Abstract 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; timescale; spatial patterns; phase-locking; 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 SSTA to 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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Equatorial Pacific pCO 2 Interannual Variability in CMIP6 Models
The El Niño‐Southern Oscillation (ENSO) in the equatorial Pacific is the dominant mode of global air‐sea carbon dioxide (CO2) flux interannual variability (IAV). Air‐sea CO2fluxes are driven by the difference between atmospheric and surface ocean pCO2, with variability of the latter driving flux variability. Previous studies found that models in Coupled Model Intercomparison Project Phase 5 (CMIP5) failed to reproduce the observed ENSO‐related pattern of CO2fluxes and had weak pCO2IAV, which were explained by both weak upwelling IAV and weak mean vertical dissolved inorganic carbon (DIC) gradients. We assess whether the latest generation of CMIP6 models can reproduce equatorial Pacific pCO2IAV by validating models against observations‐based data products. We decompose pCO2IAV into thermally and non‐thermally driven anomalies to examine the balance between these competing anomalies, which explain the total pCO2IAV. The majority of CMIP6 models underestimate pCO2IAV, while they overestimate sea surface temperature IAV. Insufficient compensation of non‐thermal pCO2to thermal pCO2IAV in models results in weak total pCO2IAV. We compare the relative strengths of the vertical transport of temperature and DIC and evaluate their contributions to thermal and non‐thermal pCO2anomalies. Model‐to‐observations‐based product comparisons reveal that modeled mean vertical DIC gradients are biased weak relative to their mean vertical temperature gradients, but upwelling acting on these gradients is insufficient to explain the relative magnitudes of thermal and non‐thermal pCO2anomalies.
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- 10386413
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 127
- Issue:
- 12
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.
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Abstract The internal atmospheric variability (IAV) of the net surface heat flux (NHF) in the observed 20th/21st century atmosphere is estimated as the residual after removing the sea surface temperature (SST) and externally forced atmospheric response derived from the four atmospheric models of the Atmospheric Model Intercomparison Project (AMIP) simulations under phase 5 of the Coupled Model Intercomparison Project (CMIP5). The mean NHF of four atmospheric reanalysis datasets is an estimate of the observed NHF. Although the AMIP models are forced with the same SST and external forcing, the forced responses differ significantly among AMIP models, suggestive of uncertainty in the models. Besides, the uncertainty of IAV in the reanalyses could also arise from the uncertainty in reanalyses as observations contain errors and reanalysis includes interpolation by models. It is concluded that: (a) The SST/NHF and SST/forced NHF correlations are significantly negative over most of world ocean in the AMIP models, indicating damping of the SST anomalies by the NHF. (b) The IAV of the AMIP models is not correlated with SST, while the positive IAV/SST correlations in the reanalyses suggests the role of IAV in forcing the SST variability in the extra‐tropics. (c) The standard deviation (STD) of the IAV of AMIP models is indistinguishable from that of the mean reanalysis over a majority of world ocean, and the STD of the NHF of the AMIP models is larger than that of the mean reanalysis in the subtropics and midlatitudes. (d) The IAV in the mean reanalysis plays a role in forcing the SST variability in the extra‐tropics (e.g., Atlantic Multidecadal Variability), while it may not be an important forcing in the tropical oceans (e.g., ENSO).
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