Increasing ENSO–rainfall variability due to changes in future tropical temperature–rainfall relationship

Yun, Kyung-Sook; Lee, June‐Yi; Timmermann, Axel; Stein, Karl; Stuecker, Malte F.; Fyfe, John C.; Chung, Eui‐Seok

doi:10.1038/s43247-021-00108-8

Cited by 85 publications

(72 citation statements)

References 42 publications

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“…3b), for which there is a monotonic increase in variance, following a similar shift in the period of the peak that was found for SST. For precipitation, the amplitude of the seasonal cycle increases over 1960-2100, consistent with the notion of precipitation variability enhancement over the tropics due to thermodynamic and dynamic processes (40).…”

Section: Forced Changes In Amplitude and Frequencysupporting

confidence: 82%

Ubiquity of human-induced changes in climate variability

Rodgers¹,

Lee²,

Rosenbloom³

et al. 2022

Preprint

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While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming will in particular alter variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, and for seasonal predictions.

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Section: Forced Changes In Amplitude and Frequencysupporting

confidence: 82%

Ubiquity of human-induced changes in climate variability

Rodgers¹,

Lee²,

Rosenbloom³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…3b), for which there is a monotonic increase in variance, following a similar 235 shift in the period of the peak that was found for SST. For precipitation, the amplitude of the seasonal cycle increases over 1960-2100, consistent with the notion of variability enhancement over the tropics due to thermodynamic and dynamic processes (Yun et al, 2021).…”

supporting

confidence: 82%

Ubiquity of human-induced changes in climate variability

Rodgers

Lee

Rosenbloom

et al. 2021

Preprint

Self Cite

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Abstract. While climate change mitigation targets necessarily concern maximum mean state change, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño-Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability, distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming will in particular alter variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and for assessing potential stressors for terrestrial and marine ecosystems.

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“…Instead, models that more realistically simulate characteristics of extreme ENSO events tend to project systematic changes 17 . These changes include an increased frequency of El Niño events with extreme rainfall in the eastern equatorial Pacific [25][26][27][28] , more frequent extreme equatorward swings of large-scale convergence zones 29,30 , a higher frequency of El Niño events featuring eastward propagating SST anomalies 31 and a higher frequency of extreme La Niña events 32 . Such projected changes are consistent with proxy records of ENSO variability, which suggest that twentieth century ENSO activity is stronger than observed during previous centuries [33][34][35] .…”

mentioning

confidence: 99%

Changing El Niño–Southern Oscillation in a warming climate

Cai

Santoso

Collins

et al. 2021

Nat Rev Earth Environ

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207

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Originating in the equatorial Pacific, the El Niño-Southern Oscillation (ENSO) has highly consequential global impacts, motivating the need to understand its responses to anthropogenic warming. In this Review, we synthesize advances in observed and projected changes of multiple aspects of ENSO, including the processes behind such changes. As in previous syntheses, there is an inter-model consensus of an increase in future ENSO rainfall variability. Now, however, it is apparent that models that best capture key ENSO dynamics also tend to project an increase in future ENSO sea surface temperature variability and, thereby, ENSO magnitude under greenhouse warming, as well as an eastward shift and intensification of ENSO-related atmospheric teleconnections -the Pacific-North American and Pacific-South American patterns. Such projected changes are consistent with palaeoclimate evidence of stronger ENSO variability since the 1950s compared with past centuries. The increase in ENSO variability, though underpinned by increased equatorial Pacific upper-ocean stratification, is strongly influenced by internal variability, raising issues about its quantifiability and detectability. Yet, ongoing coordinated community efforts and computational advances are enabling long-simulation, large-ensemble experiments and high-resolution modelling, offering encouraging prospects for alleviating model biases, incorporating fundamental dynamical processes and reducing uncertainties in projections.

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Increasing ENSO–rainfall variability due to changes in future tropical temperature–rainfall relationship

Cited by 85 publications

References 42 publications

Ubiquity of human-induced changes in climate variability

Ubiquity of human-induced changes in climate variability

Ubiquity of human-induced changes in climate variability

Changing El Niño–Southern Oscillation in a warming climate

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