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Atmosphere
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ENSO Prediction
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ENSO Prediction

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (6 August 2021) | Viewed by 14862

Special Issue Editors

Prof. Dr. Youmin Tang

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Guest Editor
Environmental Science, University of Northern British Columbia, Prince George, BC V2N 4Z9 Canada
Interests: seasonal climate; ENSO; tropical climate
Dr. Xiaoxiao Tan

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Guest Editor
College of Oceanography, Hohai University, Nanjing 210098, China
Interests: seasonal climate; ENSO
Dr. Satyaban Bishoyi Ratna

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Guest Editor
Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK
Interests: climate variability and teleconnection; climate change; Asian summer monsoon; extreme weather events; regional climate modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The El Niño–Southern Oscillation (ENSO) is the strongest interannual climate variability phenomenon across the globe, with worldwide climate and weather impacts. Understanding and improving predictions of ENSO are, thus, of vital importance. Over the past decades, there has been significant progress in the prediction of ENSO. However, serious challenges still exist in understanding ENSO and improving its prediction, highlighted particularly by the false predictions of 2014–2016 El Niño events. Further studies on ENSO are clearly needed.

This Special Issue invites contributions that focus on ENSO and ENSO-related studies. Contributions are solicited on topics including studies of the theory, modeling, and prediction of ENSO as well the impact of ENSO on climate and weather anomalies on global or local scales. Especially welcome are contributions on operational or experimental prediction systems of ENSO, including model development, initialization scheme, and ensemble construction in addition to the evaluation of ENSO predictability in the framework of deterministic, probabilistic, and intrinsic measures. Results from diagnostic, modeling, model intercomparison, and theoretical approaches are all welcome. 

Prof. Dr. Youmin Tang
Dr. Xiaoxiao Tan
Dr. Satyaban Bishoyi Ratna
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ENSO
  • seasonal climate prediction
  • tropical climate variability
  • ENSO—induced climate anomalies

Published Papers (6 papers)

