A Review of Atmosphere–Ocean Forcings Outside the Tropical Pacific on the El Niño–Southern Oscillation Occurrence

Chen, Shangfeng; Yu, Bin; Chen, Wen; Wu, Renguang

doi:10.3390/atmos9110439

Cited by 21 publications

(11 citation statements)

References 127 publications

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“…On one hand, tropical processes, including the positive airsea interaction [1] and oceanic dynamics [2], play an important role for the ENSO occurrence. On the other hand, more and more recent studies have demonstrated that atmospheric and oceanic forcings outside the tropical Pacific also play crucial role in modulating onset, development, and amplitude of the ENSO events, such as the North Pacific Oscillation (NPO; an intrinsic atmospheric variability over the extratropical North Pacific) [3,4], Aleutian Low [5], Arctic Oscillation (AO; the dominant atmospheric variability over the extratropical Northern Hemisphere) [6,7,8], North Atlantic SST [9], East Asian monsoon variability, the atmospheric circulation anomalies in the Southern Hemisphere, and the SST variability over the Indian and Atlantic Oceans [10]. For instance, Vimont et al [3] and Chen et al [4] showed that, via seasonal footprinting mechanism, NPO can exert significant impacts on the outbreak of ENSO events.…”

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confidence: 99%

Forecasting El Niño and La Niña Using Spatially and Temporally Structured Predictors and a Convolutional Neural Network

Hashemi

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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El Niño-Southern Oscillation (ENSO) is characterized by large-scale fluctuations of sea surface temperature in the central and eastern tropical Pacific accompanied by changes in the atmospheric circulation. ENSO events are of two main types: El Niño and La Niña. Oceanic Niño index (ONI) determines the five consecutive 3-month running mean of sea surface temperature (SST) anomalies, in the Niño 3.4 region (5°S-5°N, 170°W-120°W). El Niño is a phenomenon in the equatorial Pacific Ocean characterized by a value of greater than 0.5°C for ONI. La Niña is a phenomenon in the equatorial Pacific Ocean characterized by a value of less than-0.5°C for ONI. The lingering of either of these two phenomena could induce severe droughts, while either of them following the other could cause massive floods. In both cases, deaths and substantial pecuniary loss is unavoidable, making their forecast of great significance. This study takes over the challenge of forecasting these two phenomena with one year lead time which has proven difficult in the literature. This research's contribution is restructuring ENSO events' predictors, including SST, sea level pressure, surface wind speed, and wind stress in a spatially and temporally meaningful way and designing a convolutional neural network (CNN) that takes advantage of this structure to forecast ENSO events of different types (i.e. Central Pacific and Eastern Pacific) in the next year. Not only a high precision in forecasts was achieved, but also it was shown that the proposed model has the potential to achieve higher recalls if a larger number of samples from the positive class would become available.

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confidence: 99%

Forecasting El Niño and La Niña Using Spatially and Temporally Structured Predictors and a Convolutional Neural Network

Hashemi

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…2a). This winter NPO-related tripole SST anomaly pattern bears (Chiang and Vimont 2004) and the spring Arctic Oscillation (Nakamura et al 2006(Nakamura et al , 2007Chen et al 2014Chen et al , 2018a. Significant negative SST anomalies can also be seen in the tropical southern Pacific around 5°-20°S and 120°-170°W.…”

Section: Npo-enso Relationship In Observation and Canesm2mentioning

confidence: 73%

“…In addition, more and more studies showed that the extratropical atmosphere-ocean forcing also plays important roles in modulating the occurrence and amplitude of ENSO events (e.g. Vimont et al 2001Vimont et al , 2003aNakamura et al 2006;Alexander et al 2010;Chen et al 2014Chen et al , 2017Chen et al , 2018aZhang et al 2018;Luo et al 2018).…”

Section: Introductionmentioning

confidence: 99%

The seasonal footprinting mechanism in large ensemble simulations of the second generation Canadian earth system model: uncertainty due to internal climate variability

