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ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models
ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models
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ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models
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ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models
ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models

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ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models
ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models
Journal Article

ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models

2021
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Overview
This study examines historical simulations of ENSO in the E3SM-1-0, CESM2, and GFDL-CM4 climate models, provided by three leading U.S. modeling centers as part of the Coupled Model Intercomparison Project phase 6 (CMIP6). These new models have made substantial progress in simulating ENSO's key features, including amplitude, time scale, spatial patterns, phase-locking, the spring persistence barrier, and recharge oscillator dynamics. However, some important features of ENSO are still a challenge to simulate. In the central and eastern equatorial Pacific, the models' weaker-than-observed subsurface zonal current anomalies and zonal temperature gradient anomalies serve to weaken the nonlinear zonal advection of subsurface temperatures, leading to insufficient warm/cold asymmetry of ENSO's sea surface temperature anomalies (SSTA). In the western equatorial Pacific, the models' excessive simulated zonal SST gradients amplify their zonal temperature advection, causing their SSTAto extend farther west than observed. The models underestimate both ENSO's positive dynamic feedbacks (due to insufficient zonal wind stress responses to SSTA) and its thermodynamic damping (due to insufficient convective cloud shading of eastern Pacific SSTA during warm events); compensation between these biases leads to realistic linear growth rates for ENSO, but for somewhat unrealistic reasons. The models also exhibit stronger-than-observed feedbacks onto eastern equatorial Pacific SSTAs from thermocline depth anomalies, which accelerates the transitions between events and shortens the simulated ENSO period relative to observations. Implications for diagnosing and simulating ENSO in climate models are discussed.

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