Dynamics for El Niño-La Niña asymmetry constrain equatorial-Pacific warming pattern

Hayashi, Minoru; Jin, Fei‐Fei; Stuecker, Malte F.

doi:10.1038/s41467-020-17983-y

Cited by 62 publications

(72 citation statements)

References 75 publications

(169 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1b) and with the most nonlinear ENSO behavior ( Fig. 1c), in agreement with recent studies (Cai et al 2020;Hayashi et al 2020). All other models reside in the "Weak" sub-ensemble.…”

Section: Realistic Enso Dynamic Modelssupporting

confidence: 91%

“…Therefore, models with realistic ENSO feedbacks and thus possibly realistic ENSO dynamics have been identified and grouped into the "Strong" sub-ensemble. The "Strong" sub-ensemble contains the models that are able to simulate the non-linearity of ENSO most realistically (Cai et al 2020;Hayashi et al 2020). We also have investigated the unforced decadal variability of the ENSO amplitude.…”

Section: Summary and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

et al. 2021

View full text Add to dashboard Cite

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

show abstract

“…1b) and with the most nonlinear ENSO behavior ( Fig. 1c), in agreement with recent studies (Cai et al 2020;Hayashi et al 2020). All other models reside in the "Weak" sub-ensemble.…”

Section: Realistic Enso Dynamic Modelssupporting

confidence: 91%

Section: Summary and Discussionmentioning

confidence: 99%

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The 1995-2014 monthly global 0.25 • × 0.25 • gridded atmospheric temperature and wind from the fifth generation of ECMWF (the European Centre for Medium-Range Weather Forecasts) atmospheric reanalyses (ERA5, Hersbach and Dee, 2016) and the climatological data of global zonal mean temperature and wind above the 1 hPa level to 0.1 hPa at 5 • latitude interval from the COSPAR (Committee on Space Research) International Reference Atmosphere (CIRA86) are used to evaluate the vertical structure of atmospheric temperature and wind. The 1995-2014 monthly global gridded wind data from ERA5 are also used to evaluate the quasi-biennial oscillation (QBO) of the equatorial zonal wind between easterlies and westerlies in the tropical stratosphere.…”

Section: Data Used For Evaluationsmentioning

confidence: 99%

BCC-CSM2-HR: a high-resolution version of the Beijing Climate Center Climate System Model

et al. 2021

Geosci. Model Dev.

View full text Add to dashboard Cite

Abstract. BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model (T266 in the atmosphere and 1/4∘ latitude × 1/4∘ longitude in the ocean). Its development is on the basis of the medium-resolution version BCC-CSM2-MR (T106 in the atmosphere and 1∘ latitude × 1∘ longitude in the ocean) which is the baseline for BCC participation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamical core and physical processes. BCC-CSM2-HR is evaluated for historical climate simulations from 1950 to 2014, performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. Observed global warming trends of surface air temperature from 1950 to 2014 are well captured by both BCC-CSM2-MR and BCC-CSM2-HR. Present-day basic atmospheric mean states during the period from 1995 to 2014 are then evaluated at global scale, followed by an assessment on climate variabilities in the tropics including the tropical cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden–Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR represents the global energy balance well and can realistically reproduce the main patterns of atmospheric temperature and wind, precipitation, land surface air temperature, and sea surface temperature (SST). It also improves the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of the double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, almost disappears in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, and the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observations than their counterparts in BCC-CSM2-MR. Some imperfections are, however, noted in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold SST biases and the insufficient number of tropical cyclones in the North Atlantic.

show abstract

“…The simulated change in warm SST occurrences from the 20C to the present is compared with the observed change (Figures 3d and 3e). We recognize an overestimated eastern equatorial Pacific SST change ( Figure S5), which may result from a large uncertainty in the rate of warming in the eastern Pacific among climate models (Collins & The CMIP Modelling Groups, 2005;Hayashi et al, 2020;Seager et al, 2019) and from observed multidecadal natural variability (Watanabe et al, 2014), such as the Pacific Decadal Oscillation (PDO, Mantua et al, 1997). As the observed PDO phase is generally negative in 2001-2020 according to the NOAA website (https://psl.noaa.gov/pdo/), the observed western Pacific warm pool edge is also anomalously shifted to the north, potentially overestimating the long-term change in the NWPac SST in the observations ( Figure S5).…”

Section: Global Aspects Of the Northwestern Pacific Warm Pool Changesmentioning

confidence: 97%

The Northwestern Pacific Warming Record in August 2020 Occurred Under Anthropogenic Forcing

Hayashi

Shiogama

Emori

et al. 2021

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

show abstract

Dynamics for El Niño-La Niña asymmetry constrain equatorial-Pacific warming pattern

Cited by 62 publications

References 75 publications

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

BCC-CSM2-HR: a high-resolution version of the Beijing Climate Center Climate System Model

The Northwestern Pacific Warming Record in August 2020 Occurred Under Anthropogenic Forcing

Contact Info

Product

Resources

About