scholarly journals The Relationship between Contiguous El Niño and La Niña Revealed by Self-Organizing Maps

2015 ◽  
Vol 28 (20) ◽  
pp. 8118-8134 ◽  
Author(s):  
Xin Li ◽  
Chongyin Li ◽  
Jian Ling ◽  
Yanke Tan

Abstract This study introduces a new methodology for identifying El Niño and La Niña events. Sea surface temperature (SST) anomaly patterns for El Niño and La Niña onset, peak, and end phases are classified by self-organizing maps (SOM) analysis. Both onset and end phases for El Niño and La Niña exhibit eastern Pacific (EP) and central Pacific (CP) types. The SST anomaly patterns in peak phase can be classified into EP, EP-like, and CP types for El Niño, and EP, mixed (MIX), and CP types for La Niña. The general type of each El Niño or La Niña event is then defined according to the SST type for each of the three phases. There is no robust connection between the general types of the contiguous El Niño and La Niña except that the MIX La Niña rarely induces a subsequent CP El Niño. However, there are strong relationships between the end-phase type of El Niño and the onset-phase type of the subsequent La Niña. The EP-end-type El Niño favors transition to the CP-onset-type La Niña, while the CP-end-type El Niño favors transition to the EP-onset-type La Niña. On the other hand, the CP-end-type La Niña favors transition to EP-onset-type El Niño. Furthermore, an El Niño that occurs after the decay of La Niña favors initiating as an EP-onset type. These relationships are driven by different atmosphere–ocean dynamics, such as coupled air–sea feedback, thermocline feedback, slow SST mode, and Bjerknes feedbacks.

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jialin Lin ◽  
Taotao Qian

Abstract The El Nino-Southern Oscillation (ENSO) is the dominant interannual variability of Earth’s climate system, and strongly modulates global temperature, precipitation, atmospheric circulation, tropical cyclones and other extreme events. However, forecasting ENSO is one of the most difficult problems in climate sciences affecting both interannual climate prediction and decadal prediction of near-term global climate change. The key question is what cause the switch between El Nino and La Nina. For the past 30 years, ENSO forecasts have been limited to short lead times after ENSO sea surface temperature (SST) anomaly has already developed, but unable to predict the switch between El Nino and La Nina. Here, we demonstrate that the switch between El Nino and La Nina is caused by a subsurface ocean wave propagating from western Pacific to central and eastern Pacific and then triggering development of SST anomaly. This is based on analysis of all ENSO events in the past 136 years using multiple long-term observational datasets. The wave’s slow phase speed and decoupling from atmosphere indicate that it is a forced wave. Further analysis of Earth’s angular momentum budget and NASA’s Apollo Landing Mirror Experiment suggests that the subsurface wave is likely driven by lunar tidal gravitational force.


2007 ◽  
Vol 20 (1) ◽  
pp. 38-52 ◽  
Author(s):  
Motoki Nagura ◽  
Masanori Konda

Abstract The seasonal development of the sea surface temperature (SST) anomaly in the Indian Ocean is investigated in relation to El Niño–Southern Oscillation (ENSO), using NOAA optimally interpolated SST and NCEP reanalysis data. The result shows that the onset season of El Niño affects the seasonal development of surface wind anomalies over the equatorial eastern Indian Ocean (EEIO); these surface wind anomalies, in turn, determine whether the SST anomaly in the EEIO evolves into the eastern pole of the dipole pattern. In years when the dipole pattern develops, surface zonal wind anomalies over the EEIO switch from westerly to easterly in spring as La Niña switches to El Niño. The seasonal zonal wind over the EEIO also switches from westerly to easterly in spring, and the anomalous wind strengthens seasonal wind from winter to summer. Stronger winds and resultant thermal forcings produce the negative SST anomaly in the EEIO in winter, and its amplitude increases in summer. The SST anomaly becomes the eastern pole of the dipole pattern in fall. In contrast, if the change from La Niña to El Niño is delayed until late summer/fall or if La Niña persists throughout the year, a westerly anomaly persists from winter to summer over the EEIO. The persistent westerly anomaly strengthens the wintertime climatological westerlies and weakens the summertime easterlies. Therefore, negative SST anomalies are produced in the EEIO in winter, but the amplitude decreases in summer, and the eastern pole is not present in fall. The above explanation also applies to onset years of La Niña if the signs of the anomalies are reversed.