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Research

25 pages, 8142 KiB  
Article
Atlantic Niño/Niña Prediction Skills in NMME Models
by Ran Wang, Lin Chen, Tim Li and Jing-Jia Luo
Atmosphere 2021, 12(7), 803; https://doi.org/10.3390/atmos12070803 - 22 Jun 2021
Cited by 4 | Viewed by 3588
Abstract
The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By diagnosing the recently released North American Multimodel [...] Read more.
The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By diagnosing the recently released North American Multimodel Ensemble (NMME) models, we find that the Atlantic Niño/Niña prediction skills are improved, with the multi-model ensemble (MME) reaching five months. The prediction skills are season-dependent. Specifically, they show a marked dip in boreal spring, suggesting that the Atlantic Niño/Niña prediction suffers a “spring predictability barrier” like ENSO. The prediction skill is higher for Atlantic Niña than for Atlantic Niño, and better in the developing phase than in the decaying phase. The amplitude bias of the Atlantic Niño/Niña is primarily attributed to the amplitude bias in the annual cycle of the equatorial sea surface temperature (SST). The anomaly correlation coefficient scores of the Atlantic Niño/Niña, to a large extent, depend on the prediction skill of the Niño3.4 index in the preceding boreal winter, implying that the precedent ENSO may greatly affect the development of Atlantic Niño/Niña in the following boreal summer. Full article
(This article belongs to the Special Issue ENSO Prediction)
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16 pages, 10296 KiB  
Article
Time-Spatial Features of Mix El Niño
by Zhiyuan Zhang and Gen Li
Atmosphere 2021, 12(4), 476; https://doi.org/10.3390/atmos12040476 - 09 Apr 2021
Viewed by 1911
Abstract
The diversity of El Niño is a critical field of the climate research. The eastern Pacific (EP) and central Pacific (CP) types of El Niño have been identified in the previous studies. However, the extreme El Niño event that occurred in 2015–2016 is [...] Read more.
The diversity of El Niño is a critical field of the climate research. The eastern Pacific (EP) and central Pacific (CP) types of El Niño have been identified in the previous studies. However, the extreme El Niño event that occurred in 2015–2016 is quite different from both the EP and CP El Niño events. The sea surface temperatures anomalies (SSTA) for this event widely spread in both the central and eastern Pacific and have a small zonal gradient in the central-eastern Pacific. Many researchers regarded this event as a mixed type of El Niño. Using the regression-EOF method, the Mix El Niño pattern is extracted from the tropical Pacific SSTA field during the period from 1900 to 2019. Here, we reveal that the Mix El Niño is a very usual rather than a new type of El Niño, it is just that the EP and CP El Niño events are more frequent since the 1980s, while the Mix El Niño events frequently appear before the 1980s. The time-spatial features of the Mix El Niño are further investigated. The results demonstrate a unique westward propagation of the maximum SSTA for the Mix El Niño from the far eastern Pacific to the central Pacific. In contrast, the SSTA center is locked in the far eastern Pacific region for the EP El Niño and the central Pacific region for the CP El Niño. The evolutions of subsurface ocean temperature anomalies and sea surface height anomalies are also examined to support this. The ocean–atmosphere interaction plays an important role in the evolution of the Mix El Niño. The anomalous atmospheric Walker circulation for the Mix El Niño is mainly in the western and central Pacific as well as very weak in the eastern Pacific. In contrast, there are significant westerlies/easterlies in the eastern Pacific for the EP/CP El Niño. The small gradient of SSTA in the central-eastern Pacific for the Mix El Niño leads to weak zonal wind anomalies, which further weaken the zonal gradient of SSTA. All this suggests that the Mix El Niño is not unusual and fundamentally different from the EP and CP El Niño with important implications for global climate effects. Full article
(This article belongs to the Special Issue ENSO Prediction)
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14 pages, 2190 KiB  
Article
Contrasting Impacts of Three Extreme El Niños on Double ITCZs over the Eastern Pacific Ocean
by Yinlan Chen, Li Yan, Gen Li, Jianjun Xu, Jingchao Long and Shaojun Zheng
Atmosphere 2021, 12(4), 424; https://doi.org/10.3390/atmos12040424 - 26 Mar 2021
Cited by 2 | Viewed by 1937
Abstract
In the recent four decades, there were three record-breaking El Niño events: 1982/1983, 1997/1998, and 2015/2016 events. A double intertropical convergence zone (ITCZ) pattern distinctively emerges over the eastern Pacific Ocean during boreal spring. Based on reanalysis (ERA-Interim) during 1979–2018, this study examines [...] Read more.
In the recent four decades, there were three record-breaking El Niño events: 1982/1983, 1997/1998, and 2015/2016 events. A double intertropical convergence zone (ITCZ) pattern distinctively emerges over the eastern Pacific Ocean during boreal spring. Based on reanalysis (ERA-Interim) during 1979–2018, this study examines how these three extreme El Niños modulate such double ITCZs. The 1982/1983 and 1997/1998 El Niños moved both northern and southern ITCZs equatorward to form an individual and broad equatorial ITCZ. In contrast, the regulation of 2015/2016 El Niño was unique with a strengthened southern ITCZ to form a symmetric double-ITCZ. The above differences can be attributed to the different meridional structures of sea surface temperatures (SSTs). For the 1982/1983 and 1997/1998 El Niños, there was a meridionally symmetric structure of SST warming with a maximum at the equator. While for 2015/2016 El Niño, there was a meridionally symmetric structure of SST warming with a minimum at the equator. Full article
(This article belongs to the Special Issue ENSO Prediction)
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15 pages, 1823 KiB  
Article
Analyzing and Visualizing Spatiotemporal Patterns of El Niño Teleconnections Using Attribute Trajectories
by Long Zhang, Bert Van Schaeybroeck, Steven Caluwaerts, Piet Termonia and Nico Van de Weghe
Atmosphere 2021, 12(4), 414; https://doi.org/10.3390/atmos12040414 - 24 Mar 2021
Viewed by 1646
Abstract