Chen

2020

Clim Dyn

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Previous studies indicated that the wintertime North Pacific Oscillation (NPO) could exert marked impacts on the following winter El Niño-Southern Oscillation (ENSO) via the seasonal footprinting mechanism (SFM). Here, we examine this winter NPO-ENSO relationship in a 50-member ensemble of historical simulations conducted with the Canadian Centre for Climate Modeling and Analysis second generation Canadian Earth System Model (CanESM2) over the period of 1950–2005. The observed NPO pattern, featured by a meridional dipole atmospheric anomaly over the North Pacific, can be well reproduced by all of the 50 ensemble members. The multi-member ensemble (MME) mean can well simulate the observed NPO-ENSO relationship, as well as the SFM process. However, there exists a large spread of the results among the 50 members due to internal climate variability. Internal climate variability influences the winter NPO-ENSO relationship through modulating the subtropical center of the NPO. Specifically, the ensemble members with high NPO-ENSO correlations tend to have strong atmospheric anomalies over the subtropical North Pacific in winter. The atmospheric circulation anomaly brings strong sea surface temperature and precipitation anomalies in the tropical central Pacific and westerly wind anomalies over the tropical western Pacific in the following spring. These anomalies sustain in the following seasons and eventually lead to ENSO events in the following winter.

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“…Chen and Song [22] demonstrated that the winter AO and Siberian High (SH) intensity both contribute to the SAT anomalies corresponding to the first EOF mode primarily through the wind-generated horizontal temperature advection. Note that several studies indicated that the AO's impacts on the global climate systems (such as East Asian winter monsoon, El Niño-Southern Oscillation) are unstable [33][34][35][36]. For example, Li et al [33] found that impact of the winter AO on the East Asian winter monsoon underwent a significant interdecadal change around the early 1980s.…”

Section: Introductionmentioning

confidence: 99%

Recent Strengthened Impact of the Winter Arctic Oscillation on the Southeast Asian Surface Air Temperature Variation

Chen

Song

2019

Atmosphere

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A previous study indicated that the Arctic Oscillation (AO) and Siberian High (SH) are two important drivers for the interannual variation of winter surface air temperature (SAT) over southeast Asia. This study reveals that the impact of the winter SH on the southeast Asian SAT was stable. By contrast, the connection between the winter AO and southeast Asian SAT displays a pronounced interdecadal change around the late-1990s. Significant impact of the winter AO on the southeast Asian SAT can only be detected after the late-1990s. The result shows that change in the impact of the winter AO on southeast Asian SAT was mainly attributed to change in the spatial structure of the AO. Before the late-1990s, significant atmospheric signals related to the winter AO were confined to the North Atlantic region and the atmospheric anomalies over Eurasia were weak. As such, impact of the winter AO on the southeast Asian SAT was weak. By contrast, after the late-1990s, winter AO displays a more zonally symmetric structure, with significant negative sea level pressure (SLP) anomalies over the Arctic, and positive anomalies over mid-latitudes. Specifically, the positive SLP anomalies over East China induce clear northerly wind anomalies over southeast Asia, which lead to negative SAT anomalies there via wind-induced temperature advection. Hence, the winter AO has a significant impact on the southeast Asian SAT after the late-1990s. Further analysis shows that after the late-1990s, hindcast skill of the winter southeast Asian SAT anomalies was enhanced when taking both the winter AO and SH into account.

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A Review of Atmosphere–Ocean Forcings Outside the Tropical Pacific on the El Niño–Southern Oscillation Occurrence

Cited by 21 publications

References 127 publications

Forecasting El Niño and La Niña Using Spatially and Temporally Structured Predictors and a Convolutional Neural Network

Forecasting El Niño and La Niña Using Spatially and Temporally Structured Predictors and a Convolutional Neural Network

The seasonal footprinting mechanism in large ensemble simulations of the second generation Canadian earth system model: uncertainty due to internal climate variability

Recent Strengthened Impact of the Winter Arctic Oscillation on the Southeast Asian Surface Air Temperature Variation

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