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Episodic slowdown of global warming by a multi-year La Niña

Episodic slowdown of global warming by a multi-year La Niña

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Authors

Tomoki Iwakiri, Tsubasa Kohyama 

Abstract

Global mean surface temperature (GMST), which has continued to rise due to the anthropogenic greenhouse gas forcing, is closely related to the sea surface temperature variability in the tropical Pacific. In particular, GMST is known to increase during a strong and short-lived El Niño. By contrast, the global cooling effect of a weak and long-lived La Niña remains underexplored, particularly that of multi-year La Niña. This study shows that multi-year La Niña events tend to have a strong cooling effect on GMST based on observations and climate model simulations. The minimum of GMST around the second-year La Niña becomes larger despite the comparable or weaker amplitude of La Niña. The persistent La Niña cools the pantropical climate, causing a temporary GMST warming stagnancy, whereas the cooling effect of a single-year La Niña is weaker due to the lagged response of other tropical basins and its transience. Yet, even during so-called triple-dip or longer events, global cooling can persist despite the modest La Niña forcing, because the pan-tropical climate has already been cooled. Applying the resistor–capacitor (RC)-framework analogy, we demonstrate that the lagged decreases in GMST and its lower bound during multi-year La Niña episodes arise naturally from the climate system’s intrinsic transient sensitivity and the heat capacity of the ocean mixed layer. The RC framework would offer a simple, intuitive, and pedagogically useful tool for interpreting the GMST response to ENSO.

DOI

https://doi.org/10.31223/X5747M

Subjects

Physical Sciences and Mathematics

Keywords

ENSO, El Niño Southern Oscillation, Global-mean surface temperature

Dates

Published: 2026-05-12 16:48

Last Updated: 2026-05-12 16:48

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
The authors declare no competing interests.

Data Availability:
Multi-model large ensemble archive version 2 is available at https://www.cesm.ucar.edu/community-projects/mmlea/v2. Last Millennium Ensemble project is available at https://www.cesm.ucar.edu/community-projects/lme. GISTEMPv4 and ERSSTv6 are available at https://data.giss.nasa.gov/gistemp/updates_v4 and https://www.ncei.noaa.gov/products/extended-reconstructed-sst, respectively. Original figures are generated using Python with the matplotlib and cartopy libraries (https://matplotlib.org/, https://scitools.org.uk/cartopy).

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