Impacts of low-frequency internal climate variability and greenhouse warming on the El Niño-Southern Oscillation

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  • 1 Centre for Southern Hemisphere Oceans Research (CSHOR), CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia.
  • 2 CSIRO Climate Science Centre, Aspendale, Victoria, Australia.
  • 3 Key Laboratory of Physical Oceanography, Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
  • 4 Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba, Queensland, Australia.
  • 5 Bureau of Meteorology, Melbourne, Victoria, Australia
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Abstract

The El Niño-Southern Oscillation (ENSO) is the dominant mode of interannual climate fluctuations with wide-ranging socio-economic and environmental impacts. Understanding the eastern Pacific (EP) and central Pacific (CP) El Niño response to a warmer climate is paramount, yet the role of internal climate variability in modulating their response is not clear. Using large ensembles, we find that internal variability generates a spread in the standard deviation and skewness of these two El Niño types that is similar to the spread of 17 Coupled Model Intercomparison Project phase 5 (CMIP5) models that realistically simulate ENSO diversity. Based on 40 Community Earth System Model Large Ensemble (CESM-LE) and 99 Max Planck Institute for Meteorology Grand Ensemble (MPI-GE) members, unforced variability can explain more than 90% of the historical EP and CP El Niño standard deviation and all of the ENSO skewness spread in the 17 CMIP5 models. Both CESM-LE and the selected CMIP5 models show increased EP and CP El Niño variability in a warmer climate, driven by a stronger mean vertical temperature gradient in the upper ocean and faster surface warming of the eastern equatorial Pacific. However, MPI-GE shows no agreement in EP or CP standard deviation change. This is due to weaker sensitivity to the warming signal, such that when the eastern equatorial Pacific surface warming is faster, the change in upper ocean vertical temperature gradient tends to be weaker. This highlights that individual models produce a different ENSO response in a warmer climate, and that considerable uncertainty within the CMIP5 ensemble may be caused by internal climate variability.

Corresponding author: Benjamin Ng (Benjamin.Ng@csiro.au)

Abstract

The El Niño-Southern Oscillation (ENSO) is the dominant mode of interannual climate fluctuations with wide-ranging socio-economic and environmental impacts. Understanding the eastern Pacific (EP) and central Pacific (CP) El Niño response to a warmer climate is paramount, yet the role of internal climate variability in modulating their response is not clear. Using large ensembles, we find that internal variability generates a spread in the standard deviation and skewness of these two El Niño types that is similar to the spread of 17 Coupled Model Intercomparison Project phase 5 (CMIP5) models that realistically simulate ENSO diversity. Based on 40 Community Earth System Model Large Ensemble (CESM-LE) and 99 Max Planck Institute for Meteorology Grand Ensemble (MPI-GE) members, unforced variability can explain more than 90% of the historical EP and CP El Niño standard deviation and all of the ENSO skewness spread in the 17 CMIP5 models. Both CESM-LE and the selected CMIP5 models show increased EP and CP El Niño variability in a warmer climate, driven by a stronger mean vertical temperature gradient in the upper ocean and faster surface warming of the eastern equatorial Pacific. However, MPI-GE shows no agreement in EP or CP standard deviation change. This is due to weaker sensitivity to the warming signal, such that when the eastern equatorial Pacific surface warming is faster, the change in upper ocean vertical temperature gradient tends to be weaker. This highlights that individual models produce a different ENSO response in a warmer climate, and that considerable uncertainty within the CMIP5 ensemble may be caused by internal climate variability.

Corresponding author: Benjamin Ng (Benjamin.Ng@csiro.au)
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