Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization

Wang, Guojian; Cai, Wenju; Gan, Bolan; Wu, Lixin; Santoso, Agus; Lin, Xiaopei; Chen, Zhaohui; McPhaden, Michael J.

doi:10.1038/nclimate3351

Cited by 197 publications

(155 citation statements)

References 26 publications

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“…Schleussner et al (Schleussner, Rogelj, et al, 2016) revealed that the rate of sea level rise in 2100 would be reduced by about 30% under 1.5°C of warming compared with 2°C of warming. Wang et al (2017) indicated that the RCP2.6 scenario is the only pathway, which is in line with the target of 1.5°C of warming. Wang et al (2017) indicated that the RCP2.6 scenario is the only pathway, which is in line with the target of 1.5°C of warming.…”

Section: Introductionsupporting

confidence: 59%

Application of the Bias Correction and Spatial Downscaling Algorithm on the Temperature Extremes From CMIP5 Multimodel Ensembles in China

Wang

2019

Earth and Space Science

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The Bias Correction and Spatial Downscaling (BCSD) is a trend-preserving statistical downscaling algorithm, which has been widely used to generate accurate and high-resolution data set. We employ the BCSD technique to statistically downscale projected daily maximum temperature (DMT) over China from 13 general circulation models in Coupled Model Intercomparison Project Phase 5 (CMIP5) project to supplement the National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections data set under the Representative Concentration Pathway 2.6 (RCP2.6) scenario. We then compare the differences of DMT and four DMT-related indices (i.e., summer days (SU), annual maximum value of DMT (TXx), intensity, and frequency of heat wave) between before and after downscaling over eight subregions of China. The results indicate that the BCSD method reduces the cool bias of the DMT over the whole China compared with original CMIP5 simulations, especially over the Qinghai-Tibet plateau. The SU increases after downscaling for both China as a whole and most subregions except for South China. The BCSD also affects the mean value of TXx, intensity, and frequency of heat wave at subregional scales, although it shows little impact on China as a whole. Besides, the BCSD reduces the temporal variability of most indices except for the heat wave frequency. The most striking finding is that the intermodel spreads of DMT, SU, TXx, and heat wave intensity are dramatically reduced after downscaling compared with raw CMIP5 simulations. In summary, the BCSD method shows significant improvements to original CMIP5 climate projections under RCP2.6 scenario.

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Section: Introductionsupporting

confidence: 59%

Application of the Bias Correction and Spatial Downscaling Algorithm on the Temperature Extremes From CMIP5 Multimodel Ensembles in China

Wang

2019

Earth and Space Science

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“…This and the potential for increased occurrences of events similar to the 1997/1+98 El Niño highlight the need to reduce emissions (e.g., via the Paris Agreement). However, even if global warming is halted, the risk associated with increased frequency of extreme El Niño events may still continue for several decades (Power et al, ; Wang et al, ). Despite these projections, it is not yet clear to what extent they are affected by climate model biases.…”

Section: Summary and Discussionmentioning

confidence: 99%

The Defining Characteristics of ENSO Extremes and the Strong 2015/2016 El Niño

Santoso

McPhaden

Cai

2017

Reviews of Geophysics

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424

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The year 2015 was special for climate scientists, particularly for the El Niño Southern Oscillation (ENSO) research community, as a major El Niño finally materialized after a long pause since the 1997/1998 extreme El Niño. It was scientifically exciting since, due to the short observational record, our knowledge of an extreme El Niño has been based only on the 1982/1983 and 1997/1998 events. The 2015/2016 El Niño was marked by many environmental disasters that are consistent with what is expected for an extreme El Niño. Considering the dramatic impacts of extreme El Niño, and the risk of a potential increase in frequency of ENSO extremes under greenhouse warming, it is timely to evaluate how the recent event fits into our understanding of ENSO extremes. Here we provide a review of ENSO, its nature and dynamics, and through analysis of various observed key variables, we outline the processes that characterize its extremes. The 2015/2016 El Niño brings a useful perspective into the state of understanding of these events and highlights areas for future research. While the 2015/2016 El Niño is characteristically distinct from the 1982/1983 and 1997/1998 events, it still can be considered as the first extreme El Niño of the 21st century. Its extremity can be attributed in part to unusually warm condition in 2014 and to long‐term background warming. In effect, this study provides a list of physically meaningful indices that are straightforward to compute for identifying and tracking extreme ENSO events in observations and climate models.

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“…Recently, studies with precipitation‐based ENSO indices have suggested that the frequency of extreme El Niño and La Niña events will increase after the mid‐21st century under the RCP8.5 scenario (Cai et al, ; Cai, Wang, et al, ), possibly causing more severe weather and climate variations under a very high CO 2 concentrations above 650 ppm. Furthermore, it has been suggested that extreme El Niño frequency increases linearly with the global mean temperature before 2050 toward a doubling at 1.5°C warming under the RCP2.6 scenario and that an increasing frequency of extreme El Niño events continues for up to a century after global mean temperature has stabilized (Wang et al, ). The dominant mode of global precipitation‐evaporation variability on interannual timescales is mainly due to ENSO teleconnections on interannual timescales.…”

Section: Enso Teleconnections Under Global Warmingmentioning

confidence: 99%

ENSO Atmospheric Teleconnections and Their Response to Greenhouse Gas Forcing

Yeh

Cai

Min

et al. 2018

Reviews of Geophysics

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412

295

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El Niño and Southern Oscillation (ENSO) is the most prominent year‐to‐year climate fluctuation on Earth, alternating between anomalously warm (El Niño) and cold (La Niña) sea surface temperature (SST) conditions in the tropical Pacific. ENSO exerts its impacts on remote regions of the globe through atmospheric teleconnections, affecting extreme weather events worldwide. However, these teleconnections are inherently nonlinear and sensitive to ENSO SST anomaly patterns and amplitudes. In addition, teleconnections are modulated by variability in the oceanic and atmopsheric mean state outside the tropics and by land and sea ice extent. The character of ENSO as well as the ocean mean state have changed since the 1990s, which might be due to either natural variability or anthropogenic forcing, or their combined influences. This has resulted in changes in ENSO atmospheric teleconnections in terms of precipitation and temperature in various parts of the globe. In addition, changes in ENSO teleconnection patterns have affected their predictability and the statistics of extreme events. However, the short observational record does not allow us to clearly distinguish which changes are robust and which are not. Climate models suggest that ENSO teleconnections will change because the mean atmospheric circulation will change due to anthropogenic forcing in the 21st century, which is independent of whether ENSO properties change or not. However, future ENSO teleconnection changes do not currently show strong intermodel agreement from region to region, highlighting the importance of identifying factors that affect uncertainty in future model projections.

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Continued increase of extreme El Niño frequency long after 1.5 °C warming stabilization

Cited by 197 publications

References 26 publications

Application of the Bias Correction and Spatial Downscaling Algorithm on the Temperature Extremes From CMIP5 Multimodel Ensembles in China

Application of the Bias Correction and Spatial Downscaling Algorithm on the Temperature Extremes From CMIP5 Multimodel Ensembles in China

The Defining Characteristics of ENSO Extremes and the Strong 2015/2016 El Niño

ENSO Atmospheric Teleconnections and Their Response to Greenhouse Gas Forcing

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