Strong El Niño and La Niña precipitation—sea surface temperature sensitivity under a carbon removal scenario

El Niño-Southern Oscillation-induced tropical Pacific precipitation anomalies have global impacts and will intensify under greenhouse warming, but the potential for mitigating these changes is less understood. Here, we identify distinct hysteresis features in the precipitation-sea surface temperature sensitivity between strong El Niño and La Niña phases using a large ensemble carbon removal numerical simulation. The strong El Niño precipitation sensitivity exhibits a century-scale hysteretic enhancement and eastward shift, mainly due to modulated deep convection anomalies by the Intertropical Convergence Zone via cloud-longwave feedback. Instead, the strong La Niña counterpart is concentrated toward the equator, mostly in the central-western Pacific, with a shorter hysteresis period of a few decades. This primarily involves changes in shallow convection and surface thermal structures during La Niña, shaped by global warming-induced upper-ocean circulation changes. The distinct climate change regimes of strong El Niño and La Niña precipitation sensitivity hold important implications for assessing mitigation consequences. The hysteresis in precipitation-sea surface temperature sensitivity differs between strong El Niño and La Niña phases, with El Niño intensifying and shifting eastward due to deep convection, while La Niña is more equator-centered with a shorter hysteresis period, according to a large ensemble simulation of symmetric CO2 ramp-up and ramp-down pathways.

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Publication Details

Journal
Communications Earth & Environment
Published
2024-12-19
DOI
https://doi.org/10.1038/s43247-024-01958-8
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.13

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article

Strong El Niño and La Niña precipitation—sea surface temperature sensitivity under a carbon removal scenario

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Communications Earth & Environment
Climate variability and models
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article

Strong El Niño and La Niña precipitation—sea surface temperature sensitivity under a carbon removal scenario

Zixiang Yan, Seungmok Paik, Soon‐Il An, Soong‐Ki Kim, Chao Liu
article en
4 citations

Abstract

El Niño-Southern Oscillation-induced tropical Pacific precipitation anomalies have global impacts and will intensify under greenhouse warming, but the potential for mitigating these changes is less understood. Here, we identify distinct hysteresis features in the precipitation-sea surface temperature sensitivity between strong El Niño and La Niña phases using a large ensemble carbon removal numerical simulation. The strong El Niño precipitation sensitivity exhibits a century-scale hysteretic enhancement and eastward shift, mainly due to modulated deep convection anomalies by the Intertropical Convergence Zone via cloud-longwave feedback. Instead, the strong La Niña counterpart is concentrated toward the equator, mostly in the central-western Pacific, with a shorter hysteresis period of a few decades. This primarily involves changes in shallow convection and surface thermal structures during La Niña, shaped by global warming-induced upper-ocean circulation changes. The distinct climate change regimes of strong El Niño and La Niña precipitation sensitivity hold important implications for assessing mitigation consequences. The hysteresis in precipitation-sea surface temperature sensitivity differs between strong El Niño and La Niña phases, with El Niño intensifying and shifting eastward due to deep convection, while La Niña is more equator-centered with a shorter hysteresis period, according to a large ensemble simulation of symmetric CO2 ramp-up and ramp-down pathways.

Communications Earth & EnvironmentVol. 5(1)
Yonsei University (KR), Fudan University (CN)
National Research Foundation, Yonsei University, Korea Meteorological Administration, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, Korea Research Environment Open Network, National Supercomputing Center, Korea Institute of Science and Technology Information
Life below water
Openalex Percentile: Top 22%
Climate variability and models
1.13
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