile: Top 9%
Climate variability and models
3.32
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.