Response of ENSO amplitude to global warming in CESM large ensemble: uncertainty due to internal variability
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El Niño–Southern Oscillation (ENSO) is the dominant mode of variability in the coupled ocean-atmospheric system. Future projections of ENSO change under global warming are highly uncertain among models. In this study, the effect of internal variability on ENSO amplitude change in future climate projections is investigated based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. A large uncertainty is identified among ensemble members due to internal variability. The inter-member diversity is associated with a zonal dipole pattern of sea surface temperature (SST) change in the mean along the equator, which is similar to the second empirical orthogonal function (EOF) mode of tropical Pacific decadal variability (TPDV) in the unforced control simulation. The uncertainty in CESM-LE is comparable in magnitude to that among models of the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting the contribution of internal variability to the intermodel uncertainty in ENSO amplitude change. However, the causations between changes in ENSO amplitude and the mean state are distinct between CESM-LE and CMIP5 ensemble. The CESM-LE results indicate that a large ensemble of ~15 members is needed to separate the relative contributions to ENSO amplitude change over the twenty-first century between forced response and internal variability.
We acknowledge the CESM-LE project for providing model outputs, which may be obtained from http://www.cesm.ucar.edu/projects/community-projects/LENS/data-sets.html. We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. We thank Shang-Ping Xie and Qinyu Liu for helpful discussions. This work was supported by the National Basic Research Program of China (2012CB955600 and 2015CB954300), the National Natural Science Foundation of China (41476003), NSFC-Shandong Joint Fund for Marine Science Research Centers (U1406401), and the China Meteorological Public Welfare Scientific Research Project (GYHY201306027).
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