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Article

Phase-Locking of El Niño and La Niña Events in CMIP6 Models

Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai 200000, China
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Author to whom correspondence should be addressed.
Atmosphere 2024, 15(8), 882; https://doi.org/10.3390/atmos15080882
Submission received: 22 June 2024 / Revised: 17 July 2024 / Accepted: 22 July 2024 / Published: 24 July 2024

Abstract

El Niño–Southern Oscillation (ENSO) usually peaks in the boreal winter—November to January of the following year. This particular feature of ENSO is known as the seasonal phase locking of ENSO. In this study, based on 34 climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the seasonal phase-locking characteristics of the model-simulated El Niño and La Niña events are evaluated in terms of the evolution of the SST anomalies associated with ENSO and the probability distribution of the peak month—the time at which ENSO peaks. It is found that CMIP6 models underestimate the phase-locking strength of ENSO for both El Niño and La Niña events. The ensemble mean peak month matches the observations, but the inter-model spread is large. The models simulate the phase locking of El Nino events better than that of La Niña events, and the large simulation bias of CMIP6 for La Niña phase-locking in the models may have an impact on the simulation of seasonal phase-locking in the ENSO.
Keywords: phase-locking; El Niño and La Niña; coupled models; CMIP6 models; climate variability phase-locking; El Niño and La Niña; coupled models; CMIP6 models; climate variability

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MDPI and ACS Style

Yan, Y.; Sun, D.-Z. Phase-Locking of El Niño and La Niña Events in CMIP6 Models. Atmosphere 2024, 15, 882. https://doi.org/10.3390/atmos15080882

AMA Style

Yan Y, Sun D-Z. Phase-Locking of El Niño and La Niña Events in CMIP6 Models. Atmosphere. 2024; 15(8):882. https://doi.org/10.3390/atmos15080882

Chicago/Turabian Style

Yan, Yu, and De-Zheng Sun. 2024. "Phase-Locking of El Niño and La Niña Events in CMIP6 Models" Atmosphere 15, no. 8: 882. https://doi.org/10.3390/atmos15080882

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