2006 ◽  
Vol 19 (19) ◽  
pp. 4755-4771 ◽  
Author(s):  
Scott Power ◽  
Malcolm Haylock ◽  
Rob Colman ◽  
Xiangdong Wang

Abstract El Niño–Southern Oscillation (ENSO) in a century-long integration of a Bureau of Meteorology Research Centre (BMRC) coupled general circulation model (CGCM) drives rainfall and temperature changes over Australia that are generally consistent with documented observational changes: dry/hot conditions occur more frequently during El Niño years and wet/mild conditions occur more frequently during La Niña years. The relationship between ENSO [as measured by Niño-4 or the Southern Oscillation index (SOI), say] and all-Australia rainfall and temperature is found to be nonlinear in the observations and in the CGCM during June–December: a large La Niña sea surface temperature (SST) anomaly is closely linked to a large Australian response (i.e., Australia usually becomes much wetter), whereas the magnitude of an El Niño SST anomaly is a poorer guide to how dry Australia will actually become. Australia tends to dry out during El Niño events, but the degree of drying is not as tightly linked to the magnitude of the El Niño SST anomaly. Nonlinear or asymmetric teleconnections are also evident in the western United States/northern Mexico. The implications of asymmetric teleconnections for prediction services are discussed. The relationship between ENSO and Australian climate in both the model and the observations is strong in some decades, but weak in others. A series of decadal-long perturbation experiments are used to show that if these interdecadal changes are predictable, then the level of predictability is low. The model’s Interdecadal Pacific Oscillation (IPO), which represents interdecadal ENSO-like SST variability, is statistically linked to interdecadal changes in ENSO’s impact on Australia during June–December when ENSO’s impact on Australia is generally greatest. A simple stochastic model that incorporates the nonlinearity above is used to show that the IPO [or the closely related Pacific Decadal Oscillation (PDO)] can appear to modulate ENSO teleconnections even if the IPO–PDO largely reflect unpredictable random changes in, for example, the relative frequency of El Niño and La Niña events in a given interdecadal period. Note, however, that predictability in ENSO-related variability on decadal time scales might be either underestimated by the CGCM, or be too small to be detected by the modest number of perturbation experiments conducted. If there is a small amount of predictability in ENSO indices on decadal time scales, and there may be, then the nonlinearity described above provides a mechanism via which ENSO teleconnections could be modulated on decadal time scales in a partially predictable fashion.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Megha Maheshwari ◽  
Rajkumar Kamaljit Singh ◽  
Sandip Rashmikant Oza ◽  
Raj Kumar

An attempt is made to understand the long-term variability of SST using NOAA optimum interpolation SST data for the period (1982–2011) in the Southern Ocean. This dataset has been used (i) to study the interannual variability in SST anomaly and (ii) to carry out regression analysis to compute linear trend in the annual averaged Southern Ocean SST. It is observed that summer season exhibits more variability than winter. Moreover, El Nino/La Nina events apparently play a critical role in the variability of Southern Ocean SST. Thus, higher SST anomalies were observed in El Nino years (e.g., 1983), while cooler anomalies were seen during La Nina years (e.g., 1985). In addition, the eastern and western sides of Antarctica experience episodes of warm and cold SST. Western parts of the Southern Ocean experienced higher anomalies during 1992, 1993, and 1994, while the eastern part experienced positive anomalies in 1997, 1998, 2002, and 2003. The paper also highlights the different regions of the Southern Ocean showing statistically significant positive/negative trends in the variability of interannual average SST. However, in general, the Southern Ocean as a whole is showing a weak interannual cooling trend in SST.


