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Stability of ENSO teleconnections during the last millennium in CESM

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Abstract

The El Niño-Southern Oscillation (ENSO) has a significant impact on the global climate through atmospheric teleconnections. It is important to understand the stability of ENSO teleconnections, not only for future weather forecasting and climate projection, but also for ENSO reconstructions based on paleo-proxies. In this study, we investigate the decadal variations of ENSO teleconnections in global land surface temperature (LST) from 850 to 2005AD using 13 ensemble members of the Community Earth System Model-Last Millennium Ensemble (CESM-LME). The CESM can simulate the main Eurasian cooling and Arctic warming, known as the warm Arctic-cold Eurasia (WACE) pattern, during the boreal winter of an El Niño. Furthermore, it can also capture the western Antarctic warming during the developing and decaying summers of an El Niño. There is a dominant decadal variation in the ENSO-LST teleconnections, expressed as anomalous LST patterns that closely resemble those seen in the WACE pattern during boreal winter and the western Antarctic warming pattern during summer. This decadal variation of ENSO-LST teleconnections is primarily due to the varying positions of Rossby wave sources associated with distinct ENSO patterns, which are located either to the west or to the east of Hawaii. The LST response to ENSO over South Siberia, as well as the associated precipitation response over North Eurasia, even show opposite patterns at different phases of the decadal variation. The decadal variation in CESM is found to be related to the interdecadal Pacific oscillation (IPO) and is likely attributed to internal variability rather than external forcing. Our findings suggest that the decadal variation in ENSO teleconnections should be considered when using proxies from Eurasian regions to reconstruct ENSO variability.

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Data availability

CESM1 Last Millennium Ensemble (LME) database was downloaded from https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.cesmLME.html. For details regarding the LME, see https://www.cesm.ucar.edu/projects/community-projects/LME/.

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Funding

This work was jointly supported by the Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004), and the National Natural Science Foundation of China (42175061; 41975107; 42175080; 42176017).

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Authors and Affiliations

  1. Key Laboratory of Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Ministry of Natural Resources, Beijing, 100081, China

    Xue Han & Licheng Feng

  2. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Xue Han

  3. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Yanjie Li

  4. School of Atmospheric Sciences, Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory, Sun Yat-Sen University, Zhuhai, 519082, China

    Fei Liu

  5. Department of Geography, The University of Hong Kong, Pokfulam, Hong Kong SAR, China

    Jinbao Li

  6. Key Laboratory of Physical Oceanography and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao, 266100, China

    Xiaotong Zheng

  7. College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518061, China

    Yan Li

Authors
  1. Xue Han
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  2. Yanjie Li
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  3. Fei Liu
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  6. Yan Li
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Contributions

XH, YJL, and FL were responsible for design of the research. Material preparation, data collection, and analysis were performed by XH, YJL and FL. JL, XZ, LF and YL helped interpret the results. XH wrote the first draft of the manuscript. All authors provided comments on different versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Fei Liu.

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Supplementary Information

Below is the link to the electronic supplementary material.

382_2023_6878_MOESM1_ESM.jpeg

Supplementary material 1Figure S1. Simulated ENSO in CESM-LME. Evolution of monthly NINO3.4 index in 13 CESM-LME (grey lines), as well as their ensemble mean (dark line), and observed one in HadISST (red line) for (a) El Niño events and (b) La Niña events, respectively (JPEG 958.6 kb)

382_2023_6878_MOESM2_ESM.jpeg

Supplementary material 2Figure S2. ENSO teleconnections and its decadal change. Same as Fig. 1, but with a 31-year-sliding window (JPEG 1773.2 kb)

382_2023_6878_MOESM3_ESM.jpeg

Supplementary material 3Figure S3. Forced component of the decadal variations of ENSO-LST teleconnections. The first mode of three-season EOF analysis on the associated 11-year-sliding anomalies regression maps with an interval of five years for the 13-ensembles mean (JPEG 924.8 kb)

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Han, X., Li, Y., Liu, F. et al. Stability of ENSO teleconnections during the last millennium in CESM. Clim Dyn 61, 5699–5714 (2023). https://doi.org/10.1007/s00382-023-06878-5

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