El Niño influences the global climate through teleconnections that are not constant in space and time. In order to study and visualize the spatiotemporal patterns of the El Niño teleconnections, a new method inspired by the concept of attribute trajectories is proposed. The [...] Read more.
El Niño influences the global climate through teleconnections that are not constant in space and time. In order to study and visualize the spatiotemporal patterns of the El Niño teleconnections, a new method inspired by the concept of attribute trajectories is proposed. The coordinates of the trajectories are the normalized anomalies of the relevant meteorological variables in El Niño. The data structures called flocks are extracted from the trajectories to indicate the regions that are subject to the same type of El Niño teleconnection for a certain period. It is then shown how these structures can be used to get a detailed, spatiotemporal picture of the dynamics of the El Niño teleconnections. The comparison between the flocks of the same temporal scale reveals the general dynamics of the teleconnection, while the analysis among the flocks of different temporal scales indicates the relationship between the coverage and their duration. As an illustration of this method, the spatiotemporal patterns of the anomalous temperature increase caused by El Niño are presented and discussed at the monthly and seasonal scales. This study demonstrates the capability of the proposed method in analyzing and visualizing the spatiotemporal patterns of the teleconnections. Full article
(This article belongs to the Special Issue ENSO Prediction)
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14 pages, 6524 KiB  
Article
Asymmetric Effect of El Niño—Southern Oscillation on the Spring Precipitation over South China
by Bei Xu, Gen Li, Chujie Gao, Hong Yan, Ziqian Wang, Yang Li and Siguang Zhu
Atmosphere 2021, 12(3), 391; https://doi.org/10.3390/atmos12030391 - 17 Mar 2021
Cited by 15 | Viewed by 2390
Abstract
South China is one of the most densely populated and agriculture-based regions in China. Local spring precipitation is crucial to the people’s livelihood and social economic development. Using the observed and reanalysis datasets for the period 1958–2019, this study revealed an asymmetric effect [...] Read more.
South China is one of the most densely populated and agriculture-based regions in China. Local spring precipitation is crucial to the people’s livelihood and social economic development. Using the observed and reanalysis datasets for the period 1958–2019, this study revealed an asymmetric effect of El Niño—Southern Oscillation (ENSO) on the following spring precipitation over South China. During the years with positive ENSO phases, a strong positive correlation between spring precipitation and the preceding winter ENSO sea surface temperature (SST) anomalies existed over Guangdong province. For the years with negative ENSO phases, such a strong positive correlation shifts westwards to Guangxi province. To be specific, the El Niño events usually result in a precipitation surplus in the decaying spring over Guangdong province, while the La Niña events usually lead to a precipitation deficit in the decaying spring over Guangxi province. This is attributed to the nonlinear effects of ENSO on the atmospheric circulation. Compared with El Niño, the abnormal center of La Niña evidently extends westwards, inducing a westward movement of the anomalous low-level atmospheric circulation, which eventually results in a westward-shifted effect on the following spring precipitation over South China. Our findings emphasize the nonlinear responses of spring precipitation over South China to ENSO. This has important implications for the seasonal climate predictions over South China. Full article
(This article belongs to the Special Issue ENSO Prediction)
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15 pages, 6650 KiB  
Article
Evaluation of ENSO Prediction Skill Changes since 2000 Based on Multimodel Hindcasts
by Shouwen Zhang, Hui Wang, Hua Jiang and Wentao Ma
Atmosphere 2021, 12(3), 365; https://doi.org/10.3390/atmos12030365 - 10 Mar 2021
Cited by 6 | Viewed by 2004
Abstract
In this study, forecast skill over four different periods of global climate change (1982–1999, 1984–1996, 2000–2018, and 2000–2014) is examined using the hindcasts of five models in the North American Multimodel Ensemble. The deterministic evaluation shows that the forecasting skills of the Niño3.4 [...] Read more.
In this study, forecast skill over four different periods of global climate change (1982–1999, 1984–1996, 2000–2018, and 2000–2014) is examined using the hindcasts of five models in the North American Multimodel Ensemble. The deterministic evaluation shows that the forecasting skills of the Niño3.4 and Niño3 indexes are much lower during 2000–2018 than during 1982–1999, indicating that the previously reported decline in forecasting skill continues through 2018. The decreases in skill are most significant for the target months from May to August, especially for medium to long lead times, showing that the forecasts suffer more from the effect of the spring predictability barrier (SPB) post-2000. Relationships between the extratropical Pacific signal and the El Niño-Southern Oscillation (ENSO) weakened after 2000, contributing to a reduction in inherent predictability and skills of ENSO, which may be connected with the forecasting skills decline for medium to long lead times. It is a great challenge to predict ENSO using the memory of the local ocean itself because of the weakening intensity of the warm water volume (WWV) and its relationship with ENSO. These changes lead to a significant decrease in the autocorrelation coefficient of the persistence forecast for short to medium lead months. Moreover, for both the Niño3.4 and Niño3 indexes, after 2000, the models tend to further underestimate the sea surface temperature anomalies (SSTAs) in the El Niño developing year but overestimate them in the decaying year. For the probabilistic forecast, the skills post-2000 are also generally lower than pre-2000 in the tropical Pacific, and in particular, they decayed east of 120° W after 2000. Thus, the advantages of different methods, such as dynamic modeling, statistical methods, and machine learning methods, should be integrated to obtain the best applicability to ENSO forecasts and to deal with the current low forecasting skill phenomenon. Full article
(This article belongs to the Special Issue ENSO Prediction)
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