2016 ◽  
Vol 29 (6) ◽  
pp. 2201-2220 ◽  
Author(s):  
Mingcheng Chen ◽  
Tim Li ◽  
Xinyong Shen ◽  
Bo Wu

Abstract Observed SST anomaly (SSTA) in the equatorial eastern Pacific exhibits an asymmetric evolution characteristic between El Niño and La Niña. While El Niño is characterized by a rapid decay after its peak and a fast phase transition to a cold episode in the following winter, La Niña is characterized by a weaker decay after its peak and a reintensification of cold SSTA in the second year. The relative roles of dynamic (wind field) and thermodynamic (heat flux) processes in causing the asymmetric evolutions are investigated through a mixed layer heat budget analysis. The result shows both dynamic and thermodynamic processes contribute to the evolution asymmetry. The former is related to asymmetric wind responses in the western Pacific, whereas the latter is associated with asymmetric cloud–radiation–SST and evaporation–SST feedbacks. A strong negative SSTA tendency occurs during El Niño decaying phase, compared to a much weaker positive SSTA tendency during La Niña decaying phase. Such a difference leads to an SSTA sign change for El Niño but no sign change for La Niña by the end of summer of the second year. A season-dependent coupled instability kicks in during northern fall, leading to the development of a La Niña by end of the second year for El Niño, but the reoccurrence of a La Niña episode by end of the second year for La Niña. The overall heat budget analysis during the entire ENSO evolutions indicates the thermodynamic process is as important as the dynamic process in causing the El Niño–La Niña evolution asymmetry. The fundamental difference of the current result with previous theories is further discussed.


2020 ◽  
pp. 1-39
Author(s):  
Jing Ma ◽  
Shang-Ping Xie ◽  
Haiming Xu ◽  
Jiuwei Zhao ◽  
Leying Zhang

AbstractUsing the ensemble hindcasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) coupled model for the period of 1980-2005, spatio-temporal evolution in the covariability of sea surface temperature (SST) and low-level winds in the ensemble mean and spread over the tropical Atlantic is investigated with the month-reliant singular value decomposition (SVD) method, which treats the variables in a given monthly sequence as one time step. The leading mode of the ensemble mean represents a co-evolution of SST and winds over the tropical Atlantic associated with a phase transition of El Niño from the peak to decay phase, while the second mode is related to a phase transition from El Niño to La Niña, indicating a precursory role of the north tropical Atlantic (NTA) SST warming in La Niña development.The leading mode of ensemble spread in SST and winds further illustrates that an NTA SST anomaly acts as a precursor for El Niño-Southern Oscillation (ENSO). A north-tropical pathway for the delayed effect of the NTA SST anomaly on the subsequent ENSO event is identified; the NTA SST warming induces the subtropical Northeast Pacific SST cooling through the modulation of a zonal-vertical circulation, setting off a North Pacific Meridional Mode (NPMM). The coupled SST-wind anomalies migrate southwestward to the central equatorial Pacific and eventually amplify into a La Niña event in the following months due to the equatorial Bjerknes feedback. Ensemble spread greatly increases the sample size and affords insights into the inter-basin interactions between the tropical Atlantic and Pacific, as demonstrated here in the NTA SST impact on ENSO.


2017 ◽  
Vol 30 (14) ◽  
pp. 5221-5241 ◽  
Author(s):  
Yuanyuan Guo ◽  
Mingfang Ting ◽  
Zhiping Wen ◽  
Dong Eun Lee

A neural-network-based cluster technique, the so-called self-organizing map (SOM), was performed to extract distinct sea surface temperature (SST) anomaly patterns during boreal winter. The SOM technique has advantages in nonlinear feature extraction compared to the commonly used empirical orthogonal function analysis and is widely used in meteorology. The eight distinguishable SOM patterns so identified represent three La Niña–like patterns, two near-normal patterns, and three El Niño–like patterns. These patterns show the varied amplitude and location of the SST anomalies associated with El Niño and La Niña, such as the central Pacific (CP) and eastern Pacific (EP) El Niño. The impact of each distinctive SOM pattern on winter-mean surface temperature and precipitation changes over North America was examined. Based on composite maps with observational data, each SOM pattern corresponds to a distinguishable spatial structure of temperature and precipitation anomaly over North America, which seems to result from differing wave train patterns, extending from the tropics to mid–high latitudes induced by longitudinally shifted tropical heating. The corresponding teleconnection as represented by the National Center for Atmospheric Research Community Atmospheric Model, version 4 (CAM4), was compared with the observational results. It was found that the 16-member ensemble average of the CAM4 experiments with prescribed SST can reproduce the observed atmospheric circulation responses to the different SST SOM patterns, which suggests that the circulation differences are largely SST driven rather than due to internal atmospheric variability.


