scholarly journals The impact of global warming on sea surface temperature based El Niño-Southern Oscillation monitoring indices

2018 ◽  
Vol 39 (2) ◽  
pp. 1092-1103 ◽  
Author(s):  
Thea Turkington ◽  
Bertrand Timbal ◽  
Raizan Rahmat
Keyword(s):  
Global Warming ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
El Nino Southern Oscillation ◽  
Oscillation Monitoring ◽  
The Impact

scholarly journals Identification of Global Warming Contribution to the El Niño Phenomenon Using Empirical Orthogonal Function Analysis

Agromet ◽  
2021 ◽  
Vol 35 (1) ◽  
pp. 11-19
Author(s):  
Mochamad Tito Julianto ◽  
Septian Dhimas ◽  
Ardhasena Sopaheluwakan ◽  
Sri Nurdiati ◽  
Pandu Septiawan
Keyword(s):  
Global Warming ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Empirical Orthogonal Function ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
El Nino Southern Oscillation ◽  
Orthogonal Function

Sea surface temperature (SST) is identified as one of the essential climate/ocean variables. The increased SST levels worldwide is associated with global warming which is due to excessive amounts of greenhouse gases being released into the atmosphere causing the multi-decadal tendency to warmer SST. Moreover, global warming has caused more frequent extreme El Niño Southern Oscillation (ENSO) events, which are the most dominant mode in the coupled ocean-atmosphere system on an interannual time scale. The objective of this research is to calculate the contribution of global warming to the ENSO phenomenon.  SST anomalies (SSTA) variability rosed from several mechanisms with differing timescales. Therefore, the Empirical Orthogonal Function in this study was used to analyze the data of Pacific Ocean sea surface temperature anomaly. By using EOF analysis, the pattern in data such as precipitation and drought pattern can be obtained. The result of this research showed that the most dominant EOF mode reveals the time series pattern of global warming, while the second most dominant EOF mode reveals the El Niño Southern Oscillation (ENSO). The modes from this EOF method have good performance with 95.8% accuracy rate.

scholarly journals The Years of El Niño, La Niña, and Interactions with the Tropical Indian Ocean

2007 ◽  
Vol 20 (13) ◽  
pp. 2872-2880 ◽  
Author(s):  
Gary Meyers ◽  
Peter McIntosh ◽  
Lidia Pigot ◽  
Mike Pook
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
El Nino Southern Oscillation ◽  
La Nina ◽  
The Indian Ocean

Abstract The Indian Ocean zonal dipole is a mode of variability in sea surface temperature that seriously affects the climate of many nations around the Indian Ocean rim, as well as the global climate system. It has been the subject of increasing research, and sometimes of scientific debate concerning its existence/nonexistence and dependence/independence on/from the El Niño–Southern Oscillation, since it was first clearly identified in Nature in 1999. Much of the debate occurred because people did not agree on what years are the El Niño or La Niña years, not to mention the newly defined years of the positive or negative dipole. A method that identifies when the positive or negative extrema of the El Niño–Southern Oscillation and Indian Ocean dipole occur is proposed, and this method is used to classify each year from 1876 to 1999. The method is statistical in nature, but has a strong basis on the oceanic physical mechanisms that control the variability of the near-equatorial Indo-Pacific basin. Early in the study it was found that some years could not be clearly classified due to strong decadal variation; these years also must be recognized, along with the reason for their ambiguity. The sensitivity of the classification of years is tested by calculating composite maps of the Indo-Pacific sea surface temperature anomaly and the probability of below median Australian rainfall for different categories of the El Niño–Indian Ocean relationship.

scholarly journals A New Picture of the Global Impacts of El Nino-Southern Oscillation

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jialin Lin ◽  
Taotao Qian
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Sea Surface ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Global Impacts

AbstractThe El Nino-Southern Oscillation (ENSO) is the dominant interannual variability of Earth’s climate system and plays a central role in global climate prediction. Outlooks of ENSO and its impacts often follow a two-tier approach: predicting ENSO sea surface temperature anomaly in tropical Pacific and then predicting its global impacts. However, the current picture of ENSO global impacts widely used by forecasting centers and atmospheric science textbooks came from two earliest surface station datasets complied 30 years ago, and focused on the extreme phases rather than the whole ENSO lifecycle. Here, we demonstrate a new picture of the global impacts of ENSO throughout its whole lifecycle based on the rich latest satellite, in situ and reanalysis datasets. ENSO impacts are much wider than previously thought. There are significant impacts unknown in the previous picture over Europe, Africa, Asia and North America. The so-called “neutral years” are not neutral, but are associated with strong sea surface temperature anomalies in global oceans outside the tropical Pacific, and significant anomalies of land surface air temperature and precipitation over all the continents.

scholarly journals An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature

2014 ◽  
Vol 5 (1) ◽  
pp. 1-14 ◽  
Author(s):  
A. Tantet ◽  
H. A. Dijkstra
Keyword(s):  
Community Structure ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Function Analysis ◽  
Sea Surface ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation

Abstract. On interannual- to multidecadal timescales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation. The community detection method allows us to bypass some shortcomings of Empirical Orthogonal Function analysis or composite analysis and can provide additional information with respect to these classical analysis tools. In addition, the study of the relationship between the communities and indices of global surface temperature shows that, while El Niño–Southern Oscillation is most dominant on interannual timescales, the Indian West Pacific and North Atlantic may also play a key role on decadal timescales. Finally, we show that the comparison of the community structure from simulations and observations can help detect model biases.

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