2019 ◽  
Vol 3 ◽  
pp. 1219
Author(s):  
Oki Adrianto ◽  
Sudirman Sudirman ◽  
Suwandi Suwandi
Keyword(s):  
El Niño ◽  
El Nino ◽  
La Niña ◽  

Perekonomian Provinsi Nusa Tenggara Timur secara sektoral masih didominasi sektor pertanian.Tanaman jagung menjadi salah satu produksi tanaman pangan terbesar berdasarkan data dari Dinas Pertanian dan Perkebunan Provinsi Nusa Tenggara Timur tahun 2015. Peningkatan produksi pertanian dapat dilakukan melalui berbagai strategi adaptasi dan upaya penanganan bencana, salah satu upaya tersebut adalah dengan penyediaan informasi iklim terkait penentuan daerah-daerah rawan kekeringan. Tujuan dari penelitian ini adalah untuk mengetahui sebaran wilayah rawan kekeringan lahan jagung bulanan di Provinsi Nusa Tenggara Timur saat kondisi El Nino dan La Nina dengan periodeisasi bulanan januari hingga desember. Data yang digunakan dalam penelitian ini adalah data curah hujan rata rata bulanan di 19 pos hujan di Provinsi Nusa Tenggara Timur dan suhu udara rata-rata bulanan dihitung menggunakan pendekatan teori Brack dengan titik referensi Stasiun Klimatologi Lasiana Kupang. Periode dari masing-masing data yang digunakan adalah dari tahun 1991 dan 1997 digunakan sebagai tahun El Nino dan tahun 1999 dan 2010 digunakan sebagai tahun La Nina. Metode yang digunakan untuk menentukan tingkat rawan kekeringan dengan menggunakan pembobotan berdasarkan penjumlahan bobot tipe iklim Oldeman dan bobot ketersediaan air tanah. Hasil penelitian menunjukkan sebaran daerah kekeringan di Provinsi Nusa Tenggara Timurpada tahun el nino lebih luas dibandingkan tahun la nina.


2018 ◽  
Vol 1 ◽  
pp. e2018014
Author(s):  
Samya de Freitas MOREIRA ◽  
Cleiciane Silva da CONCEIÇÃO ◽  
Milla Cristina Santos da CRUZ ◽  
Antônio PEREIRA JÚNIOR
Keyword(s):  
El Niño ◽  
El Nino ◽  
La Niña ◽  

Agrometeoros ◽  
2020 ◽  
Vol 26 (2) ◽  
Author(s):  
Amanda Heemann Junges

Estudos locais de caraterização e variabilidade climática são fundamentais para geração de informações mais adaptadas às atividades agrícolas desenvolvidas em um município ou região. O objetivo desse trabalho foi caracterizar climaticamente e analisar a influência de eventos El Niño Oscilação Sul (ENOS) na série 1956-2015 de temperatura do ar de Veranópolis, RS. Para caracterização climática foram estabelecidas estatísticas descritivas das temperaturas do ar máximas, mínimas e médias mensais, estacional e anual na série e normal climatológica padrão 1961- 1990. Para identificação de diferenças entre estações e influência de eventos ENOS, os dados foram submetidos à análise de variância e teste de Duncan. Os resultados indicaram que a temperatura média anual é de 17,3ºC, variando entre 12,7ºC (julho) e 21,8ºC (janeiro). O clima é do tipo Cfb, de acordo com a classificação climática de Köppen e TE (temperado) na classificação climática do Estado. Temperaturas mínimas médias mensais inferiores a 10ºC ocorrem de maio a setembro, período de maior variabilidade interanual das temperaturas máximas (desvio padrão entre 1,5º e 1,8ºC), mínimas (1,6-1,8ºC) e médias mensais (1,4-1,7ºC). Anos de La Niña possuem temperaturas médias estacionais inferiores as de El Niño, embora diferenciação em relação a neutros ocorra somente para temperaturas mínimas na primavera e máximas no outono.


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